Discrimination of Benign and Malignant Thyroid Nodules through Comparative Analyses of Human Saliva Samples via Metabolomics and Deep-Learning-Guided Label-free SERS.

Thyroid nodules are a very common entity. The overall prevalence in the populace is estimated to be around 65-68%, among which a small portion (less than 5%) is malignant (cancerous). Therefore, it is important to discriminate benign thyroid nodules from malignant thyroid nodules.

Rapid diagnosis of bacterial vaginosis using machine-learning-assisted surface-enhanced Raman spectroscopy of human vaginal fluids.

Unlabelled: Bacterial vaginosis (BV) is an abnormal gynecological condition caused by the overgrowth of specific bacteria in the vagina. This study aims to develop a novel method for BV detection by integrating surface-enhanced Raman scattering (SERS) with machine learning (ML) algorithms. Vaginal fluid samples were classified as BV positive or BV negative using the BVBlue Test and clinical microscopy, followed by SERS spectral acquisition to construct the data set.

Identification of structural stability and fragility of mouse liver glycogen via label-free Raman spectroscopy coupled with convolutional neural network algorithm.

Glycogen structure is closely associated with its physiological functions. Previous studies confirmed that liver glycogen structure had two dominant states: mainly stable during the day and largely fragile at night. However, the diurnal change of glycogen structure is impaired, with dominant fragility in diseased conditions such as diabetes mellitus and liver fibrosis.

Identification of hypermucoviscous strains untargeted surface-enhanced Raman spectroscopy.

is one of the most common causes of hospital-acquired infections, especially due to the emergence of the hypervirulent (hvKp) strains. Multiple methods have been developed to discriminate hvKp strains from classical (cKp) strains, such as the presence of candidate genes (, -344, , and ), high level of siderophore production, hypermucoviscosity phenotype, Although the string test is commonly used to confirm the hypermucoviscosity of strains, it is a method lacking rigidity and accuracy. Surface-enhanced Raman spectroscopy (SERS) coupled with machine learning algorithms has been widely used in discriminating bacterial pathogens with different phenotypes.

Identification of chronic non-atrophic gastritis and intestinal metaplasia stages in the Correa's cascade through machine learning analyses of SERS spectral signature of non-invasively-collected human gastric fluid samples.

The progression of gastric cancer involves a complex multi-stage process, with gastroscopy and biopsy being the standard procedures for diagnosing gastric diseases. This study introduces an innovative non-invasive approach to differentiate gastric disease stage using gastric fluid samples through machine-learning-assisted surface-enhanced Raman spectroscopy (SERS). This method effectively identifies different stages of gastric lesions.

Rapid diagnosis and precision treatment of infection in clinical settings.

is a gram-negative bacterium that colonizes the stomach of approximately half of the worldwide population, with higher prevalence in densely populated areas like Asia, the Caribbean, Latin America, and Africa. infections range from asymptomatic cases to potentially fatal diseases, including peptic ulcers, chronic gastritis, and stomach adenocarcinoma. The management of these conditions has become more difficult due to the rising prevalence of drug-resistant infections, which ultimately lead to gastric cancer and mucosa-associated lymphoid tissue (MALT) lymphoma.

Pseudo-Siamese network combined with label-free Raman spectroscopy for the quantification of mixed trace amounts of antibiotics in human milk: A feasibility study.

The utilization of antibiotics is prevalent among lactating mothers. Hence, the rapid determination of trace amounts of antibiotics in human milk is crucial for ensuring the healthy development of infants. In this study, we constructed a human milk system containing residual doxycycline (DXC) and/or tetracycline (TC).

Rapid discrimination of four Salmonella enterica serovars: A performance comparison between benchtop and handheld Raman spectrometers.

Foodborne illnesses, particularly those caused by Salmonella enterica with its extensive array of over 2600 serovars, present a significant public health challenge. Therefore, prompt and precise identification of S. enterica serovars is essential for clinical relevance, which facilitates the understanding of S.

[Evidence mapping of Chinese patent medicines in treatment of premature ventricular contractions].

This study employed evidence mapping to systematically sort out the clinical studies about the treatment of premature ventricular contractions with Chinese patent medicines and to reveal the distribution of evidence in this field. The articles about the treatment of premature ventricular contractions with Chinese patent medicines were searched against PubMed, Cochrane Library, Web of Science, CNKI, Wanfang, and VIP with the time interval from January 2016 to December 2022. Evidence was analyzed and presented by charts and graphs combined with text.

Differentiation of closely-related species within Acinetobacter baumannii-calcoaceticus complex via Raman spectroscopy: a comparative machine learning analysis.

Bacterial species within the Acinetobacter baumannii-calcoaceticus (Acb) complex are very similar and are difficult to discriminate. Misidentification of these species in human infection may lead to severe consequences in clinical settings. Therefore, it is important to accurately discriminate these pathogens within the Acb complex.

Rapid discrimination and ratio quantification of mixed antibiotics in aqueous solution through integrative analysis of SERS spectra via CNN combined with NN-EN model.

Introduction: Abusing antibiotic residues in the natural environment has become a severe public health and ecological environmental problem. The side effects of its biochemical and physiological consequences are severe. To avoid antibiotic contamination in water, implementing universal and rapid antibiotic residue detection technology is critical to maintaining antibiotic safety in aquatic environments.

Detection of Helicobacter pylori Infection in Human Gastric Fluid Through Surface-Enhanced Raman Spectroscopy Coupled With Machine Learning Algorithms.

Diagnostic methods for Helicobacter pylori infection include, but are not limited to, urea breath test, serum antibody test, fecal antigen test, and rapid urease test. However, these methods suffer drawbacks such as low accuracy, high false-positive rate, complex operations, invasiveness, etc. Therefore, there is a need to develop simple, rapid, and noninvasive detection methods for H.

Rapid discrimination of spp. and label-free surface enhanced Raman spectroscopy coupled with machine learning algorithms.

and enterotoxigenic (ETEC) are major bacterial pathogens of diarrheal disease that is the second leading cause of childhood mortality globally. Currently, it is well known that spp., and .

Rapid Prediction of Multidrug-Resistant Klebsiella pneumoniae through Deep Learning Analysis of SERS Spectra.

Klebsiella pneumoniae is listed by the WHO as a priority pathogen of extreme importance that can cause serious consequences in clinical settings. Due to its increasing multidrug resistance all over the world, K. pneumoniae has the potential to cause extremely difficult-to-treat infections.

Identification of geographic origins of Linn. through surfaced enhanced Raman spectrometry and machine learning algorithms.

The leaves of Linn., which is also known as white mulberry, have been commonly used in many of traditional systems of medicine for centuries. In traditional Chinese medicine (TCM), mulberry leaf is mainly used for anti-diabetic purpose due to its enrichment in bioactive compounds such as alkaloids, flavonoids and polysaccharides.

Recent advances in surface enhanced Raman spectroscopy for bacterial pathogen identifications.

Background: The rapid and reliable detection of pathogenic bacteria at an early stage is a highly significant research field for public health. However, most traditional approaches for pathogen identification are time-consuming and labour-intensive, which may cause physicians making inappropriate treatment decisions based on an incomplete diagnosis of patients with unknown infections, leading to increased morbidity and mortality. Therefore, novel methods are constantly required to face the emerging challenges of bacterial detection and identification.

Medial meniscus posterior root tears and partial meniscectomy significantly increase stress in the knee joint during dynamic gait.

Purpose: As a simple and invasive treatment, arthroscopic medial meniscal posterior horn resections (MMPHRs) can relieve the obstructive symptoms of medial meniscus posterior root tears (MMPRTs) but with the risk of aggravating biomechanical changes of the joint. The aim of this study was to analyze dynamic simulation of the knee joint after medial meniscus posterior root tear and posterior horn resection.

Methods: This study established static and dynamic models of MMPRTs and MMPHRs on the basis of the intact medial meniscus model (IMM).

Machine learning analysis of SERS fingerprinting for the rapid determination of infection and drug resistance.

Over the past decades, conventional methods and molecular assays have been developed for the detection of tuberculosis (TB). However, these techniques suffer limitations in the identification of (), such as long turnaround time and low detection sensitivity, etc., not even mentioning the difficulty in discriminating antibiotics-resistant strains that cause great challenges in TB treatment and prevention.

Rapid discrimination of glycogen particles originated from different eukaryotic organisms.

There are many commercially available glycogen particles in the market due to their bioactive functions as food additive, drug carrier and natural moisturizer, etc. It would be beneficial to rapidly determine the origins of commercially-available glycogen particles, which could facilitate the establishment of quality control methodology for glycogen-containing products. With its non-destructive, label-free and low-cost features, surface enhanced Raman spectroscopy (SERS) is an attractive technique with high potential to discriminate chemical compounds in a rapid mode.