Early Screening Methods Research Articles

Enhanced pediatric thyroid ultrasound image segmentation using DC-Contrast U-Net

Early screening methods for the thyroid gland include palpation and imaging. Although palpation is relatively simple, its effectiveness in detecting early clinical signs of the thyroid gland may be limited, especially in children, due to the shorter thyroid growth time. Therefore, this constitutes a crucial foundational work. However, accurately determining the location and size of the thyroid gland in children is a challenging task. Accuracy depends on the experience of the ultrasound operator in current clinical practice, leading to subjective results. Even among experts, there is poor agreement on thyroid identification. In addition, the effective use of ultrasound machines also relies on the experience of the ultrasound operator in current clinical practice. In order to extract sufficient texture information from pediatric thyroid ultrasound images while reducing the computational complexity and number of parameters, this paper designs a novel U-Net-based network called DC-Contrast U-Net, which aims to achieve better segmentation performance with lower complexity in medical image segmentation. The results show that compared with other U-Net-related segmentation models, the proposed DC-Contrast U-Net model achieves higher segmentation accuracy while improving the inference speed, making it a promising candidate for deployment in medical edge devices in clinical applications in the future.

Pre-clinical study of IR808 dye for cervical cancer in vitro and in vivo imaging.

There is an urgent need for improved methods for early screening and rapid diagnosis of cervical cancer since current conventional screening methods are plagued by operator subjectivity and unnecessary biopsies. IR808 is a tumour-targeting near-infrared (NIR) fluorescent dye that permits NIR imaging without the requirement of chemical conjugation. Our study investigates an IR808-based strategy for real-time monitoring of the cervix in vivo and rapid assessment of cervical specimens in vitro. We investigated the uptake of IR808 in vitro using normal cervical epithelial cells and three cervical cancer cell lines. The biodistribution of IR808 was examined in vivo via intravenous injection into tumour-bearing mice. Additionally, in vitro tissues were stained with IR808 to simulate the identification of cervical tumors in the clinical setting. Biocompatibility of the dye in both cellular and animal models was also examined. IR808 exhibited significant tumour-to-background ratios in fluorescence molecular imaging of in vivo tumors in nude mice. The application of NIR fluorescent dye IR808 in specific imaging screening, safe and non-invasive real-time monitoring, and rapid identification of cervical tumors from tissue specimens is expected to improve current screening methods for cervical cancer.

A Zinc Oxide Nanorod-Based Electrochemical Aptasensor for the Detection of Tumor Markers in Saliva

Biosensors have emerged as a promising tool for the early detection of oral squamous cell carcinoma (OSCC) due to their rapid, sensitive, and specific detection of cancer biomarkers. Saliva is a non-invasive and easy-to-obtain biofluid that contains various biomarkers of OSCC, including the carcinoembryonic antigen (CEA). In this study, an electrochemical aptasensor for the detection of CEA in saliva has been developed towards the diagnosis and early screening of OSCC. This aptasensor utilized a CEA-sensitive aptamer as sensitive elements. A fluorine-doped Tin Oxide (FTO) chip with a surface modification of a zinc oxide nanorod was employed as a transducer. Electrochemical measurements were carried out to detect the responsive signals originating from the specific binding between aptamers and CEAs. The measurement results indicated that this aptasensor was responsive to different concentrations of CEA ranging from 1 ng/mL to 80 ng/mL in a linear relationship. The limit of detection (LOD) was 0.75 ng/mL. This aptasensor also showed very good specificity and regenerative capability. Stability testing over a 12-day period showed excellent performance of this aptasensor. All the results demonstrated that this aptasensor has great potential to be used for the detection of CEA in the saliva of OSCC patients. This aptasensor provides a promising method for the rapid detection of CEA with convenience, which has great potential to be used as a new method for clinical diagnoses and early screening of OSCC.

Screening Model for Bladder Cancer Early Detection With Serum miRNAs Based on Machine Learning: A Mixed-Cohort Study Based on 16,189 Participants.

Early detection of bladder cancer (BCa) can have a positive impact on patients' prognosis. However, there is currently no widely accepted method for early screening of BCa. We aimed to develop an efficient, clinically applicable, and noninvasive method for the early screening of BCa by detecting specific serum miRNA levels. A mixed-cohort (including BCa, 12 different other cancers, benign disease patients, and health population) study was conducted using a sample size of 16,189. Five machine learning algorithms were utilized to develop screening models for BCa using the training dataset. The performance of the model was evaluated using receiver operating characteristic curve and decision curve analysis on the testing dataset, and subsequently, the model with the best predictive power was selected. Furthermore, the selected model's screening performance was evaluated using both the validation set and external set. The BCaS3miR model, utilizing only three serum miRNAs (miR-6087, miR-1343-3p, and miR-5100) and based on the KNN algorithm, is the superior screening model chosen for BCa. BCaS3miR consistently performed well in both the testing, validation, and external sets, exceeding 90% sensitivity and specificity levels. The area under the curve was 0.990 (95% CI: 0.984-0.991), 0.964 (95% CI: 0.936-0.984), and 0.917 (95% CI: 0.836-0.953) in the testing, validation, and external set. The subgroup analysis revealed that the BCaS3miR model demonstrated outstanding screening accuracy in various clinical subgroups of BCa. In addition, we developed a BCa screening scoring model (BCaSS) based on the levels of miR-1343-3p/miR-6087 and miR-5100/miR-6087. The screening effect of BCaSS is investigated and the findings indicate that it has predictability and distinct advantages. Using a mixed cohort with the largest known sample size to date, we have developed effective screening models for BCa, namely BCaS3miR and BCaSS. The models demonstrated remarkable screening accuracy, indicating potential for the early detection of BCa.

Salivary cysteine levels as a potential biochemical indicator of oral cancer risk in tobacco consumers.

Aim: Oral cancer is the leading cause of mortality, with a survival rate of less than 5 years, and is predominantly influenced by tobacco mutagens. Invasive diagnostic methods hinder early detection of oral cancer biomarkers. The present study performed salivary biochemical analysis for early oral cancer screening in tobacco consumers.Materials & methods: Three study groups included healthy controls (n=25), tobacco users (n=25) and oral cancer patients (n=25). Salivary total protein, amylase, TNF-α and amino acid levels were evaluated using enzymatic tests, Enzyme linked Immunosorbent Assay (ELISA) and High-Performance Liquid Chromatography (HPLC).Results: Compared with healthy controls, salivary total protein and TNF-αlevels were significantly (p=0.04) higher in oral cancer patients. Salivary amylase levels were significantly lower in tobacco smokers (p=0.02) and higher in oral cancer patients (p=0.01). Interestingly, the amino acid cysteine concentration was significantly higher (p=0.02) in tobacco consumers (62.5±10) than in healthy controls (116.1±28).Conclusion: In high-risk populations, such as tobacco users, salivary biochemical analysis can serve as a promising noninvasive diagnostic method for early oral cancer screening. As a salivary biomarker, the amino acid cysteine exhibits potential as a means of detecting the progression of oral cancer in individuals who consume tobacco.

Dysphagia in schizophrenia: pathological mechanisms and treatment recommendations.

Schizophrenia is a chronic, severe, and disabling mental disorder that significantly impacts individuals' lives. Long-term treatment with antipsychotic drugs, coupled with the complications of the disease itself, increases the risk of dysphagia in patients. These disorders further heighten the likelihood of choking and asphyxia death among this population. This project aims to comprehensively review the pathological mechanisms behind dysphagia in schizophrenia, alongside proposing early screening and evaluation methods. It also suggests treatment recommendations to mitigate the risks and complications associated with dysphagia in these patients.

Deep Location Soft-Embedding-Based Network With Regional Scoring for Mammogram Classification.

Early detection and treatment of breast cancer can significantly reduce patient mortality, and mammogram is an effective method for early screening. Computer-aided diagnosis (CAD) of mammography based on deep learning can assist radiologists in making more objective and accurate judgments. However, existing methods often depend on datasets with manual segmentation annotations. In addition, due to the large image sizes and small lesion proportions, many methods that do not use region of interest (ROI) mostly rely on multi-scale and multi-feature fusion models. These shortcomings increase the labor, money, and computational overhead of applying the model. Therefore, a deep location soft-embedding-based network with regional scoring (DLSEN-RS) is proposed. DLSEN-RS is an end-to-end mammography image classification method containing only one feature extractor and relies on positional embedding (PE) and aggregation pooling (AP) modules to locate lesion areas without bounding boxes, transfer learning, or multi-stage training. In particular, the introduced PE and AP modules exhibit versatility across various CNN models and improve the model's tumor localization and diagnostic accuracy for mammography images. Experiments are conducted on published INbreast and CBIS-DDSM datasets, and compared to previous state-of-the-art mammographic image classification methods, DLSEN-RS performed satisfactorily.

Development of new NGLY1 assay systems - toward developing an early screening method for NGLY1 deficiency.

Cytosolic peptide: N-glycanase (PNGase/NGLY1 in mammals) is an amidase (EC:3.5.1.52) widely conserved in eukaryotes. It catalyzes the removal of N-glycans on glycoproteins, converting N-glycosylated Asn into Asp residues. This enzyme also plays a role in the quality control system for nascent glycoproteins. Since the identification of a patient with an autosomal recessive genetic disorder caused by NGLY1 gene dysfunction, known as NGLY1 deficiency or NGLY1 congenital disorder of deglycosylation (OMIM: 615273), in 2012, more than 100 cases have been reported worldwide. NGLY1 deficiency is characterized by a wide array of symptoms, such as global mental delay, intellectual disability, abnormal electroencephalography findings, seizure, movement disorder, hypolacrima or alacrima, and liver dysfunction. Unfortunately, no effective therapeutic treatments for this disease have been established. However, administration of adeno-associated virus 9 (AAV9) vector harboring human NGLY1 gene to an NGLY1-deficient rat model (Ngly1-/- rat) by intracerebroventricular injection was found to drastically improve motor function defects. This observation indicated that early therapeutic intervention could alleviate various symptoms originating from central nervous system dysfunction in this disease. Therefore, there is a keen interest in the development of facile diagnostic methods for NGLY1 deficiency. This review summarizes the history of assay development for PNGase/NGLY1 activity, as well as the recent progress in the development of novel plate-based assay systems for NGLY1, and also discusses future perspectives.

Establishment and Evaluation of a Noninvasive Metabolism-Related Fatty Liver Screening and Dynamic Monitoring Model: Cross-Sectional Study.

Metabolically associated fatty liver disease (MAFLD) insidiously affects people's health, and many models have been proposed for the evaluation of liver fibrosis. However, there is still a lack of noninvasive and sensitive models to screen MAFLD in high-risk populations. The purpose of this study was to explore a new method for early screening of the public and establish a home-based tool for regular self-assessment and monitoring of MAFLD. In this cross-sectional study, there were 1758 eligible participants in the training set and 200 eligible participants in the testing set. Routine blood, blood biochemistry, and FibroScan tests were performed, and body composition was analyzed using a body composition instrument. Additionally, we recorded multiple factors including disease-related risk factors, the Forns index score, the hepatic steatosis index (HSI), the triglyceride glucose index, total body water (TBW), body fat mass (BFM), visceral fat area, waist-height ratio (WHtR), and basal metabolic rate. Binary logistic regression analysis was performed to explore the potential anthropometric indicators that have a predictive ability to screen for MAFLD. A new model, named the MAFLD Screening Index (MFSI), was established using binary logistic regression analysis, and BFM, WHtR, and TBW were included. A simple rating table, named the MAFLD Rating Table (MRT), was also established using these indicators. The performance of the HSI (area under the curve [AUC]=0.873, specificity=76.8%, sensitivity=81.4%), WHtR (AUC=0.866, specificity=79.8%, sensitivity=80.8%), and BFM (AUC=0.842, specificity=76.9%, sensitivity=76.2%) in discriminating between the MAFLD group and non-fatty liver group was evaluated (P<.001). The AUC of the combined model including WHtR, HSI, and BFM values was 0.900 (specificity=81.8%, sensitivity=85.6%; P<.001). The MFSI was established based on better performance at screening MAFLD patients in the training set (AUC=0.896, specificity=83.8%, sensitivity=82.1%) and was confirmed in the testing set (AUC=0.917, specificity=89.8%, sensitivity=84.4%; P<.001). The novel MFSI model was built using WHtR, BFM, and TBW to screen for early MAFLD. These body parameters can be easily obtained using a body fat scale at home, and the mobile device software can record specific values and perform calculations. MFSI had better performance than other models for early MAFLD screening. The new model showed strong power and stability and shows promise in the area of MAFLD detection and self-assessment. The MRT was a practical tool to assess disease alterations in real time.

Importance of diet and intestinal microbiota in the prevention of colorectal cancer - colonoscopy early screening diagnosis.

Colorectal cancer is a term used to describe colon and rectal cancer, which is the third most common type of cancer. A MEDLINE and PubMed search resulted in the inclusion of manuscripts written in the last 10 years, using keywords relevant to the topic of the manuscript. By analyzing the aim of the searched studies and manuscripts, adequate articles were included that described the stated problem. The frequency of colorectal cancer varies with climate, nutrition, and many other factors, primarily endogenous, hereditary, intestinal microbiome, as well as external factors, such as exposure of the individual to stress, and bad eating habits. Colon cancer and rectal cancer or colorectal cancer in general in the early stages of the disease, may not show symptoms or are barely noticeable. Colorectal cancer symptoms will most often not develop until the disease has progressed to stage 2 or beyond. Regular screening tests for colon or rectal cancer, especially colonoscopy, are recommended as part of a regular checkup for people aged 50 years or younger who are at high risk due to a family history of the disease or other cancers. Diet and colonoscopy as an early screening method play an important role in the prevention of colorectal cancer.

Deep learning-assisted multispectral imaging for early screening of skin diseases

IntroductionMelanocytic nevi (MN), warts, seborrheic keratoses (SK), and psoriasis are four common types of skin surface lesions that typically require dermatoscopic examination for definitive diagnosis in clinical dermatology settings. This process is labor-intensive and resource-consuming. Traditional methods for diagnosing skin lesions rely heavily on the subjective judgment of dermatologists, leading to issues in diagnostic accuracy and prolonged detection times. ObjectivesThis study aims to introduce a multispectral imaging (MSI)-based method for the early screening and detection of skin surface lesions. By capturing image data at multiple wavelengths, MSI can detect subtle spectral variations in tissues, significantly enhancing the differentiation of various skin conditions. MethodsThe proposed method utilizes a pixel-level mosaic imaging spectrometer to capture multispectral images of lesions, followed by reflectance calibration and standardization. Regions of interest were manually extracted, and the spectral data were subsequently exported for analysis. An improved one-dimensional convolutional neural network is then employed to train and classify the data. ResultsThe new method achieves an accuracy of 96.82 % on the test set, demonstrating its efficacy. ConclusionThis multispectral imaging approach provides a non-contact and non-invasive method for early screening, effectively addressing the subjective identification of lesions by dermatologists and the prolonged detection times associated with conventional methods. It offers enhanced diagnostic accuracy for a variety of skin lesions, suggesting new avenues for dermatological diagnostics.

China clinical practice guideline for stage Ⅳ primary lung cancer (2024 edition)

Primary lung cancer (abbreviated as lung cancer) stands as the most prevalent malignant disease and the leading cause of cancer-related death in China, with an estimated 106.06×104 incident cases and 73.33×104 deaths in 2022. Due to the absence of effective early screening methods, most patients with lung cancer in China are in stage Ⅳ when diagnosed. Multi-disciplinary treatment based on systemic therapy is the treatment principle for patients with stage Ⅳ lung cancer. Chemotherapy remains the cornerstone, but its effectiveness is still unsatisfactory. In recent years, with the rapid development of molecular targeted therapy and immunotherapy, the treatment concept for stage Ⅳ lung cancer has been continually evolving, leading to significant improvements in patient treatment outcomes. To ensure timely updates on the global progress in the treatment of stage Ⅳ lung cancer and further improve the level of standardized diagnosis and treatment of stage Ⅳ lung cancer in China, Medical Oncology Branch of China International Exchange and Promotive Association for Medical and Health Care and Chinese Association for Clinical Oncologists organized experts to compile "China clinical practice guideline for stage Ⅳ primary lung cancer (2024 edition)". This guideline systematically and comprehensively updates epidemiological data, TNM staging, new drugs, treatment regimens, and new indications approved by China National Medical Products Administration before June 30, 2024, etc. Based on the " Clinical practice guideline for stage Ⅳ primary lung cancer in China(2021 version)" and the " Clinical practice guideline for stage Ⅳ lung cancer in China (2023 edition)." This guideline incorporates recommendation levels for therapeutic drugs and treatment flowcharts for stage Ⅳ lung cancer. The guideline covers common clinical issues and corresponding guidance in the diagnosis and treatment process of stage Ⅳ lung cancer. The guideline aims to guide the clinical practice of stage Ⅳ lung cancer, comprehensively improve the standardized diagnosis and treatment level in China, prolong the survival time of patients with stage Ⅳ lung cancer, and improve patients' quality of life.

Blood-Derived Extracellular Vesicles as a Promising Liquid Biopsy Diagnostic Tool for Early Cancer Detection.

Cancer poses a significant public health challenge worldwide, and timely screening has the potential to mitigate cancer progression and reduce mortality rates. Currently, early identification of most tumors relies on imaging techniques and tissue biopsies. However, the use of low-cost, highly sensitive, non-invasive detection methods for early cancer screening has become more attractive. Extracellular Vesicles (EVs) released by all living cells contain distinctive biological components, such as nucleic acids, proteins, and lipids. These vesicles play crucial roles in the tumor microenvironment and intercellular communication during tumor progression, rendering liquid biopsy a particularly suitable method for diagnosis. Nevertheless, challenges related to purification methods and validation of efficacy currently hinder its widespread clinical implementation. These limitations underscore the importance of refining isolation techniques and conducting comprehensive investigations on EVs. This study seeks to evaluate the potential of liquid biopsy utilizing blood-derived EVs as a practical, cost-effective, and secure approach for early cancer detection.

Case Study on Analysing the Early Disease Detection of Pancreatic Ductal Adenocarcinoma in Korean Association for Clinical Oncology.

Pancreatic ductal adenocarcinoma (PDAC) is the most pervasive sort of pancreatic malignant growth. Due to the lack of early symptoms and effective methods for early detection and screening, the majority of patients (80% to 85%) are diagnosed with advanced metastatic or locally advanced disease, resulting in a low 5-year survival rate of 12%. The case study represents a comprehensive investigation into the intricate landscape of pancreatic cancer diagnosis within the Korean population. Grounded in epidemiological bits of knowledge, the review plans to disentangle the particular examples, commonness, and segment attributes of PDAC in Korea. By scrutinizing current diagnostic modalities, including conventional imaging techniques, molecular markers, and emerging technologies, the research seeks to evaluate the strengths and limitations of existing approaches within the Korean clinical context. Central to the study is an exploration of the collaborative initiatives spearheaded by the Association of Clinical Oncology in Korea in the domain of PDAC early detection. Analysing research projects, clinical trials, and interdisciplinary collaborations, the case study sheds light on the association's pivotal role in driving innovation and progress in oncology. The goal is to offer a detailed analysis of how the association helps in furthering knowledge and enhancing results in the management of PDAC. The case study delves into the implications of early PDAC detection for patient outcomes, emphasizing the significance of timely interventions and tailored treatment strategies. By outlining the potential benefits and challenges associated with early diagnosis, the study aims to inform health care policies, shape clinical guidelines, and guide future research priorities. Through a holistic approach, the case study endeavours to offer important experiences into the multifaceted landscape of PDAC early detection within the Korean health care system, contributing to the broader discourse on effective oncological practices and patient care.

Potential diagnostic, prognostic, and predictive biomarkers of gastric cancer.

Gastric cancer (GC), a malignant epithelial tumor, is the fourth leading cause of cancer-related death worldwide. Therapeutic strategies for GC, despite the biggest challenges, can significantly improve survival rates through early detection and effective screening methods. To provide brief information on the necessity of multiple specific diagnostic, prognostic, and predictive markers for GC. This review was conducted using a variety of search engines, including PubMed Central, Scopus, Web of Science, Google Scholar, and others. Some potential biomarkers that provide essential information include circulating tumor cells (CTCs), DNA methylation, claudin 18.2, fibroblast growth factor receptor 2 (FGFR2), long noncoding RNAs (lncRNAs), cell-free DNA (cfDNA), microRNAs, and serum pepsinogens. Multiple tumor markers are essential for screening, tumor identification, staging, prognostic assessment, and monitoring recurrence after therapy due to the absence of a single tumor indicator for diagnosing, prognosticating, and predicting GC.

Rapid identification of living cancer cells based on label-free surface-enhanced Raman spectroscopy

Surface-enhanced Raman spectroscopy (SERS) is a highly sensitive vibration spectroscopy technique that can obtain fingerprint information of biomolecules in cells, and it has demonstrated significant potential in the early diagnosis of cancer. Here, we propose a rapid and efficient identification method of living cancer cells (within 10 min), which is based on the label-free SERS detection using iodide-modified Ag nanoparticles (Ag IMNPs) and the ultra-fast Raman mapping by line illumination. The Ag IMNPs achieve a better balance between sensitivity, reproducibility, and biocompatibility when compared to conventional Au or Ag nanoparticles. Statistical analysis of Raman peak frequency and intensity across substantial SERS spectra reveals a wealth of intracellular chemical information about the three cell lines 7701/7703/Caski. This method can not only accurately identify and classify normal cells, cancer cells, and various types of cancer cells, but it can also detect fingerprint changes in the distribution of intracellular chemicals. Furthermore, we discover that, among the three cell lines, liver cancer cells 7703 had the highest level of reactive oxygen species (ROS). This rapid SERS method can provide a new optical detection method for early screening, progression monitoring and prognosis assessment of tumors.

Predicting the potential deterioration of Barrett's esophagus based on gut microbiota: a Mendelian randomization analysis.

Esophageal adenocarcinoma (EAC) is one of the most malignant tumors in the digestive system. To make thing worse, the scarcity of treatment options is disheartening. However, if detected early, there is a possibility of reversing the condition. Unfortunately, there is still a lack of relevant early screening methods. Considering that Barrett's esophagus (BE), a precursor lesion of EAC, has been confirmed as the only known precursor of EAC. Analyzing which BE cases will progress to EAC and understanding the processes and mechanisms involved is of great significance for early screening of such patients. Considering the significant alterations in the gut microbiota of patients with BE and its potential role in the progression to EAC, this study aims to analyze the relationship between BE, EAC, and GM to identify potential diagnostic biomarkers and therapeutic targets. This study utilized comprehensive statistical data on gut microbiota from a large-scale genome-wide association meta-analysis conducted by the MiBioGen consortium (n = 18,340). Subsequently, we selected a set of single nucleotide polymorphisms (SNPs) that fell below the genome-wide significance threshold (1 × 10-5) as instrumental variables. To investigate the causal relationship between gut microbiota and BE and EAC, we employed various MR analysis methods, including Inverse Variance Weighting (IVW), MR-Egger regression, weighted median (WM), and weighted mean. Additionally, we assessed the level of pleiotropy, heterogeneity, and stability of genetic variations through MR-Egger intercept test, MR-PRESSO, Cochran's Q test, and "leave-one-out" sensitivity analysis. Furthermore, we conducted reverse MR analysis to identify the causal relationships between gut microbiota and BE and EAC. The results from the Inverse Variance-Weighted (IVW) analysis indicate that Alistipes (P = 4.86 × 10-2), Lactobacillus (P = 2.11 × 10-2), Prevotella 7 (P = 4.28 × 10-2), and RuminococcaceaeUCG004 (P = 4.34 × 10-2) are risk factors for Barrett's esophagus (BE), while Flavonifractor (P = 8.81 × 10-3) and RuminococcaceaeUCG004 (P = 4.99 × 10-2) are risk factors for esophageal adenocarcinoma (EAC). On the other hand, certain gut microbiota genera appear to have a protective effect against both BE and EAC. These include Eubacterium (nodatum group) (P = 4.51 × 10-2), Holdemania (P = 1.22 × 10-2), and Lactococcus (P = 3.39 × 10-2) in the BE cohort, as well as Eubacterium (hallii group) (P = 4.07 × 10-2) and Actinomyces (P = 3.62 × 10-3) in the EAC cohort. According to the results of reverse MR analysis, no significant causal effects of BE and EAC on gut microbiota were observed. Furthermore, no significant heterogeneity or pleiotropy was detected in the instrumental variables. We have established a causal relationship between the gut microbiota and BE and EAC. This study holds profound significance for screening BE patients who may be at risk of deterioration, as it can provide them with timely medical interventions to reverse the condition.

A Comprehensive Methodology for Microbial Strain Typing Using Fourier-Transform Infrared Spectroscopy.

Timely and accurate detection and characterization of microbial threats is crucial for effective infection and outbreak management. Additionally, in food production, rapid microbe identification is indispensable for maintaining quality control and hygiene standards. Current methods for typing microbial strains often rely on labor-intensive, time-consuming, and expensive DNA- and sera-serotyping techniques, limiting their applicability in rapid-response scenarios. In this context, the IR Biotyper®, utilizing Fourier-transform infrared (FTIR) spectroscopy, offers a novel approach, providing specific spectra for fast strain typing within 3 h. This methodology article serves as a comprehensive resource for researchers and technicians aiming to utilize FTIR spectroscopy for microbial strain typing. It encompasses detailed guidelines on sample preparation, data acquisition, and analysis techniques, ensuring the generation of reliable and reproducible results. We highlight the IR Biotyper®'s rapid and accurate discrimination capabilities, showcasing its potential for real-time pathogen monitoring and source-tracking to enhance public health and food safety. We propose its integration as an early screening method, followed by more detailed analysis with whole-genome sequencing, to optimize detection accuracy and response efficiency in microbial surveillance systems.

Metal organic framework derived tubular-like indium trioxide to construct photoelectrochemical sensor for detecting carcinoembryonic antigen

Photoelectrochemical (PEC) sensor realizes high sensitivity detection of biomolecules and chemical substances through the combination of photoelectric conversion and chemical reaction, which has important significance in biomedicine and environmental monitoring. In this work, we designed a flexible PEC sensor based on In2O3-CdS hierarchical heterojunction for detecting carcinoembryonic antigen (CEA) in human serum. In2O3-CdS hierarchical heterojunction exhibited outstanding photoelectrochemical performance, which lays the foundation for a highly sensitive detection process. The electron transfer process was impeded as a result of the antigen being recognized and captured by the specific antibody on the electrode surface, leading to the decline of the photocurrent signal. Based on this principle, the PEC sensor exhibited a good linear relationship range from 0.002 ng mL−1 to 20 ng mL−1 under the most suitable conditions. In addition, this PEC sensor showed better stability and reproducibility in real samples compared to the commercially available ELISA kit. This work provided a reliable method for early cancer screening and diagnosis, which exhibited great significance and broad prospect for improving cancer treatment effect and survival rate.

Serum IL-24 combined with CA125 as screening and prognostic biomarkers for NSCLC.

Noninvasive and effective methods for early screening of non-small cell lung cancer(NSCLC) still need to be developed. At present, a reasonable conclusion is that a combination of tumor markers is a superior predictor of screening. Cytokines, as important regulators of cancer development, have great potential for the screening and prognosis of NSCLC. This study screened novel biomarkers related to the early screening and prognosis of NSCLC. In the present study, the biological significance and immunoregulation of interleukin-24(IL-24) were analyzed based on The Cancer Genome Atlas data. Next, 150 serum samples from initially treated patients with NSCLC and 70 controls were collected, and we obtained pathological sections from 60 patients with NSCLC. The ELISA and immunohistochemistryresults showed the differential expression of IL-24 and carbohydrate antigen 125(CA125). The results show that IL-24 is an important tumor suppressor in NSCLCthat helps to improve the poor prognosis of these patients. A significantly negative correlation between IL-24 and CA125 levels was also found. Notably, serum IL-24 levels were significantly negatively correlated with the TNM stage of patients with NSCLC, consistent with an important role for tumor suppressors in NSCLC. The receiver operating characteristic curve analysis showed that a combination of IL-24 and CA125 was an effective panel for discriminating patients with NSCLC from HD, and individuals with other lung diseases. Serum IL-24 and CA125 levels were identified as independent prognostic markers for NSCLC. The IL-24 and CA125 panel exhibited good performance in the screening of NSCLC.