The impact of COVID-19 on patients with asthma.

BACKGROUND: An association between the severity of coronavirus disease 2019 (COVID-19) and the presence of certain chronic conditions has been suggested. However, unlike influenza and other viruses, the disease burden of COVID-19 in patients with asthma has been less evident. OBJECTIVE: To understand the impact of COVID-19 in patients with asthma. METHODS: Using big-data analytics and artificial intelligence through the SAVANA Manager clinical platform, we analysed clinical data from patients with asthma from January 1 to May 10, 2020. RESULTS: Out of 71 182 patients with asthma, 1006 (1.41%) suffered from COVID-19. Compared to asthmatic individuals without COVID-19, patients with asthma and COVID-19 were significantly older (55 versus 42 years), predominantly female (66% versus 59%), smoked more frequently and had higher prevalence of hypertension, dyslipidaemias, diabetes and obesity. Allergy-related factors such as rhinitis and eczema were less common in asthmatic patients with COVID-19 (p<0.001). In addition, higher prevalence of these comorbidities was observed in patients with COVID-19 who required hospital admission. The use of inhaled corticosteroids (ICS) was lower in patients who required hospitalisation due to COVID-19, as compared to non-hospitalised patients (48.3% versus 61.5%; OR 0.58, 95% CI 0.44-0.77). Although patients treated with biologics (n=865; 1.21%) showed increased severity and more comorbidities at the ear, nose and throat level, COVID-19-related hospitalisations in these patients were relatively low (0.23%). CONCLUSION: Patients with asthma and COVID-19 were older and at increased risk due to comorbidity-related factors. ICS and biologics are generally safe and may be associated with a protective effect against severe COVID-19 infection.

Adenovirus-Mediated Inducible Expression of a PD-L1 Blocking Antibody in Combination with Macrophage Depletion Improves Survival in a Mouse Model of Peritoneal Carcinomatosis.

Immune checkpoint inhibitors (ICIs) have demonstrated remarkable efficacy in a growing number of malignancies. However, overcoming primary or secondary resistances is difficult due to pharmacokinetics issues and side effects associated with high systemic exposure. Local or regional expression of monoclonal antibodies (mAbs) using gene therapy vectors can alleviate this problem. In this work, we describe a high-capacity adenoviral vector (HCA-EFZP-aPDL1) equipped with a mifepristone-inducible system for the controlled expression of an anti-programmed death ligand 1 (PD-L1) blocking antibody. The vector was tested in an immune-competent mouse model of colorectal cancer based on implantation of MC38 cells. A single local administration of HCA-EFZP-aPDL1 in subcutaneous lesions led to a significant reduction in tumor growth with minimal release of the antibody in the circulation. When the vector was tested in a more stringent setting (rapidly progressing peritoneal carcinomatosis), the antitumor effect was marginal even in combination with other immune-stimulatory agents such as polyinosinic-polycytidylic acid (pI:C), blocking mAbs for T cell immunoglobulin, mucin-domain containing-3 (TIM-3) or agonistic mAbs for 4-1BB (CD137). In contrast, macrophage depletion by clodronate liposomes enhanced the efficacy of HCA-EFZP-aPDL1. These results highlight the importance of addressing macrophage-associated immunoregulatory mechanisms to overcome resistance to ICIs in the context of colorectal cancer.

High-Capacity Adenoviral Vectors: Expanding the Scope of Gene Therapy.

The adaptation of adenoviruses as gene delivery tools has resulted in the development of high-capacity adenoviral vectors (HC-AdVs), also known, helper-dependent or "gutless". Compared with earlier generations (E1/E3-deleted vectors), HC-AdVs retain relevant features such as genetic stability, remarkable efficacy of in vivo transduction, and production at high titers. More importantly, the lack of viral coding sequences in the genomes of HC-AdVs extends the cloning capacity up to 37 Kb, and allows long-term episomal persistence of transgenes in non-dividing cells. These properties open a wide repertoire of therapeutic opportunities in the fields of gene supplementation and gene correction, which have been explored at the preclinical level over the past two decades. During this time, production methods have been optimized to obtain the yield, purity, and reliability required for clinical implementation. Better understanding of inflammatory responses and the implementation of methods to control them have increased the safety of these vectors. We will review the most significant achievements that are turning an interesting research tool into a sound vector platform, which could contribute to overcome current limitations in the gene therapy field.

Alpha-1 Antitrypsin Gene Variants in Patients without Severe Deficiency Diagnosed with Pulmonary Emphysema on Chest CT.

Introduction: Although pulmonary involvement due to alpha-1 antitrypsin (AAT) deficiency has been widely described, most studies focus on the genotypes causing severe deficiency (<60 mg/dL). Objective: The aim of this study was to analyze the prevalence of the different AAT gene variants that do not cause severe deficiency in patients with pulmonary emphysema diagnosed by thoracic computed tomography (CT). Furthermore, we assessed the risk associated with a non-severe decrease in AAT values in the pathogenesis of emphysema. Methods: Case-control study design that included patients who had a CT scan available of the entire thorax. In total, 176 patients with emphysema (cases) and 100 control subjects without emphysema were analyzed. Results: The prevalence of variants was higher among cases (25.6%; 45/176) than controls (22%; 22/100), although the difference was not statistically significant (P=0.504) when analyzed globally. In the control group, all the variants detected were MS. Excluding this variant, statistically significant differences were observed in the remaining variants (MZ, SS and SZ). Only 18% of the controls (all MS) presented values below our limit of normality, and all had values very close to the reference value (90 mg/dL). In contrast, 76% of patients with the other variants presented pathological levels. In a logistic regression model, both smoking and a non-severe reduction in AAT (60 to 90 mg/dL) increased the probability of emphysema. Conclusion: Our study confirms an association between certain variants in the alpha-1 antitrypsin gene that do not cause severe deficiency and the presence of pulmonary emphysema. This association with variants that are associated with reductions in serum AAT values is statistically significant and independent of smoking habit.

Chronic Respiratory Diseases as a Risk Factor for Herpes Zoster Infection.

INTRODUCTION: Herpes zoster (HZ) is a condition that results from the reactivation of the varicella zoster virus (VZV). Several diseases have been reported to increase the risk of developing HZ and postherpetic neuralgia (PHN). The objective of this study is to analyze the prevalence and risk factors for HZ and PHN in the most frequent chronic respiratory diseases, which are chronic obstructive pulmonary disease (COPD), asthma, lung cancer and obstructive sleep apnea (OSA). METHODS: We conducted an observational, retrospective, non-interventional study between January 2012 and December 2020 based on data from the Castilla-La Mancha Regional Health System in Spain. We used the Savana Manager 3.0 artificial intelligence-enabled system to collect information from electronic medical records. RESULTS: 31765 subjects presented a diagnosis of HZ. Mean age was 64.5 years (95%CI 64.3-64.7), and 58.2% were women. The prevalence of HZ showed an increasing trend in patients over the age of 50. A risk analysis adjusted for sex and comorbidities in COPD, asthma, lung cancer and OSA presented a higher risk of developing HZ in the first three (OR 1.16 [95%CI 1.13-1.19], 1.67 [1.63-1.71], 1.68 [1.60-1.76], respectively), which further increased in all three when associated with comorbidities. Regarding postherpetic neuralgia, an increased risk was only observed related to COPD and lung cancer (OR 1.24 [95%CI 1.23-1.25], 1.14 [1.13-1.16], respectively), further increasing when associated with comorbidities. CONCLUSIONS: In a standard clinical practice setting, the most prevalent respiratory diseases (asthma, COPD and lung cancer) are related to a higher risk of HZ and PHN. These data are fundamental to assess the potential impact of vaccination in this population.

Serotonin is a common thread linking different classes of antidepressants.

Depression pathology remains elusive. The monoamine hypothesis has placed much focus on serotonin, but due to the variable clinical efficacy of monoamine reuptake inhibitors, the community is looking for alternative therapies such as ketamine (neurogenesis theory of antidepressant action). There is evidence that different classes of antidepressants may affect serotonin levels; a notion we test here. We measure hippocampal serotonin in mice with voltammetry and study the effects of acute challenges of escitalopram, fluoxetine, reboxetine, and ketamine. We find that pseudo-equivalent doses of these drugs similarly raise ambient serotonin levels, despite their differing pharmacodynamics because of differences in Uptake 1 and 2, rapid SERT trafficking, and modulation of serotonin by histamine. These antidepressants have different pharmacodynamics but have strikingly similar effects on extracellular serotonin. Our findings suggest that serotonin is a common thread that links clinically effective antidepressants, synergizing different theories of depression (synaptic plasticity, neurogenesis, and the monoamine hypothesis).

Serotonin is a Common Thread Linking Different Classes of Antidepressants.

Depression pathology remains elusive. The monoamine hypothesis has placed much focus on serotonin, but due to the variable clinical efficacy of monoamine reuptake inhibitors, the community is looking for alternative therapies such as ketamine (synaptic plasticity and neurogenesis theory of antidepressant action). There is evidence that different classes of antidepressants may affect serotonin levels; a notion we test here. We measure hippocampal serotonin in mice with voltammetry and study the effects of acute challenges of antidepressants. We find that pseudo-equivalent doses of these drugs similarly raise ambient serotonin levels, despite their differing pharmacodynamics because of differences in Uptake 1 and 2, rapid SERT trafficking and modulation of serotonin by histamine. These antidepressants have different pharmacodynamics but have strikingly similar effects on extracellular serotonin. Our findings suggest that serotonin is a common thread that links clinically effective antidepressants, synergizing different theories of depression (synaptic plasticity, neurogenesis and the monoamine hypothesis).

The Synergies Between Understanding Belief Formation and Artificial Intelligence.

Understanding artificial intelligence (AI) and belief formation have interesting bidirectional synergies. From explaining the logical derivation of beliefs and their internal consistency, to giving a quantitative account of mightiness, AI still has plenty of unexploited metaphors that can illuminate belief formation. In addition, acknowledging that AI should integrate itself with our belief processes (mainly, the capacity to reflect, rationalize, and communicate that is allowed by semantic coding) makes it possible to focus on more promising lines such as Interpretable Machine Learning.

Use of N-Acetylcysteine at high doses as an oral treatment for patients hospitalized with COVID-19.

Infection by SARS-CoV-2 causing coronavirus disease 2019 (COVID-19) can be associated with serious and life-threatening conditions, including acute respiratory distress syndrome (ARDS). Severity and mortality have been related to a cytokine storm, an imbalance of oxidative stress, and a pro-thrombotic state.We conducted an observational retrospective cohort study from a community-based large population of hospitalized COVID-19 PCR + patients admitted from March 01, 2020, to January 24, 2021, with integrated primary to tertiary care information in Castilla la Mancha, Spain. We explored the potential benefits of the antioxidant, anti-inflammatory and anti-thrombotic drug N-acetylcysteine (NAC) administered orally in high doses (600 mg every 8 h), added to standard of care in COVID-19 patients by using the free text information contained in their electronic health records (EHRs).Out of 19,208 patients with a diagnosis of COVID-19 hospitalized, we studied 2071 (10.8%) users of oral NAC at high doses. COVID-19 patients treated with NAC were older, predominantly male, and with more comorbidities such as hypertension, dyslipidemia, diabetes, and COPD when compared with those not on NAC (all p < 0.05). Despite greater baseline risk, use of NAC in COVID-19 patients was associated with significantly lower mortality (OR 0.56; 95%CI 0.47-0.67), a finding that remained significant in a multivariate analysis adjusting by baseline characteristics and concomitant use of corticosteroids. There were no significant differences with the use of NAC on the mean duration of hospitalization, admission to the intensive care unit or use of invasive mechanical ventilation. The observed association signaling to better relevant outcomes in COVID-19 patients treated with NAC at high doses should be further explored in other settings and populations and in randomized controlled trials.

Clinical characteristics and prognostic factors for Crohn's disease relapses using natural language processing and machine learning: a pilot study.

BACKGROUND: The impact of relapses on disease burden in Crohn's disease (CD) warrants searching for predictive factors to anticipate relapses. This requires analysis of large datasets, including elusive free-text annotations from electronic health records. This study aims to describe clinical characteristics and treatment with biologics of CD patients and generate a data-driven predictive model for relapse using natural language processing (NLP) and machine learning (ML). METHODS: We performed a multicenter, retrospective study using a previously validated corpus of CD patient data from eight hospitals of the Spanish National Healthcare Network from 1 January 2014 to 31 December 2018 using NLP. Predictive models were created with ML algorithms, namely, logistic regression, decision trees, and random forests. RESULTS: CD phenotype, analyzed in 5938 CD patients, was predominantly inflammatory, and tobacco smoking appeared as a risk factor, confirming previous clinical studies. We also documented treatments, treatment switches, and time to discontinuation in biologics-treated CD patients. We found correlations between CD and patient family history of gastrointestinal neoplasms. Our predictive model ranked 25 000 variables for their potential as risk factors for CD relapse. Of highest relative importance were past relapses and patients' age, as well as leukocyte, hemoglobin, and fibrinogen levels. CONCLUSION: Through NLP, we identified variables such as smoking as a risk factor and described treatment patterns with biologics in CD patients. CD relapse prediction highlighted the importance of patients' age and some biochemistry values, though it proved highly challenging and merits the assessment of risk factors for relapse in a clinical setting.

Activation of the glucocorticoid receptor rapidly triggers calcium-dependent serotonin release in vitro.

AIMS: Glucocorticoids rapidly provoke serotonin (5-HT) release in vivo. We aimed to investigate molecular mechanisms of glucocorticoid receptor (GR)-triggered 5-HT release. METHODS: Employing 1C11 cells to model 5-HT neurotransmission, immunofluorescence and Pearson's Correlation Coefficient were used to analyze colocalization of GR, 5-HT, vesicle membrane protein synaptotagmin 1 and vesicle dye FM4-64FX. FFN511 and FM4-64FX dyes as well as calcium imaging were used to visualize vesicular 5-HT release upon application of GR agonist dexamethasone, GR antagonist mifepristone and voltage-gated calcium channel (VGCC) inhibitors. RESULTS: GR, 5-HT, synaptotagmin 1 and FM4-64FX showed overlapping staining patterns, with Pearson's Correlation Coefficient indicating colocalization. Similarly to potassium chloride, dexamethasone caused a release of FFN511 and uptake of FM4-64FX, indicating vesicular 5-HT release. Mifepristone, calcium depletion and inhibition of L-type VGCC significantly diminished dexamethasone-induced vesicular 5-HT release. CONCLUSIONS: In close proximity to 5-HT releasing sites, activated GR rapidly triggers L-type VGCC-dependent vesicular 5-HT release. These findings provide a better understanding of the interrelationship between glucocorticoids and 5-HT release.

Transfer of SCN1A to the brain of adolescent mouse model of Dravet syndrome improves epileptic, motor, and behavioral manifestations.

Dravet syndrome is a genetic encephalopathy characterized by severe epilepsy combined with motor, cognitive, and behavioral abnormalities. Current antiepileptic drugs achieve only partial control of seizures and provide little benefit on the patient's neurological development. In >80% of cases, the disease is caused by haploinsufficiency of the SCN1A gene, which encodes the alpha subunit of the Nav1.1 voltage-gated sodium channel. Novel therapies aim to restore SCN1A expression in order to address all disease manifestations. We provide evidence that a high-capacity adenoviral vector harboring the 6-kb SCN1A cDNA is feasible and able to express functional Nav1.1 in neurons. In vivo, the best biodistribution was observed after intracerebral injection in basal ganglia, cerebellum, and prefrontal cortex. SCN1A A1783V knockin mice received the vector at 5 weeks of age, when most neurological alterations were present. Animals were protected from sudden death, and the epileptic phenotype was attenuated. Improvement of motor performance and interaction with the environment was observed. In contrast, hyperactivity persisted, and the impact on cognitive tests was variable (success in novel object recognition and failure in Morris water maze tests). These results provide proof of concept for gene supplementation in Dravet syndrome and indicate new directions for improvement.

Gene supplementation of CYP27A1 in the liver restores bile acid metabolism in a mouse model of cerebrotendinous xanthomatosis.

Cerebrotendinous xanthomatosis (CTX) is an autosomal recessive disease caused by mutations in the CYP27A1 gene, encoding the sterol 27-hydroxylase. Disruption of the bile acid biosynthesis pathway and accumulation of toxic precursors such as cholestanol cause chronic diarrhea, bilateral juvenile cataracts, tissue deposition of cholestanol and cholesterol (xanthomas), and progressive motor/neuropsychiatric alterations. We have evaluated the therapeutic potential of adeno-associated virus (AAV) vectors expressing CYP27A1 in a CTX mouse model. We found that a vector equipped with a strong liver-specific promoter (albumin enhancer fused with the α1 anti-trypsin promoter) is well tolerated and shows therapeutic effect at relatively low doses (1.5 × 1012 viral genomes [vg]/kg), when less than 20% of hepatocytes overexpress the transgene. This vector restored bile acid metabolism and normalized the concentration of most bile acids in plasma. By contrast, standard treatment (oral chenodeoxycholic acid [CDCA]), while reducing cholestanol, did not normalize bile acid composition in plasma and resulted in supra-physiological levels of CDCA and its derivatives. At the transcriptional level, only the vector was able to avoid the induction of xenobiotic-induced pathways in mouse liver. In conclusion, the overexpression of CYP27A1 in a fraction of hepatocytes using AAV vectors is well tolerated and provides full metabolic restoration in Cyp27a1 -/- mice. These features make gene therapy a feasible option for the etiological treatment of CTX patients.

A common risk factor in global credit and equity markets: An exploratory analysis of the subprime and the sovereign-debt crises.

This paper investigates the existence of a common risk factor across asset classes and geographical areas, focusing on the crises and post-crisis periods. This factor has important implications for diversification in investor's portfolios. We assess a worldwide sample of assets: Equity, Corporate CDS and Sovereign CDS from fourteen countries across Europe, US and Asia, and focus the analysis to a time window where diversification was crucial: the crises and post-crisis periods. To identify the factors that underlie asset movements and their composition, a Principal Component Analysis (PCA) is applied. We find that there is supporting evidence for the existence of a common risk factor that underlies 86 percent of our sample' assets movements and reflects a global non-diversifiable risk that permeates the financial system. The uncovered risk factor is robust across periods, and it is evenly distributed across assets and countries, with the noticeable exception of Japan, which follows a divergent risk pattern. This is also true, to a lesser extent, for the US, Canada and China. Within the Eurozone financial assets a higher commonality is uncovered. In addition, we confirm that the common risk factor becomes more important in times of crisis. The existence of a common risk factor limits the possibilities of diversification, in particular during turmoil periods when correlations among assets' movements rise. However, the fact that some geographies display a lower commonality can be used to improve the risk profile of diversified portfolios.

Exploiting graphlet decomposition to explain the structure of complex networks: the GHuST framework.

The characterization of topology is crucial in understanding network evolution and behavior. This paper presents an innovative approach, the GHuST framework to describe complex-network topology from graphlet decomposition. This new framework exploits the local information provided by graphlets to give a global explanation of network topology. The GHuST framework is comprised of 12 metrics that analyze how 2- and 3-node graphlets shape the structure of networks. The main strengths of the GHuST framework are enhanced topological description, size independence, and computational simplicity. It allows for straight comparison among different networks disregarding their size. It also reduces the complexity of graphlet counting, since it does not use 4- and 5-node graphlets. The application of the novel framework to a large set of networks shows that it can classify networks of distinct nature based on their topological properties. To ease network classification and enhance the graphical representation of them, we reduce the 12 dimensions to their main principal components. Furthermore, the 12 dimensions are easily interpretable. This enables the connection between complex-network analyses and diverse real applications.

Characteristics and Prognosis of COVID-19 in Patients with COPD.

Patients with Chronic Obstructive Pulmonary Disease (COPD) have a higher prevalence of coronary ischemia and other factors that put them at risk for COVID-19-related complications. We aimed to explore the impact of COVID-19 in a large population-based sample of patients with COPD in Castilla-La Mancha, Spain. We analyzed clinical data in electronic health records from 1 January to 10 May 2020 by using Natural Language Processing through the SAVANA Manager® clinical platform. Out of 31,633 COPD patients, 793 had a diagnosis of COVID-19. The proportion of patients with COVID-19 in the COPD population (2.51%; 95% CI 2.33-2.68) was significantly higher than in the general population aged >40 years (1.16%; 95% CI 1.14-1.18); p < 0.001. Compared with COPD-free individuals, COPD patients with COVID-19 showed significantly poorer disease prognosis, as evaluated by hospitalizations (31.1% vs. 39.8%: OR 1.57; 95% CI 1.14-1.18) and mortality (3.4% vs. 9.3%: OR 2.93; 95% CI 2.27-3.79). Patients with COPD and COVID-19 were significantly older (75 vs. 66 years), predominantly male (83% vs. 17%), smoked more frequently, and had more comorbidities than their non-COPD counterparts. Pneumonia was the most common diagnosis among COPD patients hospitalized due to COVID-19 (59%); 19% of patients showed pulmonary infiltrates suggestive of pneumonia and heart failure. Mortality in COPD patients with COVID-19 was associated with older age and prevalence of heart failure (p < 0.05). COPD patients with COVID-19 showed higher rates of hospitalization and mortality, mainly associated with pneumonia. This clinical profile is different from exacerbations caused by other respiratory viruses in the winter season.

Hospital Epidemics Tracker (HEpiTracker): Description and pilot study of a mobile app to track COVID-19 in hospital workers.

BACKGROUND: Hospital workers have been the most frequently and severely affected professional group during the COVID-19 pandemic, and have a big impact on transmission. In this context, innovative tools are required to measure the symptoms compatible with COVID-19, the spread of infection, and testing capabilities within hospitals in real time. OBJECTIVE: We aimed to develop and test an effective and user-friendly tool to identify and track symptoms compatible with COVID-19 in hospital workers. METHODS: We developed and pilot tested Hospital Epidemics Tracker (HEpiTracker), a newly designed app to track the spread of COVID-19 among hospital workers. Hospital staff in 9 hospital centers across 5 Spanish regions (Andalusia, Balearics, Catalonia, Galicia, and Madrid) were invited to download the app on their phones and to register their daily body temperature, COVID-19-compatible symptoms, and general health score, as well as any polymerase chain reaction and serological test results. RESULTS: A total of 477 hospital staff participated in the study between April 8 and June 2, 2020. Of note, both health-related (n=329) and non-health-related (n=148) professionals participated in the study; over two-thirds of participants (68.8%) were health workers (43.4% physicians and 25.4% nurses), while the proportion of non-health-related workers by center ranged from 40% to 85%. Most participants were female (n=323, 67.5%), with a mean age of 45.4 years (SD 10.6). Regarding smoking habits, 13.0% and 34.2% of participants were current or former smokers, respectively. The daily reporting of symptoms was highly variable across participating hospitals; although we observed a decline in adherence after an initial participation peak in some hospitals, other sites were characterized by low participation rates throughout the study period. CONCLUSIONS: HEpiTracker is an already available tool to monitor COVID-19 and other infectious diseases in hospital workers. This tool has already been tested in real conditions. HEpiTracker is available in Spanish, Portuguese, and English. It has the potential to become a customized asset to be used in future COVID-19 pandemic waves and other environments. TRIAL REGISTRATION: ClinicalTrials.gov NCT04326400; https://clinicaltrials.gov/ct2/show/NCT04326400.