A generalizable and easy-to-use COVID-19 stratification model for the next pandemic via immune-phenotyping and machine learning.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has affected billions of people worldwide, and the lessons learned need to be concluded to get better prepared for the next pandemic. Early identification of high-risk patients is important for appropriate treatment and distribution of medical resources. A generalizable and easy-to-use COVID-19 severity stratification model is vital and may provide references for clinicians. Methods: Three COVID-19 cohorts (one discovery cohort and two validation cohorts) were included. Longitudinal peripheral blood mononuclear cells were collected from the discovery cohort (n = 39, mild = 15, critical = 24). The immune characteristics of COVID-19 and critical COVID-19 were analyzed by comparison with those of healthy volunteers (n = 16) and patients with mild COVID-19 using mass cytometry by time of flight (CyTOF). Subsequently, machine learning models were developed based on immune signatures and the most valuable laboratory parameters that performed well in distinguishing mild from critical cases. Finally, single-cell RNA sequencing data from a published study (n = 43) and electronic health records from a prospective cohort study (n = 840) were used to verify the role of crucial clinical laboratory and immune signature parameters in the stratification of COVID-19 severity. Results: Patients with COVID-19 were determined with disturbed glucose and tryptophan metabolism in two major innate immune clusters. Critical patients were further characterized by significant depletion of classical dendritic cells (cDCs), regulatory T cells (Tregs), and CD4+ central memory T cells (Tcm), along with increased systemic interleukin-6 (IL-6), interleukin-12 (IL-12), and lactate dehydrogenase (LDH). The machine learning models based on the level of cDCs and LDH showed great potential for predicting critical cases. The model performances in severity stratification were validated in two cohorts (AUC = 0.77 and 0.88, respectively) infected with different strains in different periods. The reference limits of cDCs and LDH as biomarkers for predicting critical COVID-19 were 1.2% and 270.5 U/L, respectively. Conclusion: Overall, we developed and validated a generalizable and easy-to-use COVID-19 severity stratification model using machine learning algorithms. The level of cDCs and LDH will assist clinicians in making quick decisions during future pandemics.

Pan-cancer analysis of ARFs family and ARF5 promoted the progression of hepatocellular carcinoma.

Background: ARF family proteins are a kind of small GTPases, which are involved in regulating a variety of basic functions of cells. In recent years, the role and molecular regulatory mechanisms of ARFs in tumor progression have received increasing attention, and research reports on most of their family members are increasing. However, research on the clinical and pathological relevance of ARF5 in cancer, especially in hepatocellular carcinoma, still needs to be improved. Methods: RNA-seq data in the Cancer Genome Atlas (TCGA) and genome tissue expression (GTEx) databases were used to analyze the expression and pathological data of ARFs family in Pan-cancer. Kaplan-Meier and Cox regression were used for prognostic analysis of ARF5 and Pan-cancer. Combined with ImmuCellAI database and TIMER2 database, the relationship between ARF5 expression and immune cell tumor infiltration in hepatocellular carcinoma (HCC) was analyzed. WGCNA is used to construct the co-expression gene network related to ARF5 expression in HCC and screen important modules and central genes. GO and KEGG path enrichment analysis were carried out for the genes in the modules with clinical significance. GSEA analysis was performed to take into account the role of genes with small differences. Finally, ceRNA network analysis was used to explore the molecular mechanism of miRNAs and lncRNAs regulating ARF5 expression. Results: ARFs family (ARF1, ARF3, ARF4, ARF5, ARF6) are generally highly expressed in Pan-cancer. ARF5 is significantly highly expressed in 29 cancers, and the high expression of ARF5 in HCC patients is significantly negatively correlated with OS, DFI, PFI and DSS, which may lead to cancer deterioration by participating in tumor immune infiltration of HCC. Through WGCNA analysis, the expression of ARF5 in HCC may be involved in many cellular processes that consume a lot of energy, such as ribosome formation, RNA and protein synthesis and lipids, as well as COVID-19, nonalcoholic fatty liver, neurodegenerative diseases and other disease pathways. Conclusion: ARFs, especially ARF5, are overexpressed in many human tumors. This study shows for the first time that ARF5 is significantly correlated with the poor prognosis of HCC patients, which may play a role as an oncogene, suggesting that ARF5 has the potential as a biomarker for the diagnosis and treatment of HCC.

Optimized adaptation algorithms for low-complexity adaptive equalizers.

In order to address the high-power consummation issue of conventional multi-input and multi-output (MIMO) adaptive equalizer (AEQ) for short-reach coherent transmissions, several state-of-the-art low-complexity AEQs have been proposed. In our work, optimized adaptation algorithms for low-complexity real-valued (RV) AEQs with different structures are analyzed. Moreover, an approach to avoid introducing additional computational complexity due to the optimized adaptation process is presented here. The advantages of proposed optimized adaptation algorithms are experimentally demonstrated in a 25 Gbaud dual-polarization 16-quadrature-amplitude-modulation (DP-16QAM) back-to-back (BtB) intradyne system with an overall bandwidth of 14 GHz. Experimental results show that a similar performance as the conventional AEQ could be achieved by using proposed adaptation algorithms and reducing the number of multiplications with up to ∼65%.

Comprehensive assessment of copper's effect on marine organisms under ocean acidification and warming in the 21st century.

Copper (Cu) has sparked widespread global concern as one of the most hazardous metals to aquatic animals. Ocean acidification (OA) and warming (OW) are expected to alter copper's bioavailability based on pH and temperature-sensitive effects; research on their effects on copper on marine organisms is still in its infancy. Therefore, under representative concentration pathways (RCP) 2.6, 4.5, and 8.5, we used the multiple linear regression-water quality criteria (MLR-WQC) method to assess the effects of OA and OW on the ecological risk posed by copper in the Ocean of East China (OEC), which includes the Bohai Sea, Yellow Sea, and East China Sea. The results showed that there was a positive correlation between temperature and copper toxicity, while there was a negative correlation between pH and copper toxicity. The short-term water quality criteria (WQC) values were 1.53, 1.41, 1.30 and 1.13 µg·L-1, while the long-term WQC values were 0.58, 0.48, 0.40 and 0.29 µg·L-1 for 2020, 2099-RCP2.6, 2099-RCP4.5 and 2099-RCP8.5, respectively. Cu in the OEC poses a moderate ecological risk. Under the current copper exposure situation, strict intervention (RCP2.6) only increases the ecological risk of copper exposure by 20 %, and no intervention (RCP8.5) will increase the ecological risk of copper exposure by nearly double. The results indicate that intervention on carbon emissions can slow down the rate at which OA and OW worsen the damage copper poses to marine creatures. This study can provide valuable information for a comprehensive understanding of the combined impacts of climate change and copper on marine organisms.

High-Throughput µPAD with Cascade Signal Amplification through Dual Enzymes for arsM in Paddy Soil.

The arsM gene is a critical biomarker for the potential risk of arsenic exposure in paddy soil. However, on-site screening of arsM is limited by the lack of high-throughput point-of-use (POU) methods. Here, a multiplex CRISPR/Cas12a microfluidic paper-based analytical device (µPAD) was constructed for the high-throughput POU analysis of arsM, with cascade amplification driven by coupling crRNA-enhanced Cas12a and horseradish peroxidase (HRP)-modified probes. First, seven crRNAs were designed to recognize arsM, and their LODs and background signal intensities were evaluated. Next, a step-by-step iterative approach was utilized to develop and optimize coupling systems, which improved the sensitivity 32 times and eliminated background signal interference. Then, ssDNA reporters modified with HRP were introduced to further lower the LOD to 16 fM, and the assay results were visible to the naked eye. A multiplex channel microfluidic paper-based chip was developed for the reaction integration and simultaneous detection of 32 samples and generated a recovery rate between 87.70 and 114.05%, simplifying the pretreatment procedures and achieving high-throughput POU analysis. Finally, arsM in Wanshan paddy soil was screened on site, and the arsM abundance ranged from 1.05 × 106 to 6.49 × 107 copies/g; this result was not affected by the environmental indicators detected in the study. Thus, a coupling crRNA-based cascade amplification method for analyzing arsM was constructed, and a microfluidic device was developed that contains many more channels than previous paper chips, greatly improving the analytical performance in paddy soil samples and providing a promising tool for the on-site screening of arsM at large scales.

Incidence, severity, and risk factors of hemorrhagic complications of epilepsy surgery after 2026 craniotomies from 2003 to 2019: a single center experience.

BACKGROUND: Surgery is effective in the treatment of epilepsy, particularly focal epilepsy. The aim of this work was to report the incidence and grade of severity of hemorrhagic complications after cranial epilepsy surgery, and investigate the risk factors. METHODS: Patients who underwent epilepsy surgery via craniotomy between October 2003 and April 2019 were retrospectively analyzed. The incidence of hemorrhagic complications occurring in a 3-month period after cranial surgery was recorded. Other outcomes included the grade of hemorrhagic severity and risk factors. RESULTS: During the inclusion period, 2026 surgical procedures were performed. Sixty-six hemorrhagic complications were recorded. The total incidence of hemorrhagic complications after cranial epilepsy surgery was 3.3%. The most common type of hemorrhagic complications was epidural hemorrhage (57.6%), followed by intraparenchymal hemorrhage (33.3%). Forty-five patients (68.2%) had grade I complications, 4(6.1%) grade II, 16(24.2%) grade III, and 1(1.5%) grade IV. The mortality due to hemorrhagic complications was 1.5% (1/66) and hemorrhagic mortality among all cranial surgery was 0.5‰ (1/2026). Left craniotomy induced a higher percentage of severe hemorrhage than the right (34.2% vs. 14.3%). Extratemporal lobe epilepsy induced a higher percentage of severe hemorrhage than other epilepsy type (34.2% vs. 14.3%). However, no statistically significant difference was observed between these two factors (p=0.067). CONCLUSIONS: Hemorrhagic complications were uncommon after open surgery for epilepsy. Most hemorrhagic complications were mild while the severe were rare. Patients with hemorrhagic complications had a good prognosis after effective treatment.

Fabrication of the Rapid Self-Assembly Hydrogels Loaded with Luteolin: Their Structural Characteristics and Protection Effect on Ulcerative Colitis.

Luteolin (LUT) is a fat-soluble flavonoid known for its strong antioxidant and anti-inflammatory properties. Nonetheless, its use in the food industry has been limited due to its low water solubility and bioavailability. In this study, hyaluronic acid, histidine, and luteolin were self-assembled to construct tubular network hydrogels (HHL) to improve the gastrointestinal stability, bioavailability, and stimulation response of LUT. As anticipated, the HHL hydrogel's mechanical strength and adhesion allow it to withstand the challenging gastrointestinal environment and effectively extend the duration of drug presence in the body. In vivo anti-inflammatory experiments showed that HHL hydrogel could successfully alleviate colitis induced by dextran sulfate sodium (DSS) in mice by reducing intestinal inflammation and restoring the integrity of the intestinal barrier. Moreover, HHL hydrogel also regulated the intestinal microorganisms of mice and promoted the production of short-chain fatty acids. The HHL hydrogel group demonstrated a notably superior treatment effect compared to the LUT group alone. The hydrogel delivery system is a novel method to improve the absorption of LUT, increasing its bioavailability and enhancing its pharmaceutical effects.

Functional Redundant Microbiome Enhanced Anaerobic Digestion Efficiency under Ammonium Inhibition Conditions.

Revealing the role of functional redundancy is of great importance considering its key role in maintaining the stability of microbial ecosystems in response to various disturbances. However, experimental evidence on this point is still lacking due to the difficulty in "manipulating" and depicting the degree of redundancy. In this study, manipulative experiments of functional redundancy were conducted by adopting the mixed inoculation strategy to evaluate its role in engineered anaerobic digestion systems under ammonium inhibition conditions. The results indicated that the functional redundancy gradient was successfully constructed and confirmed by evidence from pathway levels. All mixed inoculation groups exhibited higher methane production regardless of the ammonium level, indicating that functional redundancy is crucial in maintaining the system's efficiency. Further analysis of the metagenome-assembled genomes within different functional guilds revealed that the extent of redundancy decreased along the direction of the anaerobic digestion flow, and the role of functional redundancy appeared to be related to the stress level. The study also found that microbial diversity of key functional populations might play a more important role than their abundance on the system's performance under stress. The findings provide direct evidence and highlight the critical role of functional redundancy in enhancing the efficiency and stability of anaerobic digestion.

Sesquiterpenoids and steroids from Eupatorium fortunei and their inhibitory effects on NO production.

Two heterodimers including a clovane-phenylpropanoid hybrid (1) and a clovane-menthane hybrid (2), five linear sesquiterpenoids incorporating a tetrahydrofuran ring (3-6 & 8), and four steroids (7 & 9-11), were separated from the ethanolic extract of a well-known aromatic and medicinal herb Eupatorium fortunei. Their structures were characterised by detailed analyses of spectroscopic data and comparison with known analogues, with seven (1-7) of them being described for the first time. The hybrids 1 and 2 represent the first examples of clovane type sesquiterpenoids hybridising with other class of natural products, and compounds 3-6 and 8 are first linear sesquiterpenyl constituents reported from the title species. All the isolates were evaluated for their inhibitory effect on the NO production induced by LPS in murine RAW264.7 macrophage cells, and 1, 7, 10 and 11 exhibited moderate activity with IC50 values in the range of 24.4-43.5 µM.

Structural diversity and clustering of bacterial flagellar outer domains.

Supercoiled flagellar filaments function as mechanical propellers within the bacterial flagellum complex, playing a crucial role in motility. Flagellin, the building block of the filament, features a conserved inner D0/D1 core domain across different bacterial species. In contrast, approximately half of the flagellins possess additional, highly divergent outer domain(s), suggesting varied functional potential. In this study, we elucidate atomic structures of flagellar filaments from three distinct bacterial species: Cupriavidus gilardii , Stenotrophomonas maltophilia , and Geovibrio thiophilus . Our findings reveal that the flagella from the facultative anaerobic G. thiophilus possesses a significantly more negatively charged surface, potentially enabling adhesion to positively charged minerals. Furthermore, we analyzed all AlphaFold predicted structures for annotated bacterial flagellins, categorizing the flagellin outer domains into 682 structural clusters. This classification provides insights into the prevalence and experimental verification of these outer domains. Remarkably, two of the flagellar structures reported herein belong to a previously unexplored cluster, indicating new opportunities on the study of the functional diversity of flagellar outer domains. Our findings underscore the complexity of bacterial flagellins and open up possibilities for future studies into their varied roles beyond motility.

Integration of electronic nose, electronic tongue, and colorimeter in combination with chemometrics for monitoring the fermentation process of Tremella fuciformis.

This study proposes an efficient method for monitoring the submerged fermentation process of Tremella fuciformis (T. fuciformis) by integrating electronic nose (e-nose), electronic tongue (e-tongue), and colorimeter sensors using a data fusion strategy. Chemometrics was employed to establish qualitative identification and quantitative prediction models. The Pearson correlation analysis was applied to extract features from the e-nose and tongue sensor arrays. The optimal sensor arrays for monitoring the submerged fermentation process of T. fuciformis were obtained, and four different data fusion methods were developed by incorporating the colorimeter data features. To achieve qualitative identification, the physicochemical data and principal component analysis (PCA) results were utilized to determine three stages of the fermentation process. The fusion signal based on full features proved to be the optimal data fusion method, exhibiting the highest accuracy across different models. Notably, random forest (RF) was shown to be the most accurate pattern recognition method in this paper. For quantitative prediction, partial least squares regression (PLSR) and support vector regression (SVR) were employed to predict the sugar content and dry cell weight during fermentation. The best respective predictive R2 values for reducing sugar, tremella polysaccharide and dry cell weight were found to be 0.965, 0.988, and 0.970. Furthermore, due to its ability to capture nonlinear data relationships, SVR had superior performance in prediction modeling than PLSR. The results demonstrated that the combination of electronic sensor fusion signals and chemometrics provided a promising method for effectively monitoring T. fuciformis fermentation.

Alternative polyadenylation regulates the translation of metabolic and inflammation-related proteins in adipose tissue of gestational diabetes mellitus.

In gestational diabetes mellitus (GDM), adipose tissue undergoes metabolic disturbances and chronic low-grade inflammation. Alternative polyadenylation (APA) is a post-transcriptional modification mechanism that generates mRNA with variable lengths of 3' untranslated regions (3'UTR), and it is associated with inflammation and metabolism. However, the role of APA in GDM adipose tissue has not been well characterized. In this study, we conducted transcriptomic and proteomic sequencing on subcutaneous and omental adipose tissues from both control and GDM patients. Using Dapars, a novel APA quantitative algorithm, we delineated the APA landscape of adipose tissue, revealing significant 3'UTR elongation of mRNAs in the GDM group. Omental adipose tissue exhibited a significant correlation between elongated 3'UTRs and reduced translation levels of genes related to metabolism and inflammation. Validation experiments in THP-1 derived macrophages (TDMs) demonstrated the impact of APA on translation levels by overexpressing long and short 3'UTR isoforms of a representative gene LRRC25. Additionally, LRRC25 was validated to suppress proinflammatory polarization in TDMs. Further exploration revealed two underexpressed APA trans-acting factors, CSTF3 and PPP1CB, in GDM omental adipose tissue. In conclusion, this study provides preliminary insights into the APA landscape of GDM adipose tissue. Reduced APA regulation in GDM omental adipose tissue may contribute to metabolic disorders and inflammation by downregulating gene translation levels. These findings advance our understanding of the molecular mechanisms underlying GDM-associated adipose tissue changes.

MV-SHIF: Multi-view symmetric hypothesis inference fusion network for emotion-cause pair extraction in documents.

Emotion-cause pair extraction (ECPE) is a challenging task that aims to automatically identify pairs of emotions and their causes from documents. The difficulty of ECPE lies in distinguishing valid emotion-cause pairs from many irrelevant ones. Most previous methods have primarily focused on utilizing multi-task learning to extract semantic information solely from documents without explicitly encoding the relations between clauses. We propose a new approach that incorporates textual entailment paradigm aiming to infer the entailment relationship between the original document as the premise and the clauses or pairs described as the hypothesis. Our approach designs label-view hypothesis templates to improve ECPE by filtering out irrelevant emotion and cause clauses. Furthermore, we formulate candidate emotion-cause pairs as hypothesis statements, and define explicit multi-view symmetric templates to capture the emotion-cause relation semantics. The text entailment recognition for ECPE is finally implemented by fusing multi-view semantic information using a simplified capsule network. Our proposed model achieves state-of-the-art performance on ECPE compared to previous baselines. More importantly, this work demonstrates a novel effective way of applying the textual entailment paradigm to ECPE or clause-level causal discovery by designing multi-view hypothesis inference and information fusion.

Oleogel classification, physicochemical characterization methods, and typical cases of application in food: a review.

The harmful effects of trans and saturated fatty acids have attracted worldwide attention. Edible oleogels, which can structure liquid oils, are promising healthy alternatives to traditional fats. Active research on oleogels is focused on the interaction between unsaturated oils with different fatty acid compositions and low molecular weight or polymer oleogels. The unique network structure inside oleogels has facilitated their application in candies, spreads, meat, and other products. However, the micro- and macro-properties, as well as the functional properties of oleogels vary by preparation method and the system composition. This review discusses the characteristics of oleogels, serving as a reference for the application of oleogels in food products. Specifically, it (i) classifies oleogels and explains the influence of gelling factors on their gelation, (ii) describes the methods for measuring the physicochemical properties of oleogels, and (iii) discusses the current applications of oleogels in food products.

1T'-transition metal dichalcogenide monolayers stabilized on 4H-Au nanowires for ultrasensitive SERS detection.

Unconventional 1T'-phase transition metal dichalcogenides (TMDs) have aroused tremendous research interest due to their unique phase-dependent physicochemical properties and applications. However, due to the metastable nature of 1T'-TMDs, the controlled synthesis of 1T'-TMD monolayers (MLs) with high phase purity and stability still remains a challenge. Here we report that 4H-Au nanowires (NWs), when used as templates, can induce the quasi-epitaxial growth of high-phase-purity and stable 1T'-TMD MLs, including WS2, WSe2, MoS2 and MoSe2, via a facile and rapid wet-chemical method. The as-synthesized 4H-Au@1T'-TMD core-shell NWs can be used for ultrasensitive surface-enhanced Raman scattering (SERS) detection. For instance, the 4H-Au@1T'-WS2 NWs have achieved attomole-level SERS detections of Rhodamine 6G and a variety of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike proteins. This work provides insights into the preparation of high-phase-purity and stable 1T'-TMD MLs on metal substrates or templates, showing great potential in various promising applications.

Tetracyclic homoisoflavanoid (+)-brazilin: a natural product inhibits c-di-AMP-producing enzyme and Streptococcus mutans biofilms.

The tenacious biofilms formed by Streptococcus mutans are resistant to conventional antibiotics and current treatments. There is a growing need for novel therapeutics that selectively inhibit S. mutans biofilms while preserving the normal oral microenvironment. Previous studies have shown that increased levels of cyclic di-AMP, an important secondary messenger synthesized by diadenylate cyclase (DAC), favored biofilm formation in S. mutans. Thus, targeting S. mutans DAC is a novel strategy to inhibit S. mutans biofilms. We screened a small NCI library of natural products using a fluorescence detection assay. (+)-Brazilin, a tetracyclic homoisoflavanoid found in the heartwood of Caesalpinia sappan, was identified as one of the 11 "hits," with the greatest reduction (>99%) in fluorescence at 100 µM. The smDAC inhibitory profiles of the 11 "hits" established by a quantitative high-performance liquid chromatography assay revealed that (+)-brazilin had the most enzymatic inhibitory activity (87% at 100 µM) and was further studied to determine its half maximal inhibitory concentration (IC50 = 25.1 ± 0.98 µM). (+)-Brazilin non-competitively inhibits smDAC's enzymatic activity (Ki = 140.0 ± 27.13 µM), as determined by a steady-state Michaelis-Menten kinetics assay. In addition, (+)-brazilin's binding profile with smDAC (Kd = 11.87 µM) was illustrated by a tyrosine intrinsic fluorescence quenching assay. Furthermore, at low micromolar concentrations, (+)-brazilin selectively inhibited the biofilm of S. mutans (IC50 = 21.0 ± 0.60 µM) and other oral bacteria. S. mutans biofilms were inhibited by a factor of 105 in colony-forming units when treated with 50 µM (+)-brazilin. In addition, a significant dose-dependent reduction in extracellular DNA and glucan levels was evident by fluorescence microscopy imaging of S. mutans biofilms exposed to different concentrations of (+)-brazilin. Furthermore, colonization of S. mutans on a representative model of enamel using suspended hydroxyapatite discs showed a >90% reduction with 50 µM (+)-brazilin. In summary, we have identified a drug-like natural product inhibitor of S. mutans biofilm that not only binds to smDAC but can also inhibit the function of smDAC. (+)-Brazilin could be a good candidate for further development as a potent therapeutic for the prevention and treatment of dental caries.IMPORTANCEThis study represents a significant advancement in our understanding of potential therapeutic options for combating cariogenic biofilms produced by Streptococcus mutans. The research delves into the use of (+)-brazilin, a natural product, as a potent inhibitor of Streptococcus mutans' diadenylate cyclase (smDAC), an enzyme crucial in the formation of biofilms. The study establishes (+)-brazilin as a non-competitive inhibitor of smDAC while providing initial insights into its binding mechanism. What makes this finding even more promising is that (+)-brazilin does not limit its inhibitory effects to S. mutans alone. Instead, it demonstrates efficacy in hindering biofilms in other oral bacteria as well. The broader spectrum of anti-biofilm activity suggests that (+)-brazilin could potentially serve as a versatile tool in a natural product-based treatment for combating a range of conditions caused by resilient biofilms.

Comprehensive effects of salinity, dissolved organic carbon and copper on mortality, osmotic regulation and bioaccumulation of copper in Oryzias melastigma.

Cu, as an essential and toxic element, has gained widespread attention. Both salinity and dissolved organic carbon (DOC) are known to influence Cu toxicity in marine organisms. However, the intricate interplay between these factors and their specific influence on Cu toxicity remains ambiguous. So, this study conducted toxicity tests of Cu on Oryzias melastigma. The experiments involved three salinity levels (10, 20, and 30 ppt) and three DOC levels (0, 1, and 5 mg/L) to comprehensively investigate the underlying mechanisms of toxicity. The complex toxic effects were analyzed by mortality, NKA activity, net Na+ flux and Cu bioaccumulation in O. melastigma. The results indicate that Cu toxicity is notably influenced by both DOC and salinity. Interestingly, the discernible variation in Cu toxicity across different DOC levels diminishes as salinity levels increase. The presence of DOC enhances the impact of salinity on Cu toxicity, especially at higher Cu concentrations. Additionally, Visual MINTEQ was utilized to elucidate the chemical composition of Cu, revealing that DOC had a significant impact on Cu forms. Furthermore, we observed that fluctuations in salinity lead to the inhibition of Na+/K+-ATPase (NKA) activity, subsequently hindering the inflow of Na+. The effects of salinity and DOC on the bioaccumulation of copper were not significant. The influence of salinity on Cu toxicity is mainly through its effect on the osmotic regulation and biophysiology of O. melastigma. Additionally, DOC plays a crucial role in the different forms of Cu. Moreover, DOC-Cu complexes can be utilized by organisms. This study contributes to understanding the mechanism of copper's biological toxicity in intricate marine environments and serves as a valuable reference for developing marine water quality criteria for Cu.

Insights into the hierarchical structure and physicochemical properties of starch isolated from fermented dough.

Understanding the hierarchical structure and physicochemical properties of starch isolated from fermented dough with different times (0-120 min) is valuable for improving the quality of fermented dough-based products. The results indicate that fermentation disrupted the starch granule surface and decreased the average particle size from 19.72 µm to 18.45 µm. Short-term fermentation (< 60 min) disrupted the crystalline, lamellar, short-range ordered molecular and helical structures of starch, while long-term fermentation (60-120 min) elevated the ordered degree of these structures. For example, relative crystallinity and double helix contents increased from 23.7 % to 26.8 % and 34.4 % to 37.2 %, respectively. During short-term fermentation, the structural amorphization facilitated interactions between starch molecular chains and water molecules, which increased the peak viscosity from 275.4 to 320.6 mPa·s and the swelling power from 7.99 to 8.52 g/g. In contrast, starches extracted from long-term fermented dough displayed the opposite results. Interestingly, the hardness and springiness of starch gels gradually decreased as fermentation time increased. These findings extend our understanding of the starch structure-property relationship during varied fermentation stages, potentially benefiting the production of better-fermented foods.