Raman fiber-optic probe for rapid diagnosis of gastric and esophageal tumors with machine learning analysis or similarity assessments: a comparative study.

Gastric and esophageal cancers, the predominant forms of upper gastrointestinal malignancies, contribute significantly to global cancer mortality. Routine detection methods, including medical imaging, endoscopic examination, and pathological biopsy, often suffer from drawbacks such as low sensitivity and laborious and complex procedures. Raman spectroscopy is a non-invasive and label-free optical technique that provides highly sensitive biomolecular information to facilitate effective tumor identification.

Associations between different triglyceride glucose index-related obesity indices and periodontitis: results from NHANES 2009-2014.

Background: This study aimed to explore the associations between triglyceride glucose (TyG) index-related obesity indices and periodontitis within the American population.

Methods: This cross-sectional investigation utilized data from the National Health and Nutrition Examination Survey (NHANES) for 2009-2014. The association between the TyG-waist-to-height ratio (TyG-WHtR), TyG-weight-adjusted-waist index (TyG-WWI), TyG-waist circumference (TyG-WC), or TyG-body mass index (TyG-BMI) and periodontitis was investigated utilizing multivariable logistic regression model, subgroup, and dose-response curve analyses.

Raman spectroscopy for esophageal tumor diagnosis and delineation using machine learning and the portable Raman spectrometer.

Esophageal cancer is one of the leading causes of cancer-related deaths worldwide. The identification of residual tumor tissues in the surgical margin of esophageal cancer is essential for the treatment and prognosis of cancer patients. But the current diagnostic methods, either pathological frozen section or paraffin section examination, are laborious, time-consuming, and inconvenient.

Surface-Enhanced Raman Scattering Spectroscopy Combined With Chemical Imaging Analysis for Detecting Apple Valsa Canker at an Early Stage.

Apple Valsa canker (AVC) with early incubation characteristics is a severe apple tree disease, resulting in significant orchards yield loss. Early detection of the infected trees is critical to prevent the disease from rapidly developing. Surface-enhanced Raman Scattering (SERS) spectroscopy with simplifies detection procedures and improves detection efficiency is a potential method for AVC detection.

Heavy metal Hg stress detection in tobacco plant using hyperspectral sensing and data-driven machine learning methods.

Accurate detection of heavy metal stress on the growth status of plants is of great concern for agricultural production and management, food security, and ecological environment. A proximal hyperspectral imaging (HSI) system covered the visible/near-infrared (Vis/NIR) region of 400-1000 nm coupled with machine learning methods were employed to discriminate the tobacco plants stressed by different concentration of heavy metal Hg. After acquiring hyperspectral images of tobacco plants stressed by heavy metal Hg with concentration solutions of 0 mg·L (non-stressed groups), 1, 3, and 5 mg·L (3 stressed groups), regions of interest (ROIs) of canopy in tobacco plants were identified for spectra processing.

Differences in carbon and nitrogen metabolism between male and female Populus cathayana in response to deficient nitrogen.

Sexual dimorphism occurs regarding carbon and nitrogen metabolic processes in response to nitrogen supply. Differences in fixation and remobilization of carbon and allocation and assimilation of nitrogen between sexes may differ under severe defoliation. The dioecious species Populus cathayana was studied after two defoliation treatments with two N levels.

Potential of vibrational spectroscopy for rapid and accurate determination of the hydrogen peroxide treatment of plant leaves.

Detection and characterization of interactions between crop plants and hydrogen peroxide (HO) is significant for the exploration of the mechanisms in plant pathology. The objective of this research is to estimate spectral characteristics of rapeseed leaves (Brassica napus L.) during treatment with different HO concentrations (0, 0.