Non-invasive screening and subtyping for breast cancer by serum SERS combined with LGB-DNN algorithms.

Early detection of breast cancer and its molecular subtyping is crucial for guiding clinical treatment and improving survival rate. Current diagnostic methods for breast cancer are invasive, time consuming and complicated. In this work, an optical detection method integrating surface-enhanced Raman spectroscopy (SERS) technology with feature selection and deep learning algorithm was developed for identifying serum components and building diagnostic model, with the aim of efficient and accurate noninvasive screening of breast cancer. First, the high quality of serum SERS spectra from breast cancer (BC), breast benign disease (BBD) patients and healthy controls (HC) were obtained. Chi-square tests were conducted to exclude confounding factors, enhancing the reliability of the study. Then, LightGBM (LGB) algorithm was used as the base model to retain useful features to significantly improve classification performance. The DNN algorithm was trained through backpropagation, adjusting the weights and biases between neurons to improve the network's predictive ability. In comparison to traditional machine learning algorithms, this method provided more accurate information for breast cancer classification, with classification accuracies of 91.38 % for BC and BBD, and 96.40 % for BC, BBD, and HC. Furthermore, the accuracies of 90.11 % for HR+/HR- and 88.89 % for HER2+/HER2- can be reached when evaluating BC patients' molecular subtypes. These results demonstrate that serum SERS combined with powerful LGB-DNN algorithm would provide a supplementary method for clinical breast cancer screening.

Early diagnosis of thyroid-associated ophthalmopathy using label-free Raman spectroscopy and multivariate analysis.

Thyroid-associated ophthalmopathy (TAO) is the most common orbital disease in adults, with complex clinical manifestations and significant impacts on the life quality of patients. The current diagnosis of TAO lacks reliable biomarkers for early and non-invasive screening and detection, easily leading to poor prognosis. Therefore, it is essential to explore new methods for accurately predicting TAO development in its early stage. In this study, Raman spectroscopy, with non-destructive, label-free, and high-sensitivity characteristics, was used to analyze the differences in biochemical components of orbital adipocyte and tear samples between TAO and control groups. Furthermore, a multivariate analysis method (i.e., Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA)) was applied for data processing and analysis. Compared with controls, PCA-LDA yielded TAO diagnostic accuracies of 72.7% and 75.0% using orbital adipocytes and tears, respectively. Our proof-of-concept results suggest that Raman spectroscopy holds potential for exploring the underlying pathogenesis of TAO, and its potential application in early screening of other thyroid-associated diseases can be further expanded.

An outlier removal method based on PCA-DBSCAN for blood-SERS data analysis.

Surface-enhanced Raman spectroscopy (SERS) has shown promising potential in cancer screening. In practical applications, Raman spectra are often affected by deviations from the spectrometer, changes in measurement environments, and anomalies in spectrum characteristic peak intensities due to improper sample storage. Previous research has overlooked the presence of outliers in categorical data, leading to significant impacts on model learning outcomes. In this study, we propose a novel method, called Principal Component Analysis and Density Based Spatial Clustering of Applications with Noise (PCA-DBSCAN) to effectively remove outliers. This method employs dimensionality reduction and spectral data clustering to identify and remove outliers. The PCA-DBSCAN method introduces adjustable parameters (Eps and MinPts) to control the clustering effect. The effectiveness of the proposed PCA-DBSCAN method is verified through modeling on outlier-removed datasets. Further refinement of the machine learning model and PCA-DBSCAN parameters resulted in the best cancer screening model, achieving 97.41% macro-average recall and 97.74% macro-average F1-score. This paper introduces a new outlier removal method that significantly improves the performance of the SERS cancer screening model. Moreover, the proposed method serves as inspiration for outlier detection in other fields, such as biomedical research, environmental monitoring, manufacturing, quality control, and hazard prediction.

Smartphone-based low-cost and rapid quantitative detection of urinary creatinine with the Tyndall effect.

This research aims to develop a robust and quantitative method for measuring creatinine levels by harnessing the enhanced Tyndall effect (TE) phenomenon. The envisioned sensing assay is designed for practical deployment in resource-limited settings or homes, where access to advanced laboratory facilities is limited. Its primary objective is to enable regular and convenient monitoring of renal healthcare, particularly in cases involving elevated creatinine levels. The creatinine sensing strategy is achieved based on the aggregation of gold nanoparticles (AuNPs) triggered via the direct crosslinking reaction between creatinine and AuNPs, where an inexpensive laser pointer was used as a handheld light source and a smartphone as a portable device to record the TE phenomenon enhanced by the creatinine-induced aggregation of AuNPs. After evaluation and optimization of parameters such as AuNP concentrations and TE measurement time, the subsequent proof-of-concept experiments demonstrated that the average gray value change of TE images was linearly related to the logarithm of creatinine concentrations in the range of 1-50 µM, with a limit of detection of 0.084 µM. Meanwhile, our proposed creatinine sensing platform exhibited highly selective detection in complex matrix environments. Our approach offers a straightforward, cost-effective, and portable means of creatinine detection, presenting an encouraging signal readout mechanism suitable for point-of-care (POC) applications. The utilization of this assay as a POC solution exhibits potential for expediting timely interventions and enhancing healthcare outcomes among individuals with renal health issues.

Optical biosensor based on SERS with signal calibration function for quantitative detection of carcinoembryonic antigen.

Monitoring the levels of cancer biomarkers is essential for cancer diagnosis and evaluation. In this study, a novel sandwich type sensing platform based on surface-enhanced Raman scattering (SERS) technology was developed for the detection of carcinoembryonic antigen (CEA), with a limit of detection (LOD) of 0.258 ng/mL. In order to achieve sensitive detection of CEA in complex samples, gold nanoparticle monolayer modified with CEA antibodies and with aptamer-functionalized probes was fabricated to target CEA. Two gold layers were integrated into the SERS platform, which greatly enhanced the signal of the probe by generating tremendous "hot spots". Meanwhile, the intensity ratio of Raman probes and the second-order peak of the silicon wafer was used to achieve dynamic calibration of the Raman probe signal. Excitingly, this sensing platform was capable of distinguishing cancer patients from healthy individuals via CEA concentrations in blood samples with the accuracy of 100%. This sandwich structure SERS sensing platform presented promising potential to be an alternative tool for clinical biomarker detection in the field of cancer diagnosis.

Serum analysis method combining cellulose acetate membrane purification with surface-enhanced Raman spectroscopy for non-invasive HBV screening.

A highly sensitive, non-invasive, and rapid HBV (Hepatitis B virus) screening method combining membrane protein purification with silver nanoparticle-based surface-enhanced Raman scattering (SERS) spectroscopy was developed in this study. Reproducible serum protein SERS spectra were obtained from cellulose acetate membrane-purified human serum from 94 HBV patients and 89 normal groups. Tentative assignments of serum protein SERS spectra showed that the HBV patients primarily led to specific biomedical changes of serum protein. Principal components analysis and linear discriminate analysis were introduced to analyse the obtained spectra, with the diagnostic sensitivity of 92.6% and specificity of 77.5% were achieved for differentiating HBV patients from normal groups.

Metabolite profiling of human blood by surface-enhanced Raman spectroscopy for surgery assessment and tumor screening in breast cancer.

Mammography, a standard screening method for breast cancer, is effective for reducing the rate of death; however, it suffers from frequent false positive alarm and radiation risk. Besides, surgery treatment has a vital impact on the clinical outcomes of breast cancer, offering enormous benefits for breast cancer care and management. In this work, we analyzed the peripheral blood sample from breast cancer patients with pre- and post-surgery and healthy volunteers using label-free surface-enhanced Raman spectroscopy technology based on silver nanoparticles. Results showed that distinct patterns of blood belonging to specific subjects could be profiled, and corresponding accuracies of 95% and 100% were achieved by multivariate diagnostic algorithm for pre-surgery vs. post-surgery and pre-surgery vs. normal groups, respectively, providing a unique blood analysis method for surgery evaluation as well as tumor screening in breast cancer. Graphical abstract.

Anti-Cancerous Effect of Inonotus taiwanensis Polysaccharide Extract on Human Acute Monocytic Leukemia Cells through ROS-Independent Intrinsic Mitochondrial Pathway.

Acute leukemia is one of the commonly diagnosed neoplasms and causes human death. However, the treatment for acute leukemia is not yet satisfactory. Studies have shown that mushroom-derived polysaccharides display low toxicity and have been used clinically for cancer therapy. Therefore, we set out to evaluate the anti-cancerous efficacy of a water-soluble polysaccharide extract from Inonotus taiwanensis (WSPIS) on human acute monocytic leukemia THP-1 and U937 cell lines in vitro. Under our experimental conditions, WSPIS elicited dose-dependent growth retardation and induced apoptotic cell death. Further analysis showed that WSPIS-induced apoptosis was associated with a mitochondrial apoptotic pathway, such as the disruption of mitochondrial membrane potential (MMP), followed by the activation of caspase-9, caspase-3, and PARP (poly(ADP-ribose) polymerase) cleavage. However, a broad caspase inhibitor, Z-VAD.fmk, could not prevent WSPIS-induced apoptosis. These data imply that mechanism(s) other than caspase might be involved. Thus, the involvement of endonuclease G (endoG), a mediator arbitrating caspase-independent oligonucleosomal DNA fragmentation, was examined. Western blotting demonstrated that WSPIS could elicit nuclear translocation of endoG. MMP disruption after WSPIS treatment was accompanied by intracellular reactive oxygen species (ROS) generation. However, pretreatment with N-acetyl-l-cysteine (NAC) could not attenuate WSPIS-induced apoptosis. In addition, our data also show that WSPIS could inhibit autophagy. Activation of autophagy by rapamycin decreased WSPIS-induced apoptosis and cell death. Taken together, our findings suggest that cell cycle arrest, endonuclease G-mediated apoptosis, and autophagy inhibition contribute to the anti-cancerous effect of WSPIS on human acute monocytic leukemia cells.

The plasmid-mediated fosfomycin resistance determinants and synergy of fosfomycin and meropenem in carbapenem-resistant Klebsiella pneumoniae isolates in Taiwan.

BACKGROUND: Epidemiology of fosfomycin susceptibility and the plasmid-mediated fosfomycinase genes of carbapenem-resistant Klebsiella pneumoniae (CRKP) isolates in Taiwan remain unclear. METHODS: 642 CRKP clinical isolates were collected from a nation-wide surveillance study (16 hospitals) in Taiwan in 2012-2013. Antimicrobial susceptibilities were determined. PFGE and MLST determined the clonal relatedness. Carbapenemases and fosfomycinases genes were detected by PCR, and their flanking regions were determined by PCR and sequencing. Synergistic activity of meropenem with fosfomycin was examined by the checkerboard method. RESULTS: In total, 36.4% (234/642) of CRKP isolates in Taiwan were resistant to fosfomycin. Among 234 fosfomycin-resistant CRKP isolates, PFGE analysis revealed 81 pulsotypes. Pulsotype XXIII (n = 63) was predominant and belonged to ST11. 71 had carbapnemases (65 blaKPC-2-positive, 1 blaVIM-1-positive and 5 blaIMP-8-positive) and 62 had fosfomycinases (35 fosA3-positive and 27 foskp96-positive). Only 18.5% (5/27) of foskp96-positive isolates carried foskp96 and blaKPC-2, while 71.4% (25/35) of fosA3-positive isolates contained fosA3 and blaKPC-2. There were five types of flanking sequences for fosA3, and 85.7% (30/35) of fosA3 genes were flanked by IS26, suggesting possible horizontal gene transfer. Synergistic effect of fosfomycin and meropenem was observed in all 25 randomly selected pulsotype XXIII strains (100%; 25/25), even those containing fosfomycinase (48%, 12/25) or carbapnemase (96%, 24/25). CONCLUSIONS: A clone (pulsotype XXIII, ST11) has been found to be prevailing among fosfomycin-resistant CRKP in Taiwan. According to the in vitro data, the combination of fosfomycin and meropenem is a potentially alternative choice.

Water-Soluble Dinitrosyl Iron Complex (DNIC): a Nitric Oxide Vehicle Triggering Cancer Cell Death via Apoptosis.

Nitric oxide (NO) is an important cellular signaling molecule that modulates various physiological activities. Angiogenesis-promoting activities of NO-donor drugs have been explored in both experimental and clinical studies. In this study, a structurally well characterized and water-soluble neutral {Fe(NO)2}(9) DNIC [(S(CH2)2OH)(S(CH2)2NH3)Fe(NO)2] (DNIC 2) was synthesized to serve as a NO-donor species. The antitumor activity of DNIC 2 was determined by MTT assay, confocal imaging, and Annexin-V/PI staining. The IC50 values of DNIC 2 were 18.8, 42.9, and 38.6 µM for PC-3, SKBR-3, and CRL5866 tumor cells, respectively. Moreover, DNIC 2 promoted apoptotic cell death via activation of apoptosis-associated proteins and inhibition of survival associated proteins. In particular, DNIC 2 treatment suppressed PC-3 tumor growth by 2.34- and 19.3-fold at 7 and 21 days, in comparison with the control group. These results indicate that water-soluble DNIC 2 may serve as a promising drug for cancer therapy.