We aimed to evaluate the effects of both the expression and serum levels of Epidermal growth factor (EGF) and Transforming growth factor-β1 (TGF-β1) genes in patients with different degrees of cellular damage as mild, moderate, severe, and critical illness that can lead to fibrosis caused by SARS-CoV-2. Totally 45 individuals (male: 21(46.67%); female: 24(53.33%)) with COVID-19 infection were included in this study. Four groups were constituted as mild (n = 16)], moderate (n = 10), severe (n = 10), and critical (n = 9) according to the severity of the disease. Blood samples were drawn from the patients, and all of the hemograms, EGF and TGFβ1 gene expression, and serum levels were evaluated. The mean age of individuals was 57.311 ± 18.383 (min: 28, max: 94). Significant differences were found among the groups for PLT (χ2 = 9.955; p = 0.019), CRP (χ2 = 7.693; p = 0.053), Ferritin (χ2 = 22.196; p < 0.001), D-dimer (χ2 = 21.982; p = 0.000), LDH (χ2 = 21.807; p < 0.001) and all these parameters (exclude PLT in severe groups) was increased depending on the severity of the disease. Additionally, significant differences were detected for EGF (χ2 = 29.528; p < 0.001), TGFB1 (χ2 = 28.981; p < 0.001) expression (that increased depending on the disease severity), and EGF (χ2 = 7.84; p = 0.049), TGFB1 (χ2 = 17.451; p = 0.001) serum concentration levels (that decreased depending on the disease severity). This study found statistically significant differences for both EGF 2-ΔΔCt. TGFβ1 2-ΔΔCt and EGF, TGFβ1 serum concentration values among all patient groups. As disease severity increased, EGF 2-ΔΔCt. TGFβ1 2-ΔΔCt levels increased, while EGF and TGFβ1 serum concentration levels decreased. Perhaps this study will be useful in managing COVID-19 infection severity and pulmonary fibrosis cases secondary to COVID-19.

Coronavirus disease 2019 (COVID-19) is a respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that displays great variability in clinical phenotype. Many factors have been described to be correlated with its severity, and microbiota could play a key role in the infection, progression, and outcome of the disease. SARS-CoV-2 infection has been associated with nasopharyngeal and gut dysbiosis and higher abundance of opportunistic pathogens. To identify new prognostic markers for the disease, a multicentre prospective observational cohort study was carried out in COVID-19 patients divided into three cohorts based on symptomatology: mild (n = 24), moderate (n = 51), and severe/critical (n = 31). Faecal and nasopharyngeal samples were taken, and the microbiota was analysed. Linear discriminant analysis identified Mycoplasma salivarium, Prevotella dentalis, and Haemophilus parainfluenzae as biomarkers of severe COVID-19 in nasopharyngeal microbiota, while Prevotella bivia and Prevotella timonensis were defined in faecal microbiota. Additionally, a connection between faecal and nasopharyngeal microbiota was identified, with a significant ratio between P. timonensis (faeces) and P. dentalis and M. salivarium (nasopharyngeal) abundances found in critically ill patients. This ratio could serve as a novel prognostic tool for identifying severe COVID-19 cases.

Bile acids are microbial metabolites that can impact infection of enteric and hepatitis viruses, but their functions during systemic viral infection remain unclear. Here we show that elevated levels of the secondary bile acid taurolithocholic acid (TLCA) are associated with reduced fatality rates and suppressed viraemia in patients infected with severe fever with thrombocytopenia syndrome virus (SFTSV), an emerging tick-borne haemorrhagic fever virus. TLCA inhibits viral replication and mitigates host inflammation during SFTSV infection in vitro, and indirectly suppresses SFTSV-mediated induction of ferroptosis by upregulating fatty acid desaturase 2 via the TGR5-PI3K/AKT-SREBP2 axis. High iron and ferritin serum levels during early infection were correlated with decreased TLCA levels and fatal outcomes in SFTSV-infected patients, indicating potential biomarkers. Furthermore, treatment with either ferroptosis inhibitors or TLCA protected mice from lethal SFTSV infection. Our findings highlight the therapeutic potential of bile acids to treat haemorrhagic fever viral infection.

Ferroptosis, an iron-dependent form of regulated cell death, is emerging as a crucial regulator of human physiology and pathology. Increasing evidence showcases a reciprocal relationship between ferroptosis and dysregulated metabolism, propagating a pathogenic vicious cycle that exacerbates pathology and human diseases, particularly metabolic disorders. Consequently, there is a rapidly growing interest in developing ferroptosis-based therapeutics. Therefore, a comprehensive understanding of the intricate interplay between ferroptosis and metabolism could provide an invaluable resource for mechanistic insight and therapeutic development. In this review, we summarize the important metabolic substances and associated pathways in ferroptosis initiation and progression, outline the cascade responses of ferroptosis in disease development, overview the roles and mechanisms of ferroptosis in metabolic diseases, introduce the methods for ferroptosis detection, and discuss the therapeutic perspectives of ferroptosis, which collectively aim to illustrate a comprehensive view of ferroptosis in basic, translational, and clinical science.

Discriminate the severity level of COVID-19 disease is still a challenge. Here we investigate the capability of micro-infrared absorption spectroscopy (micro-FTIR) to probe COVID-19 severity level and predict hyperinflammation, correlating the assigned vibrational data to relevant biomolecules related to the immune system. Saliva of 184 patients was analysed by ELISA assay (Hepcidin) and micro-FTIR. Vibrational bands related to IgM and IgA can discriminate healthy from Severe individuals (sensitivity ≥ 0.749, specificity ≥ 0.945) and are less effective in discriminating Mild or Moderate individuals from the Severe group (sensitivity ≥ 0.628, specificity ≥ 0.867). Analysis of the second derivative of spectra probed increased levels of IL-6 in the saliva a key additional information for the degree of severity prediction. Because the model discriminates all the groups regarding the Severe group, it predicts an intense state of inflammation based on FTIR analysis. It is a powerful tool for predicting hyperinflammation conditions related to SARS-CoV-2 infection and may be an ally in implementing drugs or therapeutic approaches to manage COVID-19 in the Severe stage in healthcare facilities.

During the COVID-19 pandemic, identifying reliable biomarkers for predicting disease severity and patient outcomes in unvaccinated individuals is essential. This study evaluates the efficacy of key hematological markers, including leukocyte and neutrophil counts, Neutrophil-to-Lymphocyte Ratio (NLR), and cytokine profiles (IL-6, INF-γ, TNF-α, IL-17A, CCL2, and CXCL10) for predicting the necessity for mechanical ventilation and assessing survival probabilities.

We conducted an in-depth analysis on a cohort of COVID-19 patients, emphasizing the relationship between NLR, cytokine profiles, and clinical outcomes, utilizing routine leukocyte counting and cytokine quantification by flow cytometry.

Elevated leukocyte and neutrophil counts, increased NLR, and significant cytokine elevations such as IL-6 and IL-10 were strongly associated with the need for mechanical ventilation, reflecting a pronounced systemic inflammatory response indicative of severe disease outcomes.

Integrating hematological markers, particularly NLR and cytokine profiles, is crucial in predicting mechanical ventilation needs and survival in non-vaccinated COVID-19 patients. Our findings provide critical insights into the pathophysiology of COVID-19, supporting the development of more targeted clinical interventions and potentially informing future strategies for managing infectious disease outbreaks.

Infectious diseases are associated with low iron levels and the induction of hepcidin, the primary protein regulating cellular iron export. Bone morphogenetic protein 6 (BMP6), a key regulator of hepcidin expression, has not yet been analyzed in the plasma of patients with systemic inflammatory response syndrome (SIRS) or sepsis. An analysis of 38 SIRS, 39 sepsis, and 78 septic shock patients revealed similar levels of BMP6 in sepsis and septic shock, which were lower compared to patients with SIRS and healthy controls. Plasma BMP6 levels did not correlate with procalcitonin and C-reactive protein levels in patients with SIRS or sepsis/septic shock. Neither bacterial nor SARS-CoV-2 infections affected plasma BMP6 levels. There was no difference in BMP6 levels between ventilated and non-ventilated patients, or between patients with and without dialysis. Vasopressor therapy did not alter BMP6 levels. Survivors had plasma BMP6 levels similar to non-survivors. Due to the high variability of plasma BMP6 levels, these analyses have limited clinical relevance. Iron, ferritin, and transferrin levels were known in at least 50% of patients but did not correlate with plasma BMP6 levels. In conclusion, this study showed normal BMP6 plasma levels in SIRS, which are reduced in patients with sepsis and septic shock. This suggests that the commonly observed increase in hepcidin levels and the decline in iron levels in SIRS, sepsis, and septic shock are not due to higher BMP6.

Iron is an essential nutrient for humans and microbes, such as bacteria. Iron deficiency commonly occurs in critically ill patients, but supplementary iron therapy is not considered during the acute phase of critical illness since it increases iron availability for invading microbes and oxidative stress. However, persistent iron deficiency in the recovery phase is harmful and has potential adverse outcomes such as cognitive dysfunction, fatigue, and cardiopulmonary dysfunction. Therefore, it is important to treat iron deficiency quickly and efficiently. This article reviews current knowledge about iron-related biomarkers in critical illness with a focus on patients with sepsis, and provides possible criteria to guide decision-making for iron supplementation in the recovery phase of those patients.

The need for the identification of risk factors associated to COVID-19 disease severity remains urgent. Patients' care and resource allocation can be potentially different and are defined based on the current classification of disease severity. This classification is based on the analysis of clinical parameters and routine blood tests, which are not standardized across the globe. Some laboratory test alterations have been associated to COVID-19 severity, although these data are conflicting partly due to the different methodologies used across different studies. This study aimed to construct and validate a disease severity prediction model using machine learning (ML). Seventy-two patients admitted to a Brazilian hospital and diagnosed with COVID-19 through RT-PCR and/or ELISA, and with varying degrees of disease severity, were included in the study. Their electronic medical records and the results from daily blood tests were used to develop a ML model to predict disease severity. Using the above data set, a combination of five laboratorial biomarkers was identified as accurate predictors of COVID-19 severe disease with a ROC-AUC of 0.80 ​±​ 0.13. Those biomarkers included prothrombin activity, ferritin, serum iron, ATTP and monocytes. The application of the devised ML model may help rationalize clinical decision and care.

The unprecedented pandemic of COVID-19 swept millions of lives in a short period, yet its menace continues among its survivors in the form of post-COVID syndrome. An exponentially growing number of COVID-19 survivors suffer from cognitive impairment, with compelling evidence of a trajectory of accelerated aging and neurodegeneration. The novel and enigmatic nature of this yet-to-unfold pathology demands extensive research seeking answers for both the molecular underpinnings and potential therapeutic targets. Ferroptosis, an iron-dependent cell death, is a strongly proposed underlying mechanism in post-COVID-19 aging and neurodegeneration discourse. COVID-19 incites neuroinflammation, iron dysregulation, reactive oxygen species (ROS) accumulation, antioxidant system repression, renin-angiotensin system (RAS) disruption, and clock gene alteration. These events pave the way for ferroptosis, which shows its signature in COVID-19, premature aging, and neurodegenerative disorders. In the search for a treatment, melatonin shines as a promising ferroptosis inhibitor with its repeatedly reported safety and tolerability. According to various studies, melatonin has proven efficacy in attenuating the severity of certain COVID-19 manifestations, validating its reputation as an anti-viral compound. Melatonin has well-documented anti-aging properties and combating neurodegenerative-related pathologies. Melatonin can block the leading events of ferroptosis since it is an efficient anti-inflammatory, iron chelator, antioxidant, angiotensin II antagonist, and clock gene regulator. Therefore, we propose ferroptosis as the culprit behind the post-COVID-19 trajectory of aging and neurodegeneration and melatonin, a well-fitting ferroptosis inhibitor, as a potential treatment.

Iron is a trace element that possesses immunomodulatory properties and modulates the proneness to the course and outcome of a diverse viral diseases. This study intended to investigate the correlation of different iron-related factors with disease severity and outcomes as well as the mortality of coronavirus disease 2019 (COVID-19) patients.

Blood serum samples were obtained from 80 COVID-19 cases and 100 healthy controls. Concentrations of ferritin, transferrin, total iron binding capacity (TIBC) was measured by Enzyme-linked immunosorbent assay (ELISA) and iron level was measured by immunoturbidometric method.

Concentrations of iron, transferrin, and TIBC were low, while ferritin level was high in the COVID-19 cases in comparison to controls. In non-survivor (deceased) patients as well as severe subjects, the levels of iron, ferritin, transferrin, and TIBC were significantly different than survivors (discharged) and mild cases. Significant correlations were found between iron and related factors and the clinicopathological features of the patients. Based on ROC curve analysis, iron, ferritin, transferrin, and TIBC had potential to estimate disease severity in COVID-19 subjects.

Iron metabolism is involved in the pathogenesis of COVID-19. Iron and related factors correlate with disease outcomes and might serve as biomarker in diagnosis of the disease severity and estimation of mortality in the COVID-19 subjects.

COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged as a global health threat in 2019. An important feature of the disease is that multiorgan symptoms of SARS-CoV-2 infection persist after recovery. Evidence indicates that people who recovered from COVID-19, even those under the age of 65 years without cardiovascular risk factors such as smoking, obesity, hypertension, and diabetes, had a significantly increased risk of cardiovascular disease for up to one year after diagnosis. Therefore, it is important to closely monitor individuals who have recovered from COVID-19 for potential cardiovascular damage that may manifest at a later stage. Ferroptosis is an iron-dependent form of non-apoptotic cell death characterized by the production of reactive oxygen species (ROS) and increased lipid peroxide levels. Several studies have demonstrated that ferroptosis plays an important role in cancer, ischemia/reperfusion injury (I/RI), and other cardiovascular diseases. Altered iron metabolism, upregulation of reactive oxygen species, and glutathione peroxidase 4 inactivation are striking features of COVID-19-related cardiovascular injury. SARS-CoV-2 can cause cardiovascular ferroptosis, leading to cardiovascular damage. Understanding the mechanism of ferroptosis in COVID-19-related cardiovascular injuries will contribute to the development of treatment regimens for preventing or reducing COVID-19-related cardiovascular complications. In this article, we go over the pathophysiological underpinnings of SARS-CoV-2-induced acute and chronic cardiovascular injury, the function of ferroptosis, and prospective treatment approaches.

Some studies have suggested potential relationships between periodontal disease and COVID-19, explained by many possible pathological pathways. The aim of this case-control study with a longitudinal arm was to investigate this association. 80 systemically healthy individuals (apart from COVID-19) were involved in this study, divided into 40 patients who had recently had COVID-19 (test, divided into severe and mild/moderate cases) and 40 who had not had COVID-19 (control). Clinical periodontal parameters and laboratory data were recorded. Mann-Whitney U test, Wilcoxon test, and chi-square test were performed to compare variables. Multiple binary logistic regression method was used to estimate adjusted ORs and 95% confidence interval. Hs-CRP-1 and 2, Ferritin-1 and 2, lymphocyte count-1 values, and neutrophil/lymphocyte ratio-1 were higher in patients with severe COVID-19 than patients with mild/moderate COVID-19 (p < 0.05). All of these laboratory values significantly decreased after COVID-19 treatment (p < 0.05) in the test group. Presence of periodontitis (p = 0.015) was higher and periodontal health was lower (p = 0.002) in the test group than in the control group. All clinical periodontal parameters were significantly higher in the test group than in the control group (p < 0.05), except plaque index. Prevalence of periodontitis was associated with increased odds of having COVID-19 infection (PR = 1.34; 95% CI 0.23-2.45) in the multiple binary logistic regression. COVID-19 is associated with periodontitis prevalence, through a series of possible mechanisms including local and systemic inflammatory responses. Further studies should investigate whether the maintenance of periodontal health may be a factor in the reduction of the severity of COVID-19 infections.

For more than 2 years medical practice has been dealing with the Covid-19 pandemic. Atypical symptoms, such as frostbites and acrosyndromes, have appeared, and autoimmune anemias (some of which with cold agglutinins) have been described.

We planned to study the prevalence of positive direct Coombs tests (DCTs) and hemolytic autoimmune anemia in patients infected with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and its correlation with complications, and then investigate the impact of the infection on iron metabolism.

This is an observational, cross-sectional, single-center, exploratory study.

We obtained Coombs tests in a population of 179 infected patients at the CHU of Liège. We then studied iron metabolism in some of these patients, by measuring serum ferritin, erythropoietin (EPO), erythroferrone and hepcidin.

We did not identify any case of autoimmune hemolysis. However, there was a 20.3% prevalence of positive DCT, mainly with IgG (91.7%). These patients, compared to DCT-negative patients, were not only more anemic and transfused, but also required more transfers to intensive care units and had longer hospital stays and mechanical ventilation. The pattern of anemia was consistent with the anemia of inflammation, showing elevated hepcidin and ferritin levels, while EPO and erythroferrone values were lower than expected at this degree of anemia. Erythroferrone was higher and Hb was lower in DCT-positive patients. Finally, we identified a correlation between iron parameters and complicated forms of infection.

Covid-19 patients suffered from inflammatory anemia with more severe forms of infection correlated to positive DCT status. This could potentially be of interest for future clinical practice.

Background COVID-19 is a major cause of illness and mortality. The management of COVID-19-related illnesses might change if variables connected to their severity and the requirement for ICU admission could be found. The severity of COVID-19 might be efficiently predicted with several laboratory measures, such as ferritin levels and D-dimer analysis. Objectives This study aimed to evaluate the association between serum D-dimer and ferritin levels and their effects on mortality in patients with COVID-19. Methods This retrospective observational study included all patients with positive real-time polymerase chain reaction (RT-PCR) results for COVID-19 who were hospitalized in the Ministry of Health South Al-Qunfudah General Hospital between March and September 30, 2020. Their laboratory parameters, serum D-dimer, and ferritin levels were evaluated. IBM SPSS Statistics for Windows, Version 26.0 (released 2019; IBM Corp., Armonk, New York, United States) was used to analyze the data. Results A total of 318 COVID-19 patients were analyzed; 56.9% (n=181) were male and 43.1% (n=137) were female. Of these, 78.6% (n=250) survived, including 58% of men and 42% of women. The mean D-dimer was 2.1 mcg/mL (SD=3.16) and the mean ferritin was 698.59 ng/mL (SD=603.11). Non-recovered patients were substantially older (66.16 years old) and had higher D-dimer (5.46) mcg/mL and ferritin levels (992.96) ng/mL. Intubation length and gender did not affect survival. Of the non-survivors, 95.6% (n=239) were admitted to the ICU, and 50% (n=34) required mechanical ventilation. Conclusions COVID-19 infection mortality dramatically increased with older age and increased mean ferritin and plasma D-dimer values, which were significantly higher in COVID-19 non-survivors than in survivors. Therefore, assessing and monitoring these laboratory markers in the early stages of the disease may have a significant impact on preventing disease progression and death.

Recently, numerous studies have reported on different predictive models of disease severity in COVID-19 patients. Herein, we propose a highly predictive model of disease severity by integrating routine laboratory findings and plasma metabolites including cytosine as a potential biomarker of COVID-19 disease severity. One model was developed and internally validated on the basis of ROC-AUC values. The predictive accuracy of the model was 0.996 (95% CI: 0.989 to 1.000) with an optimal cut-off risk score of 3 from among 6 biomarkers including five lab findings (D-dimer, ferritin, neutrophil counts, Hp, and sTfR) and one metabolite (cytosine). The model is of high predictive power, needs a small number of variables that can be acquired at minimal cost and effort, and can be applied independent of non-empirical clinical data. The metabolomics profiling data and the modeling work stemming from it, as presented here, could further explain the cause of COVID-19 disease prognosis and patient management.

COVID-19 can cause detrimental effects on health. Vaccines have helped in reducing disease severity and transmission but their long-term effects on health and effectiveness against future viral variants remain unknown. COVID-19 pathogenesis involves alteration in iron homeostasis. Thus, a contextual understanding of iron-related parameters would be very valuable for disease prognosis and therapeutics.Accordingly, we reviewed the status of iron and iron-related proteins in COVID-19. Iron-associated alterations in COVID-19 reported hitherto include anemia of inflammation, low levels of serum iron (hypoferremia), transferrin and transferrin saturation, and high levels of serum ferritin (hyperferritinemia), hepcidin, lipocalin-2, catalytic iron, and soluble transferrin receptor (in ICU patients). Hemoglobin levels can be low or normal, and compromised hemoglobin function has been proposed. Membrane-bound transferrin receptor may facilitate viral entry, so it acts as a potential target for antiviral therapy. Lactoferrin can provide natural defense by preventing viral entry and/or inhibiting viral replication. Serum iron and ferritin levels can predict COVID-19-related hospitalization, severity, and mortality. Serum hepcidin and ferritin/transferrin ratio can predict COVID-19 severity. Here, serum levels of these iron-related parameters are provided, caveats of iron chelation for therapy are discussed and the interplay of these iron-related parameters in COVID-19 is explained.This synopsis is crucial as it clearly presents the iron picture of COVID-19. The information may assist in disease prognosis and/or in formulating iron-related adjunctive strategies that can help reduce infection/inflammation and better manage COVID-19 caused by future variants. Indeed, the current picture will augment as more is revealed about these iron-related parameters in COVID-19.

Coronavirus disease-19 (COVID-19), caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), is associated with the persistence of pre-existing or the emergence of new neurological and psychiatric manifestations as a part of a multi-system affection known collectively as "post-COVID syndrome." Cognitive decline is the most prominent feature among these manifestations. The underlying neurobiological mechanisms remain under intense investigation. Ferroptosis is a form of cell death that results from the excessive accumulation of intracellular reactive iron, which mediates lipid peroxidation. The accumulation of lipid-based reactive oxygen species (ROS) and the impairment of glutathione peroxidase 4 (GPX4) activity trigger ferroptosis. The COVID-19-associated cytokine storm enhances the levels of circulating pro-inflammatory cytokines and causes immune-cell hyper-activation that is tightly linked to iron dysregulation. Severe COVID-19 presents with iron overload as one of the main features of its pathogenesis. Iron overload promotes a state of inflammation and immune dysfunction. This is well demonstrated by the strong association between COVID-19 severity and high levels of ferritin, which is a well-known inflammatory and iron overload biomarker. The dysregulation of iron, the high levels of lipid peroxidation biomarkers, and the inactivation of GPX4 in COVID-19 patients make a strong case for ferroptosis as a potential mechanism behind post-COVID neuropsychiatric deficits. Therefore, here we review the characteristics of iron and the attenuation of ferroptosis as a potential therapeutic target for neuropsychiatric post-COVID syndrome.

The pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection involves dysregulations of iron metabolism, and although the mechanism of this pathology is not yet fully understood, correction of iron metabolism pathways seems a promising pharmacological target. The previously observed effect of inhibiting SARS-CoV-2 infection by ferristatin II, an inducer of transferrin receptor 1 (TfR1) degradation, prompted the study of competition between Spike protein and TfR1 ligands, especially lactoferrin (Lf) and transferrin (Tf). We hypothesized molecular mimicry of Spike protein as cross-reactivity of Spike-specific antibodies with Tf and Lf. Thus, strong positive correlations (R2 > 0.95) were found between the level of Spike-specific IgG antibodies present in serum samples of COVID-19-recovered and Sputnik V-vaccinated individuals and their Tf-binding activity assayed with peroxidase-labeled anti-Tf. In addition, we observed cross-reactivity of Lf-specific murine monoclonal antibody (mAb) towards the SARS-CoV-2 Spike protein. On the other hand, the interaction of mAbs produced to the receptor-binding domain (RBD) of the Spike protein with recombinant RBD protein was disrupted by Tf, Lf, soluble TfR1, anti-TfR1 aptamer, as well as by peptides RGD and GHAIYPRH. Furthermore, direct interaction of RBD protein with Lf, but not Tf, was observed, with affinity of binding estimated by KD to be 23 nM and 16 nM for apo-Lf and holo-Lf, respectively. Treatment of Vero E6 cells with apo-Lf and holo-Lf (1-4 mg/mL) significantly inhibited SARS-CoV-2 replication of both Wuhan and Delta lineages. Protective effects of Lf on different arms of SARS-CoV-2-induced pathogenesis and possible consequences of cross-reactivity of Spike-specific antibodies are discussed.

The clinical state of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been considered a pandemic disease (COVID-19) that is rapidly spreading worldwide. Despite all global efforts, the only treatment for COVID-19 is supportive care and there has been no efficient treatment to fight this plague. It is confirmed that patients with chronic diseases such as cardiovascular disorder and diabetes; are more vulnerable to COVID-19. In the severe type of COVID-19, laboratory findings showed a remarkably enhanced C-reactive protein, IL-6 serum, Iron, and ferritin, which suggest an inflammatory response. Inflammation results in iron homeostasis imbalance and causes iron overload, exacerbating the SARSCOV2 infection. More importantly, recent studies have established that SARS-CoV-2 needs iron for viral replication and also activation. As a result, managing iron overload in diabetic patients with COVID-19 could be an early therapeutic approach to limit the lethal inflammatory response of COVID-19. In this review, Deferoxamine (DFO) has been proposed as an effective iron chelator agent.

Since the beginning of the COVID-19 pandemic, numerous metabolic alterations have been observed in individuals with this disease. It is known that SARS-CoV-2 can mimic the action of hepcidin, altering intracellular iron metabolism, but gaps remain in the understanding of possible outcomes in other pathways involved in the iron cycle.

To profile iron, ferritin and hepcidin levels and transferrin receptor gene expression in patients diagnosed with COVID-19 between June 2020 and September 2020.

Cross-sectional study that evaluated iron metabolism markers in 427 participants, 218 with COVID-19 and 209 without the disease.

The primary exposure was positive diagnose to COVID-19 in general population of Santo André and São Bernardo cities. The positive and negative diagnose were determinate through RT-qPCR.

Devido a evidências de alterações do ciclo do ferro em pacientes diagnosticados com COVID-19 e devido a corregulação entre hepcidina e receptor de transferrina, uma análise da expressão gênica deste último, poderia trazer insights sobre o estado de ferro celular. A hipótese foi confirmada, mostrando aumento da expressão de receptor de transferrina concomitante com redução do nível de hepcidina circulante.

Serum iron presented lower values in individuals diagnosed with COVID-19, whereas serum ferritin presented much higher values in infected patients. Elderly subjects had lower serum iron levels and higher ferritin levels, and men with COVID-19 had higher ferritin values than women. Serum hepcidin was lower in the COVID-19 patient group and transferrin receptor gene expression was higher in the infected patient group compared to controls.

COVID-19 causes changes in several iron cycle pathways, with iron and ferritin levels being markers that reflect the state and evolution of infection, as well as the prognosis of the disease. The increased expression of the transferrin receptor gene suggests increased iron internalization and the mimicry of hepcidin action by SARS-CoV-2, reduces iron export via ferroportin, which would explain the low circulating levels of iron by intracellular trapping.

Major clinically relevant inflammatory events such as septic shock and severe COVID-19 trigger dynamic changes in the host immune system, presenting promising candidates for new biomarkers to improve precision diagnostics and patient stratification. Hepcidin, a master regulator of iron metabolism, has been intensively studied in many pathologies associated with immune system activation, however these data have never been compared to other clinical settings. Thus, we aimed to reveal the dynamics of iron regulation in various clinical settings and to determine the suitability of hepcidin and/or ferritin levels as biomarkers of inflammatory disease severity.

To investigate the overall predictive ability of hepcidin and ferritin, we enrolled the patients suffering with three different diagnoses - in detail 40 patients with COVID-19, 29 patients in septic shock and eight orthopedic patients who were compared to nine healthy donors and all cohorts to each other.

We showed that increased hepcidin levels reflect overall immune cell activation driven by intrinsic stimuli, without requiring direct involvement of infection vectors. Contrary to hepcidin, ferritin levels were more strongly boosted by pathogen-induced inflammation - in septic shock more than four-fold and in COVID-19 six-fold in comparison to sterile inflammation. We also defined the predictive capacity of hepcidin-to-ferritin ratio with AUC=0.79 and P = 0.03.

Our findings confirm that hepcidin is a potent marker of septic shock and other acute inflammation-associated pathologies and demonstrate the utility of the hepcidin-to-ferritin ratio as a predictor of mortality in septic shock, but not in COVID-19.

A history of COVID-19 (Coronavirus Disease 2019), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may have an impact on hemoglobin and ferritin levels predisposing patients to increased blood transfusion requirements following total joint arthroplasty (TJA). The current study compares ferritin levels, hemoglobin levels, and transfusion rates between SARS-CoV-2 IgG positive and SARS-CoV-2 IgG negative TJA patients.

Preoperative ferritin levels, pre- and postoperative hemoglobin levels, postoperative change in hemoglobin, and transfusion rates of 385 consecutive SARS-CoV-2 IgG positive patients undergoing TJA were compared to those of 5156 consecutive SARS-CoV-2 IgG negative patients undergoing TJA.

Preoperative hemoglobin levels were significantly lower in SARS-CoV-2 IgG positive patients [13.3 g/dL (range 8.9-17.7 g/dL)] compared to 13.5 g/dl (7.3-18.3 g/dL; p value 0.03). Ferritin levels were significantly lower in SARS-CoV-2 IgG positive patients (mean of 106.1 ng/ml (2.1-871.3.3 ng/ml) vs. 123.7 ng/ml (1.4-1985 ng/ml) (p value 0.02)). Hemoglobin on postoperative day (POD) one, after four-six weeks, and transfusion rates did not differ between the two groups.

Although preoperative hemoglobin and ferritin levels are lower in SARS-CoV2 IgG positive patients, there was no difference in hemoglobin on POD one, recovery of hemoglobin levels at four-six weeks postoperatively, and transfusion rates after surgery. Routine ferritin testing prior to TJA is not recommended in SARS-CoV-2 IgG positive patients.

The aim: The purpose of this study is to find out the association between procalcitonin and hepcidin in patients with COVID-19, in addition to their role as diagnostic markers.

Materials and methods: A total of 75 patients infected with coronavirus were included in the current study, their age is ranging between 20 to 78 years. Those patients was hospitalized in Al-Sadr Teaching Hospital in Najaf, in Iraq. This study also included 50 healthy subjects which are volunteers and considered as a (control group). Biomarker (procalcitonin and hepcidin) measurements were achieved by electrochemiluminescent immunoassay (ECLIA) in the Elecsys immunoassay system.

Results: The present study showed a significant increase the serum cencentration of hepcidin and procalcitonin in patients with COVID-19 as compared tohealthy subjects. There was a highly significant increasing(p < 0.01) in hepcidin and PCT level in patients with severe infection comparing to other catgaries.The current study also revealed that the sensitivity values of the markers were: 0.88%, 0.85 for procalcitonin and hepcidin respectively, which indicate high diagnostic power.

Conclusions: Serum levels of hepcidin and procalcitonin are increased as inflammatory markers in COVID-19 patients with relatively high sensitivity. It seems that these imflammatory markers obviously elevate in the severe cases COVID-19dusease.

Severe outcome particularly death is the largest burden of COVID-19. Clinical observations showed preliminary data that deficiency in certain trace elements, essential for the normal activity of immune system, may be associated with worse COVID-19 outcome. Relevant study of environmental epidemiology has yet to be explored. We investigated the geographical association between concentrations of Se, Zn, Fe and Cu in surface soils and case fatality rate of COVID-19 in USA. Two sets of database, including epidemiological data of COVID-19 (including case fatality rate, from the University of John Hopkinson) and geochemical concentration data of Se, Zn, Fe and Cu in surface soils (from the National Geochemical Survey), were mapped according to geographical location at the county level across conterminous USA. Characteristics of population, socio-demographics and residential environment by county were also collected. Seven cross-sectional sampling dates, with a 4-week interval between adjacent dates, constructed an observational investigation over 24 weeks from October 8, 2020, to March 25, 2021. Multivariable fractional (logit) outcome regression analyses were used to assess the association with adjustment for potential confounding factors. In USA counties with the lowest concentration of Zn, the case fatality rate of COVID-19 was the highest, after adjustment for other influencing factors. Associations of Se, Fe and Cu with case fatality rate of COVID-19 were either inconsistent over time or disappeared after adjustment for Zn. Our large study provides epidemiological evidence suggesting an association of Zn with COVID-19 severity, suggesting Zn deficiency should be avoided.

Nutritional deficiency is associated with weaken immune system and increased susceptibility to infection. Among other nutrients, several trace elements have been shown to regulate immune responses. Iron is one of the most abundant trace elements present in our body, which is required in various biological processes. Iron has an immunomodulatory function and thus influence the susceptibility to the course and outcome of a variety of viral infections. So, this present study was aimed to study relations of different iron-related biomarkers in association to severity and mortality in SARS-CoV-2 patients.

A total of 150 individuals infected with COVID-19 and 50 healthy individuals were recruited. Cases were divided based on severity (mild, moderate, and severe) and outcome (discharged or deceased). Serum iron, TIBC, ferritin, transferrin, transferrin saturation levels were analyzed by the direct colourimetric method.

In cases the median levels of serum iron, TIBC, transferrin, transferrin saturation and ferritin are 29 µg/dL, 132.53 µg/dL, 106.3 mg/dL, 17.74 % and 702.9 ng/dL respectively. Similarly, in controls the median levels of serum iron, TIBC, transferrin, transferrin saturation and ferritin are 53 µg/dL, 391.88 µg/dL, 313.51 mg/dL, 12.81 % and 13.52 ng/dL respectively. On comparing the cases with the controls, a significant lower level of iron, TIBC, and transferrin were found in the cases along with the significant higher levels of ferritin and transferrin saturation. On comparing the Receiver operating characteristic (ROC) curves of Iron, Ferritin, Transferrin, Transferrin sat % and TIBC in relation to survival in COVID-19 patients it was found that iron, followed by transferrin and ferritin has the highest area under the curve (AUC) with 74 %, 63 % and 61 % respectively. Further, in pairwise analysis of ROC curve, a significant difference was found between the Iron-transferrin (p < 0.01), iron-TIBC (p < 0.001) and transferrin-ferritin (P < 0.01). The multiple regression model based on Iron and transferrin outperformed any other combination of variables via stepwise AIC selection with an AUC of 98.2 %. The cutoff point according to Youden's J index is characterized with a sensitivity of 98 % and a specificity of 96.8 %, indicating that iron along with transferrin can be a useful marker that may contribute to a better assessment of survival chances in COVID-19.

Our study demonstrated a significantly decreased levels of iron, TIBC, & transferrin and a significantly increased levels of ferritin and transferrin saturation in COVID-19 patients when compared with controls. Further, Iron and transferrin were observed to be a good predictor of mortality in patients with COVID-19. From the above analysis we confirm that iron-related biomarkers play an important role in the development of oxidative stress and further lead to activation of the cytokine storm. So, continuous monitoring of these parameters could be helpful in the early detection of individuals developing the severe disease and can be used to decrease mortality in upcoming new waves of COVID-19.

Caused by the new SARS-CoV-2 coronavirus, COVID-19 (coronavirus disease 2019) evolves with clinical symptoms that vary widely in severity, from mild symptoms to critical conditions, which can even result in the patient's death. A critical aspect related to an individual response to SARS-CoV-2 infection is the competence of the immune system, and it is well known that several trace elements are essential for an adequate immune response and have anti-inflammatory and antioxidant properties that are of particular importance in fighting infection. Thus, it is widely accepted that adequate trace element status can reduce the risk of SARS-CoV-2 infection and disease severity. In this study, we evaluated the serum levels of Cu, Zn, Se, Fe, I and Mg in patients (n = 210) with clinical conditions of different severity ("mild", "moderate", "severe" and "exitus letalis", i.e., patients who eventually died). The results showed significant differences between the four groups for Cu, Zn, Se and Fe, in particular a significant trend of Zn and Se serum levels to be decreased and Cu to be increased with the severity of symptoms. For Mg and I, no differences were observed, but I levels were shown to be increased in all groups.

We examined the effects of psychiatric comorbidity, sex, and ICU admission on serum ferritin concentration in 628 elderly patients (79.7 ± 8.5 years) with positive SARS-CoV-2 PCR test. Hospitalization was required in 96% of patients and 17% required ICU admission. Patients with COVID-19 and psychiatric comorbidities (n = 212) compared to patients without psychiatric comorbidities (n = 416) had significantly lower ferritin concentration (570.4 ± 900.1 vs. 744.1 ± 965, P = 0.029), a greater incidence of delirium (22.6 vs. 14.4%, P = 0.013) and higher mortality (35.3 vs. 27.6%, P = 0.015). Furthermore, we found significant effects for sex (P = 0.002) and ICU admission (P = 0.007). Among patients without comorbid psychiatric conditions, males had significantly higher ferritin compared to females (1,098.3 ± 78.4 vs. 651.5 ± 94.4, P < 0.001). ICU patients without comorbid psychiatric conditions had significantly higher serum ferritin compared to ICU patients with comorbid psychiatric conditions: (1,126.6 ± 110.7 vs. 668.6 ± 156.5, P < 0.001). Our results suggest that the presence of comorbid psychiatric conditions in elderly patients with COVID-19 is associated with higher rates of delirium and mortality and lower ferritin levels during severe illness. Whether high serum ferritin is protective during severe infection requires further investigation.

Coronavirus disease 2019 (COVID-19) presents a clinical spectrum that ranges from a mild condition to critical illness. Patients with critical illness present respiratory failure, septic shock and/or multi-organ failure induced by the so called "cytokine storm". Inflammatory cytokines affect iron metabolism, mainly inducing the synthesis of hepcidin, a hormone peptide not routinely measured. High levels of hepcidin have been associated with the severity of COVID-19. The aim of this study was to analyze, retrospectively, the levels of hepcidin in a group of COVID-19 patients admitted to the intensive care unit (ICU) of the Policlinico Tor Vergata of Rome, Italy. Thirty-eight patients from November 2020 to May 2021 were enrolled in the study. Based on the clinical outcome, the patients were assigned to two groups: survivors and non-survivors. Moreover, a series of routine laboratory parameters were monitored during the stay of the patients in the ICU and their levels correlated to the outcome. Statistical differences in the level of hepcidin, D-dimer, IL-6, LDH, NLR, neutrophils level, CRP, TNF-α and transferrin were observed between the groups. In particular, hepcidin values showed significantly different median concentrations (88 ng/mL vs. 146 ng/mL) between survivors and non-survivors. In addition, ROC curves analysis revealed sensitivity and specificity values of 74% and 76%, respectively, at a cut-off of 127 (ng/mL), indicating hepcidin as a good biomarker in predicting the severity and mortality of COVID-19 in ICU patients.

The systemic viral disease caused by the SARS-CoV-2 called coronavirus disease 2019 (COVID-19) continues to be a public health problem worldwide.

This study is aimed to evaluate the association and predictive value of indices of systemic inflammation with severity and non-survival of COVID-19 in Mexican patients.

A retrospective study was carried out on 807 subjects with a confirmed diagnosis of COVID-19. Clinical characteristics, acute respiratory distress syndrome (ARDS), severity according to PaO2/FiO2 ratio, invasive mechanical ventilation (IMV), and non-survival outcome were considered to assess the predictive value and the association of 11 systemic inflammatory indices derived from hematological parameters analyzed at the hospital admission of patients. The receiver operating characteristics curve was applied to determine the thresholds for 11 biomarkers, and their prognostic values were assessed via the Kaplan-Meier method.

26% of the studied subjects showed COVID-19 severe (PaO2/FiO2 ratio ≤ 100), 82.4% required IMV, and 39.2% were non-survival. The indices NHL, NLR, RDW, dNLR, and SIRI displayed predictive values for severe COVID-19 and non-survival. NHL, SIRI, and NLR showed predictive value for IMV. The cut-off values for RDW (OR = 1.85, p < 0.001), NHL (OR = 1.67, p = 0.004) and NLR (OR = 1.56, p = 0.012) were mainly associated with severe COVID-19. NHL (OR = 3.07, p < 0.001), AISI (OR = 2.64, p < 0.001) and SIRI (OR = 2.51, p < 0.001) were associated with IMV support, while for non-survival the main indices associated were NHL (OR = 2.65, p < 0.001), NLR (OR = 2.26, p < 0.001), dNLR (OR = 1.92, p < 0.001), SIRI (OR = 1.67, p = 0.002) and SII (OR = 1.50, p = 0.010). The patients with an RDW, PLR, NLR, dNLR, MLR, SII, and NHL above the cut-off had a survival probability of COVID-19 50% lower, with an estimated mean survival time of 40 days.

The emergent systemic inflammation indices NHL, NLR, RDW, SII, and SIRI have a predictive power of severe COVID-19, IMV support, and low survival probability during hospitalization by COVID-19 in Mexican patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible and pathogenic coronavirus that has caused a 'coronavirus disease 2019' (COVID-19) pandemic in multiple waves, which threatens human health and public safety. During this pandemic, some patients with COVID-19 acquired secondary infections, such as mucormycosis, also known as black fungus disease. Mucormycosis is a serious, acute, and deadly fungal infection caused by Mucorales-related fungal species, and it spreads rapidly. Hence, prompt diagnosis and treatment are necessary to avoid high mortality and morbidity rates. Major risk factors for this disease include uncontrolled diabetes mellitus and immunosuppression that can also facilitate increases in mucormycosis infections. The extensive use of steroids to prevent the worsening of COVID-19 can lead to black fungus infection. Generally, antifungal agents dedicated to medical applications must be biocompatible, non-toxic, easily soluble, efficient, and hypoallergenic. They should also provide long-term protection against fungal growth. COVID-19-related black fungus infection causes a severe increase in fatalities. Therefore, there is a strong need for the development of novel and efficient antimicrobial agents. Recently, nanoparticle-containing products available in the market have been used as antimicrobial agents to prevent bacterial growth, but little is known about their efficacy with respect to preventing fungal growth, especially black fungus. The present review focuses on the effect of various types of metal nanoparticles, specifically those containing silver, zinc oxide, gold, copper, titanium, magnetic, iron, and carbon, on the growth of various types of fungi. We particularly focused on how these nanoparticles can impact the growth of black fungus. We also discussed black fungus co-infection in the context of the global COVID-19 outbreak, and management and guidelines to help control COVID-19-associated black fungus infection. Finally, this review aimed to elucidate the relationship between COVID-19 and mucormycosis.

Healthcare digitalization requires effective applications of human sensors, when various parameters of the human body are instantly monitored in everyday life due to the Internet of Things (IoT). In particular, machine learning (ML) sensors for the prompt diagnosis of COVID-19 are an important option for IoT application in healthcare and ambient assisted living (AAL). Determining a COVID-19 infected status with various diagnostic tests and imaging results is costly and time-consuming. This study provides a fast, reliable and cost-effective alternative tool for the diagnosis of COVID-19 based on the routine blood values (RBVs) measured at admission. The dataset of the study consists of a total of 5296 patients with the same number of negative and positive COVID-19 test results and 51 routine blood values. In this study, 13 popular classifier machine learning models and the LogNNet neural network model were exanimated. The most successful classifier model in terms of time and accuracy in the detection of the disease was the histogram-based gradient boosting (HGB) (accuracy: 100%, time: 6.39 sec). The HGB classifier identified the 11 most important features (LDL, cholesterol, HDL-C, MCHC, triglyceride, amylase, UA, LDH, CK-MB, ALP and MCH) to detect the disease with 100% accuracy. In addition, the importance of single, double and triple combinations of these features in the diagnosis of the disease was discussed. We propose to use these 11 features and their binary combinations as important biomarkers for ML sensors in the diagnosis of the disease, supporting edge computing on Arduino and cloud IoT service.

In severe COVID-19, the levels of iron (Fe), copper (Cu), zinc (Zn) and selenium (Se), do not only regulate host immune responses, but modify the viral genome, as well. While low serum Fe concentration is an independent risk factor for the increased death rate, Zn controls oxidative stress, synthesis of inflammatory cytokines and viral replication. Therefore, Zn deficiency associates with a worse prognosis. Although Cu exposure inactivates the viral genome and exhibits spike protein dispersal, increase in Cu/Zn due to high serum Cu levels, are correlated with enhanced risk of infections. Se levels are significantly higher in surviving COVID-19 patients. Meanwhile, both Zn and Se suppress the replication of SARS-CoV-2. Since the balance between the deficiency and oversupply of these metals due to a reciprocal relationship, has decisive effect on the prognosis of the SARS-CoV-2 infection, monitoring their concentrations may facilitate improved outcomes for patients suffering from COVID-19.