The Analyst

Mid-infrared spectral classification of endometrial cancer compared to benign controls in serum or plasma samples

The process for developing an accurate and reliable classification model based on the previously pre-processed data. The performance of each classification model is assessed using the Matthew's Correlation Coefficient as a metric.

Raman spectroscopy of ovarian and peritoneal tissue in the assessment of ovarian cancer

We demonstrate that Raman spectroscopy is a viable tool for ovarian cancer assessment.

Extracellular vesicles derived from ovarian cancer cell lines discriminated by biochemical and Fourier transform infrared spectroscopy approaches

Biochemical and FTIR approaches to discriminate ovarian cancer cell-derived EVs.

Characterization of ovarian cancer-derived extracellular vesicles by surface-enhanced Raman spectroscopy

EVs derived from normal ovarian (hIOSE) and ovarian cancer (OVCAR3, OV-90, EOC6, EOC18) cells were analysed by SERS. The SERS spectra of normal and cancer EVs were differentiated by PCA and machine learning, through which we achieved >99% accuracy.

Affinity-free enrichment and mass spectrometry analysis of the ovarian cancer biomarker CA125 (MUC16) from patient-derived ascites

Developing a mass spectrometry-based assay for the ovarian cancer biomarker CA125 (MUC16) is a desirable goal, because it may enable detection of proteoforms that are analytically silent in the current immunoassay.

Low-cost electrochemical paper-based device for exosome detection

A low-cost electrochemical paper-based analytical device was developed to quantify cancer cell-derived exosomes.

A dual-signal electrochemical immunosensor for the detection of HPV16 E6 oncoprotein based on PdBP dendritic ternary nanospheres and MBSi-Chi nanocomposites

A dual-signal electrochemical immunosensor was fabricated to detect HPV16 E6 oncoprotein for the first time, which meets the requirements for a quick and sensitive detection.

An improved cancer diagnosis algorithm for protein mass spectrometry based on PCA and a one-dimensional neural network combining ResNet and SENet

An improved cancer diagnosis algorithm for protein mass spectrometry based on PCA and 1D neural network combining ResNet and SENet is proposed and successfully applied to the diagnosis of ovarian cancer with high accuracy and strong fitting ability.

Qualifying P-glycoprotein in drug-resistant ovarian cancer cells: a dual-mode aptamer probe approach

Our dual-mode FI and FP aptamer probe detects P-glycoprotein in drug-resistant ovarian cancer cells, demonstrating high specificity and sensitivity with detection limits of 1.13 nM and 40 cells per mL, promising improved diagnosis strategies.

Ultrasensitive amplification-free detection of circulating miRNA via droplet-based processing of SERS tag–miRNA–magnetic nanoparticle sandwich nanocomplexes on a paper-based electrowetting-on-dielectric platform

Rapid (∼5 min) pretreatment and concentration of the MNP–miRNA–NAEB complex are accomplished using a pEWOD device. This facilitates sub-femtomolar SERS detection for analyzing microRNA in clinical samples of ovarian cancer.

PAM-free activation of CRISPR/Cas12a via semi-nested asymmetric RPA: highly specific detection of HPV16 dsDNA

SNA-RPA-CRISPR/Cas12a overcomes PAM limitations by converting dsDNA into ssDNA via semi-nested asymmetric amplification, enhancing HPV16 detection sensitivity and specificity by leveraging Cas12a's trans-cleavage activity of fluorescent reporters.

A multilayered cancer-on-a-chip model to analyze the effectiveness of new-generation photosensitizers

Three-dimensional (3D) cellular models of cancer tissue are necessary tools to analyze new anticancer drugs under in vitro conditions.

Leveraging mid-infrared spectroscopic imaging and deep learning for tissue subtype classification in ovarian cancer

This study introduces label-free, automated ovarian tissue cell recognition using O-PTIR imaging, offering 10× better resolution than FTIR. It outperforms FTIR, achieving 0.98 classification accuracy. This work aids early ovarian cancer diagnosis.

In situ grown magnetic COF@MOF with a phosphoserine anchor for in-depth N-glycopeptide analysis in serum

This work introduces the in-depth analysis of glycopeptides in human serum using a novel magnetic COF@MOF with a phosphoserine anchor.

A microfluidic-chip-based system with loop-mediated isothermal amplification for rapid and parallel detection of Trichomonas vaginalis and human papillomavirus

A microfluidic-chip system is developed using LAMP for fast and simultaneous detection of Trichomonas vaginalis and high-risk human papillomavirus, and it is promisingly applicable in various fields, particularly in co-infection diagnosis.

Duplex-immunoassay of ovarian cancer biomarker CA125 and HE4 based carbon dot decorated dendritic mesoporous silica nanoparticles

Duplex-immunoassay of CA125 and HE4 using DMSNs@CD560as a fluorescent probe.

MicroRNAs in ovarian cancer and recent advances in the development of microRNA-based biosensors

Ovarian cancer is the most aggressive of all gynaecological malignancies and is the leading cause of cancer-associated mortality worldwide.