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Emerging Biomarkers: Recent Findings and Application in Pathological Condition Detection—2nd...
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Emerging Biomarkers: Recent Findings and Application in Pathological Condition Detection—2nd Edition

A special issue of Life (ISSN 2075-1729). This special issue belongs to the section "Medical Research".

Deadline for manuscript submissions: 31 March 2025 | Viewed by 7788

Special Issue Editor

Prof. Dr. Antonella Angiolillo

E-Mail Website
Guest Editor
Department of Medicine and Health Sciences "Vincenzo Tiberio", University of Molise, 86100 Campobasso, Italy
Interests: laboratory medicine; biomarkers; metabolomics; stem cell; cystic fibrosis; neurologic diseases
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the first volume of this Special Issue being a great success (https://www.mdpi.com/journal/life/special_issues/Emerging_Biomarkers), we invite you to publish your research in the second volume.

In recent years, the search for disease biomarkers has been gaining increasing attention of the scientific community, since new strategies are needed for early and accurate diagnosis, and new therapeutic approaches, as well as to identify or modify the course of several diseases. The surge of interest in biomarker research is leading to the development of new predictive, diagnostic and prognostic products in medical practice, and biomarkers are also playing an increasingly important role in the discovery and development of new drugs.

Understanding the relationship between measurable biological processes and clinical outcomes is crucial to expanding our chances of treating several diseases, and deepening our understanding of physiological conditions.

The use of biomarkers in basic and clinical research, as well as in clinical practice has become so wide that their presence as primary endpoints in clinical trials is widely accepted.

In this Special Issue, advances will be presented in the identification of reliable, sensitive, specific, non-invasive, inexpensive and easily detectable biomarkers that could provide a dynamic and powerful approach, useful in understanding the broad spectrum of the various pathologies.

All contributions from researchers dealing with the identification of biomarkers, the elucidation of their role and the formalization of their application in modern medicine are welcome.

Dr. Antonella Angiolillo
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Life is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biomarkers
  • biological fluids
  • early diagnosis
  • laboratory medicine

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Published Papers (5 papers)

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Research

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11 pages, 2481 KiB  
Article
Inflammatory and Lipid Biomarkers in Early Atherosclerosis: A Comprehensive Analysis
by Alim Namitokov, Karina Karabakhtsieva and Olga Malyarevskaya
Life 2024, 14(10), 1310; https://doi.org/10.3390/life14101310 - 16 Oct 2024
Viewed by 1128
Abstract
Introduction: Atherosclerosis is a leading cause of cardiovascular disease, characterized by lipid accumulation and chronic inflammation within arterial walls. Early detection in young adults is crucial for preventing adverse cardiovascular events. This study investigates the associations between inflammatory indices, lipid biomarkers, and the [...] Read more.
Introduction: Atherosclerosis is a leading cause of cardiovascular disease, characterized by lipid accumulation and chronic inflammation within arterial walls. Early detection in young adults is crucial for preventing adverse cardiovascular events. This study investigates the associations between inflammatory indices, lipid biomarkers, and the presence of atherosclerosis in patients aged 18 to 55 years. Methods: A cross-sectional study was conducted involving 89 participants divided into two groups: 62 patients with documented atherosclerosis (main group) and 27 healthy controls without significant atherosclerosis. Comprehensive data—including demographic information, medication use, imaging results, laboratory parameters, and calculated inflammatory indices (SIRI, SII, AISI, NLR, PLR, MLR)—were collected. Statistical analyses included correlation assessments, group comparisons using the Mann–Whitney U test, logistic regression modeling, feature importance analysis with Random Forest and Gradient Boosting classifiers, receiver operating characteristic (ROC) curves, and K-means clustering. Results: Significant differences were observed between the main and control groups. Patients with atherosclerosis exhibited elevated inflammatory indices (SIRI, NLR, MLR, SII) and lipid profile abnormalities (higher TC and LDL-C, lower HDL-C). Lp(a) and ANGPTL3 levels were significantly higher in the main group (p < 0.001 and p < 0.01, respectively). Logistic regression identified SIRI and ANGPTL3 as significant predictors of atherosclerosis, with the model demonstrating high accuracy (77%) and sensitivity (93%). Feature importance analysis confirmed the significance of SIRI and ANGPTL3, alongside traditional lipid biomarkers, in predicting disease presence. ROC analysis showed excellent model performance (AUC > 0.80). Clustering analysis revealed two distinct patient subgroups characterized by predominant inflammatory profiles or lipid metabolism disturbances. Conclusions: Systemic inflammation and lipid abnormalities play significant roles in early atherosclerosis among young adults. Elevated SIRI and ANGPTL3 levels are potent predictors of disease presence. The integration of inflammatory indices and lipid biomarkers into predictive models enhances risk stratification and supports personalized medicine approaches. Full article
(This article belongs to the Special Issue Emerging Biomarkers: Recent Findings and Application in Pathological Condition Detection—2nd Edition)
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18 pages, 1176 KiB  
Article
Biomarkers and Data Visualization of Insulin Resistance and Metabolic Syndrome: An Applicable Approach
by Christos Sotiropoulos, Nikolaos Giormezis, Vayianos Pertsas and Theodoros Tsirkas
Life 2024, 14(9), 1197; https://doi.org/10.3390/life14091197 - 21 Sep 2024
Cited by 2 | Viewed by 1496
Abstract
Type 2 diabetes, prediabetes, and insulin resistance (IR) are widespread yet often undetected in their early stages, contributing to a silent epidemic. Metabolic Syndrome (MetS) is also highly prevalent, increasing the chronic disease burden. Annual check-ups are inadequate for early detection due to [...] Read more.
Type 2 diabetes, prediabetes, and insulin resistance (IR) are widespread yet often undetected in their early stages, contributing to a silent epidemic. Metabolic Syndrome (MetS) is also highly prevalent, increasing the chronic disease burden. Annual check-ups are inadequate for early detection due to conventional result formats that lack specific markers and comprehensive visualization. The aim of this study was to evaluate low-budget biochemical and hematological parameters, with data visualization, for identifying IR and MetS in a community-based laboratory. In a cross-sectional study with 1870 participants in Patras, Greece, blood samples were analyzed for key cardiovascular and inflammatory markers. IR diagnostic markers (TyG-Index, TyG-BMI, Triglycerides/HDL ratio, NLR) were compared with HOMA-IR. Innovative data visualization techniques were used to present metabolic profiles. Notable differences in parameters of cardiovascular risk and inflammation were observed between normal-weight and obese people, highlighting BMI as a significant risk factor. Also, the inflammation marker NHR (Neutrophils to HDL-Cholesterol Ratio) Index was successful at distinguishing the obese individuals and those with MetS from normal individuals. Additionally, a new diagnostic index of IR, combining BMI (Body Mass Index) and NHR Index, demonstrated better performance than other well-known indices. Lastly, data visualization significantly helped individuals understand their metabolic health patterns more clearly. BMI and NHR Index could play an essential role in assessing metabolic health patterns. Integrating specific markers and data visualization in routine check-ups enhances the early detection of IR and MetS, aiding in better patient awareness and adherence. Full article
(This article belongs to the Special Issue Emerging Biomarkers: Recent Findings and Application in Pathological Condition Detection—2nd Edition)
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29 pages, 7127 KiB  
Article
A Method for Real-Time Lung Nodule Instance Segmentation Using Deep Learning
by Antonella Santone, Francesco Mercaldo and Luca Brunese
Life 2024, 14(9), 1192; https://doi.org/10.3390/life14091192 - 20 Sep 2024
Viewed by 1782
Abstract
Lung screening is really crucial in the early detection and management of masses, with particular regard to cancer. Studies have shown that lung cancer screening, can reduce lung cancer mortality by 20–30% in high-risk populations. In recent times, the advent of deep learning, [...] Read more.
Lung screening is really crucial in the early detection and management of masses, with particular regard to cancer. Studies have shown that lung cancer screening, can reduce lung cancer mortality by 20–30% in high-risk populations. In recent times, the advent of deep learning, with particular regard to computer vision, demonstrated the ability to effectively detect and locate objects from video streams and also (medical) images. Considering these aspects, in this paper, we propose a method aimed to perform instance segmentation, i.e., by providing a mask for each lung mass instance detected, allowing for the identification of individual masses even if they overlap or are close to each other by classifying the detected masses into (generic) nodules, cancer or adenocarcinoma. In this paper, we considered the you-only-look-once model for lung nodule segmentation. An experimental analysis, performed on a set of real-world lung computed tomography images, demonstrated the effectiveness of the proposed method not only in the detection of lung masses but also in lung mass segmentation, thus providing a helpful way not only for radiologist to conduct automatic lung screening but also for discovering very small masses not easily recognizable to the naked eye and that may deserve attention. As a matter of fact, in the evaluation of a dataset composed of 3654 lung scans, the proposed method obtains an average precision of 0.757 and an average recall of 0.738 in the classification task. Additionally, it reaches an average mask precision of 0.75 and an average mask recall of 0.733. These results indicate that the proposed method is capable of not only classifying masses as nodules, cancer, and adenocarcinoma, but also effectively segmenting the areas, thereby performing instance segmentation. Full article
(This article belongs to the Special Issue Emerging Biomarkers: Recent Findings and Application in Pathological Condition Detection—2nd Edition)
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Review

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20 pages, 2121 KiB  
Review
The ncRNA-AURKA Interaction in Hepatocellular Carcinoma: Insights into Oncogenic Pathways, Therapeutic Opportunities, and Future Challenges
by Clarissa Joy C. Garcia, Luca Grisetti, Claudio Tiribelli and Devis Pascut
Life 2024, 14(11), 1430; https://doi.org/10.3390/life14111430 - 6 Nov 2024
Viewed by 1048
Abstract
Hepatocellular carcinoma (HCC) represents a major public health concern and ranks among the leading cancer-related mortalities globally. Due to the frequent late-stage diagnosis of HCC, therapeutic options remain limited. Emerging evidence highlights the critical role of non-coding RNAs (ncRNAs) in the regulation of [...] Read more.
Hepatocellular carcinoma (HCC) represents a major public health concern and ranks among the leading cancer-related mortalities globally. Due to the frequent late-stage diagnosis of HCC, therapeutic options remain limited. Emerging evidence highlights the critical role of non-coding RNAs (ncRNAs) in the regulation of Aurora kinase A (AURKA), one of the key hub genes involved in several key cancer pathways. Indeed, the dysregulated interaction between ncRNAs and AURKA contributes to tumor development, progression, and therapeutic resistance. This review delves into the interplay between ncRNAs and AURKA and their role in hepatocarcinogenesis. Recent findings underscore the involvement of the ncRNAs and AURKA axis in tumor development and progression. Furthermore, this review also discusses the clinical significance of targeting ncRNA-AURKA axes, offering new perspectives that could lead to innovative therapeutic strategies aimed at improving outcomes for HCC patients. Full article
(This article belongs to the Special Issue Emerging Biomarkers: Recent Findings and Application in Pathological Condition Detection—2nd Edition)
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23 pages, 3503 KiB  
Review
Endotyping Chronic Respiratory Diseases: T2 Inflammation in the United Airways Model
by Pasquale Ambrosino, Giuseppina Marcuccio, Giuseppina Raffio, Roberto Formisano, Claudio Candia, Fabio Manzo, Germano Guerra, Ennio Lubrano, Costantino Mancusi and Mauro Maniscalco
Life 2024, 14(7), 899; https://doi.org/10.3390/life14070899 - 19 Jul 2024
Viewed by 1752
Abstract
Over the past 15 years, the paradigm of viewing the upper and lower airways as a unified system has progressively shifted the approach to chronic respiratory diseases (CRDs). As the global prevalence of CRDs continues to increase, it becomes evident that acknowledging the [...] Read more.
Over the past 15 years, the paradigm of viewing the upper and lower airways as a unified system has progressively shifted the approach to chronic respiratory diseases (CRDs). As the global prevalence of CRDs continues to increase, it becomes evident that acknowledging the presence of airway pathology as an integrated entity could profoundly impact healthcare resource allocation and guide the implementation of pharmacological and rehabilitation strategies. In the era of precision medicine, endotyping has emerged as another novel approach to CRDs, whereby pathologies are categorized into distinct subtypes based on specific molecular mechanisms. This has contributed to the growing acknowledgment of a group of conditions that, in both the upper and lower airways, share a common type 2 (T2) inflammatory signature. These diverse pathologies, ranging from allergic rhinitis to severe asthma, frequently coexist and share diagnostic and prognostic biomarkers, as well as therapeutic strategies targeting common molecular pathways. Thus, T2 inflammation may serve as a unifying endotypic trait for the upper and lower airways, reinforcing the practical significance of the united airways model. This review aims to summarize the literature on the role of T2 inflammation in major CRDs, emphasizing the value of common biomarkers and integrated treatment strategies targeting shared molecular mechanisms. Full article
(This article belongs to the Special Issue Emerging Biomarkers: Recent Findings and Application in Pathological Condition Detection—2nd Edition)
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