Early Cancer Diagnosis Research Articles

Early colorectal cancer diagnosis: A novel methylated stool DNA model enhanced the diagnostic efficiency.

Methylated stool DNA (sDNA) is a reliable noninvasive biomarker for early colorectal cancer (CRC) diagnosis. However, there are barely any diagnostic panels that can achieve both a sensitivity and specificity exceeding 90% simultaneously. We aimed to identify a novel methylated sDNA panel and model for the early diagnosis of CRC. We conducted methyl-CpG binding domain isolated genome sequencing (MiGS) on CpG island methylation phenotype (CIMP)-positive (n=3) and CIMP-negative CRC tissues (n=3) and their corresponding normal adjacent tissues. Subsequently, by utilizing both the aforementioned data and public datasets, we identified a set of promising methylated sDNA markers for CRC. Next, we validated 5 of these genes using pyrosequencing in CRC patients (n=31). Then, we developed a combined diagnostic model (CDM) for CRC based on the methylation status of PRDM12, FOXE1, and SDC2 by a Training cohort (n=231). Finally, the performance of CDM was evaluated in an independent multicenter Validation cohort (n=800). A total of 1062 participants were included in this study. The area under the curve (AUC) of the CDM was 0.979 (95% CI: 0.960-0.997), and the optimal sensitivity and specificity were 97.35% and 99.05%, respectively, in the training cohort (n=231). In the independent validation cohort (n=800), the AUC was 0.950 (95% CI: 0.927-0.973), along with the optimal sensitivity of 92.75% and specificity of 97.21%. When CRC and advanced adenoma (AAD) were used as diagnostic targets, the model AUC was 0.945 (95% CI: 0.922-0.969), with an optimal sensitivity of 91.89% and a specificity of 95.21%. The model sensitivity for nonadvanced adenoma patients was 68.66%. The sDNA diagnostic model CDM, developed from both CIMP-P and CIMP-N, exhibited exceptional performance in CRC and could serve as a potential alternative strategy for CRC screening.

Magnetic 3D macroporous MOF oriented urinary exosome metabolomics for early diagnosis of bladder cancer

Bladder cancer (BCa) exhibits the escalating incidence and mortality due to the untimely and inaccurate early diagnosis. Urinary exosome metabolites, carrying critical tumor cell information and directly related to bladder, emerge as promising non-invasive diagnostic biomarkers of BCa. Herein, the magnetic 3D ordered macroporous zeolitic imidazolate framework-8 (magMZIF-8) is synthesized and used for efficient urinary exosome isolation. Notably, beyond retaining the single crystals and micropores of conventional ZIF-8, MZIF-8 is further enhanced with highly oriented and ordered macropores (150 nm) and the large specific surface area (973 m2·g–1), which could enable the high purity and yield separation of exosomes via leveraging the combination of size exclusion, affinity, and electrostatic interactions between magMZIF-8 and the surfaces of exosome. Furthermore, the magnetic and hydrophilic properties of magMZIF-8 will further simplify the process and enhance the efficiency of separation. After conditional optimization, a 50 mL of urine is sufficient for exosome metabolomics analysis, and the time for isolating exosomes from 42 urine samples was 2 hours only. Incorporating machine learning algorithms with LC-MS/MS analysis of the metabolic patterns obtained from isolated exosomes, early-stage BCa patients were differentiated from healthy controls, with area under the curve (AUC) value of 0.844–0.9970 in the training set and 0.875-1.00 in the test set, signifying its potential as a reliable diagnostic tool. This study offers a promising approach for the non-invasive and efficient diagnosis of BCa on a large scale via exosome metabolomics.Graphical

Early Cancer Detection Through Comprehensive Mapping of Dynamic Tumorigenesis.

Current strategies for early cancer detection and diagnosis need updating to achieve greater precision, necessitating the creation of a comprehensive evolutionary map of tumorigenesis. This requires establishing high-quality prospective cohorts, systematically collecting samples for integrated spatiotemporal multiomics analyses, and efficiently translating laboratory findings into clinical applications.

Identification of Plasma Protein Biomarkers for Predicting Lung Cancer.

Lung cancer remains a leading cause of cancer-related mortality worldwide, necessitating the development of effective early diagnostic strategies. Despite advancements in imaging and screening technologies, late-stage diagnoses remain common, limiting treatment options and reducing survival rates. Thus, there is a critical need for reliable, minimally invasive biomarkers to improve early detection and patient outcomes. Plasma protein biomarkers offer promising potential for early lung cancer detection and continuous disease monitoring. This study explored the potential of specific plasma protein markers as early indicators of lung cancer. Plasma samples were collected from normal healthy individuals and lung cancer patients, and protein purification and analysis were conducted using LC-MS/MS. A mixed-effect model was applied to select lung cancer-related protein markers based on label-free relative quantification values. We identified 29 proteins with potential for early lung cancer diagnosis, including complement proteins (CFB, C3, C8G, C1QA, C1R, C6), orosomucoid proteins (ORM1, ORM2), ceruloplasmin (CP), alpha-1-B glycoprotein (A1BG), and others. These proteins play diverse roles in immune response, inflammation, and cell signaling, suggesting their relevance in lung cancer pathophysiology. Our findings suggest the potential of plasma proteins as early diagnostic biomarkers for lung cancer. Further validation in larger cohorts is needed to confirm their clinical utility. Integrating these biomarkers into existing diagnostic modalities could enhance early detection accuracy, leading to improved patient outcomes.

Early Diagnosis of Triple-Negative Breast Cancer Based on Dual microRNA Detection Using a Well-Defined DNA Crown-Carbon Dots Structure as an Electrochemiluminescence Sensing Platform.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer (BC). Thus, early detection and accurate diagnosis of this cancer are crucial for improving the survival rate of patients. Specific microRNAs (miRNAs) have been implicated in the occurrence, proliferation, and metastasis of TNBC. Addressing this need, our study developed a biosensor platform for early and accurate TNBC diagnosis by integrating electrochemiluminescence (ECL) technology with a DNA sensing strategy. Specifically, synthesized positively charged carbon dots (CDs) were used to neutralize the electrostatic repulsion between DNA strands and facilitate the assembly of DNA triangular prisms (DNA TP-CDs). Hairpins were then incorporated into the DNA TP-CDs to form the final DNA crown structure. The early TNBC biomarker, microRNA-93-3p (miR-93-3p), allowed for the binding between the DNA Crown and the DNA track on the electrode and initiated the ECL signal. Subsequently, microRNA-210 (miR-210) unlocked the DNA tripedal walker, and its movement on the DNA Crown eventually quenched the ECL signal, enabling accurate TNBC diagnosis and tumor stage assessment. Our proposed biosensor had satisfactory sensing efficiency due to the ordered DNA track and rapid-moving DNA walker. The data revealed a good linear relationship between the ECL signals and the logarithm of miRNA concentrations, with miR-93-3p having a detection limit of 31.04 aM and miR-210 having a detection limit of 7.69 aM. The biosensor also showed satisfactory performance in serum samples and cells. Taken together, this study hopes to provide ideas and applications for clinical diagnosis as well as the personalized treatment of TNBC.

The effectiveness of a mobile mammography units in breast cancer screening

Breast cancer remains the leading cause of death in the female population. Screening studies are conducted in order to detect the disease at an early stage. At the same time, domestic authors emphasize the lack of alternatives to preventive mammography in breast cancer screening and the prospects of using mobile mammographs for early diagnosis of breast cancer and precancerous breast diseases.Aim. To evaluat the results of the use of mobile mammography units for active and early detection of breast cancer.Materials and methods. The research uses methods of content analysis, information and analytical materials of Russian and foreign researchers, and forms of federal statistical observation. Statistical research methods were used to analyze the data obtained.Results. Regression analysis with a very low probability of error (p = 0.001) showed that the larger the total volume of mammographic studies with preventive purposes in the subjects of the Russian Federation, the higher the proportion of cases of active detection of breast cancer, although this relationship is rather weak. Taking into account the obtained value of R2 (0.192), only 19.2% of the increase in the proportion of breast cancer cases detected actively can be explained by an increase in the volume of preventive mammograms. The correlation analysis showed that the volumes of preventive mammograms performed using mobile devices in the subjects of the Russian Federation were not associated with either the proportion of breast cancer cases detected actively or with the proportion of breast cancer cases detected in the early stages. At the same time, it is worth noting that the obtained value of p ≥ 0.5 indicates a statistically insignificant result of evaluating the relationship between variables, the interpretation of which should be performed with caution.Conclusion. Despite the high cost of mobile mammography units, the increase in their number in the subjects of the Russian Federation and the growth in their activities, the contribution of these diagnostic devices to solving the problem of early and active diagnosis of breast cancer remains uncertain. More promising are personalized approaches to the timely detection of cancers, including breast cancer, based on an assessment of the individual risk of their occurrence.

Integration of bioinformatics and cellular experiments unveils the role of SYT12 in gastric cancer

ObjectiveThis study employs integrated bioinformatics analysis and in vitro cellular experiments to elucidate the role of Synaptotagmin-12 (SYT12) in the progression of gastric cancer.MethodsWe utilized databases and platforms such as Xiantao Academic Tools, UALCAN, Kaplan-Meier plotter analysis, and The Cancer Genome Atlas (TCGA) to extract datasets on SYT12 in gastric cancer. We analyzed the relationship between SYT12 expression and the clinicopathological features, prognosis, diagnosis, and immune infiltration of stomach adenocarcinoma (STAD) patients. Verification was conducted using samples from 31 gastric cancer patients. Additionally, in vitro cellular experiments were performed to determine the role and potential mechanisms of SYT12 in the malignant behavior of gastric cancer cells.ResultsComprehensive bioinformatics analysis indicated that SYT12 is highly expressed in most cancers and is associated with promoter DeoxyriboNucleic Acid (DNA) methylation levels. SYT12 expression correlated with clinicopathological features, immune cell infiltration, immune checkpoint gene expression, and poor prognosis in STAD patients. In vitro experiments suggest that SYT12 may promote the proliferation and migration of gastric cancer cells by inducing epithelial-mesenchymal transition (EMT).ConclusionsThis study highlights the significant role of SYT12 in gastric cancer, suggesting its potential as a new target for early diagnosis, treatment, immunological, and prognostic evaluation in gastric cancer, offering new insights for precision medicine in this disease.

Modulating the organization of medical care and early diagnosis of prostate cancer

Aim. To analyze the existing system of medical care organization and timely diagnostics for prostate cancer (PC).Materials and Methods. The study utilized data from official statistics to analyze the system of medical care organization and the diagnostic methods applied for prostate cancer at different stages.Results. In the country, medical care for patients with prostate cancer is organized into three levels. The first level involves family physicians, urologists, and oncologists in oncology clinics, where access to modern diagnostic facilities is limited. The second level provides advanced diagnostic services through regional oncology centers and major urology departments. The third level offers specialized care at the National Cancer Research Center (NCRC) and select urology clinics. Based on the experience of other countries, it is recommended to improve the system of medical care for prostate cancer by establishing four stages of care. The proposed model takes into account the real situation, emphasizing the need for prevention, timely diagnosis, and effective treatment in accordance with clinical protocols, as well as the coordinated use of human and technological resources from oncology, urology, and morphological services at all stages.Conclusions. The proposed model for organizing medical care, based on evidence-based practices, aims to improve early detection of prostate cancer, enhance the clinical effectiveness of treatment, and optimize the use of resources.

Co-designed study with the Traveller Community in Ireland to determine cancer awareness & attitudes

Abstract Background Irish Travellers are a distinct ethnic minority group (formal recognition March 2017). They experience higher mortality than the general population at all ages for all causes of death. Study Aim To determine cancer awareness and attitudes among the Traveller Community in Ireland, and to identify barriers/enablers to cancer risk reduction behaviours and early diagnosis of cancer. Methods A co-designed multi-method study was developed in collaboration with Pavee Point, a national NGO for Travellers, the National Social Inclusion Office (NSIO) and the National Cancer Control Programme (NCCP) including: 1. Consultation with Pavee Point and NSIO representatives to inform the study proposal and methodology. 2. Co-design of methodology for ethics applications and subsequent data collection plan including interview topic guides and the development of a culturally appropriate version of the NCCP’s 2022 National Survey on Cancer Awareness, adding questions on social determinants of health and screening participation. 3. Collaboration with 12 peer-led Primary Health Care for Travellers Projects (PHCTPs), to provide in-person training for Traveller Community Health Workers to undertake a cross-sectional survey of 380 adult Travellers. 4. Collaboration with PHCTPs to undertake 20 semi-structured interviews with Travellers. 5. Conduct of semi-structured interviews with healthcare professionals to explore perceptions of barriers/enablers for Travellers engaging with the health system. Lessons Learned Working closely and collaboratively with our study partners, we gained valuable insights which enabled effective and efficient data collection across 8 counties, while exceeding our survey target sample size. Implications for Research: Collaborative, trusting, and respectful relationships are critical for all studies, but particularly when working with minority groups. Conclusions The study findings will inform policy for improved cancer outcomes among Travellers in Ireland. Key messages • Formation of a collaborative and respectful relationship with the Traveller community has facilitated successful research. • Traveller Community Health Workers (peer researchers) were key to the success of data collection.

Evaluation of cfDNA fragmentation characteristics in plasma for the diagnosis of lung cancer: A prospective cohort study.

Lung cancer is one of the most prevalent cancers worldwide, yet only approximately 16% of patients are diagnosed in early stage, highlighting the urgent need for novel, highly accurate detection models. In our study, patients with suspected lung cancer or lung disease, as identified through radiographic imaging, along with healthy individuals, were consecutively recruited from Beijing Chest Hospital. Circulating free DNA (cfDNA) was extracted from plasma samples, and low-depth whole-genome sequencing was performed to identify fragmentomic features for model construction. A total of 265 participants were prospectively enrolled, comprising 124 lung cancer patients and 141 noncancer individuals. The model we developed was based on four cfDNA fragmentation characteristics, including 20-bp breakpoint nucleotides motif, fragmentation size coverage, fragmentation size distribution, and copy number variation. In an independent test cohort, the model achieved an area under the curve (AUC) of 0.861 (95% CI: 0.781-0.942) and demonstrated a sensitivity of 70% (95% CI: 53.5%-83.4%) at a specificity of 89.4% (95% CI: 76.9%-96.5%). Notably, the model was also effective in detecting early-stage cancer, with an AUC of 0.808 (95% CI: 0.69-0.925). In summary, our lung cancer detection model shows strong screening capabilities by leveraging four cfDNA fragmentation characteristics, exhibiting robust performance in early cancer diagnosis.

Inhibition of M2 tumor-associated macrophages polarization by modulating the Wnt/β-catenin pathway as a possible liver cancer therapy method

The problem of liver cancer is becoming increasingly important due to the epidemic of metabolic diseases and persistent high alcohol consumption. This determines great attention to the development and improvement of methods for early diagnosis and treatment of liver cancer. Huang et al presented a study in the World Journal of Gastroenterology , in which they showed that the use of the traditional Chinese medicine Calculus bovis (CB) can suppress tumor growth in mice by inhibiting M2 tumor-associated macrophages (TAM) through modulating the activity of the Wnt/β-catenin pathway. The interaction of CB components with the Wnt/β-catenin pathway, M2 TAM polarization, and tumor dynamics were studied using network pharmacology, transcriptomics, and molecular docking. It is now generally accepted that the polarization of TAM and the differentiation of the functions of M1 and M2 phagocytes are of great importance for the progression of neoplasms. It is assumed that M2 TAM promote proliferation and migration of tumor cells. Attempts to medicinally influence the Wnt/β-catenin pathway in order to modulate phagocyte polarization now belong to one of the most promising areas of immunotherapy of oncological diseases. Undoubtedly, the work of the Chinese authors deserves attention and further development.

Development of a Novel Risk Signature for Predicting the Prognosis and Immunotherapeutic Response of Prostate Cancer by Integrating Ferroptosis and Immune-Related Genes.

Ferroptosis and immune response correlation studies have not been reported in prostate cancer (PCa), and the main goal of this paper is to identify biomarkers that can be used for early diagnosis of prostate cancer. Data on PCa were retrieved from the TCGA and MSKCC2010 databases. Thereafter, the differentially expressed ferroptosis-related genes (DE-FRGs: ACSF2) and immune-related genes (DE-IRGs: ANGPT1, NPPC, and PTGDS) were identified using the "limma" package. Additionally, we used univariate and multivariate Cox regression analyses to obtain biochemical relapse (BCR)-free survival-related genes and construct a risk signature. Patients with high-risk scores were characterized by poor BCR-free survival, relatively low immune cell abundance, and comparably weak expression of immune checkpoint molecules. Moreover, gene set variation analysis (GSVA) was performed to explore the biological pathways related to the risk signature. Single sample gene set enrichment analysis (ssGESA) was applied to evaluate the status of immune cells in patients with PCa, which demonstrated that the risk score was intimately affiliated with immune response and cancer pathways. Ultimately, the connection between the risk score and response of PCa patients to immunotherapy was appraised using the TIDE algorithm. The TIDE algorithm implied that the high-risk score PCa population might benefit more from immunotherapy regimens. Finally, qRT-PCR were used to evaluate the expression of DE-FRGs and DE-IRGs in PCa cell and normal prostate epithelial cells. The result of qRT-PCR showed that the mRNA expression levels of ACSF2, ANGPT1, NPPC, and PTGDS in normal prostate epithelial cell were higher than that in PCa cells. Therefore, a risk score model was generated based on one DE-FRG and three DE-IRGs, which could predict the BCR-free survival and response of immunotherapy for patients with PCa.

The Effectiveness of Whole Body Magnetic Resonance Imaging Used in Health Screening Programs in Early Stage Cancer Diagnosis

Objective: We aim to present the findings and effectiveness of Whole Body Magnetic Resonance Imaging (WBMRI), which we use in the Health Screening Program (HSP) to diagnose cancer in early stage. Methods: This retrospective study was conducted between January 2017-February 2023. 393 individuals, between the ages of 18 and 85, who underwent WBMRI for HSP purposes, were included. The mean age was 50. Results: Malignancy suspicious lesions were observed in the head/neck region in 25 cases. Additional Magnetic Resonance (MRI) and Ultrasound (US) were performed. Mediastinal pathology was observed in 23 cases, and non-mediastinal thoracic pathologies were detected in 15. Therefore thorax Computed Tomography (CT), mammography, and breast US were performed. Benign lesions were observed in the liver in 44 cases, and US was performed. Malignancy-suspicious lesions in the liver were observed in 4, and dynamic abdominal MRI was performed. Cholelithiasis was observed in 16, and confirmed by US. The most common renal findings were; cysts and pelvicalyceal ectasia. Adrenal adenoma was observed in 5 cases. Two of the females had suspicion of gynecological malignancy. Massive diffuse concentric wall thickening was observed in the sigmoid colon, and colonoscopy was performed on one male. Musculoskeletal benign lesions were detected in 99 cases, and malignancy-suspicious lesions were detected in 35. Additional examinations such as US, CT, MRI, PET-CT, scintigraphy, and colonoscopy were performed on 172 cases. Malignancy was detected in 11 cases (2.8%). Conclusion: WBMRI is a radiation-free, non-invasive, short-term examination method. WBMRI is beneficial in diagnosing early-stage cancer.

Electrochemical Immunosensor for the Sensitive Determination of Human Papillomavirus (HPV) 16 L1 Capsid Protein: A Leap in Cervical Cancer Diagnosis

Human Papillomavirus (HPV) is the principal cause of cervical cancer, which is still a prime universal health concern, especially in underdeveloped nations where access to advanced screening techniques is often restricted. Herein, we propose an electrochemical immunosensor for the determination of HPV 16 L1 protein, a key biomarker associated with cervical carcinogenesis. The developed immunosensor, employing glassy carbon electrode (GCE) enhanced with gold nanoparticles, provides a highly sensitive, specific, and cost-effective approach for early screening of cervical cancer. An optimized stepwise fabrication process which includes electrode surface modification and antibody immobilization, was used to enhance sensor performance. Characterization studies confirmed the effective modification of electrodes and the selectivity of immunoreactions. With an impressive limit of detection (LOD) of 0.033 fg mL−1, the immunosensor showed a linear response to L1 protein concentrations ranging from 0.1 fg mL−1 to 1 ng mL−1. Additionally, the immunosensor exhibits excellent specificity, stability, reproducibility, and regeneration capabilities. The performance of the immunosensor was compared with the enzyme-linked immunosorbent assay (ELISA) by analyzing clinical samples (positive: n = 12; healthy: n = 5) showed satisfactory results. The findings indicated that the proposed sensing platform has the potential to be utilized for the early diagnosis of cervical cancer.

Identification of Potential Predictive Transcript Isoform-Biomarkers for the Early Diagnosis of Breast Cancer Using Bioinformatics Tools

Background: Several studies have demonstrated that the expression status of isoforms is more informative as a biomarker than overall gene expression. This study aimed to determine highly but significantly expressed transcript isoforms and evaluate their prognostic and diagnostic impact in breast invasive carcinoma (BRCA) stage I patients. Methods: The differentially expressed genes and their transcript isoforms in BRCA stage I were determined using the Cancer Differentially Expressed Isoform and gene (Cancer DEIso) platform based on The Cancer Genome Atlas (TCGA) data. The prognostic and diagnostic impact of significantly upregulated top 10 genes and their transcripts were revealed using the Cancer DEIso tool, the Kaplan-Meier (KM) method, and the Receiver Operating Characteristic Curve (ROC) approach, respectively. Isoform-level protein-protein interactions (PPI) were constructed using the Domain Interaction Graph Guided ExploreR (DIGGER) database. ConsensusPathDB was used to perform pathway enrichment analysis based on the constructed interactions. Results: This study revealed that NM_024037, NM_001143782, and NM_021619 transcript isoforms have significant diagnostic ability with AUC values 93.2%, 77.1% and 75.3%, respectively to distinguish stage I BRCA patients from normal. KM-plot analysis showed that these three isoforms have no prognostic significance in stage I patients, but their upregulation was correlated with decreased survival in BRCA patients regardless of stage. Isoform-based pathway enrichment analyses indicated that these three isoforms involved in chromatin organization, senescense, DNA damage and several signalling pathways which promotes cancer when there is misregulation. . Conclusion: NM_024037, NM_001143782, and NM_021619 transcript isoforms are potential biomarkers for detecting early-stage BRCA. Thus, it is essential to find out how these three isoforms contribute to the development of breast carcinogenesis and evolve a new approach for capturing breast tumors at an earlier stage of the clinical landscape.

Colon polyp detection based on multi-scale and multi-level feature fusion and lightweight convolutional neural network

Early diagnosis and treatment of colorectal polyps are crucial for preventing colorectal cancer. This paper proposes a lightweight convolutional neural network for the automatic detection and auxiliary diagnosis of colorectal polyps. Initially, a 53-layer convolutional backbone network is used, incorporating a spatial pyramid pooling module to achieve feature extraction with different receptive field sizes. Subsequently, a feature pyramid network is employed to perform cross-scale fusion of feature maps from the backbone network. A spatial attention module is utilized to enhance the perception of polyp image boundaries and details. Further, a positional pattern attention module is used to automatically mine and integrate key features across different levels of feature maps, achieving rapid, efficient, and accurate automatic detection of colorectal polyps. The proposed model is evaluated on a clinical dataset, achieving an accuracy of 0.9982, recall of 0.9988, F1 score of 0.9984, and mean average precision (mAP) of 0.9953 at an intersection over union (IOU) threshold of 0.5, with a frame rate of 74 frames per second and a parameter count of 9.08 M. Compared to existing mainstream methods, the proposed method is lightweight, has low operating configuration requirements, high detection speed, and high accuracy, making it a feasible technical method and important tool for the early detection and diagnosis of colorectal cancer.

CNN-Based Early Diagnosis of Breast Cancer with Variable Image Resolutions

CNN-Based Early Diagnosis of Breast Cancer with Variable Image Resolutions

Enhancing Efficacy in Breast Cancer Screening with Nesterov Momentum Optimization Techniques

In the contemporary landscape of healthcare, machine learning models are pivotal in facilitating precise predictions, particularly in the nuanced diagnosis of complex ailments such as breast cancer. Traditional diagnostic methodologies grapple with inherent challenges, including excessive complexity, elevated costs, and reliance on subjective interpretation, which frequently culminate in inaccuracies. The urgency of early detection cannot be overstated, as it markedly broadens treatment modalities and significantly enhances survival rates. This paper delineates an innovative optimization framework designed to augment diagnostic accuracy by amalgamating momentum-based optimization techniques within a neural network paradigm. Conventional machine learning approaches are often encumbered by issues of overfitting, data imbalance, and the inadequacy of capturing intricate patterns in high-dimensional datasets. To counter these limitations, we propose a sophisticated framework that integrates an adaptive threshold mechanism across an array of gradient-based optimizers, including SGD, RMSprop, adam, adagrad, adamax, adadelta, nadam and Nesterov momentum. This novel approach effectively mitigates oscillatory behavior, refines parameter updates, and accelerates convergence. A salient feature of our methodology is the incorporation of a momentum threshold for early stopping, which ceases training upon the stabilization of momentum below a pre-defined threshold, thereby pre-emptively preventing overfitting. Leveraging the Wisconsin Breast Cancer Dataset, our model achieved a remarkable 99.72% accuracy and 100% sensitivity, significantly curtailing misclassification rates compared to traditional methodologies. This framework stands as a robust solution for early breast cancer diagnosis, thereby enhancing clinical decision making and improving patient outcomes.

Preclinical Aspects of [89Zr]Zr-DFO-Rituximab: A High Potential Agent for Immuno-PET Imaging.

An early diagnosis of cancer can lead to choosing more effective treatment and increase the number of cancer survivors. In this study, the preparation and preclinical aspects of [89Zr]Zr-DFO-Rituximab, a high-potential agent for PET imaging of Non- Hodgkin Lymphoma (NHL), were evaluated. DFO was conjugated to rituximab monoclonal antibody (mAb), and DFO-rituximab was successfully labeled with zirconium-89 (89Zr) at optimized conditions. The stability of the complex was assessed in human blood serum and PBS buffer. Radioimmunoreactivity (RIA) of the radioimmunoconjugate (RIC) was evaluated on CD20-overexpressing Raji cell line and CHO cells. The biodistribution of the radiolabeled mAb was studied in normal and tumorbearing rodents. Finally, the absorbed dose in human organs was estimated. The radiolabeled compound was prepared with radiochemical purity (RCP) >99% (RTLC) and a specific activity of 180±1.8 GBq/g. The RCP of the final complex PBS buffer and human blood serum was higher than 95%, even after 48 h post incubation. The RIA assay demonstrated that more than 63% of the radiolabeled compound (40 ng/ml, 0.5 mL) was bound to 5×106 Raji cells. The biodistribution of the final product in tumor-bearing mice showed a high accumulation of the RIC in the tumor site in all intervals post-injection. Tumor/ non-target ratios were increased over time, and longer imaging time was suggested. The dosimetry data indicated that the liver received the most absorbed dose after the complex injection. [89Zr]Zr-DFO-Rituximab represents a significant advancement in the field of oncological imaging and offers a robust platform for both diagnostic and therapeutic applications in the management of B-cell malignancies.

Pump-free SERS microfluidic chip based on an identification-competition strategy for ultrasensitive and efficient simultaneous detection of liver cancer-related microRNAs

In this study, we present a pump-free SERS microfluidic chip capable of detecting liver cancer-related miR-21 and miR-155 concurrently with ultra-sensitivity and high efficiency. We employed a Fe3O4@cDNA-AuNPs@Raman reporter@H composite structure and a recognition competition strategy. When the target miRNAs (miR-21 and miR-155) are present in the test liquid, they specifically compete with the nucleic acid complementary strand(H) of Fe3O4@cDNA-AuNPs@Raman reporter@H, causing AuNPs to competitively detach from the surface of Fe3O4, resulting in a decrease in the SERS signal. Consequently, this pump-free SERS microfluidic chip enables the detection of the target miRNAs more rapidly and accurately in complex environments. This method offers an approach for the simultaneous and efficient detection of miRNAs and holds promising applications in the early diagnosis of liver cancer.