• Handheld Raman spectrometer is able to generate SERS spectra with sufficient quality for Mycobacterium tuberculosis detection. • It is feasible to accurately discriminate Mtb-positive sputum from Mtb-negative sputum through SERS spectrometry. • Pulmonary and extra-pulmonary Mtb strains were able to be accurately distinguished via SERS spectral analysis. • Profiling of antibiotic resistance of Mtb strains was successfully achieved through machine learning analysis of SERS spectra.

A self-assembly hybrid of gold nanoparticles on graphene modified electrodes for low-potential NADH detection has been achieved. We used the natural polymer chitosan (Chit) to assist the stabilization of graphene in aqueous solution, and immobilize the electronegative Au nanoparticles (NPs) through electrostatic attraction. The synergy of Au NPs with graphene for catalytic oxidation of NADH made the overpotential ca. 220 mV less positive than that on the bare electrode, and remarkably increased the oxidation current. The amperometric sensors based on such modified electrodes for detection of NADH exhibited a good linearity from 1.5 to 320 μM, and showed high sensitivity with a low detection limit of 1.2 μM (S/N = 3). It could also exclude common interfering electroactive compounds like ascorbic acid and possessed good reproducibility and operational stability. Such eminent performance of the Au–RGO/Chit film together with the ability of graphene to significantly enhance the electron transfer between enzymes and the electrode suggested its promise for constructing novel graphene based dehydrogenase biosensors.

The global infection rate of fungal diseases is increasing year by year, and it has gradually become one of the most serious infectious diseases threatening human health. However, the side effects of antifungal drugs and the fungal resistance to these drugs are gradually increasing. Therefore, the development of new broad-spectrum, safe, and economical alternatives to antibacterial drugs are essential. Probiotics are microorganisms that are beneficial for human health. They boost human immunity, resist pathogen colonization, and reduce pathogen infection. Many investigations have shown their inhibitory activity on a wide range of pathogenic fungi. However, their antibacterial mechanism is still a secret. This article reviews the progress of probiotics as a new method for the treatment of fungal diseases.

Bloodstream infections (BSIs) are a critical medical concern, characterized by elevated morbidity, mortality, extended hospital stays, substantial healthcare costs, and diagnostic challenges. The clinical outcomes for patients with BSI can be markedly improved through the prompt identification of the causative pathogens and their susceptibility to antibiotics and antimicrobial agents. Traditional BSI diagnosis via blood culture is often hindered by its lengthy incubation period and its limitations in detecting pathogenic bacteria and their resistance profiles. Surface-enhanced Raman scattering (SERS) has recently gained prominence as a rapid and effective technique for identifying pathogenic bacteria and assessing drug resistance. This method offers molecular fingerprinting with benefits such as rapidity, sensitivity, and non-destructiveness. The objective of this study was to integrate deep learning (DL) with SERS for the rapid identification of common pathogens and their resistance to drugs in BSIs. To assess the feasibility of combining DL with SERS for direct detection, erythrocyte lysis and differential centrifugation were employed to isolate bacteria from blood samples with positive blood cultures. A total of 12,046 and 11,968 SERS spectra were collected from the two methods using Raman spectroscopy and subsequently analyzed using DL algorithms. The findings reveal that convolutional neural networks (CNNs) exhibit considerable potential in identifying prevalent pathogens and their drug-resistant strains. The differential centrifugation technique outperformed erythrocyte lysis in bacterial isolation from blood, achieving a detection accuracy of 98.68% for pathogenic bacteria and an impressive 99.85% accuracy in identifying carbapenem-resistant Klebsiella pneumoniae. In summary, this research successfully developed an innovative approach by combining DL with SERS for the swift identification of pathogenic bacteria and their drug resistance in BSIs. This novel method holds the promise of significantly improving patient prognoses and optimizing healthcare efficiency. Its potential impact could be profound, potentially transforming the diagnostic and therapeutic landscape of BSIs.