Development of quantitative detection methods for four Alzheimer's disease specific biomarker panels using electrochemical immunosensors based on enzyme immunoassay.

Accurate and timely diagnosis of Alzheimer's disease (AD) is necessary to maximize the effectiveness of treatment and using biomarkers for diagnosis is attracting attention as a minimally invasive method with few side effects. Electrochemical immunosensor (EI) is a method that is in the spotlight in the medical and bioanalytical fields due to its portability and field usability. Here, we quantified four AD specific biomarkers using EIs based on enzyme immunoassay. We selected and developed quantitative methods for the biomarkers using screen-printed gold electrodes. For three biomarkers, quantification was performed using competition immunoassays in which antigen-antibody premix mixtures were applied to antigen-immobilized electrodes and the limit of detection (LOD) values were secured, 1.20 ng/ml, 1.30 ng/ml, and 1.74 ng/ml, respectively. For the other, a sandwich immunoassay using antibody pair was selected for quantification and LOD was also achieved as 0.077 ng/ml. All four biomarkers in buffer samples were successfully quantified and reliable R2 values were obtained, and reliable calibration curves were secured for three biomarkers in spiked human serum samples. The immunosensors developed and will be optimized are expected to be used in various fields, including detection of biomarkers for not only AD but also related diseases.

Environmental assessment of the central Atlantic coast of Morocco using a multibiomarker approach in Mytilus galloprovincialis.

A multibiomarker approach helps assess environmental health as it provides a complete tool to understand the effects of environmental stressors on ecosystems and human health. We applied this approach in the central Atlantic Ocean of Morocco, an area subjected to the impact of many types of pollutants, threatening the durability of its resources. In this study, four biomarkers acetylcholinesterase (AChE), glutathione-s-transferase (GST), metallothioneins (MTs), and catalase (CAT) were measured in the digestive gland of the mussel Mytilus galloprovincialis collected from four sites: Imsouane (S1), Cap Ghir (S2), Imi Ouaddar (S3), and Douira (S4). These sites were chosen due to the diversity of impacts ranging from industrial to agricultural and touristic. We also assembled all the enzymatic responses (AChE, GST, CAT, and MTs), using the integrated biomarker response (IBR), to estimate the degree of impact of pollutants at the prospected sites to reveal all the complex interactions between biomarkers and to classify sites via the integrated approach. Results show a seasonal change in biomarker responses with variability between sites. We also recorded the highest levels of AChE inhibition and GST induction in S1, higher levels of catalase activity in S4, and a significant impact on metallothionein concentration in S1 and S3. This project highlights the interest in using a multibiomarker approach to ensure accurate interpretation of biomarker variation to protect the Moroccan coast and its resources.

Technological Advances of Wearable Device for Continuous Monitoring of In Vivo Glucose.

Managing diabetes is a chronic challenge today, requiring monitoring and timely insulin injections to maintain stable blood glucose levels. Traditional clinical testing relies on fingertip or venous blood collection, which has facilitated the emergence of continuous glucose monitoring (CGM) technology to address data limitations. Continuous glucose monitoring technology is recognized for tracking long-term blood glucose fluctuations, and its development, particularly in wearable devices, has given rise to compact and portable continuous glucose monitoring devices, which facilitates the measurement of blood glucose and adjustment of medication. This review introduces the development of wearable CGM-based technologies, including noninvasive methods using body fluids and invasive methods using implantable electrodes. The advantages and disadvantages of these approaches are discussed as well as the use of microneedle arrays in minimally invasive CGM. Microneedle arrays allow for painless transdermal puncture and are expected to facilitate the development of wearable CGM devices. Finally, we discuss the challenges and opportunities and look forward to the biomedical applications and future directions of wearable CGM-based technologies in biological research.

Stroke risk in rheumatoid arthritis patients: exploring connections and implications for patient care.

Rheumatoid arthritis (RA) can independently increase the risk of stroke, affecting both young and adult RA patients. Recent attention has been drawn to the association between stroke and RA, supported by mounting evidence. Given that stroke is a significant and an urgent public health concern, this review aims to highlight the relationship between stroke and RA, covering mechanisms, underlying risk factors, early detection tools, and treatment implications. By uncovering the connection that links RA to stroke, we can pave the way for targeted healthcare practices and the development of preventive strategies for individuals with RA. Therefore, further research is imperative to deepen our understanding of this association and, ideally, guide treatment decisions for individuals at risk of both RA and stroke.

Multi-biomarker combination detection system for diagnosis and classification of dry eye disease by imaging of a multi-channel metasurface.

Dry eye disease (DED) is one of the most common ocular surface diseases, characterized by unstable tear film and ocular inflammation, affecting hundreds of millions of people worldwide. Currently, the clinical diagnosis of DED mainly relies on physical methods such as optical microscopy and ocular surface interferometric imaging, but classifying DED is still difficult. Here, we propose a compact and portable immune detection system based on the direct imaging of a nanophotonic metasurface with gradient geometry, for fast and ultra-sensitive detection of multiple biomarkers (i.e. Matrix metalloproteinase-9 (MMP-9), Lipocalin-1 (LCN-1), Lactoferrin (LTF)) in tears for the diagnosis and classification of DED. This centimeter-scale concentric nanophotonic metasurface, which consists of millions of unique metallic nanostructures, was fabricated through a cost-effective nanoimprint lithography (NIL) process. The immune detection system based on the antibody-modified metasurface shows favorable detection selectivity, an ultra-high sensitivity (3350 pixels/Refractive Index Unit (RIU)) and low limit of detection (LOD) (0.3 ng/mL for MMP-9, 1 ng/mL for LTF, and 0.5 ng/mL for LCN-1). Further clinical sampling and detection results demonstrated that this multi-biomarker detection system enabled accurate determination and symptom classification of DED, manifesting high correlation and consistency with clinical diagnosis results. The advantages such as low sample consumption, one-step detection, simple operation, and simultaneous detection of multiple biomarkers make the platform promising for screening and detecting a broader range of biomarker combinations in clinical practice.

A review study on early detection of pancreatic ductal adenocarcinoma using artificial intelligence assisted diagnostic methods.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive, chemo-refractory and recalcitrant cancer and increases the number of deaths. With just around 1 in 4 individuals having respectable tumours, PDAC is frequently discovered when it is in an advanced stage. Accordingly, ED of PDAC improves patient survival. Subsequently, this paper reviews the early detection of PDAC, initially, the work presented an overview of PDAC. Subsequently, it reviews the molecular biology of pancreatic cancer and the development of molecular biomarkers are represented. This article illustrates the importance of identifying PDCA, the Immune Microenvironment of Pancreatic Cancer. Consequently, in this review, traditional and non-traditional imaging techniques are elucidated, traditional and non-traditional methods like endoscopic ultrasound, Multidetector CT, CT texture analysis, PET-CT, magnetic resonance imaging, diffusion-weighted imaging, secondary signs of pancreatic cancer, and molecular imaging. The use of artificial intelligence in pancreatic cancer, novel MRI techniques, and the future directions of AI for PDAC detection and prognosis is then described. Additionally, the research problem definition and motivation, current trends and developments, state of art of survey, and objective of the research are demonstrated in the review. Consequently, this review concluded that Artificial Intelligence Assisted Diagnostic Methods with MRI images can be proposed in future to improve the specificity and the sensitivity of the work, and to classify malignant PDAC with greater accuracy.

Development of multiple biomarker panels for prediction of sarcopenia in community-dwelling older adults.

BACKGROUND: It is required to consider multiple biomarkers simultaneously to predict sarcopenia and to understand its complex pathological mechanisms. This study aimed to develop multiple biomarker panels for predicting sarcopenia in older adults and to further examine its association with the incidence of sarcopenia. METHODS: A total of 1,021 older adults were selected from the Korean Frailty and Aging Cohort Study. Sarcopenia was defined by the Asian Working Group for Sarcopenia 2019 criteria. Among the 14 biomarker candidates at baseline, eight biomarkers that could optimally detect individuals with sarcopenia were selected to develop a multi-biomarker risk score (range from 0 to 10). The utility of developed multi-biomarker risk score in discriminating sarcopenia was investigated using receiver operating characteristic (ROC) analysis. RESULTS: The multi-biomarker risk score had an area under the ROC curve (AUC) of 0.71 with an optimal cut-off of 1.76 score, which was significantly higher than all single biomarkers with AUC of <0.7 (all, p<0.01). During the two-year follow-up, the incidence of sarcopenia was 11.1%. Continuous multi-biomarker risk score was positively associated with incidence of sarcopenia after adjusting confounders (odds ratio [OR]=1.63; 95% confidence interval [CI]=1.23-2.17). Participants with a high risk score had higher odds of sarcopenia than those with a low risk score (OR=1.82; 95% CI=1.04-3.19). CONCLUSIONS: Multi-biomarker risk score, which was a combination of eight biomarkers with different pathophysiologies, better discriminated the presence of sarcopenia than a single biomarker, and it could further predict the incidence of sarcopenia over two years in older adults.

Blood biomarkers of mitochondrial disease-One for all or all for one?

The mitochondrial disease group consists of different disorders with unprecedented variability of clinical manifestations and tissue-specific symptoms. Their tissue-specific stress responses vary depending on the patients' age and type of dysfunction. These responses include secretion of metabolically active signal molecules to systemic circulation. Such signals-metabolites or metabokines-can be also utilized as biomarkers. During the past 10 years, metabolite and metabokine biomarkers have been described for mitochondrial disease diagnosis and follow-up, to complement the conventional blood biomarkers lactate, pyruvate and alanine. These new tools include metabokines FGF21 and GDF15; cofactors (NAD-forms); sets of metabolites (multibiomarkers) and the full metabolome. FGF21 and GDF15 are messengers of mitochondrial integrated stress response that together outperform the conventional biomarkers in specificity and sensitivity for muscle-manifesting mitochondrial diseases. Metabolite or metabolomic imbalance (e.g., NAD+ deficiency) is a secondary consequence to the primary cause in some diseases, but relevant as a biomarker and a potential indicator of therapy targets. For therapy trials, the optimal biomarker set needs to be tailored to match the disease of interest. The new biomarkers have increased the value of blood samples in mitochondrial disease diagnosis and follow-up, enabling prioritization of patients to different diagnostic paths and having crucial roles in follow-up of therapy effect.

Development and validation of circulating protein signatures as diagnostic biomarkers for biliary tract cancer.

Background & Aims: Biliary tract cancer (BTC) is associated with a dismal prognosis, partly because it is typically diagnosed late, highlighting the need for diagnostic biomarkers. The purpose of this project was to identify and validate multiprotein signatures that could differentiate patients with BTC from non-cancer controls. Methods: In this study, we included treatment-naïve patients with BTC, healthy controls, and patients with benign conditions including benign biliary tract disease. Participants were divided into three non-overlapping cohorts: a case-control-based discovery cohort (BTC = 186, controls = 249); a case-control-based validation cohort (validation cohort 1: BTC = 113, controls = 241); and a cohort study-based validation cohort including participants (BTC = 8, controls = 132) referred for diagnostic work-up for suspected cancer (validation cohort 2). Immuno-Oncology (I-O)-related proteins were measured in serum and plasma using a proximity extension assay (Olink Proteomics). Lasso and Ridge regressions were used to generate protein signatures of I-O-related proteins and carbohydrate antigen 19-9 (CA19-9) in the discovery cohort. Results: Sixteen protein signatures, including 2 to 82 proteins, were generated. All signatures included CA19-9 and chemokine C-C motif ligand 20. Signatures discriminated between patients with BTC vs. controls, with AUCs ranging from 0.95 to 0.99 in the discovery cohort and 0.94 to 0.97 in validation cohort 1. In validation cohort 2, AUCs ranged from 0.84 to 0.94. Nine signatures achieved a specificity of 82% to 84% while keeping a sensitivity of 100% in validation cohort 2. All signatures performed better than CA19-9, and signatures including >15 proteins showed the best performance. Conclusion: The study demonstrated that it is possible to generate protein signatures that can successfully differentiate patients with BTC from non-cancer controls. Impact and implications: We attempted to find blood sample-based protein profiles that could differentiate patients with biliary tract cancer from those without cancer. Several profiles were found and tested in different groups of patients. The profiles were successful at identifying most patients with biliary tract cancer, pointing towards the utility of multiprotein signatures in this context.

Plasma IGFBP-1, Fas, kallistatin, and P-selectin as predictive biomarkers of histologic chorioamnionitis and associated intra-amniotic infection in women with preterm labor.

PROBLEM: To determine whether altered levels of 13 plasma biomarkers, alone or in combination, could be independently associated with histologic chorioamnionitis (HCA) and microbial-associated HCA (defined as the presence of HCA along with microbial invasion) in women with preterm labor (PTL). METHODS OF STUDY: This was a retrospective cohort study involving 77 singleton pregnant women with PTL (23-34 gestational weeks) who delivered within 96 h of plasma and amniotic fluid (AF) sampling. DKK-3, E-selectin, Fas, haptoglobin, IGFBP-1, kallistatin, MMP-2, MMP-8, pentraxin 3, progranulin, P-selectin, SAA4, and TGFBI levels were assayed in plasma samples by ELISA. AF obtained via amniocentesis was used for microorganism identification. RESULTS: Multiple logistic regression analyses revealed significant associations between low plasma IGFBP-1 levels and acute HCA, and between low plasma Fas and kallistatin levels, and elevated plasma P-selectin levels and microbial-associated HCA (all p < .05), after adjusting for gestational age. Using a stepwise regression procedure, a multi-biomarker panel for microbial-associated HCA was developed, which included plasma MMP-2, kallistatin, and P-selectin levels (area under the curve [AUC], .867). The AUC for this three-marker panel was significantly or borderline significantly greater than that of any single variable included in the panel. However, a predictive model for acute HCA could not be developed because only one variable (MMP-2) was selected. CONCLUSIONS: These findings demonstrate that IGFBP-1, Fas, kallistatin, and P-selectin are associated with acute HCA and microbial-associated HCA in women with PTL. Their combined use can significantly improve the diagnostic ability for the detection of microbial-associated HCA.

One-Shot Full-Range Quantification of Multi-Biomarkers With Different Abundance by a Tandem Giant Magnetoresistance Assay.

In this study, we reported a tandem giant magnetoresistance (GMR) assay that realized the one-shot quantification of multi-biomarkers of infection, C-reactive protein (CRP) with procalcitonin (PCT), and neutrophil gelatinase-associated lipocalin (NGAL), all of which could cover their clinically relevant concentration ranges under a different principle. In the presence of co-determined assay, we quantified these three biomarkers in undiluted human blood serum in a single test. The tandem principle, based on which quantification of CRP occurs, combines a sandwich assay and an indirect competitive assay, which allows for the discrimination of the concentration values resulting from the multivalued dose-response curve ('Hook' effect), which characterizes the one-step sandwich assay at high CRP concentrations. However, the entire diagnostically dynamic range, in the quantification of PCT and NGAL, was achieved by differential coating of two identical GMR sensors operated in tandem and by combining two standard curves. The sensor quantified low detection limits and a broader dynamic range for the detection of infection biomarkers. The noticeable features of the assay are its dynamic range and small sample volume requirement (50 µL), and the need for a short measurement time of 15 min. These figures of merit render it a prospective candidate for practical use in point-of-care analysis.

Plasma E-selectin and kallistatin as predictive markers of histologic chorioamnionitis in women with preterm premature rupture of membranes.

PROBLEM: We aimed to assess the predictive potential of 12 plasma biomarkers to predict acute histologic chorioamnionitis (HCA) in women with preterm premature rupture of membranes (PPROM) and to develop multi-biomarker panels based on these biomarkers in combination with widely used conventional laboratory markers. METHOD OF STUDY: This was a retrospective cohort study involving 81 singleton pregnant women (24-34 weeks of gestation) who delivered within 96 h of blood sampling. White blood cell (WBC) count, differential counts, and C-reactive protein (CRP) levels were measured at admission. The levels of DKK-3, Fas, haptoglobin, IGFBP-2, kallistatin, MIP-1α, MMP-2, MMP-8, pentraxin 3, progranulin, E-selectin, and P-selectin were evaluated by ELISA using stored plasma samples. The primary outcome measure was acute HCA. RESULTS: Multivariate analyses showed that low plasma E-selectin and kallistatin levels were independently associated with HCA occurrence after adjusting for gestational age. Using a stepwise regression analysis, a multi-biomarker panel comprising plasma E-selectin, serum CRP, and WBC was developed, which provided a good prediction of acute HCA in women with PPROM (area under the curve [AUC], 0.899), with a significantly higher AUC than that of any single variable included in the panel (P < 0.05). The plasma levels of DKK-3, Fas, haptoglobin, IGFBP-2, MIP-1α, MMP-2, MMP-8, pentraxin 3, and P-selectin were not significantly associated with HCA occurrence. CONCLUSIONS: This study identified E-selectin and kallistatin as potential plasma biomarkers associated with acute HCA in women with PPROM. Their combined analysis with serum CRP and WBC counts significantly improved acute HCA diagnosis.

Risk Assessment after ST-Segment Elevation Myocardial Infarction: Can Biomarkers Improve the Performance of Clinical Variables?

INTRODUCTION: Myocardial infarction with ST-segment elevation (STEMI) is the coronary artery disease associated with the highest risk of morbimortality; however, this risk is heterogeneous, usually being evaluated by clinical scores. Risk assessment is a key factor in personalized clinical management of patients with this disease. AIM: The aim of this study was to assess whether some new cardiac biomarkers considered alone, combined in a multibiomarker model or in association with clinical variables, improve the short- and long-term risk stratification of STEMI patients. MATERIALS AND METHODS: This was a retrospective observational study of 253 patients with STEMI. Blood samples were obtained before or during the angiography. The assessed biomarkers were C-terminal fragment of insulin-like growth factor binding protein-4 (CT-IGFBP4), high sensitive cardiac troponin T (hs-cTnT), N-terminal fragment of probrain natriuretic peptide (NT-proBNP), and growth differentiation factor 15 (GDF-15); they reflect different cardiovascular (CV) physiopathological pathways and underlying pathologies. We registered in-hospital and follow-up mortalities and their causes (cardiovascular and all-cause) and major adverse cardiac events (MACE) during a two year follow-up. Discrimination, survival analysis, model calibration, and reclassification of the biomarkers were comprehensively evaluated. RESULTS AND DISCUSSION: In total, 55 patients (21.7%) died, 33 in-hospital and 22 during the follow-up, most of them (69.1%) from CV causes; 37 MACE occurred during follow-up. Biomarkers showed good prognostic ability to predict mortality, alone and combined with the multibiomarker model. A predictive clinical model based on age, Killip-Kimball class, estimated glomerular filtration rate (eGFR), and heart rate was derived by multivariate analysis. GDF-15 and NT-proBNP significantly improved risk assessment of the clinical model, as shown by discrimination, calibration, and reclassification of all the end-points except for all-cause mortality. The combination of NT-proBNP and hs-cTnT improved CV mortality prediction. CONCLUSIONS: GDF-15 and NT-proBNP added value to the usual risk assessment of STEMI patients.

Impacts of di-(2-ethylhexyl) phthalate on Folsomia candida (Collembola) assessed with a multi-biomarker approach.

Di-(2-ethylhexyl) phthalate (DEHP) is extensively used as an additive to produce plastics, but it may damage non-target organisms in soil. In this study, the effects of DEHP on Folsomia candida in terms of survival, reproduction, enzyme activities, and DNA damage were investigated in spiked artificial soil using a multi-biomarker strategy. The 7-day LC50 (median lethal concentration) and 28-day EC50 (median effect concentration) values of DEHP were 1256.25 and 19.72 mg a.i. (active ingredient) kg-1 dry soil, respectively. Biomarkers involved in antioxidant defense including catalase (CAT-catalase), glutathione S-transferases (GST), detoxifying enzymes including acetylcholinesterase (AChE), Cytochrome P450 (CYP450), and peroxidative damage (LPO-lipid peroxide) were also measured (EC10, EC20, and EC50) after exposure for 2, 4, 7, and 14 days. The Comet assay was also applied to assess the level of genetic damage. The activity of CAT and LPO was drastically enhanced by the highest dose (EC50) of DEHP on day two. The activities of GST and AChE in DEHP treatment groups were found to be blocked. In contrast, the activity of CYP450 was significantly enhanced compared to the respective control groups during the first four days of incubation. The Comet assay in F.candida demonstrated that DEHP (EC50) could induce DNA damage. The obtained multi-biomarker data were analyzed using an integrated biomarker response (IBR) index, indicating that limited-time exposure triggered higher stress than long-term exposure at low concentrations of DEHP. These results demonstrate that DEHP may cause biochemical and genetic toxicity to F. candida, which illustrated the potential risks of DEHP in the soil environment and might affect soil ecosystem processes. Further studies are necessary to elucidate the toxic mechanisms of DEHP on other non-target organisms in soil.

Assessment of the marine ecotoxic state in the Moroccan coastal area Anza-Taghazout following the installation of two wastewater treatment plants: a multibiomarker study using Mytilus galloprovincialis.

The aim of the present study is the first to evaluate the ecotoxic state of the marine environment in Anza-Taghazout coasts (Morocco) after installation of two wastewater treatment plants using a natural population of marine bivalves Mytilus galloprovincialis. These coasts are exposed to many discharges generating, thus, different sources of pollutants. These pollutants can modulate the physiological responses of marine bivalves to environmental stress. In this context, a multibiomarker approach consisting of a battery of biomarker evaluation was used to assess the response of these species to stress. In the whole soft tissues of M. galloprovincialis, four biomarkers were evaluated as follows: acetylcholinesterase (AChE), glutathione S-transferase (GST), catalase (Cat), and malondialdehyde activity (MDA). In parallel, physico-chemical parameters were measured in the marine water of Anza-Taghazout within three selected sites: S1 considered as "hotspot" located at Anza city; S2 located near of Aourir city; and the third site, S3 "reference" located in Imouran beach. Our results showed that activities of both glutathione S-transferase and catalase were higher in M. galloprovincialis collected from site S1, but high values of malondialdehyde and acetylcholinesterase activities were observed successively at S3 and S2. Application of integrated biomarker response (IBR) index was suitable for classifying the stress response in the M. galloprovincialis but did not allow to evaluate the level of the xenobiotic exposure in the studied sites. The statistical results did not show any significant differences between the three studied sites, and therefore, S1 has recently become clean due to the installation of two wastewater treatment plants.

An integrated approach using chemical ecological risk assessment and multi-integrated biomarker indexes approach to assess pollution: A case study of Ruditapes philippinarum in four bays on the Shandong Peninsula in China.

Considering the ecological risks of polycyclic aromatic hydrocarbons (PAHs) to the marine environment, it is urgent to find scientific and effective monitoring methods. In this study, an integrated approach combining chemical ecological risk assessment and multi-integrated biomarker indexes approach was used to assess the marine environment. Samples included seawater, sediments, and clam Ruditapes philippinarum were collected from four bays on the Shandong Peninsula, China in the four seasons of 2019. The concentrations, composition, potential sources, and ecological risk of PAHs were investigated in seawater and sediments. Risk quotient (RQ) and sediment quality guidelines (SQGs) were calculated to assess the ecological risks of PAHs in seawater and sediment, respectively. And then, clam Ruditapes philippinarum's multi-level biological response, including its ethoxyresorufin-O-deethylase (EROD), glutathione S-transferase (GST), superoxide dismutase (SOD), lipid peroxidation (LPO), and acetylcholinesterase (AChE) were investigated in-depth, by which multi-integrated biomarker indexes approach were calculated to evaluate marine environmental quality. Taken together, the results showed that the concentration of PAHs was in good agreement with the response of biomarkers, and the usefulness of the combined use of chemical ecological risk assessment and integrated biomarker indexes to assess PAHs pollution was verified.

Multibiomarker approach to assess the magnitude of occupational exposure and effects induced by a mixture of metals.

Metals and metalloids including lead (Pb), arsenic (As) and manganese (Mn) can occur as mixtures in occupational contexts, such as mines. These chemicals are all known to be neurotoxic and provoke changes in heme metabolism also known to induce neurotoxicity. The objective of this work was to propose a multi-biomarker (BM) methodology to screen subjects exposed to the mixture of Pb, As and Mn and assess the severity of their exposure/effects, in an individual basis. The urinary levels of the metals, dela-aminolevulinic acid (ALA) and porphyrins were determined in Portuguese miners and in a control group. The combination of Pb and As urinary levels had the highest capability to identify subjects occupationally exposed to this mixture in mines, as evaluated through Receiver Operating Characteristic (ROC) (A = 98.2%; p < 0.05), allowing that 94.2% of 86 studied subjects were properly identified and the generation of an equation indicating the odd of a subject be considered as exposed to the metal mixture. The combination of urinary ALA and porphyrins revealed to be best one to be applied in the assessment of subjects with high, intermediate, and low magnitudes of exposure/effects, with 95.7% of 46 miners classified correctly according to their severity sub-group and allowing to generate equations, which can be applied in new subjects. The proposed methodology showed a satisfactory performance, evaluating in an integrated manner the magnitude of exposure/effects of the exposed workers, may contributing to improve the control of their health.

Multi-biomarker is an early-stage predictor for progression of Coronavirus disease 2019 (COVID-19) infection.

Coronavirus disease 2019 (COVID-19) has spread widely in the communities in many countries. Although most of the mild patients could be cured by their body's ability to self-heal, many patients quickly progressed to severe disease and had to undergo treatment in the intensive care unit (ICU). Thus, it is very important to effectively predict which patients with mild disease are more likely to progress to severe disease. A total of 72 patients hospitalized with COVID-19 in Shandong Provincial Public Health Clinical Center and 1141 patients included in the published papers were enrolled in this study. We determined that the combination of interleukin-6 (IL-6), Neutrophil (NEUT), and Natural Killer (NK) cells had the highest prediction accuracy (with 75% sensitivity and 95% specificity) for progression of COVID-19 infection. A binomial regression equation that accounted for a multiple risk score for the combination of IL-6, NEUT, and NK was also established. The multiple risk score is a good indicator for early stratification of mild patients into risk categories, which is very important for adjusting the treatment plan and preventing death.

Biological responses in pesticide exposed lizards (Podarcis siculus).

The release of contaminants as herbicides, fungicides and insecticides into the environment has been listed as one of the six major contributors to the global decline of reptiles. Although reptiles may face severe risk from contaminants due to their ecology and physiology, they are currently less studied than other vertebrate groups. In the present work, we investigated if and how different types of field treatment (conventional and organic) affected the health status of Italian wall lizard (Podarcis siculus) individuals in central Italy. We chose a multi-biomarker approach that evaluated the biological responses of lizards to the treatment by means of AChE activity in the nervous system, biotransformation enzymes activities and oxidative stress in the liver, micronuclei frequency measured in the erythrocytes, and rate of intestinal parasitic infection. Our findings showed evidence of effects of treatment in conventional areas and between sexes with significant oxidative stress due to hydroxyl radicals, that caused DNA damage. No difference of intestinal parasite infections was found among treatments. Podarcis siculus seems to be a good bioindicator in ecotoxicological studies and potentially in risk assessment of pesticides, although further analyses in laboratory and in the field are needed to achieve more accurate quantification of specific pesticide effects in relation to known exposure history and to understand if other mechanisms were involved in the toxicity and detoxification process of pesticides for this species.

Evaluation of a Three-Marker Panel for the Detection of Uveal Melanoma Metastases: A Single-Center Retrospective Analysis.

Blood-based B-cell activating factor (BAFF), growth differentiation factor-15 (GDF-15) and osteopontin (OPN) have been identified to be promising biomarkers for the metastases of uveal melanoma (UM). This study intended to assess their kinetics and to evaluate their significance as a three-marker panel. A group of 36 UM patients with and 137 patients without metastases were included in the study. Their plasma OPN levels were measured by ELISA; serum BAFF and GDF-15 levels were determined with a Luminex MAGPIX system. Receiver operating characteristic (ROC) analysis was performed to calculate the cutoff values of the three markers for identifying the patients with metastases. The ability to identify patients with metastases was compared between the single markers and the combination as a three-marker panel. By using the Student's t-test, we also investigated the kinetic changes of the levels of BAFF, GDF-15 and OPN across six periods (i.e., 0-6 months, 6-12 months, 12-18 months, 18-24 months, >24 months and post-metastasis) before the imaging diagnosis of metastases. By maximizing the Youden's index, the serum GDF-15 level of 1209 pg/mL and the plasma OPN level of 92 ng/mL were identified to have the best performance for distinguishing the metastatic patients from non-metastatic patients. The three-marker panel offered a better performance in distinguishing patients with metastases, with an area under the curve of 0.802, than any single biomarker. Increasing trends of the levels of three biomarkers were observed in the two-year period before the imaging diagnosis of metastases. The combined panel of BAFF, GDF-15 and OPN might be a utilizable implementation for the detection of UM metastases. In the bioinformatics study with two external datasets, the high expression of gene BAFF and GDF-15 in primary UM tissues was identified to be associated with poor overall survival rates. As the current work is a single-center retrospective study, more well-designed prospective investigations employing larger cohorts are urgently needed to validate our findings.