Advances in biomarker sciences and technology最新文献

Background

Materials and methods

Results

Conclusion

Persistent inflammation can trigger the development of colorectal cancer, especially in patients with inflammatory bowel disease (IBD). The precise molecular mechanisms underlying this process are not fully understood. This study investigated the molecular modifications that occur in the cellular microenvironment during inflammation-induced and colitis-associated cancers. Studies showed that genetic mutations and post-translational modifications of oncogene proteins can alter the biological functions of macrophage inflammatory proteins, complicating the intricate interactions between inflammation and cancer. The researchers also observed abnormal glycosylation patterns in cases of inflammation and colitis-associated cancers. This observation suggests that glycoproteins present in bodily fluids could potentially serve as valuable disease markers. Additionally, the researchers investigated general signaling alterations that manifest in cases of colitis-associated cancer. They proposed a provisional molecular model that suggests the involvement of endoplasmic reticulum (ER) stress during the transition from inflammation to cancer. This potential pathway is mediated through the FKBP/c-Myc/p53 signaling axis. In the context of protein glycosylation, we summarize the potential molecular mechanisms of IBD-induced carcinogenesis. This knowledge could potentially lead to the development of novel targets for the clinical treatment of colorectal cancer.

Background

Biliary atresia (BA) is a disease of the intrahepatic or extrahepatic bile ducts with an unknown etiology. It presents in neonates with jaundice, clay-colored stool, and often hepatomegaly. Early diagnosis of the disease is pivotal for long-term prognosis. If the BA is left untreated, progressive liver cirrhosis and death can occur. Persisting jaundice in infants born at term should lead to further examination of liver diseases. A range of laboratory analyses is used, but none is specific for BA. In this review, we investigate whether the level of matrix metalloproteinase 7 (MMP-7) in serum can be used as an early diagnostic biomarker for BA.

Method

A systematic literature search of the PubMed database revealed the two terms “matrix metalloproteinase 7” and “biliary atresia”. A total of 24 articles were identified; these articles were screened, and eight articles were found to be relevant for this literature review, each describing an independent study.

Results

In all eight articles, the diagnostic cut-off values for serum MMP-7 in BA patients vs. non-BA patients were determined by receiver operating characteristic (ROC) curve analysis and by determining the area under the curve (AUC). The AUC ranged from 0.96 to 0.99. All studies had a sensitivity of 95 % or above and a specificity of 83 % or above. The cut-off values were discordant and ranged from 1.43 ng/ml to 52.85 ng/ml. The calculated positive likelihood ratio (PLR) varied from 5.66 to 21.86, and the negative likelihood ratio (NLR) varied from 0.01 to 0.05 among the eight studies. Finally, the diagnostic odds ratio (DOR) varied from 168.64 to 1406.00 in seven out of the eight studies.

Conclusion

The serum MMP-7 concentration can be used as a diagnostic biomarker according to the eight studies investigated in this review. However, further assessments of MMP-7 in larger, multicenter, and multiethnic studies are needed to validate its potential for biomarker development and, ultimately, its standard use in clinical practice.

A stroke is a medical emergency characterized by the sudden interruption of blood flow to the brain, leading to cell death from oxygen deprivation. As a leading cause of mortality and long-term disability worldwide, strokes present a growing socioeconomic challenge, exacerbated by demographic shifts and an increasing incidence in younger populations. Analyzing post-stroke conditions is essential for predicting recovery trajectories and guiding personalized treatments. The process is crucial for mitigating long-term cognitive deficits and improving the quality of life for stroke survivors and their families. Epigenetic mechanisms are emerging as key influencers, with four significant modulators—miRNAs, lncRNAs, DNA methylation, and histone modifications—being identified as central to modulating neuronal repair and regeneration. However, this is a lack of knowledge as to how major epigenetic signatures affect post-stroke recovery. The paper systematically reviews the capacity of miRNAs to fine-tune neuroprotective responses and the broader regulatory functions of lncRNAs. Additionally, we examine how shifts in DNA methylation patterns and histone modifications correlate with stroke outcomes, presenting a case for precise epigenetic therapies. In this review, we highlight that these modulators offer promising therapeutic targets for enhancing recovery and provide novel insights into stroke pathology and treatment. We also offer a comparative analysis of the four modulators and present the challenges and future perspectives for each one. The review sets forth a trajectory for future research, underscoring the development of novel epigenetic-based therapeutics as a groundbreaking approach to enhance post-stroke neurorehabilitation and improve patient prognoses.

Alzheimer's Disease (AD) is a disorder that worsens over time causing loss of memory and decline of cognitive functions. Current methods for diagnosis consist of neuroimaging scans, magnetic resonance imaging (MRI scans), positron emission tomography (PET scans), and identifying biomarkers in cerebrospinal fluid (CSF). New forms of advanced technology such as machine learning are rising to quickly diagnose AD. This work is a comprehensive review of the research that uses machine learning methods to classify AD cases early. It is a study to provide details for MRI scans and biomarkers used for the recognition of AD and evaluates the execution of both applications while using different classifiers. This paper will discuss and compare various machine learning methods that can be implemented for the classification of Alzheimer's disease. The applications of these algorithms (MRI and biomarkers) are also discussed ultimately proposing the best algorithm and application for classification.

The art of uroscopy (Greek ouron-urine and skopeo-examination), the visual inspection of urine, is as old as the history of mankind. It had seen its ups and downs, was praised and derided, but was ultimately perfected to become a complex visual and tasting examination tool. As centuries passed, it was replaced by urinalysis which was first based on iatrochemical principles and then followed by transmutation into modern biochemical analyses. Recent rapid development of sophisticated ‘omics’ technologies opened new avenues for the exploration of this important body fluid. This brief overview will take a journey through this fascinating history and will give a glimpse of what is to come in the future.

Lung cancer remains a global health crisis, responsible for significant morbidity and mortality. Late-stage diagnosis often limits treatment options and patient survival. Therefore, identifying reliable and sensitive biomarkers for early detection is crucial. Glycosylation, the addition of glycans to protein/RNA/lipid, is a vital cellular process. Normal glycosylation regulates healthy cell function, while alterations, particularly in fucosylation and sialylation, contribute to lung cancer development and progression. These aberrant glycosylation patterns are associated with processes such as immune modulation, cell migration, proliferation, and cell-cell recognition. Fucosylation, a specific type of glycosylation, is frequently altered in lung cancer, with high levels detected in tumors. Understanding the mechanisms behind this altered fucosylation holds immense potential. It can pave the way for the development of novel therapeutic and diagnostic tools for lung cancer. By analyzing specific fucosylation patterns in bodily fluids, it could lead to early-stage diagnosis. This review delves into the mechanisms of fucosylation in lung cancer initiation and metastasis, proposing promising strategies to target the mechanisms, aiming to inhibit tumor growth and disease progression.