Common-Unique Decomposition Driven Diffusion Model for Contrast-Enhanced Liver MR Images Multi-Phase Interconversion.

All three contrast-enhanced (CE) phases (e.g., Arterial, Portal Venous, and Delay) are crucial for diagnosing liver tumors. However, acquiring all three phases is constrained due to contrast agents (CAs) risks, long imaging time, and strict imaging criteria. In this paper, we propose a novel Common-Unique Decomposition Driven Diffusion Model (CUDD-DM), capable of converting any two input phases in three phases into the remaining one, thereby reducing patient wait time, conserving medical resources, and reducing the use of CAs. 1) The Common-Unique Feature Decomposition Module, by utilizing spectral decomposition to capture both common and unique features among different inputs, not only learns correlations in highly similar areas between two input phases but also learns differences in different areas, thereby laying a foundation for the synthesis of remaining phase. 2) The Multi-scale Temporal Reset Gates Module, by bidirectional comparing lesions in current and multiple historical slices, maximizes reliance on previous slices when no lesions and minimizes this reliance when lesions are present, thereby preventing interference between consecutive slices. 3) The Diffusion Model-Driven Lesion Detail Synthesis Module, by employing a continuous and progressive generation process, accurately captures detailed features between data distributions, thereby avoiding the loss of detail caused by traditional methods (e.g., GAN) that overfocus on global distributions. Extensive experiments on a generalized CE liver tumor dataset have demonstrated that our CUDD-DM achieves state-of-the-art performance (improved the SSIM by at least 2.2% (lesions area 5.3%) comparing the seven leading methods). These results demonstrate that CUDD-DM advances CE liver tumor imaging technology.

Biomimetic leaves with immobilized catalase for machine learning-enabled validating fresh produce sanitation processes.

Washing and sanitation are vital steps during the postharvest processing of fresh produce to reduce the microbial load on the produce surface. Although current process control and validation tools effectively predict sanitizer concentrations in wash water, they have significant limitations in assessing sanitizer effectiveness for reducing microbial counts on produce surfaces. These challenges highlight the urgent need to improve the validation of sanitation processes, especially considering the presence of dynamic organic contaminants and complex surface topographies. This study aims to provide the fresh produce industry with a novel, reliable, and highly accurate method for validating the sanitation efficacy on the produce surface. Our results demonstrate the feasibility of using a food-grade, catalase (CAT)-immobilized biomimetic leaf in combination with vibrational spectroscopy and machine learning to predict microbial inactivation on microgreen surfaces. This was tested using two sanitizers: sodium hypochlorite (NaClO) and hydrogen peroxide (H2O2). The developed CAT-immobilized leaf-replicated PDMS (CAT@L-PDMS) effectively mimics the microscale topographies and bacterial distribution on the leaf surface. Alterations in the FTIR spectra of CAT@L-PDMS, following simulated sanitation processes, indicate chemical changes due to CAT oxidation induced by NaClO or H2O2 treatments, facilitating the subsequent machine learning modeling. Among the five algorithms tested, the competitive adaptive reweighted sampling partial least squares discriminant analysis (CARS-PLSDA) algorithm was the most effective for classifying the inactivation efficacy of E. coli on microgreen leaf surfaces. It predicted bacterial reduction on microgreen surfaces with 100% accuracy in both training and prediction sets for NaClO, and 95% in the training set and 86% in the prediction set for H2O2. This approach can improve the validation of fresh produce sanitation processes and pave the way for future research.

Improving the prediction performance of soluble solids content (SSC) in kiwifruit by means of near-infrared spectroscopy using slope/bias correction and calibration updating.

Soluble solids content (SSC) is particularly important for kiwifruit, as it not only determines its flavor, but also helps assess its maturity. Visible/near-infrared (Vis/NIR) spectroscopy has been widely used to evaluate the SSC of kiwifruit. Still, the local calibration models may be ineffective for new batches of samples with biological variability, which limits the commercial application of this technology. Thus, a calibration model was developed using one batch of fruit and the prediction performance was tested with a different batch, which differs in origin and harvest time. Four calibration models were established with Batch 1 kiwifruit to predict SSC, which were based on full spectra (i.e., partial least squares regression (PLSR) model based on full spectra), continuous effective wavelengths (i.e., changeable size moving window-PLSR (CSMW-PLSR) model), and discrete effective wavelengths (i.e., competitive adaptive reweighted sampling-PLSR (CARS-PLSR) model and PLSR-variable importance in projection (PLSR-VIP) model) respectively. The Rv2 values of these four models in the internal validation set were 0.83, 0.92, 0.96, and 0.89, with corresponding RMSEV values of 1.08 %, 0.75 %, 0.56 %, and 0.89 %, and RPDv values of 2.49, 3.61, 4.80, and 3.02, respectively. Clearly, all four PLSR models performed acceptably in the validation set. However, these models performed very poorly in predicting the Batch 2 samples, with their RMSEP values all exceeding 1.5 %. Although the models could not be used to predict exact SSC, they could still interpret the SSC values of Batch 2 kiwifruit to some extent because the predicted SSC values could fit a specific line. To enable the CSMW-PLSR calibration model to predict the SSC of Batch 2 kiwifruit, the robustness of this model was improved by calibration updating and slope/bias correction (SBC). Different numbers of new samples were randomly selected for updating and SBC, and the minimum number of samples for updating and SBC was finally determined to be 30 and 20, respectively. After calibration updating and SBC, the new models had average Rp2, average RMSEP, and average RPDp values of 0.83 and 0.89, 0.69 % and 0.57 %, and 2.45 and 2.97, respectively, in the prediction set. Overall, the methods proposed in this study can effectively address the issue of poor performance of calibration models in predicting new samples with biological variability and make the models more robust, thus providing important guidance for the maintenance of SSC online detection models in practical applications.

Photochemical Reactivity of Humic Substances in an Aquatic System Revealed by Excitation-Emission Matrix Fluorescence.

The photochemical reactivity of humic substances plays a critical role in the global carbon cycle, and influences the toxicity, mobility, and bioavailability of contaminants by altering their molecular structure and the mineralization of organic carbon to CO2. Here, we examined the simulated irradiation process of Chinese standard fulvic acid (FA) and humic acid (HA) by using excitation-emission matrix fluorescence combined with fluorescence regional integration (FRI), parallel factor (PARAFAC) analysis, and kinetic models. Humic-like and fulvic-like materials were the main materials (constituting more than 90%) of both FA and HA, according to the FRI analysis. Four components were identified by the PARAFAC analysis: fulvic-like components composed of both carboxylic-like and phenolic-like chromophores (C1), terrestrial humic-like components primarily composed of carboxylic-like chromophores (C2), microbial humic-like overwhelming composed of phenolic-like fluorophores (C3), and protein-like components (C4). After irradiation for 72 h, the maximum fluorescence intensity (F max) of C1 and C2 of FA was reduced to 36.01-58.34%, while the F max of C3 of both FA and HA also decreased to 0-9.63%. By contrast, for HA, the F max of its C1 and C2 increased to 236.18-294.77% when irradiated for 72 h due to greater aromaticity and photorefractive tendencies. The first-order kinetic model (R 2 = 0.908-0.990) fitted better than zero-order kinetic model (R 2 = 0-0.754) for the C1, C2, and C3, of both FA and HA, during their photochemical reactivity. The photodegradation rate constant (k 1) of C1 had values (0.105 for FA; 0.154 for HA) that surpassed those of C2 (0.059 for FA, 0.079 for HA) and C3 (0.079 for both FA and HA) based on the first-order kinetic model. The half-life times of C1, C2, and C3 ranged from 6.61-11.77 h to 4.50-8.81 h for FA and HA, respectively. Combining an excitation-emission matrix with FRI and PARAFAC analyses is a powerful approach for elucidating changes to humic substances during their irradiation, which is helpful for predicting the environmental toxicity of contaminants in natural ecosystems.

Experimental and modeling study of proton and copper binding properties onto fulvic acid fractions using spectroscopic techniques combined with two-dimensional correlation analysis.

Fulvic acid (FA) significantly influences the bioavailability and fate of heavy metals in environments, while its acid-base characters and metal binding processes are still unclear. Here, spectroscopic techniques combined with multiple models (e.g., NICA-Donnan model) and two-dimensional correlation spectroscopy (2D COS) were applied to explore the proton and copper binding properties of FA sub-fractions (FA3-FA13). The charge densities, average contents of carboxylic and phenolic groups, average dissociation constants pKa1 and pKa2 of sub-fractions ranged 0-16 meq∙g∙C-1, 5.03-9.58 meq∙g∙C-1, 2.52-4.67 meq∙g∙C-1, 4.15-4.33 and 8.52-9.72, respectively. FA sub-fractions had a relatively narrow distribution of carboxyl group and a broad distribution of phenolic group. FA sub-fractions also exhibited roughly two phenolic hydroxyl groups per every 1-3 phenyl rings. Differential absorbance spectra (DAS) derived Gaussian bands were associated to the inter-chromophore interactions, the changes of molecular conformations and functional groups with copper addition. Differential spectra slopes (DSlope275-295&325-375) were more significant with higher copper concentration and copper amounts bonded to carboxylic groups. UV-Vis and fluorescence spectra with 2D heterospectral COS revealed the copper binding heterogeneities and sequential orders of chromophores and fluorophores, quantitatively confirming by the order of conditional stability constants (log KCu: 4.64-5.56). Salicylic-/polyhydroxyphenolic, hydroxyl and amino groups were strongly associated to the basic units for fluorophores. Sequential changes followed the order of humic-like→fulvic-like materials for FA3/FA5, humic-like→fulvic-like→tryptophan-like materials for FA7, and humic-like→tryptophan-like→fulvic-like→tyrosine-like materials for FA9/FA13. Spectroscopic techniques combined with various models (especially for 2D COS) are beneficial to elucidate the binding heterogeneity and sensitivity for metal-organic matters at the functional group level.

Biotransformation and tissue distribution of protopine and allocryptopine and effects of Plume Poppy Total Alkaloid on liver drug-metabolizing enzymes.

In this study, the biotransformation in the plasma, urine and feces of rats following oral administration of protopine (PRO) and allocryptopine (ALL)were explored using HPLC-QqTOF MS. An HPLC-MS/MS method for the determination of tissues was developed and applied to the tissue distribution study in rats following intragastric administration of Plume Poppy Total Alkaloid for 3 weeks. A total of ten PRO metabolites and ten ALL metabolites were characterized in rats in vivo. Among these metabolites, six PRO metabolites and five ALL metabolites were reported for the first time. The predicated metabolic pathways including ring cleavage, demethylation following ring cleavage, and glucuronidation were proposed. The low-concentration residue of PRO and ALL in various tissues was detected at 24 h and 48 h after dosing, which indicated that both compounds could be widely distributed in tissues and exist as low levels of residue. The activities of erythromycin N-demethylase, aminopyrine N-demethylase and NAD (P)H quinone oxidoreductase in female rats can be induced post-dose, but these activities were inhibited in male rats. The proposed biotransformation and residues of PRO and ALL and their effects on enzymes may provide a basis for clarifying the metabolism and interpreting pharmacokinetics.