Prognosis Monitoring Research Articles

Recent Advances in Wash-Free Detection Methods of Extracellular Vesicles: A Mini Review.

Extracellular vesicles (EVs) are emerging biomarkers in liquid biopsy that have gained increasing attention in disease diagnosis and prognosis monitoring. Most reported detection methods require the isolation of EVs from complex body liquids, often involving multiple washing steps to remove excess reagents and eliminate background interference. Nonetheless, these methods not only cause the loss of EVs but also result in poor repeatability and prolonged detection duration. The focus on wash-free detection methods is increasing due to the specific ability to avoid the removal of surplus reagents and, in some cases, even the isolation and purification of EVs. Viewing from different methodological perspectives, this review summarizes the recent advances in wash-free detection of EVs, containing aggregation induction, proximity sensing, allosteric probes, phase separation, Roman spectroscopy, field-effect transistor and microcantilever. The pros and cons of each detection strategy are impartially evaluated and this review concludes the prospects for future developments in this field.

Urine-based SERS and multivariate statistical analysis for identification of non-muscle-invasive bladder cancer and muscle-invasive bladder cancer.

Bladder cancer (BC) is an epidemiological urologic malignancy that continues to increase each year. Early diagnosis and prognosis monitoring is always significant in clinical practice, especially in distinguishing non-muscle-invasive bladder cancer (NMIBC) from muscle-invasive bladder cancer (MIBC), due to the various depths of tumor invasion related to different therapeutic schedules and recurrence rates. Common diagnostic approaches are too invasive or generally inefficient in accuracy and specificity. In this work, a totally non-invasive and cost-effective method is established by investigating urine samples using surface-enhanced Raman spectroscopy (SERS) and multivariate statistical analysis. The comparison of urine SERS spectra shows the intensities of characteristic peaks for DNA/RNA, hypoxanthine, albumin, D-( +)-galactosamine, fatty acids, and some amino acids are distinguishable in BC occurrence and invasion progression. A PLS-LDA-based two-step binary classification scheme is performed on urine SERS spectra and the diagnostic accuracies were 97.7% and 96.3% for healthy individuals versus BC patients and NMIBC versus MIBC patients, respectively. Moreover, the impact of urine SERS spectral lengths in reaching high-precision recognition of BC is investigated. The results show that the Raman peaks at 803, 893, 1139, 1375, and 1466cm-1 play an essential role in correctly categorizing healthy control, NMIBC, and MIBC patients, and SERS spectra ranges from 400 to 1600cm-1 are enough for this identification task. These findings provide a sensitive, label-free, rapid, and totally non-invasive way for assessment of invasion depth of BC to its early diagnosis and prognosis monitoring, as well as valuable insights for selecting reasonable spectral range to enhance the measurement efficiency especially in large-scale sample datasets.

Development of photoelectrochemical immunosensor based on halide perovskite protected by organometallic compounds for determining interleukin-17A (IL-17A).

The overexpression of interleukin-17A (IL-17A) is closely associated with the pathogenesis of autoimmune diseases and cancer, rendering precise identification of IL-17A level critical for disease diagnosis and prognosis monitoring. In this study, CsPbBr3 nanoclusters (NCs) were embedded in C16H14Br2O6Pb2 organometallic compound (Pb-MA MOC) via a hot injection approach. Through this way, the issue of CsPbBr3 NCs susceptible to decomposition in water was solved, and the photocurrent intensity that isgenerated by CsPbBr3 was significantly enhanced. A highly sensitive photoelectrochemical (PEC) sensor for detecting IL-17A in human serum was developed using CsPbBr3/Pb-MA as the photoactive material. The electrode was initially modified with CsPbBr3/Pb-MA. Then, antibody-modified Fe3O4 magnetic nanoparticles (MNs) with target analyte IL-17A captured, and IL-17A antibody-modified Au@CuNi diatomic catalyst (DAC) formed sandwich immune complex structure on theelectrode. The existence of CuNi DAC led to a substantial reduction in photoelectric signal intensity due to oxidation of ascorbic acid in thesupporting electrolyte. The photocurrent intensity exhibited linear correlation with IL-17A concentration within the range 15-750pg/mL, and achieving an impressive detection limit of1pg/mL. Moreover, the sensor was successfully applied to the determination of IL-17A in human serum, suggesting its potential clinical applications.

Optimal preservation condition for the extraction of cell-free DNA from bile of patients with biliary tract cancer.

Patients with biliary tract cancer (BTC) often have dismal outcomes due to the poor performance of traditional methods for early diagnosis. Recently, bile cell-free DNA (cfDNA) has been reported as a potential liquid biopsy material for BTC diagnosis. However, bile is a complex alkaline aqueous medium, and the proper storage conditions for bile remain to be explored. The aim of this study is to explore the effects of storing bile under various conditions on the stability of bile cfDNA and to determine the optimal conditions, thereby establishing a foundation for the subsequent application of bile cfDNA in liquid biopsy for early diagnostic and prognosis monitoring of patients with malignant BTC. We evaluated the storage temperature and storage time for the preservation of bile samples. Bile samples were collected in cfDNA tubes with protectant covered inside or regular tubes without, and the stability of bile cfDNA was analyzed during 10 days at room temperature (RT) or after 2 months of storage at low temperatures. Bile cfDNA remained stable for bile samples being collected with cfDNA tubes and stored for 10 days at RT, while degraded with time for the case with regular tubes. When bile samples were collected with cfDNA tubes and stored for 2 months at 4 ℃, bile cfDNA remained stable, however, if collected with regular tubes, bile cfDNA exhibited a slight loss of integrity. No significant difference was observed for 2 months storage at -20 or -80 ℃. Our findings suggested that for bile cfDNA research, bile samples should be collected with cfDNA tubes and it can be transported for short-term shipment at RT, and could be stored at 4 ℃ with cfDNA tubes, or frozen at -20 ℃ with regular tubes.

An intelligent fluorescence sensing platform based on entropy-driven toehold-mediated strand displacement cycle reaction for point-of-care testing of miRNA

BackgroundMicroRNA (miRNA) has gradually become an emerging biomarker for early diagnosis and prognosis of various diseases due to its specific gene expression and high stability. With the development of molecular diagnosis and point-of-care testing (POCT) technology, developing simple, fast, sensitive, efficient, and low-cost miRNA sensors is of great significance for clinical applications and emergency rapid diagnosis. At present, entropy-driven toehold mediated chain displacement reaction, as a promising enzyme free isothermal amplification technique, is an important tool for ultra-sensitive biosensing applications. ResultsIn this study, we used gold nanoparticles (AuNPs) as carriers and quenchers, modified them using self-assembled triple chain composite substrates AuNPs@A@B1/B2, and used dual reporter molecules for cascade cyclic amplification to amplify fluorescence signals, which proposed a fluorescent biosensor based on this reaction and build an intelligent fluorescence sensing platform for rapid detection of miRNA. We designed a highly specific self-programmable sensor using the acute ischemic stroke (AIS) biomarker miRNA-125a-5p as a sample, and achieved sensitive detection of miRNA in the range of 0.01 μM∼10 μ M under optimal conditions. It broke through the traditional detection limitations of weak signals and liberated the fluorescence detection environment. SignificanceIn summary, this creative miRNA biosensor combined with POCT has demonstrated extraordinary detection potential, broad application prospects in the early diagnosis and prognosis monitoring of AIS, provides a novel miRNA universal detection strategy for the fields of biological and life sciences.

Advancing Lung Cancer Diagnosis through NH2-MON-SPME-GC-MS/MS: Enhanced Sensitivity in Aldehyde Biomarker Detection from Exhaled Breath.

The sensitive detection of trace biomarkers in exhaled breath for lung cancer diagnosis represents a critical area of research in life analytical chemistry, with profound implications for early disease detection, therapeutic intervention, and prognosis monitoring. Despite its potential, the analytical process faces significant challenges due to the ultratrace levels of disease biomarkers present and the complex, high-humidity composition of exhaled breath. This study introduces a highly sensitive method for detecting aldehyde biomarkers in exhaled breath by integrating the use of amino-functionalized microporous organic networks (NH2-MON) as a solid-phase microextraction (SPME) fiber coating with gas chromatography-triple quadrupole mass spectrometry (GC-MS/MS) analysis. The method innovatively combines sample collection and extraction, achieving a dual-step enrichment process that significantly enhances both the enrichment efficiency and reproducibility of biomarker detection while effectively mitigating the interference caused by water vapor in exhaled breath. The NH2-MON, utilized as an SPME fiber coating, demonstrates exceptional enrichment capacity for five key aldehyde biomarkers, facilitating the development of a highly sensitive detection approach for these biomarkers in exhaled breath. Compared to previously reported methods, the proposed technique exhibits significantly lower limits of quantification, ranging from 0.77 to 11.89 pg mL-1, and achieves substantially higher enrichment factors, ranging from 9156- to 35723-fold. The practicality and feasibility of the method were validated through the analysis of exhaled breath samples from lung cancer patients, underscoring its potential application in the early diagnosis and monitoring of lung cancer.

Therapeutic Effect of Superficial Scalp Hypothermia on Chemotherapy-Induced Alopecia in Breast Cancer Survivors.

Alopecia is a common adverse effect of neoadjuvant or adjuvant chemotherapy in patients with early breast cancer. While hair typically regrows over time, more than 40% of patients continue to suffer from permanent partial alopecia, significantly affecting body image, psychological well-being, and quality of life. This concern is a recognized reason why some breast cancer patients decline life-saving chemotherapy. It is critical for healthcare professionals to consider the impact of this distressing side effect and adopt supportive measures to mitigate it. Among the various strategies investigated to reduce chemotherapy-induced alopecia (CIA), scalp cooling has emerged as the most effective. This article reviews the pathophysiology of CIA and examines the efficacy of different scalp cooling methods. Scalp cooling has been shown to reduce the incidence of CIA, defined as less than 50% hair loss, by 50% in patients receiving chemotherapy. It is associated with high patient satisfaction and does not significantly increase the risk of scalp metastasis or compromise overall survival. Promising new scalp cooling technologies, such as cryogenic nitrogen oxide cryotherapy, offer the potential to achieve and maintain lower scalp temperatures, potentially enhancing therapeutic effects. Further investigation into these approaches is warranted. Research on CIA is hindered by significant heterogeneity and the lack of standardised methods for assessing hair loss. To advance the field, further interdisciplinary research is crucial to develop preclinical models of CIA, establish a uniform, internationally accepted and standardised classification system, and establish an objective, personalised prognosis monitoring system.

Inhalable explosive nanosensor for real-time visual monitoring of therapeutic effects of lung cancer

Lung cancer, as one of the major diseases that endanger human health, has a very high fatality rate. Consequently, effective evaluation of clinical treatment outcomes for lung cancer is crucial for the formulation of subsequent treatment plans for patients. In this work, we utilized amorphous calcium carbonate nanoparticles (CaCO3 NPs) as sources of calcium ions (Ca2+) to develop CPs (CaCO3@PDA) core–shell nanoprobes. Concurrently, we functionalized the surface of gold nanoparticles with Cy5.5-peptide, AS1411, and (4-aminosulfonylphenyl) boronic acid (4-APBA) to produce APAAs (Au NPs@pep-AS1411-(4-APBA)), which were further assembled with CPs using PEG to construct an innovative explosive nanosensor, CPAs (CaCO3@PDA-APAAs). The CPs component of the nanosensor could cause the release of a substantial amount of Ca2+ in response to the tumor microenvironment (TME), which in turn induced cellular Ca2+ overload and subsequent apoptosis. This event triggers caspase-3 activation, causing the cleavage of a specific peptide sequence (DEVD), resulting in the fluorescence signal being reinstated. Additionally, the 4-APBA moiety on the probe interacted with H2O2 resulting in alterations in surface-enhanced Raman spectroscopy (SERS) signals, which aided in the detection of reactive oxygen species (ROS) during the physiological processes. By utilizing atomization, the nanoprobes were strategically deposited in the affected lung regions to enhance the fluorescence imaging capabilities and effectively mirror the therapeutic outcomes. Overall, the CPAs explosive nanosensor has a potential in advancing the non-invasive visual monitoring of lung cancer prognosis and can be a valuable tool in ongoing efforts to improve the management of this challenging disease.

Engineering of a DNA/γPNA Hybrid Nanoreporter for ctDNA Mutation Detection via γPNA Urinalysis.

Detection of circulating tumor DNA (ctDNA) mutations, which are molecular biomarkers present in bodily fluids of cancer patients, can be applied for tumor diagnosis and prognosis monitoring. However, current profiling of ctDNA mutations relies primarily on polymerase chain reaction (PCR) and DNA sequencing and these techniques require preanalytical processing of blood samples, which are time-consuming, expensive, and tedious procedures that increase the risk of sample contamination. To overcome these limitations, here the engineering of a DNA/γPNA (gamma peptide nucleic acid)hybrid nanoreporter is disclosed for ctDNA biosensing via in situ profiling and recording of tumor-specific DNA mutations. The low tolerance of γPNA to single mismatch in base pairing with DNA allows highly selective recognition and recording of ctDNA mutations in peripheral blood. Owing to their remarkable biostability, the detached γPNA strands triggered by mutant ctDNA will be enriched in kidneys and cleared into urine for urinalysis. It is demonstrated that the nanoreporter has high specificity for ctDNA mutation in peripheral blood, and urinalysis of cleared γPNA can provide valuable information for tumor progression and prognosis evaluation. This work demonstrates the potential of the nanoreporter for urinary monitoring of tumor and patient prognosis through in situ biosensing of ctDNA mutations.

Artificial Intelligence-Based Algorithms and Healthcare Applications of Respiratory Inductance Plethysmography: A Systematic Review

Respiratory Inductance Plethysmography (RIP) is a non-invasive method for the measurement of respiratory rates and lung volumes. Accurate detection of respiratory rates and volumes is crucial for the diagnosis and monitoring of prognosis of lung diseases, for which spirometry is classically used in clinical applications. RIP has been studied as an alternative to spirometry and shown promising results. Moreover, RIP data can be analyzed through machine learning (ML)-based approaches for some other purposes, i.e., detection of apneas, work of breathing (WoB) measurement, and recognition of human activity based on breathing patterns. The goal of this study is to provide an in-depth systematic review of the scope of usage of RIP and current RIP device developments, as well as to evaluate the performance, usability, and reliability of ML-based data analysis techniques within its designated scope while adhering to the PRISMA guidelines. This work also identifies research gaps in the field and highlights the potential scope for future work. The IEEE Explore, Springer, PLoS One, Science Direct, and Google Scholar databases were examined, and 40 publications were included in this work through a structured screening and quality assessment procedure. Studies with conclusive experimentation on RIP published between 2012 and 2023 were included, while unvalidated studies were excluded. The findings indicate that RIP is an effective method to a certain extent for testing and monitoring respiratory functions, though its accuracy is lacking in some settings. However, RIP possesses some advantages over spirometry due to its non-invasive nature and functionality for both stationary and ambulatory uses. RIP also demonstrates its capabilities in ML-based applications, such as detection of breathing asynchrony, classification of apnea, identification of sleep stage, and human activity recognition (HAR). It is our conclusion that, though RIP is not yet ready to replace spirometry and other established methods, it can provide crucial insights into subjects’ condition associated to respiratory illnesses. The implementation of artificial intelligence (AI) could play a potential role in improving the overall effectiveness of RIP, as suggested in some of the selected studies.

Identification of Circular RNAs as Biomarker Candidates in Lung Cancer Treatment.

Lung cancer is the most common malignancy and among the leading cause of cancer death worldwide. Therefore, there is an important need for biomarkers that can be used in the early diagnosis of the disease and in the follow-up of treatment. Circular RNAs (circRNAs) have a covalently closed circular structure that lacks 3' and 5' polar ends and is resistant to RNAase enzymes. Due to these properties, they can be stably found in body fluids. Therefore, they can serve as potential biomarkers in the diagnosis, monitoring of therapeutic response and prognosis of cancer. In our study, we aimed to investigate the expression levels of circRNA molecules in the treatment of lung cancer and to determine those that have the potential to be biomarkers. In this in vitro study, expression levels of 163 circRNAs were investigated in A549 cells, a non-small cell lung cancer cell line, before and after treatment with carboplatin and pemetrexed. Total RNA isolation and cDNA synthesis were performed after treatments. Expression levels of circRNA genes were determined by RT-qPCR method with the designed divergent primer sequences. The study revealed the characterisation of differentially expressed circRNAs by treatment in lung cancer cells. Of them, hsa_circ_0001320 is not expressed in cancer cells, is expressed only after treatment, and increased the level of its expression in response to combination therapy. As a result, while carboplatin, pemetrexed, and combined drug applications changed the expression levels of some circRNAs in lung cancer cells, some circRNAs were expressed only after treatment. In treatment follow-up and management, hsa_circ_0001320 has been identified as potential biomarker candidate.

Ultrasensitive Detection of Tumor Suppressor Gene Methylation by Piezoelectric Sensing Based on Enrichment of Transcription Activator-Like Effectors.

The detection of DNA methylation at cytosine/guanine dinucleotide (CpG) islands in promoter regions of tumor suppressor genes has great potential for early cancer screening, diagnosis, and prognosis monitoring. Nevertheless, achieving accurate, sensitive, cost-effective, and quantitative detection of target methylated DNA remains challenging. Herein, we propose a novel piezoelectric sensor (series piezoelectric quartz crystal (SPQC)) based on transcription activator-like effectors (TALEs) for detecting DNA methylation of Ras association domain family 1 isoform A (RASSF1A) tumor suppressor genes (R-5mC). The sensor employs TALEs-Ni magnetic beads to specifically recognize and separate the R-5mC, thereby improving the detection selectivity. The TALEs-Ni magnetic beads-R-5mC complex is sheared by a nucleic acid enzyme (DNAzyme) to release the single-stranded DNA (ST). ST initiates a catalyzed hairpin assembly (CHA) reaction on the surface of the electrode, which in turn triggers the hybridization chain reaction (HCR) and silver staining for enhanced detection sensitivity. The strategy exhibits a linear response in the detection of R-5mC in the range of 1 fM to 1 nM with a detection limit of 0.79 fM. R-5mC as low as 0.01% can be detected, even in the presence of large numbers of unmethylated DNA. The detection of R-5mC in circulating cell-free DNA (cfDNA) derived from clinical plasma specimens of lung cancer patients yielded satisfactory results.

Evaluation of the relationship between immunohistochemical markers and the prognosis of patients with hepatocellular carcinoma

Aims: This study aimed to evaluate whether prognosis and survival time in patients hepatocellular carcinoma (HCC) were associated with immunohistochemistry results for Heat Shock Protein 70 (HSP70), Glutamine synthetase (GS), Cyclase Associated Protein 2 (CAP2), Enhancer of zeste homolog 2 (EZH2) and B-cell-specific Moloney murine leukemia virus integration site 1 (Bmi-1). Methods: In this retrospective study, the medical records of 50 HCC cases were evaluated. Tissues were stained for the targeted antigens. Immunohistochemical stains were scored for cytoplasmic (HSP70, GS, CAP2) or nuclear (EZH2, Bmi-1) staining patterns under light microscopy. Results: Twenty-nine (58%) of the HCC cases died and the overall survival time was 30±3 (24-37) months. Survival times were similar in terms of age (p=0.262), sex (p=0.707), cause of disease (p=0.655), tumor size (p=0.191) and degree of differentiation (p=0.280). The overall survival of HCC patients with vascular invasion was shorter (p=0.019). The frequency of EZH2 (p=0.025) and Bmi-1 (p=0.004) +/++ was higher in patients with vascular invasion. No correlation was found between overall survival time and HSP70 positivity (p=0.140) and CAP2 positivity (p=0.278); however, survival time was significantly shorter in HCC cases stained (++/+++) with EZH2 (p=0.034), Bmi-1 (p=0.008) and GS (p=0.018). Conclusion: The results of this study showed that GS, EZH2, and Bmi-1 predicted prognosis and survival time in patients with HCC, possible due to relationships with vascular invasion. There is a need for more comprehensive, population-based studies on biomarkers that can be used in prognosis monitoring of HCC cases.

A homogeneous electrochemiluminescence immunoassay platform based on carbon quantum dots and magnetic beads enrichment for detection of thyroglobulin in serum

Considering the high probability of recurrence or metastasis after thyroidectomy, it is meaningful to develop a rapid, sensitive and specific method for monitoring thyrophyma-related biomarkers. In this study, a homogeneous electrochemiluminescence immunoassay (HO-ECLIA) coupled with magnetic beads (MBs)-based enrichment tactic was established for the determination of thyrophyma-related thyroglobulin (Tg). Importantly, owing to the abundant surface groups and good biocompatibility of carbon quantum dots (CQDs), the incorporation of CQDs onto the Tg antigen surface was achieved, resulting in the formation of Tg-encapsulated CQDs (CQDs-Tg), which served not only as an ECL probe but as a biorecognition element. Under optimal experimental conditions, the proposed platform demonstrated a wide linear range from 0.01 to 100 ng·mL−1 with a detection limit of 6.9 pg·mL−1 (S/N = 3), and performed well in real serum sample analysis against interference. Collectively, the proposed platform exhibited the rapid response, satisfactory sensitivity and specificity toward Tg in complex serum milieu, and held a considerable potential for clinical prognosis monitoring of thyrophyma.

The deregulation of arachidonic acid metabolism in ovarian cancer.

Arachidonic acid (AA) is a crucial polyunsaturated fatty acid in the human body, metabolized through the pathways of COX, LOX, and cytochrome P450 oxidase to generate various metabolites. Recent studies have indicated that AA and its metabolites play significant regulatory roles in the onset and progression of ovarian cancer. This article examines the recent research advancements on the correlation between AA metabolites and ovarian cancer, both domestically and internationally, suggesting their potential use as biological markers for early diagnosis, targeted therapy, and prognosis monitoring.

Human epididymis protein 4, a novel potential biomarker for diagnostic and prognosis monitoring of lung cancer.

This study aimed to explore the application value of human epididymis protein 4 (HE4) in diagnosing and monitoring the prognosis of lung cancer. First, TCGA (The Cancer Genome Atlas) databases were used to analyze whey-acidic-protein 4-disulfide bond core domain 2 (WFDC2) gene expression levels in lung cancer tissues. Then, a total of 160 individuals were enrolled, categorized into three groups: the lung cancer group (n = 80), the benign lesions group (n = 40), and the healthy controls group (n = 40). Serum HE4 levels and other biomarkers were quantified using an electro-chemiluminescent immunoassay. Additionally, the expression of HE4 in tissues was analyzed through immunohistochemistry (IHC). In vitro cultures of human airway epithelial (human bronchial epithelial [HBE]) cells and various lung cancer cell lines (SPC/PC9/A594/H520) were utilized to detect HE4 levels via western blot (WB). Analysis of the TCGA and UALCAN (The University of Alabama at Birmingham Cancer Data Analysis Portal) databases showed that WFDC2 gene expression levels were upregulated in lung cancer tissues (p < 0.01). Compared with the control group and the benign group, HE4 was significantly higher in the serum of patients with lung cancer (p < 0.001). Receiver operating characteristic (ROC) analysis confirmed that HE4 had better diagnostic efficacy than classical markers in the differential diagnosis of lung cancer and benign lesions and had the highest diagnostic value in lung adenocarcinoma (area under the ROC curve [AUC] = 0.826). HE4 increased in early lung cancer and positively correlated with poor prognosis (p < 0.001). Moreover, the results of WB and IHC revealed that the expression of HE4 was increased in lung cancer cells (SPC/A549/H520) and lung cancer tissues but decreased in PC9 cells with a lack of exon EGFR19 (p < 0.05). Serum HE4 emerges as a promising novel biomarker for the diagnosis and prognosis assessment of lung cancer.

Dual-Aptamer Recognition of DNA Logic Gate Sensor-Based Specific Exosomal Proteins for Ovarian Cancer Diagnosis.

Clinical diagnosis of ovarian cancer lacks high accuracy due to the weak selection of specific biomarkers along with the circumstance biomarkers localization. Clustering analysis of proteins transported on exosomes enables a more precise screening of effective biomarkers. Herein, through bioinformatics analysis of ovarian cancer and exosome proteomes, two coexpressed proteins, EpCAM and CD24, specifically enriched, were identified, together with the development of an as-derived dual-aptamer targeted exosome-based strategy for ovarian cancer screening. In brief, a DNA ternary polymer with aptamers targeting EpCAM and CD24 was designed to present a logic gate reaction upon recognizing ovarian cancer exosomes, triggering a rolling circle amplification chemiluminescent signal. A dynamic detection range of 6 orders of magnitude was achieved by quantifying exosomes. Moreover, for clinical samples, this strategy could accurately differentiate exosomes from healthy persons, other cancer patients, and ovarian cancer patients, enabling promising in situ detection. By accurately selecting biomarkers and constructing a dual-targeted exosomal protein detection strategy, the limitation of insufficient specificity of traditional protein markers was circumvented. This work contributed to the development of exosome-based prognosis monitoring in ovarian cancer through the identification of disease-specific exosome protein markers.

PE-Ynet: a novel attention-based multi-task model for pulmonary embolism detection using CT pulmonary angiography (CTPA) scan images.

Pulmonary Embolism (PE) has diverse manifestations with different etiologies such as venous thromboembolism, septic embolism, and paradoxical embolism. In this study, a novel attention-based multi-task model is proposed for PE segmentation and detection from Computed Tomography Pulmonary Angiography (CTPA) images. A Y-Net architecture is used to implement this model, which facilitates segmentation and classification jointly, improving performance and efficiency. It is leveraged with Multi Head Attention (MHA), which allows the model to focus on important regions of the image while suppressing irrelevant information, improving the accuracy of the segmentation and detection tasks. The proposed PE-YNet model is tested with two public datasets, achieving a maximum mean detection and segmentation accuracy of 99.89% and 99.83%, respectively, on the CAD-PE challenge dataset. Similarly, it also achieves a detection accuracy of 99.75% and a segmentation accuracy of 99.81% on the FUMPE dataset. Additionally, sensitivity analysis also shows a high sensitivity of 0.9885 for the localization error ɛ = 0 for the CAD-PE dataset, demonstrating the model's robustness against false predictions compared to state-of-the-art models. Further, this model also exhibits lower inference time, size, and memory usage compared to representative models. An automated PE-YNet tool can assist physicians with PE diagnosis, treatment, and prognosis monitoring in the clinical management of CoVID-19.

Alterations in serum metabolic profiles of early-stage hepatocellular carcinoma patients after radiofrequency ablation therapy

ObjectiveTo investigate the alterations in serum metabolic profiles and early-stage hepatocellular carcinoma (HCC) patient characteristics after radiofrequency ablation (RFA) therapy. This evaluation aimed to assess treatment effectiveness and identify potential novel approaches and targets for HCC treatment and prognosis monitoring. MethodsUntargeted metabolomics technology was employed to analyze serum metabolic profiles in healthy volunteer controls (NCs) and early stage HCC patients before and after RFA therapy. Additionally, Human Metabolome Database and Kyoto Encyclopedia of Genes and Genomes database were used to identify the differential metabolites (DMs) and metabolic pathways. Cystoscape was utilized to construct DM gene networks. Amino acid analyses were performed to validate our findings. ResultsWe identified 11, 14, and six DMs between the NC and HCC groups, HCC patients before and after RFA therapy, and post-RFA HCC and NC groups, respectively. The expression levels of these DMs, particularly those of amino acids and lipids, significantly changed. Compared with the NC group, higher levels of L-tyrosine, aspartate, and 18-oxo-oleate were observed in HCC patients, which were significantly reduced in patients after RFA therapy. Meanwhile, HCC patients after RFA therapy had increased levels of L-arginine, phosphatidic acid (20:3), and lysophosphatidyl choline (LPC) (20:4) compared to those before therapy, while their levels before therapy were lower than those of NC. Moreover, most metabolites in the post-RFA and NC groups showed no significant changes in expression, except for L-tyrosine and LPC (16:0). These metabolites could potentially serve as characteristic factors of early-stage HCC patients after RFA therapy. Joint pathway analysis revealed striking changes, mainly in phenylalanine, tyrosine, and tryptophan biosynthesis; alanine, aspartate, and glutamate metabolism; and arginine and aminoacyl-tRNA biosynthesis. Bioinformatics analysis of publicly available data preliminarily identified 187 DM-related metabolic enzymes. ConclusionOur study proposed novel targets for early-stage HCC treatment, laying the groundwork for improving treatment efficacy and prognosis of early-stage HCC patients.

Metabolomic biomarkers in liquid biopsy: accurate cancer diagnosis and prognosis monitoring.

Liquid biopsy, a novel detection method, has recently become an active research area in clinical cancer owing to its unique advantages. Studies on circulating free DNA, circulating tumor cells, and exosomes obtained by liquid biopsy have shown great advances and they have entered clinical practice as new cancer biomarkers. The metabolism of the body is dynamic as cancer originates and progresses. Metabolic abnormalities caused by cancer can be detected in the blood, sputum, urine, and other biological fluids via systemic or local circulation. A considerable number of recent studies have focused on the roles of metabolic molecules in cancer. The purpose of this review is to provide an overview of metabolic markers from various biological fluids in the latest clinical studies, which may contribute to cancer screening and diagnosis, differentiation of cancer typing, grading and staging, and prediction of therapeutic response and prognosis.