Fully resolved high-precision measurement of 36S for sulfur reference materials.

RATIONALE: Advances in sulfur isotope measurement techniques have led to increased analytical precision. However, accurate measurement of 36S remains a challenge. This difficulty arises primarily from unresolved isobaric interferences of 36SF5 + at m/z = 131 u, 186WF4 2+ and 12C3F5 +, which lead to scale compression. Theoretically, unresolved interference with 2% relative intensity could cause 1‰ underestimation in a sample with real δ36S = +60‰. METHODS: Our study develops an interference-free four-sulfur isotope measurement method by using the high-resolution mass spectrometer Panorama. The mass resolving power of Panorama allows the distinction of 186WF4 2+ and 12C3F5 + from 36SF5 +. RESULTS: The 186WF4 2+ relative intensity was initially 9.4% that of 36SF5 + but reduced to 1.5% through tuning, while 12C3F5 + relative intensity dropped from 74% to 40% after flushing with air. Three IAEA standards were analyzed with both Panorama and MAT 253. We obtained Δ36SIAEA-S-2 = 1.238 ± 0.040‰ and Δ36SIAEA-S-3 = -0.882 ± 0.030‰, relative to IAEA-S-1, from Panorama, and Δ36SIAEA-S-2 = 0.18 ± 0.02‰ and Δ36SIAEA-S-3 = 0.11 ± 0.14‰ from MAT 253, while δ34S values from the two instruments are consistent. CONCLUSION: The measurement discrepancies on 36S between Panorama and MAT 253 highlight the impact of scale compression due to unresolved isobaric interferences. Resolving this problem is crucial for accurate 36S analysis. We recommend replacing the filament material with rhenium, tuning the filament voltage, and avoiding carbon in instruments to eliminate or mitigate interferences. We propose future systematic efforts to calibrate the δ33S, δ34S, and δ36S of IAEA-S-1, IAEA-S-2, and IAEA-S-3 and advise bracketing all three reference materials in the measurement sequences, to enable calibration.

Geniposidic acid alleviates osteoarthritis progression through inhibiting inflammation and chondrocytes ferroptosis.

Osteoarthritis is one of the common diseases that seriously affects the quality of life of middle-aged and elderly people worldwide. Geniposidic acid (GPA) is extracted from Eucommia ulmoides that exhibits various pharmacological effects. This study investigated the function of GPA on osteoarthritis (OA) in IL-1ß-stimulated mouse chondrocytes and mouse OA model. Mouse OA model was established by destabilization of the medial meniscus (DMM) and GPA was given intraperitoneal injection. The results demonstrated that GPA could alleviate DMM-induced OA in mice. In vitro, IL-1ß-induced PGE2, NO, MMP1 and MMP3 were suppressed by GPA. Furthermore, IL-1ß-induced ferroptosis was inhibited by GPA, as confirmed by the inhibition of MDA, iron, and ROS, as well as the upregulation of GSH, GPX4, and Ferritin. In addition, GPA was found to increase the expression of Nrf2 and HO-1. And the inhibition of GPA on IL-1ß-induced inflammation and ferroptosis were prevented by Nrf2 inhibitor. In conclusion, GPA alleviates OA progression through inhibiting inflammation and chondrocytes ferroptosis via Nrf2 signalling pathway.

Ruscogenin attenuates cartilage destruction in osteoarthritis through suppressing chondrocyte ferroptosis via Nrf2/SLC7A11/GPX4 signaling pathway.

Osteoarthritis (OA) is a common joint degenerative disease, and chondrocyte injury is the main pathological and physiological change. Ruscogenin (Rus), a bioactive compound isolated from Radix Ophiopogon japonicus, exhibits various pharmacological effects. The aim of this research was to test the role and mechanism of Rus on OA both in vivo and in vitro. Destabilized medial meniscus (DMM)-induced OA model was established in vivo and IL-1ß-stimulated mouse chondrocytes was used to explore the role of Rus on OA in vitro. In vivo, Rus exhibited protective effects against DMM-induced OA model. Rus could inhibit MMP1 and MMP3 expression in OA mice. In vitro, IL-1ß-induced inflammation and degradation of extracellular matrix were inhibited by Rus, as confirmed by the inhibition of PGE2, NO, MMP1, and MMP3 by Rus. Also, IL-1ß-induced ferroptosis was suppressed by Rus, as confirmed by the inhibition of MDA, iron, and ROS, as well as the upregulation of GSH, GPX4, Ferritin, Nrf2, and SLC7A11 expression induced by Rus. Furthermore, the suppression of Rus on IL-1ß-induced inflammation, MMPs production, and ferroptosis were reversed when Nrf2 was knockdown. In conclusion, Rus attenuated OA progression through inhibiting chondrocyte ferroptosis via Nrf2/SLC7A11/GPX4 signaling pathway.

Tracing sources of atmospheric methane using clumped isotopes.

We apply a recently developed measurement technique for methane (CH4) isotopologues* (isotopic variants of CH4-13CH4, 12CH3D, 13CH3D, and 12CH2D2) to identify contributions to the atmospheric burden from fossil fuel and microbial sources. The aim of this study is to constrain factors that ultimately control the concentration of this potent greenhouse gas on global, regional, and local levels. While predictions of atmospheric methane isotopologues have been modeled, we present direct measurements that point to a different atmospheric methane composition and to a microbial flux with less clumping (greater deficits relative to stochastic) in both 13CH3D and 12CH2D2 than had been previously assigned. These differences make atmospheric isotopologue data sufficiently sensitive to variations in microbial to fossil fuel fluxes to distinguish between emissions scenarios such as those generated by different versions of EDGAR (the Emissions Database for Global Atmospheric Research), even when existing constraints on the atmospheric CH4 concentration profile as well as traditional isotopes are kept constant.

Prediction method for the truck's fault time in open-pit mines based on exponential smoothing neural network.

The transport truck is one of the important equipment for open-pit mines, and predicting the truck's fault time is of great significance in improving the economic benefits of open-pit mines. In this paper, we discuss the reason for the large prediction error of the exponential smoothing method. Then, we propose a novel nonlinear exponential smoothing method (ESNN) for predicting the truck's fault time, and demonstrate the equivalence between our approach and the neural network structure. Finally, based on the augmented Lagrange function, the solving method of ESNN is proposed. We conduct experiments on real-world datasets and our results demonstrate the effectiveness of ESNN in comparison to existing state-of-the-art methods. Our approach makes it easier for maintenance personnel to predict fault situations in advance and provides a basis for enterprises to develop preventive maintenance plans.

Brevilin A attenuates cartilage destruction in osteoarthritis mouse model by inhibiting inflammation and ferroptosis via SIRT1/Nrf2/GPX4 signaling pathway.

Osteoarthritis (OA) is a serious orthopedic disease that affects people's quality of life. Although there are many treatment methods, the treatment effect is still not good. Brevilin A is a bioactive compound isolated from the medicinal herbCentipeda minima. The potential efficacy of brevilin A on OA was explored in this study. Mouse chondrocytes were isolated and stimulated by IL-1ß and mouse OA model was induced by destabilization of the medial meniscus (DMM). The results demonstrated that brevilin A markedly inhibited IL-1ß-induced MMP1 and MMP3 production. IL-1ß-induced PGE2, NO, MDA, and iron production were alleviated by brevilin A. The production of GSH and the expression of SIRT1, Nrf2, HO-1, GPX4, and Ferritin were increased by brevilin A. Furthermore, the inhibition of brevilin A on IL-1ß-induced inflammation and ferroptosis were prevented by SIRT1 inhibitor. In vivo, the results showed brevilin A markedly attenuated OA progression in DMM-induced mouse OA model. Also, brevilin A could alleviate MMP1, MMP3, iNOS, and COX2 expression in OA mice. In conclusion, brevilin A protected mice against OA via suppressing inflammatory response and ferroptosis by regulating SIRT1/Nrf2/GPX4 signaling.

Kukoamine A protects mice against osteoarthritis by inhibiting chondrocyte inflammation and ferroptosis via SIRT1/GPX4 signaling pathway.

AIMS: Osteoarthritis (OA) is one of the common chronic degenerative joint diseases, characterized by cartilage damage, subchondral bone changes, osteophyte formation, and synovitis. Kukoamine A (KuKA) is a bioactive compound isolated from Lycium chinense which is known as its anti-inflammatory activity. In this study, we detected the regulatory role of KuKA on OA both in vivo and in vitro. MATERIALS AND METHODS: Mouse chondrocytes were cultured and mouse model of OA was established. Inflammatory mediator was measured by ELISA. The signaling pathway was tested by western blot analysis. KEY FINDINGS: KuKA inhibited IL-1ß-induced PGE2 and NO production and iNOS and COX-2 expression. IL-1ß-induced MMP1 and MMP3 production was attenuated by KuKA. IL-1ß-induced MDA, iron, and ROS were alleviated by KuKA. Meanwhile, GSH content, GPX4, Ferritin, SIRT1, Nrf2, and HO-1 expression were upregulated by KuKA. Furthermore, the inhibitory role of KuKA on IL-1ß-induced inflammation, MMPs production, and ferroptosis were reversed by SIRT1 inhibitor. In vivo, KuKA could attenuate OA development in mouse model. KuKA markedly alleviated MMP1, MMP3, iNOS, and COX2 expression in OA mice. SIGNIFICANCE: In conclusion, KuKA could inhibit OA development through suppressing chondrocyte inflammation and ferroptosis via SIRT1/GPX4 signaling pathway.

Risk Factors for New Vertebral Compression Fracture After Percutaneous Vertebral Augmentation: A Retrospective Study.

BACKGROUND Percutaneous vertebral augmentation is the mainstream treatment of osteoporotic vertebral compression fracture (OVCF). New vertebral compression fracture (NVCF) after percutaneous vertebral augmentation may be an issue that cannot be ignored. Nevertheless, the risk factors for NVCF are still uncertain. This research aimed to study the risk factors for NVCF after percutaneous vertebral augmentation. MATERIAL AND METHODS All patients who underwent percutaneous vertebral augmentation for OVCF from January 2019 to December 2020 were enrolled in the study. These patients were divided into NVCF and control groups according to whether they had NVCF. The covariates including sex, age, BMI, diabetes, hypertension, smoking, alcohol, fracture level, surgical method, cement leakage, cement volume, preoperative anterior vertebral height ratio, and Hounsfield unit (HU) value were reviewed. Univariate and multivariate analyses were performed to identify risk factors. RESULTS A total of 279 patients were included in this study, of which 47 had NVCF after percutaneous vertebral augmentation. Univariate analysis demonstrated that there were significant differences in age (OR=1.040, 95% CI=1.003-1.078, P=0.033), BMI (OR=0.844, 95% CI=0.758-0.939, P=0.002) and HU value (OR=0.945, 95% CI=0.929-0.962, P<0.001) between the 2 groups. Multivariate regression analysis revealed that HU value (OR=0.942, 95% CI=0.924-0.960, P<0.001) were independent risk factor for NVCF after percutaneous vertebral augmentation. CONCLUSIONS Hounsfield unit value was an independent risk factor for new vertebral compression fracture after percutaneous vertebral augmentation, whereas age and BMI were not.

Improved GWO and its application in parameter optimization of Elman neural network.

Traditional neural networks used gradient descent methods to train the network structure, which cannot handle complex optimization problems. We proposed an improved grey wolf optimizer (SGWO) to explore a better network structure. GWO was improved by using circle population initialization, information interaction mechanism and adaptive position update to enhance the search performance of the algorithm. SGWO was applied to optimize Elman network structure, and a new prediction method (SGWO-Elman) was proposed. The convergence of SGWO was analyzed by mathematical theory, and the optimization ability of SGWO and the prediction performance of SGWO-Elman were examined using comparative experiments. The results show: (1) the global convergence probability of SGWO was 1, and its process was a finite homogeneous Markov chain with an absorption state; (2) SGWO not only has better optimization performance when solving complex functions of different dimensions, but also when applied to Elman for parameter optimization, SGWO can significantly optimize the network structure and SGWO-Elman has accurate prediction performance.

Cytokine-induced killer cell treatment is superior to chemotherapy alone in esophageal cancer.

Background: The therapeutic efficacy of cytokine-induced killer (CIK) cells versus dendritic cells (DC) co-cultured with CIK cells (DC-CIK) in treating esophageal cancer (EC) remains unclear due to the absence of a direct comparison of these two regimens. This study evaluated the comparative efficacy and safety of CIK cells versus DC-CIK using network meta-analysis in treating EC. Material and methods: We identified eligible studies from previous meta-analyses, then conducted an updated search to retrieve additional trials between February 2020 and July 2021. The primary outcomes included overall survival (OS), objective response rate (ORR), and disease control rate (DCR), and the secondary outcomes included quality of life improved rate (QLIR) and adverse events (AEs). A network meta-analysis of 12 studies was conducted using ADDIS software. Results: Twelve studies were identified, including six comparing CIK or DC-CIK plus chemotherapy (CT) with CT alone. Immunotherapy plus CT significantly improved overall survival (OS) (odds ratio [OR] 4.10, 95% confidence interval [CI] 1.23-13.69), objective response rate (ORR) (OR 2.72, 95% CI 1.79-4.11), disease control rate (DCR) (OR 3.45, 95% CI 2.32-5.14), and quality of life improvement rate (QLIR) (OR 3.54, 95% CI 2.31-5.41). DC-CIK+CT decreased the risk of leukopenia compared with CT alone. However, no statistical difference was detected between CIK-CT and DC-CIK+CT. Conclusion: Based on the available evidence, we concluded that CIK cell treatment is superior to CT alone, but CIK-CT and DC-CIK+CT may be comparable in treating EC. However, comparing CIK-CT and DC-CIK+CT is only based on indirect evidence, so it is undoubtedly necessary to conduct studies to compare CIK-CT with DC-CIK+CT in EC patients directly.

Comprehensive lipidomics analysis of the lipids in hazelnut oil during storage.

Although hazelnut oil is is nutritious, it is easily oxidized during storage. Thus far, changes in lipids during storage have not been comprehensively analyzed. Here, we used ultra-high liquid chromatography tandem quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) to dynamically monitor the lipid composition of hazelnut oil during accelerated storage for 24 d. A total of 10 subclasses of 103 lipids were identified. After 24 d, the content of triacylglycerol, diacylglycerol, phosphatidic acid, phosphatidylethanolamine, phosphatidylethanol, ceramide, and total lipids decreased significantly (P < 0.05). A total of 51 significantly different lipids were screened (Variable Importance in Projection > 1, P < 0.05), and these lipids could be used as biomarkers to distinguish fresh and oxidized hazelnut oil. We also detected seven most important pathways by bioinformatics analysis to explore the mechanism underlying changes. Our results provide useful information for future applications of hazelnut oil and provide new insight into edible oil oxidation.

Controllable Nanoparticle Aggregation through a Superhydrophobic Laser-Induced Graphene Dynamic System for Surface-Enhanced Raman Scattering Detection.

Surface-enhanced Raman scattering (SERS) is widely used for low-concentration molecular detection; however, challenges related to detection uniformity and repeatability are bottlenecks for practical application, especially as regards ultrasensitive detection. Here, through the coupling of bionics and fluid mechanics, a lotus-leaf effect and rose-petal effect (LLE-RPE)-integrated superhydrophobic chip is facilely developed using laser-induced graphene (LIG) fabricated on a polyimide film. Dense and uniform aggregation of gold nanoparticles (AuNPs) in droplets is realized through a constant contact angle (CCA) evaporation mode in the dynamic enrichment process, facilitating reliable ultrasensitive detection. The detection chip consists of two components: an LLE zone containing an ethanol-treated LIG superhydrophobic surface with a low-adhesive property, which functions as an AuNP-controllable aggregation zone, and an RPE zone containing an as-fabricated LIG superhydrophobic surface with water-solution pinning ability, which functions as a droplet solvent evaporation and a AuNP blending zone. AuNPs realize uniform aggregation during rolling on the LLE zone, and then get immobilized on the RPE zone to complete evaporation of the solvent, followed by Raman detection. Here, based on dense and uniform AuNP aggregation, the detection system achieves high-efficiency (242 s/18 µL) and ultralow-concentration (10-17 M) detection of a target analyte (rhodamine 6G). The proposed system constitutes a simple approach toward high-performance detection for chemical analysis, environmental monitoring, biological analysis, and medical diagnosis.

Expression of interferon-γ and its effect on cough hypersensitivity in chronic refractory cough patients.

Chronic refractory cough (CRC) is characterised by cough hypersensitivity. Interferon-γ (IFN-γ) has been reported to induce calcium influx, action potentials of vagal neurons in vitro and cough response in guinea pigs. While the effect of IFN-γ in CRC patients remains unknown. Here, via flow-cytometry and inhalation cough challenge, we found CRC patients had significantly increased levels of sputum IFN-γ+CD4+ T cells, IFN-γ+CD8+ T cells as well as supernatant of IFN-γ. The average number of coughs in CRC patients increased as the concentration of inhaled IFN-γ went up in IFN-γ cough challenge. Two or more coughs and five or more coughs elicited by inhaled IFN-γ in CRC patients occurred in 7 of 10 and 2 of 10, respectively. Preinhaled IFN-γ (100 µg/mL) increased the capsaicin cough sensitivity in CRC patients but not healthy volunteers. Targeting IFN-γ may be a potential effective anti-tussive strategy in CRC patients.

Targeted Lipidomics Analysis of Oxylipids in Hazelnut Oil during Storage by Liquid Chromatography Coupled to Tandem Mass Spectrometry.

Hazelnut oil is a high-grade edible oil with high nutritional value and unique taste. However, it is prone to oxidative degradation during storage. Herein, we used liquid chromatography coupled to tandem mass spectrometry to carry out a lipidomics analysis of the storage process of hazelnut oil. A total of 41 triacylglycerols and 12 oxylipids were determined. The contents of all oxylipids increased significantly after storage (p < 0.05). The oxylipid accumulation of hazelnut oil during storage was clarified for the first time. Nine significantly different oxylipids were further screened out. It was considered that the 15th day of storage is the dividing point. In addition, the lipoxygenase-catalyzed oxidation may be the major contributor to lipid oxidation of hazelnut oil. This study provides a new insight and theoretical basis to explore the storage oxidation mechanism of hazelnut oil and take quality control measures.

A cross-sectional investigation of SARS-CoV-2 seroprevalence and associated risk factors in children and adolescents in the United States.

BACKGROUND: Pediatric SARS-CoV-2 data remain limited and seropositivity rates in children were reported as <1% early in the pandemic. Seroepidemiologic evaluation of SARS-CoV-2 in children in a major metropolitan region of the US was performed. METHODS: Children and adolescents ≤19 years were enrolled in a cross-sectional, observational study of SARS-CoV-2 seroprevalence from July-October 2020 in Northern Virginia, US. Demographic, health, and COVID-19 exposure information was collected, and blood analyzed for SARS-CoV-2 spike protein total antibody. Risk factors associated with SARS-CoV-2 seropositivity were analyzed. Orthogonal antibody testing was performed, and samples were evaluated for responses to different antigens. RESULTS: In 1038 children, the anti-SARS-CoV-2 total antibody positivity rate was 8.5%. After multivariate logistic regression, significant risk factors included Hispanic ethnicity, public or absent insurance, a history of COVID-19 symptoms, exposure to person with COVID-19, a household member positive for SARS-CoV-2 and multi-family or apartment dwelling without a private entrance. 66% of seropositive children had no symptoms of COVID-19. Secondary analysis included orthogonal antibody testing with assays for 1) a receptor binding domain specific antigen and 2) a nucleocapsid specific antigen had concordance rates of 80.5% and 79.3% respectively. CONCLUSIONS: A much higher burden of SARS-CoV-2 infection, as determined by seropositivity, was found in children than previously reported; this was also higher compared to adults in the same region at a similar time. Contrary to prior reports, we determined children shoulder a significant burden of COVID-19 infection. The role of children's disease transmission must be considered in COVID-19 mitigation strategies including vaccination.

Subcategorizing EHR diagnosis codes to improve clinical application of machine learning models.

BACKGROUND: Electronic health record (EHR) data is commonly used for secondary purposes such as research and clinical decision support. However, reuse of EHR data presents several challenges including but not limited to identifying all diagnoses associated with a patient's clinical encounter. The purpose of this study was to assess the feasibility of developing a schema to identify and subclassify all structured diagnosis codes for a patient encounter. METHODS: To develop a subclassification schema we used EHR data from an interhospital transport data repository that contained complete hospital encounter level data. Eight discrete data sources containing structured diagnosis codes were identified. Diagnosis codes were normalized using the Unified Medical Language System and additional EHR data were combined with standardized terminologies to create and validate the subcategories. We then employed random forest to assess the usefulness of the new subcategorized diagnoses to predict post-interhospital transfer mortality by building 2 models, one using standard diagnosis codes, and one using the new subcategorized diagnosis codes. RESULTS: Six subcategories of diagnoses were identified and validated. The subcategories included: primary or admitting diagnoses (10%), past medical, surgical or social history (9%), problem list (20%), comorbidity (24%), discharge diagnoses (6%), and unmapped diagnoses (31%). The subcategorized model outperformed the standard model, achieving a training AUROC of 0.97 versus 0.95 and testing model AUROC of 0.81 versus 0.46. DISCUSSION: Our work demonstrates that merging structured diagnosis codes with additional EHR data and secondary data sources provides additional information to understand the role of diagnosis throughout a clinical encounter and improves predictive model performance. Further work is necessary to assess if subcategorizing produces benefits in interpreting the results of prognostic models and/or operationalizing the results in clinical decision support applications.

Development of Predictive Informatics Tool Using Electronic Health Records to Inform Personalized Evidence-Based Pressure Injury Management for Veterans with Spinal Cord Injury.

BACKGROUND: Pressure injuries (PrI) are serious complications for many with spinal cord injury (SCI), significantly burdening health care systems, in particular the Veterans Health Administration. Clinical practice guidelines (CPG) provide recommendations. However, many risk factors span multiple domains. Effective prioritization of CPG recommendations has been identified as a need. Bioinformatics facilitates clinical decision support for complex challenges. The Veteran's Administration Informatics and Computing Infrastructure provides access to electronic health record (EHR) data for all Veterans Health Administration health care encounters. The overall study objective was to expand our prototype structural model of environmental, social, and clinical factors and develop the foundation for resource which will provide weighted systemic insight into PrI risk in veterans with SCI. METHODS: The SCI PrI Resource (SCI-PIR) includes three integrated modules: (1) the SCIPUDSphere multidomain database of veterans' EHR data extracted from October 2010 to September 2015 for ICD-9-CM coding consistency together with tissue health profiles, (2) the Spinal Cord Injury Pressure Ulcer and Deep Tissue Injury Ontology (SCIPUDO) developed from the cohort's free text clinical note (Text Integration Utility) notes, and (3) the clinical user interface for direct SCI-PIR query. RESULTS: The SCI-PIR contains relevant EHR data for a study cohort of 36,626 veterans with SCI, representing 10% to 14% of the U.S. population with SCI. Extracted datasets include SCI diagnostics, demographics, comorbidities, rurality, medications, and laboratory tests. Many terminology variations for non-coded input data were found. SCIPUDO facilitates robust information extraction from over six million Text Integration Utility notes annually for the study cohort. Visual widgets in the clinical user interface can be directly populated with SCIPUDO terms, allowing patient-specific query construction. CONCLUSION: The SCI-PIR contains valuable clinical data based on CPG-identified risk factors, providing a basis for personalized PrI risk management following SCI. Understanding the relative impact of risk factors supports PrI management for veterans with SCI. Personalized interactive programs can enhance best practices by decreasing both initial PrI formation and readmission rates due to PrI recurrence for veterans with SCI.

Needs, priorities, and attitudes of individuals with spinal cord injury toward nerve stimulation devices for bladder and bowel function: a survey.

STUDY DESIGN: Survey. OBJECTIVES: To investigate the needs and priorities of people with spinal cord injury for managing neurogenic bladder and bowel function and to determine their willingness to adopt neuromodulation interventions for these functions. METHODS: Anonymous online survey. It was advertised by word-of-mouth by community influencers and social media, and by advertisement in newsletters of advocacy groups. RESULTS: Responses from 370 individuals (27% female, 73% male) were included. Bladder emptying without catheters was the top priority for restoring bladder function, and maintaining fecal continence was the top priority for restoring bowel function. The biggest concerns regarding external stimulation systems were wearing a device with wires connecting to electrodes on the skin and having to don and doff the system daily as needed. The biggest concerns for implanted systems were the chances of experiencing problems with the implant that required a revision surgery or surgical removal of the whole system. Respondents were willing to accept an external (61%) or implanted (41%) device to achieve improved bladder or bowel function. CONCLUSIONS: Bladder and bowel dysfunction remain important unmet challenges for individuals living with SCI who answered our survey. These individuals are willing to accept some potential risks of nerve stimulation approaches given potential benefits. Additional consumer input is critical for guiding both research and translation to clinical use and personalized medicine.

Investigating the Association between Motor Function, Neuroinflammation, and Recording Metrics in the Performance of Intracortical Microelectrode Implanted in Motor Cortex.

Long-term reliability of intracortical microelectrodes remains a challenge for increased acceptance and deployment. There are conflicting reports comparing measurements associated with recording quality with postmortem histology, in attempts to better understand failure of intracortical microelectrodes (IMEs). Our group has recently introduced the assessment of motor behavior tasks as another metric to evaluate the effects of IME implantation. We hypothesized that adding the third dimension to our analysis, functional behavior testing, could provide substantial insight on the health of the tissue, success of surgery/implantation, and the long-term performance of the implanted device. Here we present our novel analysis scheme including: (1) the use of numerical formal concept analysis (nFCA) and (2) a regression analysis utilizing modern model/variable selection. The analyses found complimentary relationships between the variables. The histological variables for glial cell activation had associations between each other, as well as the neuronal density around the electrode interface. The neuronal density had associations to the electrophysiological recordings and some of the motor behavior metrics analyzed. The novel analyses presented herein describe a valuable tool that can be utilized to assess and understand relationships between diverse variables being investigated. These models can be applied to a wide range of ongoing investigations utilizing various devices and therapeutics.

Assessing a novel, lab-free, point-of-care test for SARS-CoV-2 (CovidNudge): a diagnostic accuracy study.

BACKGROUND: Access to rapid diagnosis is key to the control and management of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Laboratory RT-PCR testing is the current standard of care but usually requires a centralised laboratory and significant infrastructure. We describe our diagnostic accuracy assessment of a novel, rapid point-of-care real time RT-PCR CovidNudge test, which requires no laboratory handling or sample pre-processing. METHODS: Between April and May, 2020, we obtained two nasopharyngeal swab samples from individuals in three hospitals in London and Oxford (UK). Samples were collected from three groups: self-referred health-care workers with suspected COVID-19; patients attending emergency departments with suspected COVID-19; and hospital inpatient admissions with or without suspected COVID-19. For the CovidNudge test, nasopharyngeal swabs were inserted directly into a cartridge which contains all reagents and components required for RT-PCR reactions, including multiple technical replicates of seven SARS-CoV-2 gene targets (rdrp1, rdrp2, e-gene, n-gene, n1, n2 and n3) and human ribonuclease P (RNaseP) as sample adequacy control. Swab samples were tested in parallel using the CovidNudge platform, and with standard laboratory RT-PCR using swabs in viral transport medium for processing in a central laboratory. The primary analysis was to compare the sensitivity and specificity of the point-of-care CovidNudge test with laboratory-based testing. FINDINGS: We obtained 386 paired samples: 280 (73%) from self-referred health-care workers, 15 (4%) from patients in the emergency department, and 91 (23%) hospital inpatient admissions. Of the 386 paired samples, 67 tested positive on the CovidNudge point-of-care platform and 71 with standard laboratory RT-PCR. The overall sensitivity of the point-of-care test compared with laboratory-based testing was 94% (95% CI 86-98) with an overall specificity of 100% (99-100). The sensitivity of the test varied by group (self-referred healthcare workers 94% [95% CI 85-98]; patients in the emergency department 100% [48-100]; and hospital inpatient admissions 100% [29-100]). Specificity was consistent between groups (self-referred health-care workers 100% [95% CI 98-100]; patients in the emergency department 100% [69-100]; and hospital inpatient admissions 100% [96-100]). Point of care testing performance was similar during a period of high background prevalence of laboratory positive tests (25% [95% 20-31] in April, 2020) and low prevalence (3% [95% 1-9] in inpatient screening). Amplification of viral nucleocapsid (n1, n2, and n3) and envelope protein gene (e-gene) were most sensitive for detection of spiked SARS-CoV-2 RNA. INTERPRETATION: The CovidNudge platform was a sensitive, specific, and rapid point of care test for the presence of SARS-CoV-2 without laboratory handling or sample pre-processing. The device, which has been implemented in UK hospitals since May, 2020, could enable rapid decisions for clinical care and testing programmes. FUNDING: National Institute of Health Research (NIHR) Imperial Biomedical Research Centre, NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at Oxford University in partnership with Public Health England, NIHR Biomedical Research Centre Oxford, and DnaNudge.