Oral candidiasis, a common opportunistic infection of the oral cavity, is mainly caused by the following four Candida species (in decreasing incidence rate): Candida albicans, Candida glabrata, Candida tropicalis, and Candida krusei. This study offers in-depth Raman spectroscopy analyses of these species and proposes procedures for an accurate and rapid identification of oral yeast species. We first obtained average spectra for different Candida species and systematically analyzed them in order to decode structural differences among species at the molecular scale. Then, we searched for a statistical validation through a chemometric method based on principal component analysis (PCA). This method was found only partially capable to mechanistically distinguish among Candida species. We thus proposed a new Raman barcoding approach based on an algorithm that converts spectrally deconvoluted Raman sub-bands into barcodes. Barcode-assisted Raman analyses could enable on-site identification in nearly real-time, thus implementing preventive oral control, enabling prompt selection of the most effective drug, and increasing the probability to interrupt disease transmission.

This study targets on-site/real-time taxonomic identification and metabolic profiling of seven different Candida auris clades/subclades by means of Raman spectroscopy and imaging. Representative Raman spectra from different Candida auris samples were systematically deconvoluted by means of a customized machine-learning algorithm linked to a Raman database in order to decode structural differences at the molecular scale. Raman analyses of metabolites revealed clear differences in cell walls and membrane structure among clades/subclades. Such differences are key in maintaining the integrity and physical strength of the cell walls in the dynamic response to external stress and drugs. It was found that Candida cells use the glucan structure of the extracellular matrix, the degree of α-chitin crystallinity, and the concentration of hydrogen bonds between its antiparallel chains to tailor cell walls’ flexibility. Besides being an effective ploy in survivorship by providing stiff shields in the α–1,3–glucan polymorph, the α–1,3–glycosidic linkages are also water-insoluble, thus forming a rigid and hydrophobic scaffold surrounded by a matrix of pliable and hydrated β–glucans. Raman analysis revealed a variety of strategies by different clades to balance stiffness, hydrophobicity, and impermeability in their cell walls. The selected strategies lead to differences in resistance toward specific environmental stresses of cationic/osmotic, oxidative, and nitrosative origins. A statistical validation based on principal component analysis was found only partially capable of distinguishing among Raman spectra of clades and subclades. Raman barcoding based on an algorithm converting spectrally deconvoluted Raman sub-bands into barcodes allowed for circumventing any speciation deficiency. Empowered by barcoding bioinformatics, Raman analyses, which are fast and require no sample preparation, allow on-site speciation and real-time selection of appropriate treatments.

Due to sulfur agglomeration and drastic volume expansion during charging, a significant challenge for lithium–sulfur battery applications is to achieve favorable energy densities while realizing substantial sulfur loading. The rational design of cathode materials is therefore essential. Here we show a new type of low-cost sulfur/silica/carbon hybrid cathode by integrating carbon-coated and sulfur-encapsulated mesoporous SiO₂ nanospheres with a carbon fiber cross-linked graphene framework (denoted as 3D-GCSS). The porous morphology of SiO₂ ensures electrolyte accessibility, while the mechanical robustness of graphene and the carbon fiber contributes to structural sturdiness and flexibility. The synergistic effect exerted by polar SiO₂ together with conductive graphene and the carbon fiber helps to confine sulfur and intermediate polysulfides as well as providing abundant charge transfer paths. Benefiting from these merits, a coin cell fabricated based on the freestanding 3D-GCSS with an 8 mg cm⁻² sulfur content displayed a high capacity of 1462 mA h g⁻¹ at 0.5C, satisfactory rate performance and cycling stability. More importantly, a type of ultra-flexible soft-packaged cell was assembled utilizing the 3D-GCSS electrode. At a considerable sulfur loading of 20 mg cm⁻², the battery delivered an outstanding capacity of 2.15 A h, a gravimetric energy density of 371 W h kg⁻¹ (1055 W h kg⁻¹ based on the cathode) and a volumetric energy density of 582 W h l⁻¹.