Normal Ranges for Acute Phase Reactants (Interleukin-6, Tumour Necrosis Factor-alpha and C-reactive Protein) in Umbilical Cord Blood of Healthy Term Neonates at the Mount Hope Women's Hospital, Trinidad

Role of biomarkers in prognostication of moderate and severe COVID-19 cases

Background

COVID-19 pandemic demanded upgrading of laboratory medicine to limit morbidity, disability and mortality from moderate and severe SARS-COV-2 infections.

Objective

To assess among moderate and severe COVID-19 patients, C-reactive protein (CRP), procalcitonin (PCT), ferritin, D-dimer, interleukin 6 (IL-6), lactate dehydrogenase (LDH), total and differential leucocyte count (TLC and DLC), neutrophil-to-lymphocyte ratio (NLR), absolute platelet count (APC), prothrombin time (PT), activated partial thromboplastin time (APTT) and international normalized ratio (INR) to find their interdependence and role in prognosis.

Methods

This open label analytical cross-sectional noninterventional study evaluated array of independent biochemical, haematological and coagulopathy markers, viz. CRP, PCT, ferritin, D-dimer, IL-6, LDH, TLC, DLC, NLR, absolute platelet count, PT, APTT and INR on consecutive 100 patients with diagnosis of moderate and severe COVID-19 from July to August 2021.

Results

In our study, on consecutive designated 100 cases (55 cases moderate and 45 cases severe), more severity were reported as the age progressed; gender difference was not noted. Among independent markers, CRP, PCT, ferritin, D-dimer, IL-6 and LDH had statistically significant relation in comparison with severity of the disease as Chi-square calculated value (P < 0.05). TLC, DLC and APC showed no significant relation in comparison with severity of the disease; NLR had highly significant relation. PT showed significant relation in comparison with severity, though APTT and INR did not show significant relation.

Conclusion

Our research group felt that CRP, PCT, ferritin, D-dimer, IL-6, LDH and NLR should be in included in clinical practice guidelines to prognosticate COVID-19 cases. Furthermore, translational researches are needed at all levels of healthcare to improve validity for practices of primary care physicians.

Hs-CRP and TNF-α Effects on Postnatal Umbilical Coiling: Impact Assessment of the Gestational Diabetes Mellitus

Background

No study has been conducted to specifically demonstrate the relationship between gestational diabetes mellitus (GDM) status, inflammatory factors, and postnatal umbilical coiling index (pUCI). Understanding this relationship could help select the best interventions to save the fetus. To evaluate the effects of maternal venous and umbilical cord blood levels of high sensitivity C-reactive protein (hs-CRP) and tumor necrosis factor-alpha (TNF-alpha) on pUCI in GDM and non-GDM groups.

Methods

This prospective observational study included 40 participants in each of the GDM and non-GDM groups, matched for maternal age, ethnicity, and parity. The GDM diagnosis was confirmed by 24 to 28 weeks of gestation (WOG) and a 2-step strategy. The covariates of interest were maternal hs-CRP and TNF-α, measured at 37 to 40 WOG, and their UC analogous was measured during delivery. The gross morphologies were assessed immediately after delivery. The UC coiling was quantitatively assessed by the pUCI. To compare the GDM and non-GDM groups, the t test and the Mann-Whitney test were used for normal and non-normal variables, respectively.

Results

There was not a significant difference in hs-CRP and TNF-a levels in maternal venous blood or UC blood between the GDM and non-GDM groups. The mean (SD) of pUCI in the GDM and non-GDM groups were 0.28 (0.15) and 0.24 (0.21) (P = 0.441), respectively. In the GDM group, none of the 4 covariates of interest had significant effects on the UCI. Among the non-GDM participants, merely the UC hs-CRP had a direct association with the pUCI, with a Pearson correlation of 0.54 (P = 0.001). Impacts of hs-CRP and TNF-α on the pUCI were assessed using Poisson regression models and no significant findings were detected (95% CI, 0.999-1.001, for all parameters).

Conclusion

In the GDM group, no apparent association was observed between inflammatory factors and pUCI, although a direct association was detected between UC hs-CRP and pUCI in the non-GDM.

Umbilical cord blood interleukin-6 level as a predictor of early-onset neonatal sepsis

    Background Neonatal sepsis is a global health problem contributing significantly to neonatal morbidity and mortality. It is difficult to clinically distinguish neonates with and without sepsis. Interleukin-6 (IL-6) concentration in neonates has high sensitivity and specificity to predict neonatal sepsis in infants at risk. Objective  To determine the utility of umbilical cord blood IL-6 as a predictor of early-onset neonatal sepsis. Methods This prospective cohort study was conducted in neonates born to mothers with sepsis risk factors from December 2020 to January 2021. We measured IL-6 from umbilical cord blood taken after placental expulsion. IL-6 ³16.4 pg/ml was considered to be elevated. Subjects were monitored for signs of clinical sepsis until 72 hours after birth. We also recorded the presence of other maternal and infant risk factors of sepsis and assessed association between IL-6 and other risk factors with the occurrence of sepsis, expressed as relative risk (RR) with 95% confidence interval (95%CI). Results During the study period, 40 neonates were born to mothers with sepsis risk factors; 13 (32.5%) developed clinical sepsis. Significantly more infants with elevated IL-6 developed neonatal sepsis (55.5%) than those with normal IL-6 (13.6%). After multivariate analysis incorporating other significant variables, the risk factors predictive of clinical early-onset neonatal sepsis were IL-6 [RR 5.54 (95%CI 1.68-18.25); P=0.016], prematurity [RR 4.92 (95%CI 1.66-14.59); P=0.014], and initial Apgar score [RR 3.38 (95%CI 1.34-3.38); P=0.046]. Conclusion In neonates with maternal risk factors, an IL-6 level of ³16.4 pg/ml is associated with an increased risk of early-onset neonatal sepsis.

Detection of COVID-19-related biomarkers by electrochemical biosensors and potential for diagnosis, prognosis, and prediction of the course of the disease in the context of personalized medicine

As a more efficient and effective way to address disease diagnosis and intervention, cutting-edge technologies, devices, therapeutic approaches, and practices have emerged within the personalized medicine concept depending on the particular patient's biology and the molecular basis of the disease. Personalized medicine is expected to play a pivotal role in assessing disease risk or predicting response to treatment, understanding a person's health status, and, therefore, health care decision-making. This work discusses electrochemical biosensors for monitoring multiparametric biomarkers at different molecular levels and their potential to elucidate the health status of an individual in a personalized manner. In particular, and as an illustration, we discuss several aspects of the infection produced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a current health care concern worldwide. This includes SARS-CoV-2 structure, mechanism of infection, biomarkers, and electrochemical biosensors most commonly explored for diagnostics, prognostics, and potentially assessing the risk of complications in patients in the context of personalized medicine. Finally, some concluding remarks and perspectives hint at the use of electrochemical biosensors in the frame of other cutting-edge converging/emerging technologies toward the inauguration of a new paradigm of personalized medicine.

Polymerized β-Cyclodextrin-Based Injectable Hydrogel for Sustained Release of 5-Fluorouracil/Methotrexate Mixture in Breast Cancer Management: In Vitro and In Vivo Analytical Validations

An inclusion complexation, between polymerized β-cyclodextrin and cholesterol end-capping branched polyethylene glycol, was utilized for constructing a self-assembled hydrogel. The physicochemical properties, the in vitro release profiles of 5-Fluorouracil/methotrexate (anticancer drugs), and the surface morphology of the resulting hydrogel were studied. Moreover, in vivo studies were carried out on female rats bearing breast cancer. The results revealed that the prepared systems were white in color, rubbery, and homogenous. The in vitro release studies showed an efficient ability of the modified system for drug loading and release in a sustained release manner for 14 days. The surface morphology was spongy porous. Moreover, the tumors’ healing was indicated from the analysis of tumor volume, plasma tumor markers, and histopathological analysis, compared to the controlled rats. The pharmacokinetic parameters appeared significant differences (p < 0.05) in the Cmax and Tmax of the medicated hydrogel samples, as compared with sole or combined saline-injected samples. The whole AUC of each drug in the medicated hydrogel samples was five-fold more than the mixture administrated in PBS. In conclusion, the proposed work delivered a hydrogel system that has a convenient ability for localized sustained release of breast cancer management.

Smart Injectable Chitosan Hydrogels Loaded with 5-Fluorouracil for the Treatment of Breast Cancer

The treatment of breast cancer requires long chemotherapy management, which is accompanied by severe side effects. Localized delivery of anticancer drugs helps to increase the drug concentration at the site of action and overcome such a problem. In the present study, chitosan hydrogel was prepared for local delivery of 5-Fluorouracil. The in vitro release behavior was investigated and the anticancer activity was evaluated against MCF-7 cells using MTT assay. The in vivo studies were investigated via intra-tumoral injection of a 5-FU loaded hydrogel into breast cancer of female rats. The results indicated that the modified hydrogel has excellent physicochemical properties with a sustained in vitro release profile matching a zero-order kinetic for one month. In addition, the hydrogel showed superior inhibition of cell viability compared with the untreated control group. Moreover, the in vivo studies resulted in antitumor activity with minor side effects. The tumor volume and level of tumor markers in blood were inhibited significantly by applying the hydrogel compared with the untreated control group. In conclusion, the designed injectable hydrogels are potential drug delivery systems for the treatment of breast cancer with a controlled drug release profile, which could be suitable for decreasing the side effects of chemotherapy agents.

Recent Advances in Bedside Device-Based Early Detection of Sepsis

Early detection of sepsis is challenging to achieve with current diagnostic methods, leading to expenditures of $27 billion annually in the United States with significant associated mortality. Various scoring systems have been proposed such as the sequential organ failure assessment (SOFA) and systemic inflammatory response syndrome (SIRS) criteria for identification of sepsis, but their sensitivities range from 60% to 70% when used in the emergency department triage. Other methods for the recognition of sepsis may rely on laboratory work, in addition to vitals monitoring, and are often outpaced by the development of sepsis. Automated alerts have not shown any reduction in mortality thus far. New technology may fill a critical gap in the early detection of sepsis. The ideal bedside screening device for would demonstrate rapid time to result, high portability, and high sensitivity to not miss cases, but also reasonable specificity to prevent provider fatigue from excessive false alerts. Non-invasive end-organ perfusion devices analyzing lactate and capillary refill time (CRT) tend to perform well in speed and portability, but may be less sensitive. Biomarker devices demonstrate a wider array of performance metrics. Those analyzing a single biomarker tend to be more sensitive but are less specific to the diagnosis of sepsis than technologies that assess multiple biomarkers, which in turn have lower sensitivity. Additionally, biomarker devices are generally invasive requiring blood samples, which may or may not be feasible in all patients especially when serial draws are needed. Sepsis is a complex disease process and most likely will require a combination of improved technology in addition to vital signs and high-risk patient history for better recognition. This review examines recent advances in the device-based early detection of sepsis between 2017 and 2020 with emphasis on bedside diagnostics, divided into markers of perfusion and biomarkers commonly implicated in sepsis.

Infection-Mediated Clinical Biomarkers for a COVID-19 Electrical Biosensing Platform

The race towards the development of user-friendly, portable, fast-detection, and low-cost devices for healthcare systems has become the focus of effective screening efforts since the pandemic attack in December 2019, which is known as the coronavirus disease 2019 (COVID-19) pandemic. Currently existing techniques such as RT-PCR, antigen-antibody-based detection, and CT scans are prompt solutions for diagnosing infected patients. However, the limitations of currently available indicators have enticed researchers to search for adjunct or additional solutions for COVID-19 diagnosis. Meanwhile, identifying biomarkers or indicators is necessary for understanding the severity of the disease and aids in developing efficient drugs and vaccines. Therefore, clinical studies on infected patients revealed that infection-mediated clinical biomarkers, especially pro-inflammatory cytokines and acute phase proteins, are highly associated with COVID-19. These biomarkers are undermined or overlooked in the context of diagnosis and prognosis evaluation of infected patients. Hence, this review discusses the potential implementation of these biomarkers for COVID-19 electrical biosensing platforms. The secretion range for each biomarker is reviewed based on clinical studies. Currently available electrical biosensors comprising electrochemical and electronic biosensors associated with these biomarkers are discussed, and insights into the use of infection-mediated clinical biomarkers as prognostic and adjunct diagnostic indicators in developing an electrical-based COVID-19 biosensor are provided.

Advancement in biosensors for inflammatory biomarkers of SARS-CoV-2 during 2019-2020

COVID-19 pandemic has affected everyone throughout the world and has resulted in the loss of lives of many souls. Due to the restless efforts of the researchers working hard day and night, some success has been gained for the detection of virus. As on date, the traditional polymerized chain reactions (PCR), lateral flow devices (LFID) and enzyme linked immunosorbent assays (ELISA) are being adapted for the detection of this deadly virus. However, a more exciting avenue is the detection of certain biomarkers associated with this viral infection which can be done by simply re-purposing our existing infrastructure. SARS-CoV-2 viral infection triggers various inflammatory, biochemical and hematological biomarkers. Because of the infection route that the virus follows, it causes significant inflammatory response. As a result, various inflammatory markers have been reported to be closely associated with this infection such as C-reactive proteins, interleukin-6, procalcitonin and ferritin. Sensing of these biomarkers can simultaneously help in understanding the illness level of the affected patient. Also, by monitoring these biomarkers, we can predict the viral infections in those patients who have low SARS-CoV-2 RNA and hence are missed by traditional tests. This can give more targets to the researchers and scientists, working in the area of drug development and provide better prognosis. In this review, we propose to highlight the conventional as well as the non-conventional methods for the detection of these inflammatory biomarkers which can act as a single platform of knowledge for the researchers and scientists working for the treatment of COVID-19.