The Role of Host Cholesterol During Flavivirus Infection

In recent years the emergence and resurgence of arboviruses have generated a global health alert. Among arboviruses, Dengue (DENV), Zika (ZIKV), Yellow Fever (YFV), and West Nile (WNV) virus, belong to the genus Flavivirus, cause high viremia and occasionally fatal clinical disease in humans. Given the genetic austerity of the virus, they depend on cellular factors and organelles to complete its replication. One of the cellular components required for flavivirus infection is cholesterol. Cholesterol is an abundant lipid in biomembranes of eukaryotes cells and is necessary to maintain the cellular homeostasis. Recently, it has been reported, that cholesterol is fundamental during flavivirus infection in both mammal and insect vector models. During infection with DENV, ZIKV, YFV, and WNV the modulation of levels of host-cholesterol facilitates viral entry, replicative complexes formation, assembly, egress, and control of the interferon type I response. This modulation involves changes in cholesterol uptake with the concomitant regulation of cholesterol receptors as well as changes in cholesterol synthesis related to important modifications in cellular metabolism pathways. In view of the flavivirus dependence of cholesterol and the lack of an effective anti-flaviviral treatment, this cellular lipid has been proposed as a therapeutic target to treat infection using FDA-approved cholesterol-lowering drugs. This review aims to address the dependence of cholesterol by flaviviruses as well as the basis for anti flaviviral therapy using drugs which target is cholesterol synthesis or uptake

Occult Follicular Thyroid Carcinoma presenting as Primary Breast Tumor with Sternal and Skull Metastasis

Introduction: Follicular thyroid carcinoma (FTC) that initially presented as breast tumor with no previous medical history of malignancy of thyroid gland is relatively rare and may cause diagnostic confusion.Presentation of case: We report a 59-year-old Mexican woman with no prior history of malignant thyroid neoplasm that presents with pain and swelling in the upper outer quadrant of the left breast with a year of evolution. Subsequently, subcutaneous tumor was identified in left parietal region. Clinically it was thought in primary breast tumor metastasis to skull. Furthermore, computerized tomography scan identified a tumor in the deep portion of the left breast, infiltrating the sternum that subsequently was confirmed a follicular carcinoma of the thyroid gland.Conclusion: Metastatic FTC may mimic a primary breast tumor. The combined use of clinical information, histopathology and immunohistochemistry were important to establishing a correct cancer diagnosis

The Usefulness of Peripheral Blood Cell Counts to Distinguish COVID-19 from Dengue during Acute Infection

COVID-19 and dengue disease are challenging to tell apart because they have similarities in clinical and laboratory features during the acute phase of infection, leading to misdiagnosis and delayed treatment. The present study evaluated peripheral blood cell count accuracy to distinguish COVID-19 non-critical patients from non-severe dengue cases between the second and eleventh day after symptom onset. A total of 288 patients infected with SARS-CoV-2 (n = 105) or dengue virus (n = 183) were included in this study. Neutrophil, platelet, and lymphocyte counts were used to calculate the neutrophil–lymphocyte ratio (NLR), the platelet–lymphocyte ratio (PLR), and the neutrophil–lymphocyte*platelet ratio (NLPR). The logistic regression and ROC curves analysis revealed that neutrophil and platelet counts, NLR, LPR, and NLPR were higher in COVID-19 than dengue. The multivariate predictive model showed that the neutrophils, platelets, and NLPR were independently associated with COVID-19 with a good fit predictive value (p = 0.1041). The neutrophil (AUC = 0.95, 95% CI = 0.84–0.91), platelet (AUC = 0.89, 95% CI = 0.85–0.93) counts, and NLR (AUC = 0.88, 95% CI = 0.84–0.91) were able to discriminate COVID-19 from dengue with high sensitivity and specificity values (above 80%). Finally, based on predicted probabilities on combining neutrophils and platelets with NLR or NLPR, the adjusted AUC was 0.97 (95% CI = 0.94–0.98) to differentiate COVID-19 from dengue during the acute phase of infection with outstanding accuracy. These findings might suggest that the neutrophil, platelet counts, and NLR or NLPR provide a quick and cost-effective way to distinguish between dengue and COVID-19 in the context of co-epidemics in low-income tropical regions

A Dual Pharmacological Strategy against COVID-19: The Therapeutic Potential of Metformin and Atorvastatin

Metformin (MET) and atorvastatin (ATO) are promising treatments for COVID-19. This review explores the potential of MET and ATO, commonly prescribed for diabetes and dyslipidemia, respectively, as versatile medicines against SARS-CoV-2. Due to their immunomodulatory and antiviral capabilities, as well as their cost-effectiveness and ubiquitous availability, they are highly suitable options for treating the virus. MET’s effect extends beyond managing blood sugar, impacting pathways that can potentially decrease the severity and fatality rates linked with COVID-19. It can partially block mitochondrial complex I and stimulate AMPK, which indicates that it can be used more widely in managing viral infections. ATO, however, impacts cholesterol metabolism, a crucial element of the viral replicative cycle, and demonstrates anti-inflammatory characteristics that could modulate intense immune reactions in individuals with COVID-19. Retrospective investigations and clinical trials show decreased hospitalizations, severity, and mortality rates in patients receiving these medications. Nevertheless, the journey from observing something to applying it in a therapeutic setting is intricate, and the inherent diversity of the data necessitates carefully executed, forward-looking clinical trials. This review highlights the requirement for efficacious, easily obtainable, and secure COVID-19 therapeutics and identifies MET and ATO as promising treatments in this worldwide health emergency

Protocol to evaluate the antiviral effect of FDA-approved drugs against dengue virus in Huh7 cells and AG129 mice

Summary: Finding an effective therapy against diseases caused by flaviviruses remains a challenge. Here, we present a protocol to test Food and Drug Administration-approved drugs that inhibit host nuclear protein import, promoting a reduction of dengue infection. We describe steps for analyzing the drug effect on nuclear import inhibition of cellular and viral proteins by confocal microscopy or western blotting. We then describe procedures for measuring the antiviral drug effects on virus-infected cells by flow cytometry and testing drug efficacy in dengue-infected AG129 mice by survival assays.For complete details on the use and execution of this protocol, please refer to Palacios-Rápalo et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics

Clinical Predictors of Monkeypox Diagnosis: A Case-Control Study in a Nonendemic Region during the 2022 Outbreak

Monkeypox (Mpox) is an emerging zoonotic disease with the potential for severe complications. Early identification and diagnosis are essential to prompt treatment, control its spread, and reduce the risk of human-to-human transmission. This study aimed to develop a clinical diagnostic tool and describe the clinical and sociodemographic features of 19 PCR-confirmed Mpox cases during an outbreak in a nonendemic region of northwestern Mexico. The median age of patients was 35 years, and most were male. Mpox-positive patients commonly reported symptoms such as fever, lumbago, and asthenia, in addition to experiencing painful ulcers and a high frequency of HIV infection among people living with HIV (PLWH). Two diagnostic models using logistic regression were devised, with the best model exhibiting a prediction accuracy of 0.92 (95% CI: 0.8–1), a sensitivity of 0.86, and a specificity of 0.93. The high predictive values and accuracy of the top-performing model highlight its potential to significantly improve early Mpox diagnosis and treatment in clinical settings, aiding in the control of future outbreaks