Contemporary strategies and approaches for characterizing composition and enhancing biofilm penetration targeting bacterial extracellular polymeric substances.

Extracellular polymeric substances (EPS) constitutes crucial elements within bacterial biofilms, facilitating accelerated antimicrobial resistance and conferring defense against the host's immune cells. Developing precise and effective antibiofilm approaches and strategies, tailored to the specific characteristics of EPS composition, can offer valuable insights for the creation of novel antimicrobial drugs. This, in turn, holds the potential to mitigate the alarming issue of bacterial drug resistance. Current analysis of EPS compositions relies heavily on colorimetric approaches with a significant bias, which is likely due to the selection of a standard compound and the cross-interference of various EPS compounds. Considering the pivotal role of EPS in biofilm functionality, it is imperative for EPS research to delve deeper into the analysis of intricate compositions, moving beyond the current focus on polymeric materials. This necessitates a shift from heavy reliance on colorimetric analytic methods to more comprehensive and nuanced analytical approaches. In this study, we have provided a comprehensive summary of existing analytical methods utilized in the characterization of EPS compositions. Additionally, novel strategies aimed at targeting EPS to enhance biofilm penetration were explored, with a specific focus on highlighting the limitations associated with colorimetric methods. Furthermore, we have outlined the challenges faced in identifying additional components of EPS and propose a prospective research plan to address these challenges. This review has the potential to guide future researchers in the search for novel compounds capable of suppressing EPS, thereby inhibiting biofilm formation. This insight opens up a new avenue for exploration within this research domain.

Comprehensive multicomponent characterization and quality assessment of Xiaoyao Wan by UPLC-Q-Orbitrap-MS, HS-SPME-GC-MS and HS-GC-IMS.

Xiaoyao Wan (XYW) is a prescription medicine of traditional Chinese medicine (TCM) with the effects of "soothing the liver and relieving depression," and "strengthening spleen and nourishing blood". XYW has been widely concerned in the treatment of depression and has become one of the commonly used classic formulas in clinical practice. However, the pharmacodynamic substance basis and the quality control studies of XYW are hitherto quite limited. Here, we aim to fully utilize an advanced ultra - performance liquid chromatography-quadrupole - Orbitrap mass spectrometry (UPLC-Q-Orbitrap-MS), headspace-solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) technique to deep characterization of the pharmacological substance basis and quantitatively evaluate the quality of XYW. Firstly, 299 compounds were identified or tentatively characterized, including 198 non-volatile organic compounds (n-VOCs) and 101 volatile organic compounds (VOCs). Secondly, principal component analysis (PCA) and hierarchical cluster analysis (HCA) was used to analyze quality differences in XYW at different manufacturers. Thirdly, a parallel reaction monitoring (PRM) method was established and validated to quantify the fourteen major effective substances in different manufacturers of XYW, which were chosen as the benchmarked substances to evaluate the quality of XYW. In conclusion, this study shows that the strategy provides a useful method for quality control of TCM and offers a practical workflow for exploring the quality consistency of TCM.

Additives in Nanocrystalline Tin Dioxide: Recent Progress in the Characterization of Materials for Gas Sensor Applications.

Tin dioxide has huge potential and is widely studied and used in different fields, including as a sensitive material in semiconductor gas sensors. The specificity of the chemical activity of tin dioxide in its interaction with the gas phase is achieved via the immobilization of various modifiers on the SnO2 surface. The type of additive, its concentration, and the distribution between the surface and the volume of SnO2 crystallites have a significant effect on semiconductor gas sensor characteristics, namely sensitivity and selectivity. This review discusses the recent approaches to analyzing the composition of SnO2-based nanocomposites (the gross quantitative elemental composition, phase composition, surface composition, electronic state of additives, and mutual distribution of the components) and systematizes experimental data obtained using a set of analytical methods for studying the concentration of additives on the surface and in the volume of SnO2 nanocrystals. The benefits and drawbacks of new approaches to the high-accuracy analysis of SnO2-based nanocomposites by ICP MS and TXRF methods are discussed.

Insight into the crucial reason causing the difference in secondary organic aerosol yields of monocyclic aromatic hydrocarbons with different methyl substituent numbers.

The secondary organic aerosol (SOA) yield of toluene photooxidation was reported to substantially higher than that of trimethylbenzene due to the effect of the number of methyl substituents. However, the intrinsic mechanism for this disparity is not clear enough. In this study, a highly-sensitive thermal-desorption photoinduced associative ionization mass spectrometer (TD-PAI-MS) was used to real-time characterize the molecular composition and its evolution of the SOA generated from the photooxidation of toluene and 1,2,3-trimethylbenzene (1,2,3-TMB) in a smog chamber. In the new particle formation (NPF) stage, toluene generated more variety of nucleation precursors, such as benzaldehyde (MW 106) and benzoic acid (MW 122), resulting in a much higher nucleation rate and SOA number concentration. In the SOA growth/aging stage, the key SOA components of toluene were mainly dialdehydes, e.g., 2-oxopropanedial (MW 86) and 4-oxopent-2-enedial (MW 112), which played an important role in the formation of highly oxidized species (HOS) through oligomerization or cyclization reactions. In contrast, due to the presence of more methyl groups, 1,2,3-TMB was inclined to produce ketones, e.g., 2,3-butanedione (MW 86) and 3-methyl-4-oxopent-2-enal (MW 112), which would be cleaved into high-volatility low molecular compounds, e.g., acetic acid, through fragmentation. Taken together, relative to 1,2,3-TMB, the higher nucleation rate during NPF and the significant oligomerization/functionalization process during SOA growth are thought to be the major reasons resulting in the higher SOA yield of toluene. This work provides a reference for the insight into the different SOA yields of monocyclic aromatic hydrocarbons (MAHs) through further revealing the SOA formation mechanism during toluene and 1,2,3-TMB photooxidation.

Milk microfiltration process dataset annotated from a collection of scientific papers.

Milk microfiltration process plays a key role in the dairy industry. Crossflow microfiltration of skimmed milk using a membrane with 0.1 µm mean pore size is widely used to fractionate the two main groups of dairy proteins: casein micelles (~150 nm) and serum proteins (~2-15 nm). Retentate, containing mainly casein micelles, is generally used to enrich vat milk for cheese making. Permeate, containing serum proteins, lactose and minerals, is usually ultrafiltered in order to produce protein-rich concentrate with a high nutritional value dedicated to specific populations such as infants and seniors. The great interest in these protein fractions explains the increasing number of microfiltration equipments in the dairy industry. This data article contains data associated with milk microfiltration process experiments and properties of the resulting dairy fractions annotated from a collection of scientific documents. These data are stored in INRAE public repository (see Data accessibility in the Specification Table for direct links to data). They have been structured using MILK MICROFILTRATION ontology and are replicated in @Web data warehouse providing additional querying tools (https://www6.inrae.fr/cati-icat-atweb/).

Differentiating calcium oxalate and hydroxyapatite stones in vivo using dual-energy CT and urine supersaturation and pH values.

RATIONALE AND OBJECTIVES: Knowledge of urinary stone composition can guide therapeutic intervention for patients with calcium oxalate (CaOx) or hydroxyapatite (HA) stones. In this study, we determined the accuracy of noninvasive differentiation of these two stone types using dual-energy CT (DECT) and urine supersaturation (SS) and pH values. MATERIALS AND METHODS: Patients who underwent clinically indicated DECT scanning for stone disease and subsequent surgical intervention were enrolled. Stone composition was determined using infrared spectroscopy. DECT images were processed using custom-developed software that evaluated the ratio of CT numbers between low- and high-energy images. Clinical information, including patient age, gender, and urine pH and supersaturation profile, was obtained from electronic medical records. Simple and multiple logistic regressions were used to determine if the ratio of CT numbers could discriminate CaOx from HA stones alone or in conjunction with urine supersaturation and pH. RESULTS: Urinary stones (CaOx n = 43, HA n = 18) from 61 patients were included in this study. In a univariate model, DECT data, urine SS-HA, and urine pH had an area under the receiver operating characteristic curve of 0.78 (95% confidence interval [CI] 0.66-0.91, P = .016), 0.76 (95% CI 0.61-0.91, P = .003), and 0.60 (95% CI 0.44-0.75, P = .20), respectively, for predicting stone composition. The combination of CT data and the urinary SS-HA had an area under the receiver operating characteristic curve of 0.79 (95% CI 0.66-0.92, P = .007) for correctly differentiating these two stone types. CONCLUSIONS: DECT differentiated between CaOx and HA stones similarly to SS-HA, whereas pH was a poor discriminator. The combination of DECT and urine SS or pH data did not improve this performance.