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The dissolved organic matter (DOM) with high mobility and reactivity plays a crucial role in soil. In this study, the characteristics and phytotoxicity of DOM released from the hydrochars prepared from different feedstocks (cow manure, corn stalk and Myriophyllum aquaticum) under three hydrothermal carbonization (HTC) temperatures (180, 200 and 220°C) were evaluated. The results showed that the hydrochars had high dissolved organic carbon content (20.15 to 37.65 mg/g) and its content showed a gradual reduction as HTC temperature increased. Three fluorescent components including mixed substance of fulvic acid-like and humic acid-like substances (C1, 30.92%-58.32%), UVA humic acid-like substance (C2, 25.27%-29.94%) and protein-like substance (C3, 11.74%-41.92%) were identified in hydrochar DOM by excitation emission matrix spectra coupled with parallel factor analysis. High HTC temperature increased the relative proportion of aromatic substances (C1+C2) and humification degree of hydrochar DOM from cow manure, while it presented adverse effects on the hydrochar DOM from corn stalk and Myriophyllum. aquaticum. The principal component analysis suggested that feedstock type and HTC temperature posed significant effects on the characteristics of hydrochar DOM. Additionally, seed germination test of all hydrochar DOM demonstrated that the root length was reduced by 8.88%-26.43% in contrast with control, and the germination index values were 73.57%-91.12%. These findings provided new insights into the potential environmental effects for hydrochar application in soil.

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Catalytic hydrogenation of CO2 to ethanol is a promising solution to address the greenhouse gas (GHG) emissions, but many current catalysts face efficiency and cost challenges. Cobalt based catalysts are frequently examined due to their abundance, cost-efficiency, and effectiveness in the reaction, where managing the Co0 to Coδ+ ratio is essential. In this study, we adjusted support nature (Al2O3, MgO-MgAl2O4, and MgO) and reduction conditions to optimize this balance of Co0 to Coδ+ sites on the catalyst surface, enhancing ethanol production. The selectivity of ethanol reached 17.9% in a continuous flow fixed bed micro-reactor over 20 mol% Co@MgO-MgAl2O4 (CoMgAl) catalyst at 270 °C and 3.0 MPa, when reduced at 400 °C for 8 h. Characterisation results coupled with activity analysis confirmed that mild reduction condition (400 °C, 10% H2 balance N2, 8 h) with intermediate metal support interaction favoured the generation of partially reduced Co sites (Coδ+ and Co0 sites in single atom) over MgO-MgAl2O4 surface, which promoted ethanol synthesis by coupling of dissociative (CHx*)/non-dissociative (CHxO*) intermediates, as confirmed by density functional theory analysis. Additionally, the CoMgAl, affordably prepared through the coprecipitation method, offers a potential alternative for CO2 hydrogenation to yield valuable chemicals.

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The rapid detection of fertilizer nutrient information is a crucial element in enabling intelligent and precise variable fertilizer application. However, traditional detection methods possess limitations, such as the difficulty in quantifying multiple components and cross-contamination. In this study, a rapid detection method was proposed, leveraging Raman spectroscopy combined with machine learning, to identify five types of fertilizers: K2SO4, (CO(NH2)2, KH2PO4, KNO3, and N:P:K (15-15-15), along with their concentrations. Qualitative and quantitative models of fertilizers were constructed using three machine learning algorithms combined with five spectral preprocessing methods. Two variable selection methods were used to optimize the quantitative model. The results showed that the classification accuracy of the five fertilizer solutions obtained by random forest (RF) was 100 %. Moreover, in terms of regression, partial least squares regression (PLSR) outperformed extreme learning machine (ELM) and least squares support vector machine (LSSVM), yielding prediction Rp2 within the range of 0.9843-0.9990 and a root mean square error in the range of 0.0486-0.1691. In addition, this study evaluated the impact of different water types (deionized water, well water, and industrial transition water) on the detection of fertilizer information via Raman spectroscopy. The results showed that while different water types did not notably affect the identification of fertilizer nutrients, they did exert a pronounced effect on the quantification of concentrations. This study highlights the efficacy of combining Raman spectroscopy with machine learning in detecting fertilizer nutrients and their concentration information effectively.

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This study comprehensively investigated the effects of high-temperature cooking (HT), complex enzyme hydrolysis (CE), and high-temperature cooking combined enzymatic hydrolysis (HE) on the chemical composition, microstructure, and functional attributes of soluble dietary fiber (SDF) extracted from corn bran. The results demonstrated that HE-SDF yielded the highest output at 13.80 ± 0.20 g/100 g, with enhancements in thermal stability, viscosity, hydration properties, adsorption capacity, and antioxidant activity. Cluster analysis revealed three distinct categories of SDF's physicochemical properties. Principal component analysis (PCA) confirmed the superior functional properties of HE-SDF. Correlation analysis showed positive relationships between the monosaccharide composition, purity, and viscosity of SDF and most of its functional attributes, whereas particle size and zeta potential were inversely correlated. Furthermore, a highly significant positive correlation was observed between crystallinity and thermal properties. These findings suggest that the HE method constitutes a viable strategy for enhancing the quality of SDF sourced from corn bran.

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Over a decade has passed since the development of the Hi-C method for genome-wide analysis of 3D genome organization. Hi-C utilizes next-generation sequencing (NGS) technology to generate large-scale chromatin interaction data, which has accumulated across a diverse range of species and cell types, particularly in eukaryotes. There is thus a growing need to streamline the process of Hi-C data analysis to utilize these data sets effectively. Hi-C generates data that are much larger compared to other NGS techniques such as chromatin immunoprecipitation sequencing (ChIP-seq) or RNA-seq, making the data reanalysis process computationally expensive. In an effort to bridge this resource gap, the 4D Nucleome (4DN) Data Portal has reanalyzed approximately 600 Hi-C data sets, allowing users to access and utilize the analyzed data. In this chapter, we provide detailed instructions for the implementation of the common workflow language (CWL)-based Hi-C analysis pipeline adopted by the 4DN Data Portal ecosystem. This reproducible and portable pipeline generates standard Hi-C contact matrices in formats such as .hic or .mcool from FASTQ files. It enables users to output their own Hi-C data in the same format as those registered in the 4DN Data portal, facilitating comparative analysis using data registered in the portal. Our custom-made scripts are available on GitHub at https://github.com/kuzobuta/4dn_cwl_pipeline .

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Hexavalent chromium (CrVI) poses a serious risk to both human and environment health. Hence, a simple, robust, and efficient analytical method must be developed to monitor the presence of Cr(VI) in the environment. The current investigation concentrated on the colorimetric detection of Cr(VI) using TMB as indicator in the presence of H2O2. The study found that Cr(VI) reacts with H2O2 to generate hydroxyl radicals which oxidize TMB in a concentration dependent manner. Under optimized conditions, the method obtained a good linearity range (0.025-0.5 mg/L, r2 = 0.9944) with LOD and LOQ of 0.009 mg/L and 0.029 mg/L, respectively. The technique was further improved by the addition of EDTA in the sample preparation protocol to reduce the false positive result by the presence of ions like Cu2+, Fe3+, etc. The study recorded improved Cr(VI) recoveries (81.73-111.40 %) at different fortification levels (0.1-0.5 mg/L). Under optimized conditions, the EDTA added method obtained a good linear response (r2 = 0.9952) with a detection limit of 0.023 mg/L which is less than the prescribed limits by WHO (0.05 mg/L) and US EPA (0.1 mg/L) for drinking water. The developed analytical method is very simple without use of any nanomaterial and the results with natural water samples show that it has the potential for real-time detection of Cr(VI) in the environment.

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Curcumae Radix (CR) is a widely used traditional Chinese medicine with significant pharmaceutical importance, including enhancing blood circulation and addressing blood stasis. This study aims to establish an integrated and rapid quality assessment method for CR from various botanical origins, based on chemical components, antiplatelet aggregation effects, and Fourier transform near-infrared (FT-NIR) spectroscopy combined with multivariate algorithms. Firstly, ultra-performance liquid chromatography-photodiode array (UPLC-PDA) combined with chemometric analyses was used to examine variations in the chemical profiles of CR. Secondly, the activation effect on blood circulation of CR was assessed using an in vitro antiplatelet aggregation assay. The studies revealed significant variations in chemical profiles and antiplatelet aggregation effects among CR samples from different botanical origins, with constituents such as germacrone, ß-elemene, bisdemethoxycurcumin, demethoxycurcumin, and curcumin showing a positive correlation with antiplatelet aggregation biopotency. Thirdly, FT-NIR spectroscopy was integrated with various machine learning algorithms, including Artificial Neural Network (ANN), K-Nearest Neighbors (KNN), Logistic Regression (LR), Support Vector Machine (SVM), and Subspace K-Nearest Neighbors (Subspace KNN), to classify CR samples from four distinct sources. The result showed that FT-NIR combined with KNN and SVM classification algorithms after SNV and MSC preprocessing successfully distinguished CR samples from four plant sources with an accuracy of 100%. Finally, Quantitative models for active constituents and antiplatelet aggregation bioactivity were developed by optimizing the partial least squares (PLS) model with interval combination optimization (ICO) and competitive adaptive reweighted sampling (CARS) techniques. The CARS-PLS model achieved the best predictive performance across all five components. The coefficient of determination (R2p) and root mean square error (RMSEP) in the independent test sets were 0.9708 and 0.2098, 0.8744 and 0.2065, 0.9511 and 0.0034, 0.9803 and 0.0066, 0.9567 and 0.0172 for germacrone, ß-elemene, bisdemethoxycurcumin, demethoxycurcumin and curcumin, respectively. The ICO-PLS model demonstrated superior predictive capabilities for antiplatelet aggregation biotency, achieving an R2p of 0.9010, and an RMSEP of 0.5370. This study provides a valuable reference for the quality evaluation of CR in a more rapid and comprehensive manner.

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DNA meiotic recombinase 1 (disrupted meiotic cDNA, Dmc1) protein is homologous to the Escherichia coli RecA protein, was first identified in Saccharomyces cerevisiae. This gene has been well studied as an essential role in meiosis in many species. However, studies on the dmc1 gene in reptiles are limited. In this study, a cDNA fragment of 1,111 bp was obtained from the gonadal tissues of the Chinese soft-shell turtle via RT-PCR, containing a 60 bp 3' UTR, a 22 bp 5' UTR, and an ORF of 1,029 bp encoding 342 amino acids, named Psdmc1. Multiple sequence alignments showed that the deduced protein has high similarity (>95 %) to tetrapod Dmc1 proteins, while being slightly lower (86-88 %) to fish species.Phylogenetic tree analysis showed that PsDmc1 was clustered with the other turtles' Dmc1 and close to the reptiles', but far away from the teleost's. RT-PCR and RT-qPCR analyses showed that the Psdmc1 gene was specifically expressed in the gonads, and much higher in testis than the ovary, especially highest in one year-old testis. In situ hybridization results showed that the Psdmc1 was mainly expressed in the perinuclear cytoplasm of primary and secondary spermatocytes, weakly in spermatogonia of the testes. These results indicated that dmc1 would be majorly involved in the developing testis, and play an essential role in the germ cells' meiosis. The findings of this study will provide a basis for further investigations on the mechanisms behind the germ cells' development and differentiation in Chinese soft-shell turtles, even in the reptiles.

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BACKGROUND: Although progress has been made in accurate diagnosis and targeted treatments, breast cancer (BC) patients with metastasis still present a grim prognosis. With the continuous emergence and development of new personalized and precision medicine targeting specific tumor biomarkers, there is an urgent need to find new metastatic and prognostic biomarkers for BC patients. METHODS: We were dedicated to identifying genes linked to metastasis and prognosis in breast cancer through a combination of in silico analysis and experimental validation. RESULTS: A total of 25 overlap differentially expressed genes were identified. Ten hub genes (namely MRPL13, CTR9, TCEB1, RPLP0, TIMM8B, METTL1, GOLT1B, PLK2, PARL and MANBA) were identified and confirmed. MRPL13, TCEB1 and GOLT1B were shown to be associated with the worse overall survival (OS) and were optionally chosen for further verification by western blot. Only MRPL13 was found associated with cell invasion, and the expression of MRPL13 in metastatic BC was significantly higher than in primary BC. CONCLUSION: We proposed MRPL13 could be a potential novel biomarker for the metastasis and prognosis of breast cancer.

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The development of biosensing electronics for real-time sweat analysis has attracted increasing research interest due to their promising applications for non-invasive health monitoring. However, one of the critical challenges lies in the sebum interference that largely limits the sensing reliability in practical scenarios. Herein, we report a flexible epidermal secretion-purified biosensing patch with a hydrogel filtering membrane that can effectively eliminate the impact of sebum and sebum-soluble substances. The as-prepared sebum filtering membranes feature a dual-layer sebum-resistant structure based on the poly(hydroxyethyl methacrylate) hydrogel functionalized with nano-brush structured poly(sulfobetaine) to eliminate interferences and provide self-cleaning capability. Furthermore, the unidirectional flow microfluidic channels design based on the Tesla valve was incorporated into the biosensing patch to prevent external sebum contamination and allow effective sweat refreshing for reliable sensing. By seamlessly combining these components, the epidermal secretion-purified biosensing patch enables continuous monitoring of sweat uric acid, pH, and sodium ions with significantly improved accuracy of up to 12 %. The proposed strategy for enhanced sweat sensing reliability without sebum interference shows desirable compatibility for different types of biosensors and would inspire the advances of flexible and wearable devices for non-invasive healthcare.

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Purpose: We aimed to perform a meta-analysis with the intention of evaluating the reliability and test accuracy of the aMAP risk score in the identification of HCC. Methods: A systematic search was performed in PubMed, Scopus, Cochrane, Embase, and Web of Science databases from inception to September 2023, to identify studies measuring the aMAP score in patients for the purpose of predicting the occurrence or recurrence of HCC. The meta-analysis was performed using the meta package in R version 4.1.0. The diagnostic accuracy meta-analysis was conducted using Meta-DiSc software. Results: Thirty-five studies 102,959 participants were included in the review. The aMAP score was significantly higher in the HCC group than in the non-HCC group, with a mean difference of 6.15. When the aMAP score is at 50, the pooled sensitivity, specificity, negative likelihood ratio, and positive likelihood ratio with 95% CI was 0.961 (95% CI 0.936, 0.976), 0.344 (95% CI 0.227, 0.483), 0.114 (95% CI 0.087, 0.15), and 1.464 (95% CI 1.22, 1.756), respectively. At a cutoff value of 60, the pooled sensitivity, specificity, negative likelihood ratio, and positive likelihood ratio with 95% CI was 0.594 (95% CI 0.492, 0.689), 0.816 (95% CI 0.714, 0.888), 0.497 (95% CI 0.418, 0.591), and 3.235 (95% CI 2.284, 4.582), respectively. Conclusion: The aMAP score is a reliable, accurate, and easy-to-use tool for predicting HCC patients of all stages, including early-stage HCC. Therefore, the aMAP score can be a valuable tool for surveillance of HCC patients and can help to improve early detection and reduce mortality.

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Background: The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as non-alcoholic fatty liver disease, is increasing globally. Noninvasive methods, such as bioelectrical impedance analysis (BIA), which measures body composition, including visceral fat, are gaining interest in evaluating MASLD patients. Our study aimed to identify factors associated with significant liver fibrosis, compare noninvasive scores, and highlight the importance of visceral fat measurement using BIA. Methods: MASLD patients seen in our out-patient department underwent comprehensive evaluations, including liver stiffness using transient elastography, body composition analysis using BIA, and metabolic measurements. Significant fibrosis was defined as a liver stiffness measurement of ≥8.2 kPa. Using multivariate analysis, we identified factors associated with significant liver fibrosis and compared four noninvasive scores with a novel diabetes-visceral fat 15 (DVF15) score. Results: We analyzed data from 609 MASLD patients seen between February 2022 and March 2023. The median age was 43 years (81% male). Among these, 78 (13%) had significant fibrosis. Patients with significant fibrosis had higher rates of type 2 diabetes (41% vs 21%, P < 0.001) and elevated levels of aspartate aminotransferase, alanine aminotransferase, hemoglobin A1c, Fibosis-4, aspartate-aminotransferase-to platelet-ratio index, and NAFLD fibrosis scores. They also exhibited higher visceral and subcutaneous fat. Binary logistic regression revealed type 2 diabetes and a visceral fat level of >15% as associated with significant liver fibrosis. Additionally, the DVF15 score, combining these factors, showed a modest area under the receiver operating characteristic curve of 0.664 (P < 0.001). Conclusion: Our study identified diabetes and high visceral fat as factors associated with significant liver fibrosis in MASLD patients. We recommend that visceral fat measurement using BIA be an essential part of MASLD evaluation. The presence of either diabetes or a visceral fat level of >15% should prompt clinicians to check for significant fibrosis in MASLD patients. Further research is warranted to validate our findings and evaluate the utility of the DVF15 score in larger cohorts and diverse populations.

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Background: The incidence of hepatitis A virus (HAV) infection is on the rise, with a minority of patients at risk for poor outcomes. This study investigates the prognostic impacts of race and gender on hospital outcomes among admitted HAV-infected patients. Methods: Using the National Inpatient Sample from 2012 to 2017, patients admitted with HAV were selected and stratified by gender (male and female) and race (White, Black, Hispanic, Asian-Pacific Islander, Other). Propensity score-matching and statistical analysis were implemented with comparison to the controls ("Female" and "White"). Primary endpoints included mortality, length of stay (LOS), and hospitalization costs, while secondary endpoints consisted of hepatic-related medical complications such as ascites, hepatic encephalopathy, varices, and acute liver failure. Results: Females with compensated cirrhosis had increased odds of mortality (aOR 2.59, 95% CI: 1.14-5.91, P = 0.02). Otherwise, no other differences in mortality were detected between genders and races. Females had a shorter hospital LOS (aOR 0.97, 95% CI: 0.96-0.98, P < 0.001), lower adjusted cost ($12,241 vs. $13,510, aOR 0.92, 95% CI: 0.92-0.92, P < 0.001), lower odds of esophageal varices (aOR 0.74, 95% CI: 0.57-0.97, P = 0.03) and hepatic encephalopathy (aOR 0.67, 95% CI: 0.53-0.84, P < 0.001) compared to males. Black patients exhibited higher LOS (aOR 1.06, 95% CI: 1.04-1.08, P < 0.001) and adjusted costs ($13,392 vs $12,592, aOR 1.02, 95% CI: 1.02-1.03, P < 0.001). Hispanic patients exhibited higher rates of esophageal varices (aOR 2.19, 95% CI: 1.28-3.76, P = 0.005) and adjusted costs ($14,202 vs. $12,381, aOR 1.07, 95% CI: 1.07-1.07, P < 0.001), and Asian patients experienced higher adjusted costs ($18,426 vs. $13,137, aOR 1.10, 95% CI: 1.10-1.10, P < 0.001) compared to White patients. Conclusion: Various nuanced impacts of gender and race on hospitalization outcomes in HAV infection were observed, with only one subgroup analysis demonstrating a higher rate of mortality. Further research is warranted to better understand these findings and their implications.

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4-Nitrophenol (4-NP), as a toxic and refractory pollutant, has generated significant concern due to its adverse effects. However, the potential toxic effects and mechanism remained unclear. In this study, the reproduction, development, locomotion and reactive oxygen species (ROS) production of Caenorhabditis elegans were investigated to evaluate the 4-NP toxicity. We used metabolomics to assess the potential damage mechanisms. The role of metabolites in mediating the relationship between 4-NP and phenotypes was examined by correlation and mediation analysis. 4-NP (8 ng/L and 8 µg/L) caused significant reduction of brood size, ovulation rate, total germ cells numbers, head thrashes and body bends, and an increase in ROS. However, the oosperm numbers in uterus, body length and body width were decreased in 8 µg/L. Moreover, 36 differential metabolites were enriched in the significant metabolic pathways, including lysine biosynthesis, ß-alanine metabolism, tryptophan metabolism, pentose phosphate pathway, pentose and glucuronate interconversions, amino sugar and nucleotide sugar metabolism, starch and sucrose metabolism, galactose metabolism, propanoate metabolism, glycerolipid metabolism, and estrogen signaling pathway. The mechanism of 4-NP toxicity was that oxidative stress caused by the perturbation of amino acid, which had effects on energy metabolism through disturbing carbohydrate and lipid metabolism, and finally affected the estrogen signaling pathway to exert toxic effects. Moreover, correlation and mediation analysis showed glycerol-3P, glucosamine-6P, glucosamine-1P, UDP-galactose, L-aspartic acid, and uracil were potential markers for the reproduction and glucose-1,6P2 for developmental toxicity. The results provided insight into the pathways involved in the toxic effects caused by 4-NP and developed potential biomarkers to evaluate 4-NP toxicity.

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Secondary iron-sulfate minerals such as jarosite, which are easily formed in acid mine drainage, play an important role in controlling metal mobility. In this work, the typical iron-oxidizing bacterium Acidithiobacillus ferrooxidans ATCC 23270 was selected to synthesize jarosite in the presence of antimony ions, during which the solution behavior, synthetic product composition, and bacterial metabolism were studied. The results show that in the presence of Sb(V), Fe2+ was rapidly oxidized to Fe3+ by A. ferrooxidans and Sb(V) had no obvious effect on the biooxidation of Fe2+ under the current experimental conditions. The presence of Sb(III) inhibited bacterial growth and Fe2+ oxidation. For the group with Sb(III), products with amorphous phases were formed 72 hr later, which were mainly ferrous sulfate and pentavalent antimony oxide, and the amorphous precursor was finally transformed into a more stable crystal phase. For the group with Sb(V), the morphology and structure of jarosite were changed in comparison with those without Sb. The biomineralization process was accompanied by the removal of 94% Sb(V) to form jarosite containing the Fe-Sb-O complex. Comparative transcriptome analysis shows differential effects of Sb(III) and Sb(V) on bacterial metabolism. The expression levels of functional genes related to cell components were much more downregulated for the group with Sb(III) but much more regulated for that with Sb(V). Notably, cytochrome c and nitrogen fixation-relevant genes for the A.f_Fe2+_Sb(III) group were enhanced significantly, indicating their role in Sb(III) resistance. This study is of great value for the development of antimony pollution control and remediation technology.

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To better understand the migration behavior of plastic fragments in the environment, development of rapid non-destructive methods for in-situ identification and characterization of plastic fragments is necessary. However, most of the studies had focused only on colored plastic fragments, ignoring colorless plastic fragments and the effects of different environmental media (backgrounds), thus underestimating their abundance. To address this issue, the present study used near-infrared spectroscopy to compare the identification of colored and colorless plastic fragments based on partial least squares-discriminant analysis (PLS-DA), extreme gradient boost, support vector machine and random forest classifier. The effects of polymer color, type, thickness, and background on the plastic fragments classification were evaluated. PLS-DA presented the best and most stable outcome, with higher robustness and lower misclassification rate. All models frequently misinterpreted colorless plastic fragments and its background when the fragment thickness was less than 0.1mm. A two-stage modeling method, which first distinguishes the plastic types and then identifies colorless plastic fragments that had been misclassified as background, was proposed. The method presented an accuracy higher than 99% in different backgrounds. In summary, this study developed a novel method for rapid and synchronous identification of colored and colorless plastic fragments under complex environmental backgrounds.

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Background and Aim: Endoscopic ultrasound shear wave elastography (EUS-SWE) can facilitate an objective evaluation of pancreatic fibrosis. Although it is primarily applied in evaluating chronic pancreatitis, its efficacy in assessing early chronic pancreatitis (ECP) remains underinvestigated. This study evaluated the diagnostic accuracy of EUS-SWE for assessing ECP diagnosed using the Japanese diagnostic criteria 2019. Methods: In total, 657 patients underwent EUS-SWE. Propensity score matching was used, and the participants were classified into the ECP and normal groups. ECP was diagnosed using the Japanese diagnostic criteria 2019. Pancreatic stiffness was assessed based on velocity (Vs) on EUS-SWE, and the optimal Vs cutoff value for ECP diagnosis was determined. A practical shear wave Vs value of ≥50% was considered significant. Results: Each group included 22 patients. The ECP group had higher pancreatic stiffness than the normal group (2.31 ± 0.67 m/s vs. 1.59 ± 0.40 m/s, p < 0.001). The Vs cutoff value for the diagnostic accuracy of ECP, as determined using the receiver operating characteristic curve, was 2.24m/s, with an area under the curve of 0.82 (95% confidence interval: 0.69-0.94). A high Vs was strongly correlated with the number of EUS findings (rs = 0.626, p < 0.001). Multiple regression analysis revealed that a history of acute pancreatitis and ≥2 EUS findings were independent predictors of a high Vs. Conclusions: There is a strong correlation between EUS-SWE findings and the Japanese diagnostic criteria 2019 for ECP. Hence, EUS-SWE can be an objective and invaluable diagnostic tool for ECP diagnosis.

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Significance: Standardization of fluorescence molecular imaging (FMI) is critical for ensuring quality control in guiding surgical procedures. To accurately evaluate system performance, two metrics, the signal-to-noise ratio (SNR) and contrast, are widely employed. However, there is currently no consensus on how these metrics can be computed. Aim: We aim to examine the impact of SNR and contrast definitions on the performance assessment of FMI systems. Approach: We quantified the SNR and contrast of six near-infrared FMI systems by imaging a multi-parametric phantom. Based on approaches commonly used in the literature, we quantified seven SNRs and four contrast values considering different background regions and/or formulas. Then, we calculated benchmarking (BM) scores and respective rank values for each system. Results: We show that the performance assessment of an FMI system changes depending on the background locations and the applied quantification method. For a single system, the different metrics can vary up to ∼ 35 dB (SNR), ∼ 8.65 a . u . (contrast), and ∼ 0.67 a . u . (BM score). Conclusions: The definition of precise guidelines for FMI performance assessment is imperative to ensure successful clinical translation of the technology. Such guidelines can also enable quality control for the already clinically approved indocyanine green-based fluorescence image-guided surgery.

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The functional properties of biofilms are intimately related to their spatial architecture. Structural data are therefore of prime importance to dissect the complex social and survival strategies of biofilms and ultimately to improve their control. Confocal laser scanning microscopy (CLSM) is the most widespread microscopic tool to decipher biofilm structure, enabling noninvasive three-dimensional investigation of their dynamics down to the single-cell scale. The emergence of fully automated high content screening (HCS) systems, associated with large-scale image analysis, has radically amplified the flow of available biofilm structural data. In this contribution, we present a HCS-CLSM protocol used to analyze biofilm four-dimensional structural dynamics at high throughput. Meta-analysis of the quantitative variables extracted from HCS-CLSM will contribute to a better biological understanding of biofilm traits.

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Metabolomics is the study of low molecular weight biochemical molecules (typically <1500 Da) in a defined biological organism or system. In case of food systems, the term "food metabolomics" is often used. Food metabolomics has been widely explored and applied in various fields including food analysis, food intake, food traceability, and food safety. Food safety applications focusing on the identification of pathogen-specific biomarkers have been promising. This chapter describes a nontargeted metabolite profiling workflow using gas chromatography coupled with mass spectrometry (GC-MS) for characterizing three globally important foodborne pathogens, Escherichia coli O157:H7, Listeria monocytogenes, and Salmonella enterica, from selective enrichment liquid culture media. The workflow involves a detailed description of food spiking experiments followed by procedures for the extraction of polar metabolites from media, the analysis of the extracts using GC-MS, and finally chemometric data analysis using univariate and multivariate statistical tools to identify potential pathogen-specific biomarkers.

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