OBJECTIVE: The purpose of this study was to evaluate the correlations and consistency among the central corneal thickness (CCT) of healthy myopic patients measured with three different anterior segment analysis systems.
METHODS: This was a retrospective study. The study included myopia patients who had undergone preoperative examinations in the refractive surgery department of our hospital between January 2021 and December 2023. The CCT was measured separately using Pentacam, Sirius, and IOLMaster 700.
METHODS: Statistical analysis was conducted using SPSS software. Correlations among the three groups of measured values were assessed using the Pearson method, and a simple scatter plot and fitting line were drawn. Bland‒Altman scatter plots and 95 % limits of agreement (LoAs) were used to evaluate consistency in the data among the systems.
RESULTS: A total of 269 patients participated in the study, including 134 males (49.8 %) and 135 females (50.2 %). The CCT measurements by Pentacam, Sirius, and IOLMaster 700 instruments were found to be 541.63 ± 31.67 μm, 541.74 ± 33.36 μm, and 548.90 ± 34.19 μm respectively; significant differences were observed among these measurements (p < 0.05). Significant differences were also observed in CCT between Pentacam and IOLMaster 700 as well as between Sirius and IOLMaster 700 (p < 0.05). The CCT measurements by all three devices showed high positive correlation with all p values less than 0.001: Pentacam and Sirius, r = 0.972; Pentacam and IOLMaster 700, r = 0.966; and Sirius and IOLMaster 700, r = 0.962. The respective 95 % LoAs were -0.18∼0.18; -1.51∼-1.11; and -1.52∼-1.
CONCLUSIONS: The results indicate that there is a high correlation in measuring CCT for healthy myopic eyes using three different anterior segment analysis systems. However, the differences in the values measured by the three devices were statistically significant. Therefore, in actual clinical practice, it is suggested that the same device should be used to measure and evaluate the CCT across visits.

Bitter orange (Citrus aurantium) is an important source of essential oils with high antimicrobial activities, however the composition and antifungal potential of the decoction peels is little explored. This study assessed the peel decoction\'s chemical profile at the secondary metabolism level and its antifungal activity against the melon phytopathogen Fusarium jinanense. The decoction\'s antifungal potential was investigated using a bioassay-guided fractionation approach based on Solid-Phase Extraction (SPE) and LC-HRMS/MS analysis. Coumarins and flavones were the most abundant classes of compounds in the high-value fractions responsible for up to 61% of the mycelial inhibition of F. jinanense. Overall, this study has presented for the first time the chemical composition, the antifungal potential of the decoction of C. aurantium peels and the compounds associated with these results. This strategy can guide the exploration of under-explored food sources and add value to compounds or fractions enriched with bioactive compounds.

Plant specialized metabolites have diversified vastly over the course of plant evolution, and they are considered key players in complex interactions between plants and their environment. The chemical diversity of these metabolites has been widely explored and utilized in agriculture and crop enhancement, the food industry, and drug development, among other areas. However, the immensity of the plant metabolome can make its exploration challenging. Here we describe a protocol for exploring plant specialized metabolites that combines high-resolution mass spectrometry and computational metabolomics strategies, including molecular networking, identification of structural motifs, as well as prediction of chemical structures and metabolite classes.

OBJECTIVE: To assess the level of agreement and evaluate the reliability of measurements between two Scheimpflug imaging modalities, Scansys (MediWorks, China) and Sirius (CSO, Italy), in quantifying the anterior segment parameters in healthy eyes.
METHODS: In a cross-sectional study, the right eyes of 38 healthy participants without any ocular or systemic diseases were examined. A range of anterior segment parameters including anterior and posterior flat and steep keratometry, central corneal thickness (CCT), thinnest corneal thickness (TCT), anterior chamber depth (ACD), anterior chamber angle (ACA), corneal volume, anterior chamber volume, and horizontal white to white diameter, derived from the sagittal curvature maps were measured. To evaluate the reliability of the measurements, intraclass correlation coefficient (ICC) and correlation coefficient were measured. Additionally, Bland-Altman plots were employed to examine the agreement in mean (bias line) and 95% limits of agreement between the two devices.
RESULTS: The mean age was 31.5 ± 6.9 (range: 19-47) years. The ICC indicated that the majority of anterior segment parameters had an excellent or good level of reliability, surpassing the threshold of 0.9. Nevertheless, CCT and ACA exhibited a moderate level of reliability, with ICC values of 0.794 and 0.728, respectively. The correlation analysis showed a strong correlation for all the variables tested. The Bland-Altman plots revealed that the bias line was near zero and the 95% limits of agreement were narrow for most variables, except for the anterior flat and steep keratometry, which were found to range from - 0.57 to 0.84 D and - 0.68 to 0.87 D, respectively.
CONCLUSIONS: Scansys and Sirius devices can be effectively used interchangeably for the evaluation of most anterior segment parameters; however, for anterior corneal curvatures, CCT and ACA, their alternative use is not recommended.

Nontarget high-resolution mass spectrometry screening (NTS HRMS/MS) can detect thousands of organic substances in environmental samples. However, new strategies are needed to focus time-intensive identification efforts on features with the highest potential to cause adverse effects instead of the most abundant ones. To address this challenge, we developed MLinvitroTox, a machine learning framework that uses molecular fingerprints derived from fragmentation spectra (MS2) for a rapid classification of thousands of unidentified HRMS/MS features as toxic/nontoxic based on nearly 400 target-specific and over 100 cytotoxic endpoints from ToxCast/Tox21. Model development results demonstrated that using customized molecular fingerprints and models, over a quarter of toxic endpoints and the majority of the associated mechanistic targets could be accurately predicted with sensitivities exceeding 0.95. Notably, SIRIUS molecular fingerprints and xboost (Extreme Gradient Boosting) models with SMOTE (Synthetic Minority Oversampling Technique) for handling data imbalance were a universally successful and robust modeling configuration. Validation of MLinvitroTox on MassBank spectra showed that toxicity could be predicted from molecular fingerprints derived from MS2 with an average balanced accuracy of 0.75. By applying MLinvitroTox to environmental HRMS/MS data, we confirmed the experimental results obtained with target analysis and narrowed the analytical focus from tens of thousands of detected signals to 783 features linked to potential toxicity, including 109 spectral matches and 30 compounds with confirmed toxic activity.

Eleusine indica (L.) Gaertn is a perennial herb belonging to the Poaceae family. As the only species of Eleusine found abundantly in Malaysia, it is locally known as \"rumput sambau\" and has been traditionally used to treat various ailments including pain relief from vaginal bleeding, hastening the placenta delivery after childbirth, asthma, hemorrhoids, urinary infection, fever, and as a tonic for flu-related symptoms. A diverse array of biological activities have been reported for the plant, such as antimicrobial, cytotoxic, anticonvulsant, anti-inflammatory, analgesic, antipyretic, and hepatoprotective action. Despite many reports on its traditional uses and biological activities, limited chemical databases are available for the plant. Thus, the aims of this study were to annotate and identify the phytochemical constituents in the methanolic extract of E. indica through tandem LCMS-based analysis techniques using MZmine, GNPS, Compound Discoverer, and SIRIUS platforms. This technique managed to identify a total of 65 phytochemicals in the extract, comprising primary and secondary metabolites, and was verified by the isolation of one of the identified phytochemicals. The structural elucidation mainly using 1D and 2D NMR as well as comparison with values in the literature confirms the isolated phytochemical to be a 3-OH anomer of loliolide, a benzofuran-type of compound, which consequently increases the level of confidence in the applied technique. The research describes a useful method for the fast and simultaneous identification of phytochemicals in E. indica, contributing to the study of the chemical properties of the genus and family.

OBJECTIVE: To compare the root mean square (RMS) of anterior corneal higher-order aberrations (HOAs) in ametropic and emmetropic eyes.
METHODS: This retrospective observational study was conducted at the Department of Ophthalmology, Tishreen University Hospital, Latakia, Syria. Study eyes were divided into four groups based on refractive error: mild-to-moderate myopia, hypermetropia, myopic astigmatism, and emmetropic eyes as controls. The following anterior corneal HOAs were evaluated using the Scheimpflug-Placido Sirius (CSO, Italy) tomographer over 6 mm pupil: Root mean square (RMS) total corneal HOAs, RMS trefoil, RMS coma and RMS spherical aberrations.
RESULTS: RMS values of total HOAs, trefoil and coma showed statistically significant differences in all four groups (P < 0.05, all). HOAs were noted to be lowest in the control group (0.18 ± 0.09, 011 ± 0.08 and 0.09 ± 0.08 μm, respectively) and highest in the myopic astigmatism group (0.31 ± 0.16, 0.15 ± 0.12, 0.17 ± 0.14 μm, respectively). RMS spherical aberration was lowest in the astigmatism group (0.00 ± 0.16 μm) with a statistically significant difference from that in the control group (0.05 ± 0.07 μm, P = 0.049).
CONCLUSIONS: The mean RMS values of total HOAs, trefoil and coma were highest in the astigmatism group and lowest in the control group. However, spherical aberration was minimal in the astigmatism group. A better understanding and targeted treatment of higher-order aberrations in ametropic human eyes, and in particular eyes with astigmatism, may enhance visual quality and performance in the treatment of refractive errors. Recognising atypical HOAs may also assist in the early detection of pathological conditions such as keratoconus.

Castor cake is a major by-product generated after castor oil extraction and has been widely used as an organic fertilizer. Once applied to soil, a toxic alkaloid ricinine in castor cake may be released into soils and subsequently taken up by crops, which poses a potential threat to food safety and human health. However, the environmental fate of castor cake derived ricinine in agroecosystems remains unclear. In this study, the release and metabolism of ricinine in soils were conducted using soil pot experiments with different castor cake application rates. The analytical methodology of ricinine quantification in soil pore water was first established using solid phase extraction (SPE) coupled with liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF/MS). A non-target screening workflow associated with LC-QTOF/MS and SIRIUS platform was further developed to identify ricinine metabolites in soil pore water. After castor cake application, the ricinine concentrations in soil pore water significantly increased to 297-7990 μg L-1 at 1 day and then gradually decreased to 62.1-3460 μg L-1 at 7 days and 1.70-279 μg L-1 at 14 days for the selected two tested soils with castor cake application rates of 2, 10, and 20 g castor cake/kg soil. In addition, two ricinine metabolites R-194 and R-180 were tentatively identified and one ricinine metabolite N-demethyl-ricinin was confirmed through authentic reference standard for the first time by the developed non-target screening workflow. This study highlights the release and metabolism of toxic alkaloid ricinine in soils once applied castor cake as an organic fertilizer. Ricinine could be released into soil pore water in a short-term after castor cake application and then undergo demethylation, hydroxylation, and hydroxylation followed by methylation metabolisms over time in agroecosystems.

Dinotefuran (DNT) is a neonicotinoid insecticide widely used in pest control. Identification of structurally related impurities is indispensable during material purification and pesticide registration and certified reference material development, and therefore needs to be carefully characterized. In this study, a combined strategy with liquid chromatography high-resolution mass spectrometry and SIRIUS has been developed to elucidate impurities from DNT material. MS and MS/MS spectra were used to score the impurity candidates by isotope score and fragment tree in the computer assisted tool, SIRIUS. DNT, the main component, worked as an anchor for formula identification and impurity structure elucidation. With this strategy, two by-product impurities and one stereoisomer were identified. Their fragmentation pathways were concluded, and the mechanism for impurity formation was also proposed. This result showed a successful application for combined human intelligence and machine learning, in the identification of pesticide impurities.

Thiamethoxam (TMX) is a widely used neonicotinoid insecticide in pest control. Identification of structurally related impurities is very important during certified reference material development and pesticide registration, thus it needs to be carefully characterized. In this study, a combined strategy with liquid chromatography-high resolution mass spectrometry and computer assisted elucidation (SIRIUS) has been developed for the impurity elucidation in TMX material. MS and MS/MS spectra were used to score the impurity candidates by isotope score and fragment tree in SIRIUS. TMX, the main component, worked as an anchor for formula identification and structure elucidation of impurity. With this strategy, four impurities were identified, including two byproducts (TMX-OCH3 and TMX-Cl) and two metabolites (clothianidin and TMX-urea). Their fragmentation pathways were concluded, and mechanism of impurity formation was also proposed. This result showed successful application of combining human intelligence with machine learning in impurity identification from chemicals.