Comparing novel small-angle x-ray scattering approaches for absolute size and number concentration measurements of spherical SiO2particles to established methods.

Biomedical analytical applications, as well as the industrial production of high-quality nano- and sub-micrometre particles, require accurate methods to quantify the absolute number concentration of particles. In this context, small-angle x-ray scattering (SAXS) is a powerful tool to determine the particle size and concentration traceable to the Système international d'unités (SI). Therefore, absolute measurements of the scattering cross-section must be performed, which require precise knowledge of all experimental parameters, such as the electron density of solvent and particles, whereas the latter is often unknown. Within the present study, novel SAXS-based approaches to determine the size distribution, density and number concentrations of sub-micron spherical silica particles with narrow size distributions and mean diameters between 160 nm and 430 nm are presented. For the first-time traceable density and number concentration measurements of silica particles are presented and current challenges in SAXS measurements such as beam-smearing, poorly known electron densities and moderately polydisperse samples are addressed. In addition, and for comparison purpose, atomic force microscopy has been used for traceable measurements of the size distribution and single particle inductively coupled plasma mass spectrometry with the dynamic mass flow approach for the accurate quantification of the number concentrations of silica particles. The possibilities and limitations of the current approaches are critically discussed in this study.

Identification of COVID-19 patients at risk of hospital admission and mortality: a European multicentre retrospective analysis of mid-regional pro-adrenomedullin.

BACKGROUND: Mid-Regional pro-Adrenomedullin (MR-proADM) is an inflammatory biomarker that improves the prognostic assessment of patients with sepsis, septic shock and organ failure. Previous studies of MR-proADM have primarily focussed on bacterial infections. A limited number of small and monocentric studies have examined MR-proADM as a prognostic factor in patients infected with SARS-CoV-2, however there is need for multicenter validation. An evaluation of its utility in predicting need for hospitalisation in viral infections was also performed. METHODS: An observational retrospective analysis of 1861 patients, with SARS-CoV-2 confirmed by RT-qPCR, from 10 hospitals across Europe was performed. Biomarkers, taken upon presentation to Emergency Departments (ED), clinical scores, patient demographics and outcomes were collected. Multiclass random forest classifier models were generated as well as calculation of area under the curve analysis. The primary endpoint was hospital admission with and without death. RESULTS: Patients suitable for safe discharge from Emergency Departments could be identified through an MR-proADM value of ≤ 1.02 nmol/L in combination with a CRP (C-Reactive Protein) of ≤ 20.2 mg/L and age ≤ 64, or in combination with a SOFA (Sequential Organ Failure Assessment) score < 2 if MR-proADM was ≤ 0.83 nmol/L regardless of age. Those at an increased risk of mortality could be identified upon presentation to secondary care with an MR-proADM value of > 0.85 nmol/L, in combination with a SOFA score ≥ 2 and LDH > 720 U/L, or in combination with a CRP > 29.26 mg/L and age ≤ 64, when MR-proADM was > 1.02 nmol/L. CONCLUSIONS: This international study suggests that for patients presenting to the ED with confirmed SARS-CoV-2 infection, MR-proADM in combination with age and CRP or with the patient's SOFA score could identify patients at low risk where outpatient treatment may be safe.

Circulating levels of calprotectin, a signature of neutrophil activation in prediction of severe respiratory failure in COVID-19 patients: a multicenter, prospective study (CalCov study).

OBJECTIVE: Severe COVID-19 is characterized by a dysregulated immune response in which neutrophils play a critical role. Calprotectin reflects neutrophil activation and is involved in the self-amplifying thrombo-inflammatory storm in severe COVID-19. We aimed to evaluate the role of calprotectin in early prediction of severity in COVID-19 patients. METHODS: This was a multicenter prospective observational study enrolling consecutive adult COVID-19 patients. On arrival to emergency department, blood samples were collected for laboratory tests, including serum calprotectin. The primary outcome was severe respiratory failure requiring invasive mechanical ventilation and the secondary outcome was need for Intensive Care Unit (ICU) admission. RESULTS: Study population included 395 patients, 57 (14.4%) required invasive mechanical ventilation and 100 (25.3%) were admitted to ICU. Median serum calprotectin levels were significantly higher in intubated (3.73 mg/L vs. 2.63 mg/L; p < 0.001) and ICU patients (3.48 mg/L vs. 2.60 mg/L; p = 0.001). Calprotectin showed a significant accuracy to predict the need for invasive mechanical ventilation (ROC AUC 0.723) and ICU admission (ROC AUC 0.650). In multivariate analysis, serum calprotectin was an independent predictor of invasive mechanical ventilation (OR 1.161) and ICU admission (OR 1.068). CONCLUSION: Serum calprotectin can be used as an early predictor of severity in COVID-19 patients.

Dyslipidemia and Inflammation as Hallmarks of Oxidative Stress in COVID-19: A Follow-Up Study.

Recent works have demonstrated a significant reduction in cholesterol levels and increased oxidative stress in patients with coronavirus disease 2019 (COVID-19). The cause of this alteration is not well known. This study aimed to comprehensively evaluate their possible association during the evolution of COVID-19. This is an observational prospective study. The primary endpoint was to analyze the association between lipid peroxidation, lipid, and inflammatory profiles in COVID-19 patients. A multivariate regression analysis was employed. The secondary endpoint included the long-term follow-up of lipid profiles. COVID-19 patients presented significantly lower values in their lipid profile (total, low, and high-density lipoprotein cholesterol) with greater oxidative stress and inflammatory response compared to the healthy controls. Lipid peroxidation was the unique oxidative parameter with a significant association with the total cholesterol (OR: 0.982; 95% CI: 0.969-0.996; p = 0.012), IL1-RA (OR: 0.999; 95% CI: 0.998-0.999; p = 0.021) IL-6 (OR: 1.062; 95% CI: 1.017-1.110; p = 0.007), IL-7 (OR: 0.653; 95% CI: 0.433-0.986; p = 0.042) and IL-17 (OR: 1.098; 95% CI: 1.010-1.193; p = 0.028). Lipid abnormalities recovered after the initial insult during long-term follow-up (IQR 514 days); however, those with high LPO levels at hospital admission had, during long-term follow-up, an atherogenic lipid profile. Our study suggests that oxidative stress in COVID-19 is associated with derangements of the lipid profile and inflammation. Survivors experienced a recovery in their lipid profiles during long-term follow-up, but those with stronger oxidative responses had an atherogenic lipid profile.

MR-proADM as marker of endotheliitis predicts COVID-19 severity.

BACKGROUND: Early identification of patients at high risk of progression to severe COVID-19 constituted an unsolved challenge. Although growing evidence demonstrates a direct association between endotheliitis and severe COVID-19, the role of endothelial damage biomarkers has been scarcely studied. We investigated the relationship between circulating mid-regional proadrenomedullin (MR-proADM) levels, a biomarker of endothelial dysfunction, and prognosis of SARS-CoV-2-infected patients. METHODS: Prospective observational study enrolling adult patients with confirmed COVID-19. On admission to emergency department, a blood sample was drawn for laboratory test analysis. Primary and secondary endpoints were 28-day all-cause mortality and severe COVID-19 progression. Area under the curve (AUC) and multivariate regression analysis were employed to assess the association of the biomarker with the established endpoints. RESULTS: A total of 99 patients were enrolled. During hospitalization, 25 (25.3%) cases progressed to severe disease and the 28-day mortality rate was of 14.1%. MR-proADM showed the highest AUC to predict 28-day mortality (0.905; [CI] 95%: 0.829-0.955; P < .001) and progression to severe disease (0.829; [CI] 95%: 0.740-0.897; P < .001), respectively. MR-proADM plasma levels above optimal cut-off (1.01 nmol/L) showed the strongest independent association with 28-day mortality risk (hazard ratio [HR]: 10.470, 95% CI: 2.066-53.049; P < .005) and with progression to severe disease (HR: 6.803, 95% CI: 1.458-31.750; P = .015). CONCLUSION: Mid-regional proadrenomedullin was the biomarker with highest performance for prognosis of death and progression to severe disease in COVID-19 patients and represents a promising predictor for both outcomes, which might constitute a potential tool in the assessment of prognosis in early stages of this disease.

Low-density lipoprotein cholesterol levels are associated with poor clinical outcomes in COVID-19.

BACKGROUND AND AIMS: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the sole causative agent of coronavirus infectious disease-19 (COVID-19). METHODS AND RESULTS: We performed a retrospective single-center study of consecutively admitted patients between March 1st and May 15th, 2020, with a definitive diagnosis of SARS-CoV-2 infection. The primary end-point was to evaluate the association of lipid markers with 30-days all-cause mortality in COVID-19. A total of 654 patients were enrolled, with an estimated 30-day mortality of 22.8% (149 patients). Non-survivors had lower total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-c) levels during the entire course of the disease. Both showed a significant inverse correlation with inflammatory markers and a positive correlation with lymphocyte count. In a multivariate analysis, LDL-c ≤ 69 mg/dl (hazard ratio [HR] 1.94; 95% confidence interval [CI] 1.14-3.31), C-reactive protein >88 mg/dl (HR 2.44; 95% CI, 1.41-4.23) and lymphopenia <1000 (HR 2.68; 95% CI, 1.91-3.78) at admission were independently associated with 30-day mortality. This association was maintained 7 days after admission. Survivors presented with complete normalization of their lipid profiles on short-term follow-up. CONCLUSION: Hypolipidemia in SARS-CoV-2 infection may be secondary to an immune-inflammatory response, with complete recovery in survivors. Low LDL-c serum levels are independently associated with higher 30-day mortality in COVID-19 patients.

Corticosteroid Pulses for Hospitalized Patients with COVID-19: Effects on Mortality.

OBJECTIVES: To assess the influence of corticosteroid pulses on 60-day mortality in hospitalized patients with severe COVID-19. METHODS: We designed a multicenter retrospective cohort study in three teaching hospitals of Castilla y León, Spain (865,096 people). We selected patients with confirmed COVID-19 and lung involvement with a pO2/FiO2<300, excluding those exposed to immunosuppressors before or during hospitalization, patients terminally ill at admission, or those who died in the first 24 hours. We performed a propensity score matching (PSM) adjusting covariates that modify the probability of being treated. Then, we used a Cox regression model in the PSM group to consider factors affecting mortality. RESULTS: From 2933 patients, 257 fulfilled the inclusion and exclusion criteria. 124 patients were on corticosteroid pulses (250 mg of methylprednisolone for three days), and 133 were not. 30.3% (37/122) of patients died in the corticosteroid pulse group and 42.9% (57/133) in the nonexposed cohort. These differences (12.6%, 95% CI [8·54-16.65]) were statically significant (log-rank 4.72, p = 0, 03). We performed PSM using the exact method. Mortality differences remained in the PSM group (log-rank 5.31, p = 0.021) and were still significant after a Cox regression model (HR for corticosteroid pulses 0.561; p = 0.039). CONCLUSIONS: This study provides evidence about treatment with corticosteroid pulses in severe COVID-19 that might significantly reduce mortality. Strict inclusion and exclusion criteria with that selection process set a reliable frame to compare mortality in both the exposed and nonexposed groups.

MR- proADM to detect specific types of organ failure in infection.

BACKGROUND: Following the SEPSIS-3 consensus, detection of organ failure as assessed by the SOFA (Sequential Organ Failure Assessment) score, is mandatory to detect sepsis. Calculating SOFA outside of the Intensive Care Unit (ICU) is challenging. The alternative in this scenario, the quick SOFA, is very specific but less sensible. Biomarkers could help to detect the presence of organ failure secondary to infection either in ICU and non-ICU settings. MATERIALS AND METHODS: We evaluated the ability of four biomarkers (C-Reactive protein (CRP), lactate, mid-regional proadrenomedullin (MR-proADM) and procalcitonin (PCT)) to detect each kind of organ failure considered in the SOFA in 213 patients with infection, sepsis or septic shock, by using multivariate regression analysis and calculation of the area under the receiver operating curve (AUROC). RESULTS: In the multivariate analysis, MR-proADM was an independent predictor of five different failures (respiratory, coagulation, cardiovascular, neurological and renal). In turn, lactate predicted three (coagulation, cardiovascular and neurological) and PCT two (cardiovascular and renal). CRP did not predict any of the individual components of SOFA. The highest AUROCs were those of MR-proADM and PCT to detect cardiovascular (AUROC, CI95%): MR-proADM (0.82 [0.76-0.88]), PCT (0.81 [0.75-0.87] (P < .05) and renal failure: MR-proADM (0.87 [0.82-0.92]), PCT (0.81 [0.75-0.86]), (P < .05). None of the biomarkers tested was able to detect hepatic failure. CONCLUSIONS: In patients with infection, MR-proADM was the biomarker detecting the largest number of SOFA score components, with the exception of hepatic failure.

Quantification of Immune Dysregulation by Next-generation Polymerase Chain Reaction to Improve Sepsis Diagnosis in Surgical Patients.

OBJECTIVES: To quantify immunological dysfunction in surgical patients with presence/absence of sepsis using a droplet digital polymerase chain reaction (ddPCR) transcriptomic analysis. The study also aims to evaluate this approach for improving identification of sepsis in these patients. BACKGROUND: Immune dysregulation is a central event in sepsis. Quantification of the expression of immunological genes participating in the pathogenesis of sepsis could represent a new avenue to improve its diagnosis. METHODS: Expression of 6 neutrophil protease genes (MMP8, OLFM4, LCN2/NGAL, LTF, PRTN3, MPO) and also of 5 genes involved in the immunological synapse (HLA-DRA, CD40LG, CD3E, CD28, ICOS) was quantified in blood from 101 surgical patients with sepsis, 53 uninfected surgical patients, and 16 blood donors by using ddPCR. Areas under receiver operating characteristic curves (AUROC) and multivariate regression analysis were employed to test individual genes and gene ratios to identify sepsis, in comparison with procalcitonin. RESULTS: Sepsis-induced overexpression of neutrophil protease genes and depressed expression of immunological synapse genes. MMP8/HLA-DRA, LCN2/HLA-DRA outperformed procalcitonin in differentiating between patients with sepsis and surgical controls in the AUROC analysis: LCN2/HLA-DRA: 0.90 (0.85-0.96), MMP8/HLA-DRA: 0.89 (0.84-0.95), procalcitonin: 0.80 (0.73-0.88) (AUROC, confidence interval 95%), and also in the multivariate analysis: LCN2/HLA-DRA: 8.57 (2.25-32.62); MMP8/HLA-DRA: 8.03 (2.10-30.76), procalcitonin: 4.20 (1.15-15.43) [odds ratio (confidence interval 95%)]. Gene expression levels of HLA-DRA were an independent marker of hospital mortality. CONCLUSIONS: Quantifying the transcriptomic ratios MMP8/HLA-DRA, LCN2/HLA-DRA by ddPCR is a promising approach to improve sepsis diagnosis in surgical patients.

A Prognostic Enrichment Strategy for Selection of Patients With Acute Respiratory Distress Syndrome in Clinical Trials.

OBJECTIVES: Incomplete or ambiguous evidence for identifying high-risk patients with acute respiratory distress syndrome for enrollment into randomized controlled trials has come at the cost of an unreasonable number of negative trials. We examined a set of selected variables early in acute respiratory distress syndrome to determine accurate prognostic predictors for selecting high-risk patients for randomized controlled trials. DESIGN: A training and testing study using a secondary analysis of data from four prospective, multicenter, observational studies. SETTING: A network of multidisciplinary ICUs. PATIENTS: We studied 1,200 patients with moderate-to-severe acute respiratory distress syndrome managed with lung-protective ventilation. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We evaluated different thresholds for patient's age, PaO2/FIO2, plateau pressure, and number of extrapulmonary organ failures to predict ICU outcome at 24 hours of acute respiratory distress syndrome diagnosis. We generated 1,000 random scenarios as training (n = 900, 75% of population) and testing (n = 300, 25% of population) datasets and averaged the logistic coefficients for each scenario. Thresholds for age (< 50, 50-70, > 70 yr), PaO2/FIO2 (≤ 100, 101-150, > 150 mm Hg), plateau pressure (< 29, 29-30, > 30 cm H2O), and number of extrapulmonary organ failure (< 2, 2, > 2) stratified accurately acute respiratory distress syndrome patients into categories of risk. The model that included all four variables proved best to identify patients with the highest or lowest risk of death (area under the receiver operating characteristic curve, 0.86; 95% CI, 0.84-0.88). Decision tree analyses confirmed the accuracy and robustness of this enrichment model. CONCLUSIONS: Combined thresholds for patient's age, PaO2/FIO2, plateau pressure, and extrapulmonary organ failure provides prognostic enrichment accuracy for stratifying and selecting acute respiratory distress syndrome patients for randomized controlled trials.

Composed endotypes to guide antibiotic discontinuation in sepsis.

Overuse of empiric antibiotic therapy in the ICU is responsible for promoting the dissemination of multidrug-resistant (MDR) bacteria. Shortened antibiotic treatment duration could contribute to palliating the emergence of MDR. Uncertainty about patient evolution is a major concern for deciding to stop antibiotics. Biomarkers could represent a complementary tool to identify those patients for whom antibiotic treatment could be safely discontinued. The biomarker most extensively studied to guide antibiotic withdrawal is procalcitonin (PCT), but its real impact on decreasing the duration of antibiotic treatment is a matter of controversy. Combining biomarkers to rule out complicated outcomes in sepsis patients could represent a better option. Some candidate biomarkers, including mid-regional proadrenomedullin, the percentage of human leukocyte antigen DR (HLA-DR)-positive monocytes, means of fluorescence intensities of HLA-DR on monocytes, interleukin-7 receptor expression levels, immunoglobulin M levels in the serum or the absence of increased proteolysis, have already demonstrated the potential to exclude the risk of progression to septic shock, nosocomial infections, and mortality when tested along the sepsis course. Other promising biomarkers to rule out complicated outcomes are neutrophil protease activity, the adaptive/coagulopathic signatures identified by whole transcriptome analysis by Sweeney et al., and the SRS1 signature identified by Davenport et al. In conclusion, there are a number of promising biomarkers involved in proteolytic, vascular, immunological, and coagulation alterations that could be useful to build composed endotypes to predict uncomplicated outcomes in sepsis. These endotypes could help to identify patients deserving the discontinuation of antibiotics.

World Workshop on Oral Medicine VII: Biomarkers predicting lymphoma in the salivary glands of patients with Sjögren's syndrome-A systematic review.

OBJECTIVE: To conduct a systematic review of studies exploring potential biomarkers for development, course, and efficacy of treatment of lymphomas in salivary glands of patients with Sjögren's syndrome. MATERIAL AND METHODS: Eligible studies were identified through a comprehensive search of two databases, that is, PubMed and EMBASE. Quality of included articles was assessed with the "Quality In Prognosis Studies" (QUIPS) tool. The "CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies" (CHARMS) was used to facilitate data extraction. RESULTS: Fifty-eight studies met the inclusion criteria. Only one study assessed the progression of lymphoma. Moderate risk of bias was detected in "outcome measurement," "study participation," and "study confounding" domains. Parotid gland enlargement, mixed monoclonal cryoglobulins, and low C4 levels represented strongest predictors of lymphoma development. The role of histological biomarkers, and specifically germinal centers, remains controversial. Clinical and methodological heterogeneity across studies precluded conduct of a meta-analysis. CONCLUSIONS: Specific biomarkers in combination with clinical manifestations represent potential candidates for advancing precision medicine approaches to lymphoma prediction in patients with Sjögren's syndrome. Current focus has increasingly been on genetic and epigenetic markers as candidate predictors. Predictive accuracy of key biomarker candidates remains to be tested in well-designed prospectively followed Sjögren's syndrome cohorts.

World Workshop on Oral Medicine VII: Prognostic biomarkers in oral leukoplakia: A systematic review of longitudinal studies.

OBJECTIVE: To identify the prognostic biomarker candidates for stratification and long-term surveillance of oral leukoplakia progressing to cancer via a systematic literature review. MATERIALS AND METHODS: Systematic searches with no date restrictions were conducted on March 29, 2018, targeting the databases PubMed (Ovid), EMBASE (Ovid), EBM (Ovid), and Web of Science (ISI). Bias was assessed using the Quality in Prognosis Studies tool. Biomarkers were stratified based on hallmarks of cancer. RESULTS: Inclusion criteria were met by 25 of 3,415 studies. A range of biomarkers were evaluated experimentally for risk stratification, prognosis, and surveillance of oral leukoplakia in tissue, blood, and saliva. However, the studies were highly heterogeneous and require further validation. Biomarkers reported in these studies included inflammatory or oxidative markers, growth factors, ion channels, genetic and cellular regulatory factors, and epigenetic biomarkers. Studies tended to include small sample sizes, under-reported or variably reported histopathological data, did not address potential confounding, reported limited/variable follow-up data, or lacked a control group. Inclusion of subsets from chemoprevention trials may have introduced bias regarding reported malignant transformation rates and accuracy of prognostic biomarkers. CONCLUSIONS: This review identified insufficient longitudinal evidence to support validated prognostic biomarkers for oral leukoplakia. Further studies are needed to identify molecular targets with the potential to mitigate risk of malignant transformation.

Age, PaO2/FIO2, and Plateau Pressure Score: A Proposal for a Simple Outcome Score in Patients With the Acute Respiratory Distress Syndrome.

OBJECTIVES: Although there is general agreement on the characteristic features of the acute respiratory distress syndrome, we lack a scoring system that predicts acute respiratory distress syndrome outcome with high probability. Our objective was to develop an outcome score that clinicians could easily calculate at the bedside to predict the risk of death of acute respiratory distress syndrome patients 24 hours after diagnosis. DESIGN: A prospective, multicenter, observational, descriptive, and validation study. SETTING: A network of multidisciplinary ICUs. PATIENTS: Six-hundred patients meeting Berlin criteria for moderate and severe acute respiratory distress syndrome enrolled in two independent cohorts treated with lung-protective ventilation. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Using individual demographic, pulmonary, and systemic data at 24 hours after acute respiratory distress syndrome diagnosis, we derived our prediction score in 300 acute respiratory distress syndrome patients based on stratification of variable values into tertiles, and validated in an independent cohort of 300 acute respiratory distress syndrome patients. Primary outcome was in-hospital mortality. We found that a 9-point score based on patient's age, PaO2/FIO2 ratio, and plateau pressure at 24 hours after acute respiratory distress syndrome diagnosis was associated with death. Patients with a score greater than 7 had a mortality of 83.3% (relative risk, 5.7; 95% CI, 3.0-11.0), whereas patients with scores less than 5 had a mortality of 14.5% (p < 0.0000001). We confirmed the predictive validity of the score in a validation cohort. CONCLUSIONS: A simple 9-point score based on the values of age, PaO2/FIO2 ratio, and plateau pressure calculated at 24 hours on protective ventilation after acute respiratory distress syndrome diagnosis could be used in real time for rating prognosis of acute respiratory distress syndrome patients with high probability.

The original sins of clinical trials with intravenous immunoglobulins in sepsis.

Intravenous immunoglobulins (IVIGs) have not yet demonstrated robust evidence in the benefit for treatment of sepsis. In spite of multiple clinical trials performed with IVIG in sepsis, it remains an experimental therapy for this severe condition. Nonetheless, these trials do not address a number of potential confounding factors, concerning both the patient and the IVIG preparations, which could greatly affect the final result. To name a few, endogenous levels of immunoglobulin isotypes and subclasses are not assessed prior to treatment. The presence/absence of patient antibodies against the microorganism(s) causing sepsis is not evaluated. The accuracy of antibiotic prescription is not included as an adjusting variable. The degree of patient immunosuppression (previous or induced by sepsis) is not documented. In turn, the concentration and antimicrobial specificities of the antibodies contained in the batches of IVIG are not assessed. Neither the pharmacokinetics of IVIG nor its potential immunomodulatory effects are evaluated. In addition, the concept of 'window of opportunity' for IVIG administration following diagnosis of sepsis is not considered. In conclusion, addressing these factors could help to individualise treatment with IVIG for sepsis, which could enhance the opportunities of this drug to show benefits in terms of survival in this severe condition.

West Nile virus in Mexico: Why vectors matter for explaining the current absence of epidemics.

Since 2002, West Nile Virus (WNV) has been reported in 18 states in Mexico, either by PCR or serological testing. However, it is believed that the virus is present in more states. Only four states (out of 32) have reported confirmed human cases, and one state has serological evidence. In the country, WNV is present in mainly horses and birds, but its presence extends to crocodiles, felines, canines, swines, donkeys, caprines, antilopes, cattle, bats, and camelids. Positive mosquito species include Aedes and Culex spp. Different hypotheses have been proposed to explain the absence of WNV epidemics in Latin America. Since some regions of Mexico and the United States share ecological and climatic conditions, these hypotheses may not be sufficient to account for the absence of WNV outbreaks or epidemics. This paper discusses the proposed ideas and attempts to contextualize them for Mexico, particularly for the U.S.-Mexico border, where WNV infections have been reported in humans, horses, and mosquitoes. We propose that integration of urban ecology and entomology knowledge is needed to better understand the absence of WN cases in Mexico.

Traceable characterization of hollow organosilica beads as potential reference materials for extracellular vesicle measurements with optical techniques.

The concentration of cell-type specific extracellular vesicles (EVs) is a promising biomarker for various diseases. However, concentrations of EVs measured by optical techniques such as flow cytometry (FCM) or particle tracking analysis (PTA)  in clinical practice are incomparable. To allow reliable and comparable concentration measurements suitable reference materials (RMs) and SI-traceable (SI-International system of units) methods are required. Hollow organosilica beads (HOBs) are promising RM candidates for concentration measurements of EVs based on light scattering, as the shape, low refractive index, and number concentration of HOBs are comparable to EVs of the respective size range that can be detected with current optical instrumentation. Here, we present traceable methods for measuring the particle size distribution of four HOB types in the size range between 200 and 500 nm by small-angle X-ray scattering (SAXS) and atomic force microscopy (AFM), as well as the number concentration by single-particle inductively coupled plasma mass spectrometry (spICP-MS). Based on the size and shape results, traceable reference values were obtained to additionally determine the refractive index of the shell of the HOB samples by FCM. Furthermore, the estimated refractive indexes of the HOBs plausibly agree with the refractive indexes of EVs of corresponding size. Due to their narrow size distribution and their similar shape, and low refractive index, all HOB samples studied are suitable RM candidates for calibration of the measured sample volume by optical methods within the photon wavelength range used, and thus for calibration of number concentration measurements of EVs in the size range indicated. This was confirmed as the number concentration values obtained by PTA and two independent flow cytometric measurements agreed with the concentration reference values obtained by two independent spICP-MS measurements within the calculated uncertainty limits.

Clinical value of the red blood cell distribution width to albumin ratio in the assessment of prognosis in critically ill patients with sepsis: a retrospective analysis.

Background: Red blood cell (RBC) distribution width (RDW) to albumin ratio is a novel biomarker and its prognostic effect on critically ill patients with sepsis has not been extensively investigated. The objective of this study was to identify the prognostic value of the RDW to albumin ratio in these patients. Methods: Data were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. A Cox proportional hazards model and restricted cubic spline model were used to determine the association of RDW to albumin ratio with mortality. Receiver operating characteristic (ROC) curves and Kaplan-Meier survival curves were applied, and the area under the curve (AUC) was used to compare the predictive value. Results: A total of 3,969 eligible patients were enrolled. The median RDW to albumin ratio was significantly higher in non-survivors than in survivors at 30 and 90 days. Patients were divided into groups according to the RDW to albumin ratio, and the risk of 30- and 90-day mortality markedly increased in the group with a higher ratio. The relationship between the RDW to albumin ratio as a continuous variable and 30-day mortality also showed an upward trend in the restricted cubic spline. The AUC of the RDW to albumin ratio was 0.633 in discriminating 30-day mortality which was similar to that of the lactate to albumin ratio (AUC =0.617; P=0.133) and higher than that of the neutrophil percentage to albumin ratio (AUC =0.559; P<0.001). Conclusions: The RDW to albumin ratio is a promising biomarker for assessing the prognosis of critically ill patients with sepsis. Its predictive value in determining mortality was found to be similar to that of the lactate to albumin ratio and superior to that of the neutrophil percentage to albumin ratio.

Immunological monitoring to prevent and treat sepsis.

The clinical, human and economic burden associated with sepsis is huge. Initiatives such as the Surviving Sepsis Campaign aim to effectively reduce risk of death from severe sepsis and septic shock. Nonetheless, although substantial benefits raised from the implementation of this campaign have been obtained, much work remains if we are to realise the full potential promised by this strategy. A deeper understanding of the processes leading to sepsis is necessary before we can design an effective suite of interventions. Dysregulation of the immune response to infection is acknowledged to contribute to the pathogenesis of the disease. Production of both proinflammatory and immunosuppressive cytokines is observed from the very first hours following diagnosis. In addition, hypogammaglobulinemia is often present in patients with septic shock. Moreover, levels of IgG, IgM and IgA at diagnosis correlate directly with survival. In turn, nonsurvivors have lower levels of C4 (a protein of the complement system) than the survivors. Natural killer cell counts and function also seem to have an important role in this disease. HLA-DR in the surface of monocytes and counts of CD4+CD25+ T-regulatory cells in blood could also be useful biomarkers for sepsis. At the genomic level, repression of networks corresponding to major histocompatibility complex antigen presentation is observed in septic shock. In consequence, cumulative evidence supports the potential role of immunological monitoring to guide measures to prevent or treat sepsis in a personalised and timely manner (early antibiotic administration, immunoglobulin replacement, immunomodulation). In conclusion, although diffuse and limited, current available information supports the development of large comprehensive studies aimed to urgently evaluate immunological monitoring as a tool to prevent sepsis, guide its treatment and, as a consequence, diminish the morbidity and mortality associated with this severe condition.