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Abstract Increasing access to water quality tests in low-income communities is a crucial strategy toward achieving global water equality. Recent studies in the Water Sanitation and Hygiene (WASH) sector underscore the importance of addressing practical concerns in water testing, such as robustness and results communication. In response, we present the WaterScope testing kit; an open-source, validated platform for drinking water quality assessment. It modernises the testing process with the inclusion of a unique cartridge/slider mechanism, machine-learning-enhanced classification and full digitalisation of results. WaterScope’s equivalency to conventional methods for quantifying E. coli is established through extensive validation experiments in both laboratory and field environments. This versatile platform provides potential to expand its applications to test other bacteria, perform colorimetric assays, and analyse clinical samples such as blood/urine samples. We anticipate that the system’s ease-of-use, portability, affordability, robustness, and digital nature will accelerate progress toward global water equality.

Abstract Background Coronary inflammation induces changes in pericoronary adipose tissue (PCAT) can be detected by coronary computed tomography angiography (CCTA). Our aim was to investigate whether different PCAT radiomics model based on CCTA could improve the prediction of major adverse cardiovascular events (MACE) within 3 years. Methods This retrospective study included 141 consecutive patients with MACE and matched to patients with non-MACE (n = 141). Patients were randomly assigned into training and test datasets at a ratio of 8:2. After the robust radiomics features were selected by using the Spearman correlation analysis and the least absolute shrinkage and selection operator, radiomics models were built based on different machine learning algorithms. The clinical model was then calculated according to independent clinical risk factors. Finally, an overall model was established using the radiomics features and the clinical factors. Performance of the models was evaluated for discrimination degree, calibration degree, and clinical usefulness. Results The diagnostic performance of the PCAT model was superior to that of the RCA-model, LAD-model, and LCX-model alone, with AUCs of 0.723, 0.675, 0.664, and 0.623, respectively. The overall model showed superior diagnostic performance than that of the PCAT-model and Cli-model, with AUCs of 0.797, 0.723, and 0.706, respectively. Calibration curve showed good fitness of the overall model, and decision curve analyze demonstrated that the model provides greater clinical benefit. Conclusion The CCTA-based PCAT radiomics features of three major coronary arteries have the potential to be used as a predictor for MACE. The overall model incorporating the radiomics features and clinical factors offered significantly higher discrimination ability for MACE than using radiomics or clinical factors alone.

Trichloroethylene (TCE) is a prevalent groundwater contaminant detected worldwide, and microbes are sensitive indicators and initial responders to these chemical contaminants causing disturbances to their ecosystem. In this study, microbes isolated from San Marcos River sediment were screened for their TCE degradation potential. Among the twelve isolates (SAN1-12), five isolates demonstrated TCE degradation within 5 days at 25 °C and 40 mg/L of TCE concentration in the following order: SAN8 (87.56%), SAN1 (77.31%), SAN2 (76.58%), SAN3 (49.20%), and SAN7 (3.36%). On increasing the TCE concentration to 80 mg/L, the degradation efficiency of these isolates declined, although SAN8 remained the prominent TCE degrader with 75.67% degradation. The prominent TCE-degrading isolates were identified as Aeromonas sp. SAN1, Bacillus sp. SAN2, Gordonia sp. SAN3, and Bacillus proteolyticus SAN8 using 16S rRNA sequencing. The TCE degradation and cell biomass of Bacillus proteolyticus SAN8 were significantly improved when the incubation temperature was increased from 25 °C to 30 °C. However, both slightly acidic and alkaline pH levels, as well as higher TCE concentrations, lowered the efficacy of TCE degradation. Nevertheless, these conditions led to an increase in bacterial cell biomass.

Surface-enhanced Raman scattering (SERS) substrates based on chemical mechanism (CM) have received widespread attentions for the stable and repeatable signal output due to their excellent chemical stability, uniform molecular adsorption and controllable molecular orientation. However, it remains huge challenges to achieve the optimal SERS signal for diverse molecules with different band structures on the same substrate. Herein, we demonstrate a graphene oxide (GO) energy band regulation strategy through ferroelectric polarization to facilitate the charge transfer process for improving SERS activity. The Fermi level (Ef) of GO can be flexibly manipulated by adjusting the ferroelectric polarization direction or the temperature of the ferroelectric substrate. Experimentally, kelvin probe force microscopy (KPFM) is employed to quantitatively analyze the Ef of GO. Theoretically, the density functional theory calculations are also performed to verify the proposed modulation mechanism. Consequently, the SERS response of probe molecules with different band structures (R6G, CV, MB, PNTP) can be improved through polarization direction or temperature changes without the necessity to redesign the SERS substrate. This work provides a novel insight into the SERS substrate design based on CM and is expected to be applied to other two-dimensional materials.

Surface‐enhanced Raman spectroscopy (SERS) has emerged as a distinctive fingerprinting technique, offering a broad spectrum of applications encompassing environmental monitoring, chemical detection, and biomolecular analysis. Electrically modulated SERS (E‐SERS) stands as a technique which leverages an electric field to finely control the Raman signal based on the foundational principles of SERS. Through the manipulation of the physicochemical attributes of a metal or 2D material substrate, E‐SERS brings about an enhancement of the SERS signal. This enhancement occurs through a charge transfer process and modulation of the plasma resonance. This article showcases recent strides in the domain of E‐SERS, encompassing advancements such as the integration of paired integrated electrodes, piezoelectric materials, and pyroelectric materials in the construction of substrates. An exhaustive analysis of the mechanism underpinning the enhancement of the Raman signal is undertaken, alongside an exploration of the prominent attributes characterizing diverse methods for conditioning Raman signals. Elucidations are provided on the significance of employed electric fields in the augmentation of SERS and their manifold applications in drug identification, chemical detection, and catalysis. In summation, a delineation of challenges and perspectives inherent to E‐SERS substrates is presented, delineating a path for prospective comprehensive exploration within this auspicious realm of research.