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Phenotyping of bacteria with vibrational spectroscopy has caught much attention in bacteria-related research. It is known that many factors could affect this process. Among them, solution pH maintenance is crucial, yet its impact on the bacterial SERS spectra is surprisingly neglected. In this work, we focused on two situations related to pH maintenance: the effect of the same buffer on the SERS spectra of bacteria under different pH values, and the influence of different buffers on the SERS spectra of bacteria under the same pH value. Specifically, Britton-Robison (BR) buffer was used to evaluate the effect of pH value on bacteria SERS spectra thanks to its wide pH range. Four different buffers, namely BR buffer, acetate buffer, phosphate buffer, and carbonate buffer, were used to illustrate the impact of buffer types on SERS spectra of bacteria. The results showed that the intensity and number of characteristic peaks of the SERS spectra of Gram-negative (G -) bacteria changed more significantly than Gram-positive (G +) bacteria with the change of pH value. Furthermore, compared with phosphate buffer and carbonate buffer, BR buffer could bring more characteristic SERS bands with better reproducibility, but slightly inferior to acetate buffer. In conclusion, the influence of the pH and types of the buffer on the SERS spectra of bacteria are worthy of further discussion.

Surface-enhanced Raman scattering (SERS) is a powerful tool for constructing biomolecular fingerprints, which play a vital role in differentiation of bacteria. Due to the rather subtle differences in the SERS spectra among different bacteria, artificial intelligence is usually adopted and enormous amounts of spectral data are required to improve the differentiation efficiency. However, in many cases, large volume data acquisition on bacteria is not only technical difficult but labour intensive. It is known that surface modification of SERS nanomaterials can bring additional dimensionality (difference) of the SERS fingerprints. Here in this work, we show that the concept could be used to improve the bacteria differentiation efficiency. Ag NPs were modified with 11-mercaptoundecanoic acid, 11-mercapto-1-undecanol, and 1-dodecanethiol to provide additional dimensionality. The modified NPs then were mixed with cell lysate from different strains of Bacillus cereus (B. cereus). Even by applying a simple PCA process to the resulting SERS spectra data, all the three modified Ag NPs showed superior differentiation results compared with bare Ag NPs, which could only separate Staphylococcus aureus (S. aureus) and B. cereus. It is believed that the multidimensional SERS could find great potential in bacteria differentiation.

Surface-enhanced Raman spectroscopy (SERS) stands out in the field of microbial analysis due to its rich molecular information, fast analysis speed, and high sensitivity. However, achieving strain-level differentiation is still challenging because numerous bacterial species inevitably have very similar SERS profiles. Here, a method inspired by the black-box theory was proposed to boost the spectral differences, where the undifferentiated bacteria was considered as a type of black-box, external environmental stress was used as the input, and the SERS spectra of bacteria exposed to the same stress was output. For proof of the concept, three types of environmental stress were explored, i.e., ethanol, ultraviolet light (UV), and ultrasound.

A series of shape memory polyurethanes (SPU) with different component ratio of PEG, MDI, BDO, and crosslinker DEA were synthesized by stepwise polymerization in DMF. WAXD, SAXS, DMTA, and DTA were used to study the microphase structure of SPU. No obvious phase-separation and crystalline evidence of the PEG soft segment and hard segment were obtained in this work. The water-swollen ratio increases with both the increasing molecular weight of PEG soft segment and the decreasing density of the chemical crossbonding. All the samples show good thermally stimulated shape memory properties. When the molar ratio of soft segment to hard segment is close, the shape recovery time reduces along with the increasing density of the chemical crossbonding. When the densities of the chemical crossbonding are similar, the shape recovery time reduces with the increasing molecular weight of the PEG soft segment. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 84: 1504–1512, 2002; DOI 10.1002/app.10357