The effects of central bank extraordinary measures on financial conditions: Evidence from Mexico

This paper analyses the effects of the extraordinary measures implemented by the Central Bank of Mexico during the COVID-19 pandemic on financial conditions. For this purpose, we estimate a factor-augmented vector autoregressive model for the period 2001–2021. Based on this model, we construct a Financial Conditions Index, estimate the response of this indicator and its components from a shock to the outstanding amount of these measures, and conduct a counterfactual exercise to further analyse the effect of the aforementioned measures. The main results indicate that these extraordinary measures seem to have contributed to improve financial conditions. In particular, we find that if these measures had not been implemented, the sovereign risk premium, the 10-year government bond yield, the slope of the yield curve, and the long- and short-term yield spreads between Mexico and the US would have been higher by around 56, 31, 27, 37, and 49 basis points in December 2020, respectively. At the same time, the Mexican peso/US dollar exchange rate and its volatility would have been higher by 5 and 2 percentage points, respectively. In turn, the Mexican stock market index would have been lower by 10 percentage points. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

A Novel Statistical and Neural Network Combined Approach for the Cloud Spot Market

The price of virtual machine instances in the Amazon EC2 spot model is often much lower than in the on-demand counterpart. However, this price reduction comes with a decrease in the availability guarantees. Several mechanisms have been proposed to analyze the spot model in the last years, employing different strategies. To our knowledge, there is no work that accurately captures the trade-off between spot price and availability, for short term analysis, and does long term analysis for spot price tendencies, in favor of user decision making. In this work, we propose (a) a utility-based strategy, that balances cost and availability of spot instances and is targeted to short-term analysis, and (b) a LSTM (Long Short Term Memory) neural network framework for long term spot price tendency analysis. Our experiments show that, for r4.2xlarge, 90 percent of spot bid suggestions ensured at least 5.73 hours of availability in the second quarter of 2020, with a bid price of approximately 38 percent of the on-demand price. The LSTM experiments were able to predict spot prices tendencies for several instance types with very low error. Our LSTM framework predicted an average value of 0.19 USD/hour for the r5.2xlarge instance type (Mean Squared Error [Formula Omitted]) for a 7-day period of time, which is about 37 percent of the on-demand price. Finally, we used our combined mechanism on an application that compares thousands of SARS-CoV-2 DNA sequences and show that our approach is able to provide good choices of instances, with low bids and very good availability.

Capital flows to emerging economies and global risk aversion during the COVID-19 pandemic

This paper analyses recent changes in the relative importance of the determinants of capital flows to emerging market economies. For this purpose, we estimate vector autoregressive (VAR) models for the period 2009–2021. Based on these models, we estimate the effects on debt flows from shocks to their determinants. Then, we quantify the contribution of each of the variables included in the model to explain the evolution of these flows in each month of the sample through a historical decomposition analysis. The main results indicate that the contribution of global risk aversion to explain the evolution of debt flows increased during March 2020 compared to the past, although its relative importance has decreased since, particularly as central banks in systemically important economies restored liquidity and the performance of financial markets improved. © 2023 John Wiley & Sons Ltd.

SARS-COV-2 INFECTION IN IBD: PANDEMIC WAVES AND PREDICTORS OF SEVERE OR PERSISTENT COVID-19

Background This study aimed to compare the risk of COVID-19 in patients with IBD versus the general population, and to evaluate predictors of infection acquisition, progression to severe forms, and risk of developing persistent COVID-19. We also assess the differences between cases across the different COVID-19 pandemic waves in our target population. Methods This single-center prospective, cohort study included consecutive IBD patients diagnosed of COVID-19 either by a positive polymerase chain reaction test and/or antigen test in nasopharyngeal swabs, or by anti-SARS-CoV-2 antibodies, and that they had a followup of at least 4 months. Using logistic regression, we evaluated cases versus IBD controls included in the IBD Unit database for predictors of COVID-19 acquisition. COVID-19 cases were distributed according to pandemic waves. Cox regression analysis was used for predictors of severe and persistent COVID-19. Results By May 31, 2021, 160 out of 1911 IBD patients (8.3%) were diagnosed with COVID-19. IBD patients had a similar adjusted incidence of COVID-19 (OR 0.94;95% CI 0.86-1.02;P=0.42), and a similar associated mortality ratio (OR 0.83;95% CI 0.6-1.06;P=0.48), compared to the general population. In multivariable analysis, treatment with biologics was associated with a higher risk (OR 2.22, 95% CI 1.54-3.2, P<0.001), and treatment with salicylates with a lower risk (OR 0.71, 95% CI 0.50-0.99, P=0.048) of contracting COVID-19. Sixty-two COVID-19 cases were diagnosed during the first wave of pandemic (until the end of June 2020), and 54 and 44 cases during the second and third waves (until the end of December 2020 and May 2021, respectively). (Figure 1) In multivariate analysis, first wave cases were associated with a higher risk of progression to severe forms of infection (OR 4.76, 95% CI 1.83-12.37, P= 0.001), and development of persistent COVID-19 (OR 2.4, 95% CI 1.16-4.95, P=0.018). Twenty-nine patients (18.1%) required hospitalization and were classified as severe COVID- 19, which was associated in multivariable analysis with age>48 (HR 3.68, P=0.007), cases diagnosed in the first wave (HR 6.04, P<0.001), and comorbidities (evaluated with Duke Severity of Illness Checklist [DUSOI], P<0.001). (Table 1) During a median follow-up of 8.4 months, 68 patients (42.5%) were diagnosed with persistent COVID-19. Multivariable analysis identified UC (OR 2.00, 95% CI 0.99-4.03, P=0.053), comorbidities (P=0.090), and being diagnosed during the first wave (OR 2.48, 95% CI 1.23-5.00, P=0.011) as risk factors for persistent COVID-19. Conclusion IBD patients have a similar risk of COVID- 19 and associated mortality as the general population. Cases diagnosed during the first wave of the pandemic had severe and persistent forms of COVID-19 more frequently. Age and comorbidity were the main risk factors for severe forms of the disease. (Figure Presented) (Table Presented)

The effect of laboratory-verified smoking on SARS-CoV-2 infection: results from the Troina sero-epidemiological survey.

Previous research yielded conflicting results on the association between cigarette smoking and risk of SARS-CoV-2 infection. Since the prevalence of smoking is high globally, the study of its impact on COVID-19 pandemic may have considerable implications for public health. This study is the first to investigate the association between the SARS-CoV-2 antibody sero-positivity and biochemically verified smoking status, to refine current estimates on this association. SARS-CoV-2-specific IgG and serum cotinine levels (a well-known marker of tobacco exposure) were assessed in a large sero-epidemiological survey conducted in the town of Troina (Sicily, Italy). A propensity score matching was carried out to reduce the effect of possible factors on SARS-CoV-2 infection risk among study participants. Of the 1785 subjects included in our study, one-third was classified as current smokers, based on serum cotinine levels. The overall proportion of subjects with positive serology for SARS-CoV-2 IgG was 5.4%. The prevalence of SARS-CoV-2 antibody positivity and previous COVID-19 diagnosis were reduced in smokers. This reduced prevalence persisted after adjusting for possible confounders (such as sex, age, previous infection, chronic conditions, and risk group) at regression analyses, and the point estimates based on the PS-matched models resulted consistent with those for the unmatched population. This study found a lower proportion of positive SARS-CoV-2 serology among current smokers, using direct laboratory measures of tobacco exposure and thus avoiding possible bias associated with self-reported smoking status. Results may also serve as a reference for future clinical research on potential pharmaceutical role of nicotine or nicotinic-cholinergic agonists against COVID-19.

Magnitude and Dynamics of the T-Cell Response to SARS-CoV-2 Infection and Vaccination

Background. T cells are central to the early identification and clearance of viral infections and support antibody generation by B cells, making them desirable for assessing the immune response to SARS-CoV-2 infection and vaccines. We combined 2 high-throughput immune profiling methods to create a quantitative picture of the SARS-CoV-2 T-cell response that is highly sensitive, durable, diagnostic, and discriminatory between natural infection and vaccination. Methods. We deeply characterized 116 convalescent COVID-19 subjects by experimentally mapping CD8 and CD4 T-cell responses via antigen stimulation to 545 Human Leukocyte Antigen (HLA) class I and 284 class II viral peptides. We also performed T-cell receptor (TCR) repertoire sequencing on 1815 samples from 1521 PCR-confirmed SARS-CoV-2 cases and 3500 controls to identify shared public TCRs from SARS-CoV-2-associated CD8 and CD4 T cells. Combining these approaches with additional samples from vaccinated individuals, we characterized the response to natural infection as well as vaccination by separating responses to spike protein from other viral targets. Results. We find that T-cell responses are often driven by a few immunodominant, HLA-restricted epitopes. As expected, the SARS-CoV-2 T-cell response peaks about 1-2 weeks after infection and is detectable at least several months after recovery. Applying these data, we trained a classifier to diagnose past SARS-CoV-2 infection based solely on TCR sequencing from blood samples and observed, at 99.8% specificity, high sensitivity soon after diagnosis (Day 3-7 = 85.1%;Day 8-14 = 94.8%) that persists after recovery (Day 29+/convalescent = 95.4%). Finally, by evaluating TCRs binding epitopes targeting all non-spike SARS-CoV-2 proteins, we were able to separate natural infection from vaccination with > 99% specificity. Conclusion. TCR repertoire sequencing from whole blood reliably measures the adaptive immune response to SARS-CoV-2 soon after viral antigenic exposure (before antibodies are typically detectable) as well as at later time points, and distinguishes post-infection vs. vaccine immune responses with high specificity. This approach to characterizing the cellular immune response has applications in clinical diagnostics as well as vaccine development and monitoring.

Sars-cov-2 infection in ibd: Pandemic waves and predictors of severe or persistent covid-19

Background: This study aimed to compare the risk of COVID-19 in patients with IBD versus the general population, and to evaluate predictors of infection acquisition, progression to severe forms, and risk of developing persistent COVID-19. We also assess the differences between cases across the different COVID-19 pandemic waves in our target population. Methods: This single-centre prospective, cohort study included consecutive IBD patients diagnosed of COVID-19 either by a positive polymerase chain reaction test and/or antigen test in nasopharyngeal swabs, or by anti-SARS-CoV-2 antibodies, and that they had a follow-up of at least 4 months. Using logistic regression, we evaluated cases versus IBD controls included in the IBD Unit database for predictors of COVID-19 acquisition. COVID-19 cases were distributed according to pandemic waves. Cox regression analysis was used for predictors of severe and persistent COVID-19. Results: By May 31, 2021, 160 out of 1911 IBD patients (8.3%) were diagnosed with COVID-19. IBD patients had a similar adjusted incidence of COVID-19 (OR 0.94;95% CI 0.86-1.02;P=0.42), and a similar associated mortality ratio (OR 0.83;95% CI 0.6-1.06;P=0.48), compared to the general population. In multivariable analysis, treatment with biologics was associated with a higher risk (OR 2.22, P<0.001), and treatment with salicylates with a lower risk (OR 0.71, P=0.048) of contracting COVID-19.(Table 1) 62 COVID-19 cases were diagnosed during the first wave of pandemic (until the end of June 2020), and 54 and 44 cases during the second and third waves (until the end of December 2020 and May 2021, respectively).(Figure 1) In multivariate analysis, first wave cases were associated with a higher risk of progression to severe forms of infection (OR 4.76, 95% CI 1.83-12.37, P=0.001), and development of persistent COVID-19 (OR 2.4, 95% CI 1.16-4.95, P=0.018). 29 patients (18.1%) required hospitalisation and were classified as severe COVID-19, which was associated in multivariable analysis with age>48 (HR 3.68, P=0.007), cases diagnosed in the first wave (HR 6.04, P<0.001), and comorbidities (evaluated with Duke Severity of Illness Checklist [DUSOI], P<0.001).(Table 2) During a median follow-up of 8.4 months, 68 patients (42.5%) were diagnosed with persistent COVID-19. Multivariable analysis identified UC (P=0.053), comorbidities (P=0.090), and being diagnosed during the first wave (P=0.011) as risk factors for persistent COVID-19.(Table 3) Conclusion: IBD patients have a similar risk of COVID-19 and associated mortality as the general population. Cases diagnosed during the first wave of the pandemic had severe and persistent forms of COVID-19 more frequently. Age and comorbidity were the main risk factors for severe forms of the disease.

Utility of telemedicine 3d transesophageal echocardiography in interventional procedures in covid-19 pandemic and its impact on physician learning

Background: Three-dimensional transesophageal echocardiography (3DTEE) is a diagnostic tool in cardiac procedures, but COVID-19 has made utility challenging. Training junior (JR) attendings and fellows in 3DTEE guidance cases in procedural rooms make it tough to maintain adequate social distance. Collaboration Live (CL) is an application on the ultrasound machine that allows for live communication and access to real time images with a remote user. The study aims were to assess the usefulness of CL during 3DTEE guided procedures and its impact on physician learning. Methods: 3DTEE was obtained in 8 cohorts ranging 4-52 years of age on the EPIQ ultrasound machine. CL was used in transcatheter atrial/ventricular septal defect closures, transvenous pacemaker lead placement, and Fontan fenestration closure. 3DTEE was directed by a senior (SR) 3D attending over CL at a remote workstation while a JR attending, cardiac fellow, and echocardiographer performed 3DTEE in the procedural room. A CL post survey was given. Wait time from received page to the start of TEE, TEE duration, fluoroscopy time, absorbed X-ray dose, and saved amount of personal protective equipment (PPE) was noted. Results: A JR attending was in 8/8 cases. CL decreased reliance on SR attending and improved independence in 86% of cases, and no change in 14%. A fellow was in 6/8 cases. CL decreased reliance on SR 3D attending and increased independence in 67% of cases, and no change in 33%. A SR attending was remotely present in all cases. CL allowed flexibility for SR attending in 89% of cases and no flexibility in 11%. Preferred learning skill, comfort performing/giving results over CL, learning/teaching impact, remote user wait time, reduced radiation exposure, and saved amount of PPE are shown in Table 1. Conclusions: CL is valuable in 3DTEE guidance procedures. It increases cost savings by reducing PPE and promotes learner independence. CL allows flexibility and reduces radiation exposure for remote users.

SARS-CoV-2 infection of primary human lung epithelium for COVID-19 modeling and drug discovery

Coronavirus disease 2019 (COVID-19) is the latest respiratory pandemic resulting from zoonotic transmission of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2). Severe symptoms include viral pneumonia secondary to infection and inflammation of the lower respiratory tract, in some cases causing death. We developed primary human lung epithelial infection models to understand responses of proximal and distal lung epithelium to SARS-CoV-2 infection. Differentiated air-liquid interface cultures of proximal airway epithelium and 3D organoid cultures of alveolar epithelium were readily infected by SARS-CoV-2 leading to an epithelial cell-autonomous proinflammatory response. We validated the efficacy of selected candidate COVID-19 drugs confirming that Remdesivir strongly suppressed viral infection/replication. We provide a relevant platform for studying COVID-19 pathobiology and for rapid drug screening against SARS-CoV-2 and future emergent respiratory pathogens. One Sentence Summary: A novel infection model of the adult human lung epithelium serves as a platform for COVID-19 studies and drug discovery.

What Do We Know about Candida auris? State of the Art, Knowledge Gaps, and Future Directions.

Candida auris has unprecedently emerged as a multidrug resistant fungal pathogen, considered a serious global threat due to its potential to cause nosocomial outbreaks and deep-seated infections with staggering transmissibility and mortality, that has put health authorities and institutions worldwide in check for more than a decade now. Due to its unique features not observed in other yeasts, it has been categorised as an urgent threat by the Centers for Disease Control and Prevention and other international agencies. Moreover, epidemiological alerts have been released in view of the increase of healthcare-associated C. auris outbreaks in the context of the COVID-19 pandemic. This review summarises the current evidence on C. auris since its first description, from virulence to treatment and outbreak control, and highlights the knowledge gaps and future directions for research efforts.

A CPU-FPGA heterogeneous approach for biological sequence comparison using high-level synthesis

Summary This article presents a high-level synthesis implementation of the longest common subsequence (LCS) algorithm combined with a weighted-based scheduler for comparing biological sequences prioritizing energy consumption or execution time. The LCS algorithm has been thoroughly tailored using Vivado High-Level Synthesis tool, which is able to synthesize register transfer level (RTL) from high-level language descriptions, such as C/C++. Performance and energy consumption results were obtained with a CPU Intel Core i7-3770 CPU and an Alpha-Data ADM-PCIE-KU3 board that has a Xilinx Kintex UltraScale XCKU060 FPGA chip. We executed a batch of 20 comparisons of sequences on 10k, 20k, and 50k sizes. Our experiments showed that the energy consumption on the combined approach was significantly lower when compared to the CPU, achieving 75% energy reduction on 50k comparisons. We also used the tool proposed in this article to do a case study on Covid-19, with real SARS-CoV-2 sequences, comparing their LCS scores.

SARS-CoV-2 infection of primary human lung epithelium for COVID-19 modeling and drug discovery.

Coronavirus disease 2019 (COVID-19) is the latest respiratory pandemic resulting from zoonotic transmission of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2). Severe symptoms include viral pneumonia secondary to infection and inflammation of the lower respiratory tract, in some cases causing death. We developed primary human lung epithelial infection models to understand responses of proximal and distal lung epithelium to SARS-CoV-2 infection. Differentiated air-liquid interface cultures of proximal airway epithelium and 3D organoid cultures of alveolar epithelium were readily infected by SARS-CoV-2 leading to an epithelial cell-autonomous proinflammatory response. We validated the efficacy of selected candidate COVID-19 drugs confirming that Remdesivir strongly suppressed viral infection/replication. We provide a relevant platform for studying COVID-19 pathobiology and for rapid drug screening against SARS-CoV-2 and future emergent respiratory pathogens. ONE SENTENCE SUMMARY: A novel infection model of the adult human lung epithelium serves as a platform for COVID-19 studies and drug discovery.