Luobitong Potentiates MTX's Anti-Rheumatoid Arthritis Activity via Targeting Multiple Inflammatory Pathways.

Background: The LuoBiTong (LBT) capsule, a novel traditional Chinese medicine formulation, is currently in Phase III clinical trials. Preliminary preclinical and Phase II clinical studies suggest its efficacy and safety in treating rheumatoid arthritis (RA). However, the underlying mechanisms of its action remain to be elucidated.This research aims to explore the effects and mechanisms of LBT in conjunction with a maintenance dose of methotrexate (M-MTX) on RA. Methods: A Collagen-Induced Arthritis (CIA) mouse model was used to evaluate the anti-RA effects of LBT combined with M-MTX. Assessments included foot swelling, arthritis scoring, serum inflammatory factor analysis, and histopathological examination of the foot. These effects were compared with those of high-dose MTX (H-MTX). Network pharmacology was employed to construct a compound-target network for RA, based on drug composition, to predict its potential mechanism of action. Flow cytometry, Western Blot, and immunohistochemical analyses in animal models identified multiple inflammatory pathways targeted by LBT to augment the anti-RA effects of MTX. Results: The study revealed that LBT combined with M-MTX significantly alleviated CIA-induced arthritis without adverse effects. The combination of LBT and M-MTX showed similar or superior efficacy in regulating macrophage polarization, NF-κB, MAPK signaling pathways, and in the suppression of TH-17 expression in proinflammatory cells. These findings suggest that LBT may exert a multi-pathway therapeutic effect in RA treatment. The predicted pharmacological targets and mechanisms align well with this hypothesis. Conclusion: LBT, when combined with MTX, enhances the anti-RA effect by targeting multiple inflammatory pathways, demonstrating significant therapeutic potential.

Dose-dependent effects of different parabens on food waste biorefinery for volatile fatty acids production: Insight into specific fermentation processes, substrates transformation and microbial metabolic traits.

Parabens are largely concentrated in food waste (FW) due to their large consumption as the widely used preservative. To date, whether and how they affect FW resource recovery via anaerobic fermentation is still largely unknown. This work unveiled the hormesis-like effects of two typical parabens (i.e., methylparaben and n-butylparaben) on VFAs production during FW anaerobic fermentation (i.e., parabens increased VFAs by 6.73-14.49 % at low dose but caused 82.51-87.74 % reduction at high dose). Mechanistic exploration revealed that the parabens facilitated the FW solubilization and enhanced the associated substrates' biodegradability. The low parabens enriched the functional microorganisms (e.g., Firmicutes and Actinobacteria) and upregulated those critical genes involved in VFAs biosynthesis (e.g., GCK and PK) by activating the microbial adaptive capacity (i.e., quorum sensing and two-component system). Consequently, the metabolism rates of fermentation substrates and subsequent VFAs production were accelerated. However, due to increased biotoxicity of high parabens, the functional microorganisms and relevant metabolic activities were depressed, resulting in the significant reduction of VFAs biosynthesis. Structural equation modeling clarified that microbial community was the predominant factor affecting VFAs generation, followed by metabolic pathways. This work elucidated the dose-dependent effects and underlying mechanisms of parabens on FW anaerobic fermentation, providing insights for the effective management of FW resource recovery.

Artificial intelligence for neuro MRI acquisition: a review.

OBJECT: To review recent advances of artificial intelligence (AI) in enhancing the efficiency and throughput of the MRI acquisition workflow in neuroimaging, including planning, sequence design, and correction of acquisition artifacts. MATERIALS AND METHODS: A comprehensive analysis was conducted on recent AI-based methods in neuro MRI acquisition. The study focused on key technological advances, their impact on clinical practice, and potential risks associated with these methods. RESULTS: The findings indicate that AI-based algorithms have a substantial positive impact on the MRI acquisition process, improving both efficiency and throughput. Specific algorithms were identified as particularly effective in optimizing acquisition steps, with reported improvements in workflow efficiency. DISCUSSION: The review highlights the transformative potential of AI in neuro MRI acquisition, emphasizing the technological advances and clinical benefits. However, it also discusses potential risks and challenges, suggesting areas for future research to mitigate these concerns and further enhance AI integration in MRI acquisition.

Combining metabolomics with network pharmacology to reveal the therapeutic mechanism of Dingchuan Decoction in rats with OVA-induced allergic asthma.

Dingchuan Decoction (DCD) is a traditional Chinese medicine prescription commonly used in the treatment of asthma, but the mechanism of DCD in treating asthma has not yet been determined. In this study, we employed a combination of metabolomics and network pharmacology to investigate the mechanism of DCD in treating asthma. An allergic asthma rat model was induced by ovalbumin (OVA). Metabolomics based on 1H NMR and UHPLC-MS was used to identify differential metabolites and obtain the major metabolic pathways and potential targets. Network pharmacology was utilized to explore potential targets of DCD for asthma treatment. Finally, the results of metabolomics and network pharmacology were integrated to obtain the key targets and metabolic pathways of DCD for the therapy of asthma, and molecular docking was utilized to validate the key targets. A total of 76 important metabolites and 231 potential targets were identified through metabolomics. Using network pharmacology, 184 potential therapeutic targets were obtained. These 184 targets were overlaid with the 231 potential targets obtained through metabolomics and were analyzed in conjunction with metabolic pathways. Ultimately, the key targets were identified as aldehyde dehydrogenase 2 (ALDH2) and amine oxidase copper-containing 3 (AOC3), and the relevant metabolic pathways affected were glycolysis and gluconeogenesis as well as arginine and proline metabolism. Molecular docking showed that the key targets had high affinity with the relevant active ingredients in DCD, which further demonstrated that DCD may exert therapeutic effects by acting on the key targets. The present study demonstrated that DCD can alleviate OVA-induced allergic asthma and that DCD may have a therapeutic effect by regulating intestinal flora and polyamine metabolism through its effects on ALDH2 and AOC3.

Multi-regional sequencing reveals the genetic and immune heterogeneity of non-cancerous tissues in gastric cancer.

Gastric cancer (GC) is one of the most heterogeneous tumors. However, research on normal tissue adjacent to the tumor (NAT) is very limited. We performed multi-regional omics sequencing on 150 samples to assess the genetic basis and immune microenvironment in NAT and matched primary tumor or lymph node metastases. NATs demonstrated different mutated genes compared with GC, and NAT genomes underwent independent evolution with low variant allele frequency. Mutation profiles were predominated by aging and smoking-associated signatures in NAT instead of signatures associated with genetic instability. Although the immune microenvironment within NATs shows substantial intra-patient heterogeneity, the proportion of shared TCR clones among NATs is five times higher than that of tumor regions. These findings support the notion that subclonal expansion is not pronounced in NATs. We also demonstrated remarkable intra-patient heterogeneity of GCs and revealed heterogeneity of focal amplification of CD274 (encoding PD-L1) that leads to differential expression. Finally, we identified that monoclonal seeding is predominant in GC, which is followed by metastasis-to-metastasis dissemination in individual lymph nodes. These results provide novel insights into GC carcinogenesis. © 2024 The Pathological Society of Great Britain and Ireland.

Network pharmacology combined with metabolomics to reveal the anti-fibrotic mechanism of Polygoni Orientalis Fructus in CCl4-induced hepatic fibrosis rats.

Polygoni Orientalis Fructus (POF), a dried ripe fruit of Polygonum orientale L., is commonly used in China for liver disease treatment. However, its therapeutic mechanism remains unclear. The aim of this study was to elucidate the effects of POF on the regulation of endogenous metabolites and identify its key therapeutic targets in hepatic fibrosis (HF) rats by integrating network pharmacology and metabolomics approaches. First, serum liver indices and histopathological analyses were used to evaluate the therapeutic effects of POF on carbon tetrachloride (CCl4)-induced HF. Subsequently, differential metabolites and potential therapeutic targets of POF were screened using plasma metabolomics and network pharmacology, respectively. The key targets of POF were identified by overlapping differential metabolite-associated targets with the potential targets and validated by molecular docking and ELISA experiments. The results showed that POF effectively alleviated HF in rats. A total of 51 metabolites related to HF were screened, and 24 were associated with POF. 232 potential therapeutic targets were identified by network pharmacology analysis. Finally, six key targets were identified through a combined analysis. Furthermore, molecular docking and ELISA validation revealed that AGXT, PAH, and NOS3 are targets of POF action, while CBS, ALDH2, and ARG1 were identified as potential targets. SIGNIFICANCE: POF is now commonly used in the treatment of liver disease, but its mechanism of action remains unclear. Current studies on metabolomics of liver disease primarily focuse on the interpretation of differential metabolites and related metabolic pathways. This research delves into the intricate details of metabolomics findings via network pharmacology to uncover the targets and pathways of drug action.

MIFAM-DTI: a drug-target interactions predicting model based on multi-source information fusion and attention mechanism.

Accurate identification of potential drug-target pairs is a crucial step in drug development and drug repositioning, which is characterized by the ability of the drug to bind to and modulate the activity of the target molecule, resulting in the desired therapeutic effect. As machine learning and deep learning technologies advance, an increasing number of models are being engaged for the prediction of drug-target interactions. However, there is still a great challenge to improve the accuracy and efficiency of predicting. In this study, we proposed a deep learning method called Multi-source Information Fusion and Attention Mechanism for Drug-Target Interaction (MIFAM-DTI) to predict drug-target interactions. Firstly, the physicochemical property feature vector and the Molecular ACCess System molecular fingerprint feature vector of a drug were extracted based on its SMILES sequence. The dipeptide composition feature vector and the Evolutionary Scale Modeling -1b feature vector of a target were constructed based on its amino acid sequence information. Secondly, the PCA method was employed to reduce the dimensionality of the four feature vectors, and the adjacency matrices were constructed by calculating the cosine similarity. Thirdly, the two feature vectors of each drug were concatenated and the two adjacency matrices were subjected to a logical OR operation. And then they were fed into a model composed of graph attention network and multi-head self-attention to obtain the final drug feature vectors. With the same method, the final target feature vectors were obtained. Finally, these final feature vectors were concatenated, which served as the input to a fully connected layer, resulting in the prediction output. MIFAM-DTI not only integrated multi-source information to capture the drug and target features more comprehensively, but also utilized the graph attention network and multi-head self-attention to autonomously learn attention weights and more comprehensively capture information in sequence data. Experimental results demonstrated that MIFAM-DTI outperformed state-of-the-art methods in terms of AUC and AUPR. Case study results of coenzymes involved in cellular energy metabolism also demonstrated the effectiveness and practicality of MIFAM-DTI. The source code and experimental data for MIFAM-DTI are available at https://github.com/Search-AB/MIFAM-DTI.

Toward Designing Reactive Metal Clusters for Dinitrogen Activation: A Guideline Based on N2 Initial Adsorption.

Gas-phase metal clusters are ideal models to explore transition-metal-mediated N2 activation mechanism. However, the effective design and search of reactive clusters in N2 activation are currently hindered by the lack of clear guidelines. Inspired by the Sabatier principle, we discovered in this work that N2 initial adsorption energy (ΔEads) is an important parameter to control the N2 activation reactivity of metal clusters in the gas phase. This mechanistic insight obtained from high-level calculations rationalizes the N2 activation reactivity of many previously reported metal clusters when combined with the known factor determining the N≡N cleavage process. Furthermore, based on this guideline of ΔEads, we successfully designed several new reactive clusters for cleaving N≡N triple bond under mild conditions, including FeV2S2-, TaV2C2-, and TaV2C3-, the high N2 activation reactivity of which has been fully corroborated in our gas phase experiments employing mass spectrometry with collision-induced dissociation. The importance of ΔEads revealed in this work not only reshapes our understanding of N2 activation reactions in the gas phase but also could have implication for other N2 activation processes in the condensed phase. The more general establishment of this new perspective on N2 activation reactivity warrants future experimental and computational studies.

A novel reverse perilesional home phototherapy can promote the repigmentation of vitiligo patches with complete leukotrichia: A 12-week, open-label, double-arm, multicenter, randomized clinical trial.

BACKGROUND/PURPOSE: Existing phototherapies are ineffective for treating patients with vitiligo with complete leukotrichia. We compared the efficacy of reverse perilesional irradiation, during which only the lesional areas are covered, with conventional narrowband ultraviolet B (NB-UVB) home phototherapy for repigmentation of non-segmental vitiligo in patients with complete leukotrichia. METHODS: This was a 12-week, open-label, double-arm, multicenter clinical trial, with a total of 121 patients with non-segmental vitiligo who were randomly divided into two groups (both received topical tacrolimus): the conventional NB-UVB irradiation (CI) and reverse perilesional NB-UVB irradiation (RI) groups. RESULTS: A statistically significant difference in improvement from baseline was observed in the RI group compared with the findings in the CI group (-30.8% ± 11.8% vs. -25.5% ± 11.05%, respectively [p = .010]; pair-wise comparison p = .900 at week 4, p = .104 at week 8, and p = .010 at week 12). At week 12, the average percentage change from baseline of leukotrichia in the irradiation area significantly decreased from 100% to 82.2% ± 13.65% in the RI group, and from 100% to 88.7% ± 9.64% in the CI group (p = .027). Adverse events were minor, including desquamation, dryness, erythema, and blisters. No severe or lasting side effects were observed during the study. CONCLUSION: RI mediated better repigmentation of vitiligo with complete leukotrichia than CI.

Iron-catalyzed benzylic C-H thiolation via photoinduced ligand-to-metal charge-transfer.

Here, we describe an iron-catalyzed benzylic C-H thiolation of alkylarenes via photoinduced ligand-to-metal charge-transfer. The protocol features operational simplicity, mild reaction conditions, and the use of FeCl3 as catalyst and thiols/disulfides as sulfur sources, which enables the transformation of diverse benzylic C-H bonds into C-S bonds with a high efficiency.

Cadonilimab with chemotherapy in HER2-negative gastric or gastroesophageal junction adenocarcinoma: the phase 1b/2 COMPASSION-04 trial.

Treatment with anti-programmed cell death protein 1 (PD-1) therapy and chemotherapy prolongs the survival of patients with unresectable advanced or metastatic gastric or gastroesophageal junction (GEJ) adenocarcinoma. The benefit from anti-PD-1 therapy is enriched in patients with programmed cell death 1 ligand 1 (PD-L1) combined positive score (CPS)-positive or CPS-high tumors compared with patients with PD-L1 CPS-negative or CPS-low tumors. In this phase 1b/2 study, we evaluated the efficacy and safety of cadonilimab, a bispecific antibody targeting PD-1 and cytotoxic T-lymphocyte antigen-4, plus chemotherapy as first-line treatment in patients with human epidermal growth factor receptor 2-negative unresectable advanced or metastatic gastric or GEJ adenocarcinoma. The primary endpoint was the recommended phase 2 dose (RP2D) for phase 1b and the objective response rate for phase 2. Secondary endpoints included disease control rate, duration of response, time to response, progression-free survival, overall survival (OS) and safety. The primary endpoint was met. No dose-limiting toxicities were observed during dose escalation in phase 1b; the recommended phase 2 dose was determined as 6 mg kg-1 every 2 weeks. The objective response rate was 52.1% (95% confidence interval (CI) = 41.6-62.5), consisting of complete and partial responses in 4.3% and 47.9% of patients, respectively. The median duration of response, progression-free survival and OS were 13.73 months (95% CI = 7.79-19.12), 8.18 months (95% CI = 6.67-10.48) and 17.48 months (95% CI = 12.35-26.55), respectively. The median OS in patients with a PD-L1 CPS ≥ 5 was 20.32 months (95% CI = 4.67-not estimable); in patients with a PD-L1 CPS < 1, the median OS reached 17.64 months (95% CI = 11.63-31.70). The most common treatment-related grade 3 or higher adverse events were decreased neutrophil count (19.1%), decreased platelet count (16.0%), anemia (12.8%) and decreased leukocyte count (8.5%). No new safety signal was identified. The current regimen showed promising clinical activity and manageable safety in patients with gastric or GEJ adenocarcinoma regardless of PD-L1 expression. Chinadrugtrials.org.cn registration: CTR20182027.

DIMOND: DIffusion Model OptimizatioN with Deep Learning.

Diffusion magnetic resonance imaging is an important tool for mapping tissue microstructure and structural connectivity non-invasively in the in vivo human brain. Numerous diffusion signal models are proposed to quantify microstructural properties. Nonetheless, accurate estimation of model parameters is computationally expensive and impeded by image noise. Supervised deep learning-based estimation approaches exhibit efficiency and superior performance but require additional training data and may be not generalizable. A new DIffusion Model OptimizatioN framework using physics-informed and self-supervised Deep learning entitled "DIMOND" is proposed to address this problem. DIMOND employs a neural network to map input image data to model parameters and optimizes the network by minimizing the difference between the input acquired data and synthetic data generated via the diffusion model parametrized by network outputs. DIMOND produces accurate diffusion tensor imaging results and is generalizable across subjects and datasets. Moreover, DIMOND outperforms conventional methods for fitting sophisticated microstructural models including the kurtosis and NODDI model. Importantly, DIMOND reduces NODDI model fitting time from hours to minutes, or seconds by leveraging transfer learning. In summary, the self-supervised manner, high efficacy, and efficiency of DIMOND increase the practical feasibility and adoption of microstructure and connectivity mapping in clinical and neuroscientific applications.

Comparison of uncut Roux-en-Y anastomosis and Billroth-II with Braun anastomosis after distal gastrectomy.

Background: This study aimed to compare the clinical outcomes and patient benefits of uncut Roux-en-Y (URY) anastomosis and Billroth-II with Braun (BB) anastomosis after distal gastrectomy. Methods: We retrospectively reviewed the data of patients who underwent URY or BB anastomosis after distal gastrectomy between March 2015 and December 2017. Clinical characteristics, survival data, postoperative recovery data, and long-term outcomes were recorded and compared between the two groups. Results: A total of 231 patients were included, with 167 in the URY group and 64 in the BB group. Kaplan-Meier curves for overall survival showed no differences after propensity score matching (p = 0.488). Long-term postoperative quality of life evaluation also showed no significant differences. Compared to the BB group, patients in the URY group had a significantly shorter time to start a liquid diet after propensity score matching (67.6 h vs. 46.5 h, p = 0.003), and a lower occurrence of bile reflux on follow-up gastroscopy (p < 0.001). Conclusion: The URY anastomosis appears to be a feasible method for digestive tract reconstruction after distal gastrectomy, resulting in less bile reflux and better postoperative recovery. However, there is no significant difference between URY and BB anastomosis in terms of overall survival and long-term quality of life.

An oncolytic virus delivering tumor-irrelevant bystander T cell epitopes induces anti-tumor immunity and potentiates cancer immunotherapy.

Tumor-specific T cells are crucial in anti-tumor immunity and act as targets for cancer immunotherapies. However, these cells are numerically scarce and functionally exhausted in the tumor microenvironment (TME), leading to inefficacious immunotherapies in most patients with cancer. By contrast, emerging evidence suggested that tumor-irrelevant bystander T (TBYS) cells are abundant and preserve functional memory properties in the TME. To leverage TBYS cells in the TME to eliminate tumor cells, we engineered oncolytic virus (OV) encoding TBYS epitopes (OV-BYTE) to redirect the antigen specificity of tumor cells to pre-existing TBYS cells, leading to effective tumor inhibition in multiple preclinical models. Mechanistically, OV-BYTE induced epitope spreading of tumor antigens to elicit more diverse tumor-specific T cell responses. Remarkably, the OV-BYTE strategy targeting human severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific T cell memory efficiently inhibited tumor progression in a human tumor cell-derived xenograft model, providing important insights into the improvement of cancer immunotherapies in a large population with a history of SARS-CoV-2 infection or coronavirus disease 2019 (COVID-19) vaccination.

Machine Learning for Experimental Reactivity of a Set of Metal Clusters toward C-H Activation.

Understanding the mechanisms of C-H activation of alkanes is a very important research topic. The reactions of metal clusters with alkanes have been extensively studied to reveal the electronic features governing C-H activation, while the experimental cluster reactivity was qualitatively interpreted case by case in the literature. Herein, we prepared and mass-selected over 100 rhodium-based clusters (RhxVyOz- and RhxCoyOz-) to react with light alkanes, enabling the determination of reaction rate constants spanning six orders of magnitude. A satisfactory model being able to quantitatively describe the rate data in terms of multiple cluster electronic features (average electron occupancy of valence s orbitals, the minimum natural charge on the metal atom, cluster polarizability, and energy gap involved in the agostic interaction) has been constructed through a machine learning approach. This study demonstrates that the general mechanisms governing the very important process of C-H activation by diverse metal centers can be discovered by interpreting experimental data with artificial intelligence.

Perioperative versus adjuvant S-1 plus oxaliplatin chemotherapy for stage II/III resectable gastric cancer (RESONANCE): a randomized, open-label, phase 3 trial.

Evidence from Europe shows that perioperative chemotherapy may be beneficial for the treatment of locally advanced gastric cancer, but reliable and robust data is lacking. To rectify this, the phase 3 RESONANCE trial investigated the efficacy and safety of S-1 plus oxaliplatin (SOX) as a perioperative chemotherapy regimen for gastric cancer. This randomized, open-label trial enrolled patients from 19 medical centers with stage II/III resectable gastric cancer who were centrally randomly assigned to either perioperative chemotherapy (PC) arm or adjuvant chemotherapy (AC) arm. Patients in the PC arm received two to four cycles of SOX followed by surgery and four to six cycles of SOX. Patients in the AC arm received upfront surgery and eight cycles of SOX. 386 patients in each group were enrolled and 756 (382 in PC and 374 in AC) were included in the mITT population. The three-year DFS rate was 61.7% in the PC arm and 53.8% in the AC arm (log-rank p = 0.019). The R0 resection rate in the PC arm was significantly higher than that in the AC arm (94.9% vs. 83.7%, p < 0.0001). There was no difference between two arms in surgical outcomes or postoperative complications. Safety-related data were like the known safety profile. In conclusion, from a clinical perspective, this trial indicated a trend towards higher three-year disease-free survival rate with perioperative SOX in stage II/III resectable gastric cancer with well-tolerated toxicity compared to adjuvant SOX, which might provide a theoretical basis for applying perioperative SOX in advanced gastric cancer patients. (ClinicalTrials.gov NCT01583361).

Reverse water-gas shift catalyzed by RhnVO3,4- (n = 3-7) cluster anions under variable temperatures.

A fundamental understanding of the exact structural characteristics and reaction mechanisms of interface active sites is vital to engineering an energetic metal-support boundary in heterogeneous catalysis. Herein, benefiting from a newly developed high-temperature ion trap reactor, the reverse water-gas shift (RWGS) (CO2 + H2 → CO + H2O) catalyzed by a series of compositionally and structurally well-defined RhnVO3,4- (n = 3-7) clusters were identified under variable temperatures (298-773 K). It is discovered that the Rh5-7VO3,4- clusters can function more effectively to drive RWGS at relatively low temperatures. The experimentally observed size-dependent catalytic behavior was rationalized by quantum-chemical calculations; the framework of RhnVO3,4- is constructed by depositing the Rhn clusters on the VO3,4 "support", and a sandwiched base-acid-base [Rhout--Rhin+-VO3,4-; Rhout and Rhin represent the outer and inner Rh atoms, respectively] feature in Rh5-7VO3,4- governs the adsorption and activation of reactants as well as the facile desorption of the products. In contrast, isolated Rh5-7- clusters without the electronic modification of the VO3,4 "support" can only catalyze RWGS under relatively high-temperature conditions.

Rapid Silicification of a DNA Origami with Shape Fidelity.

High-fidelity patterning of DNA origami nanostructures on various interfaces holds great potential for nanoelectronics and nanophotonics. However, distortion of a DNA origami often occurs due to the strong interface interactions, e.g., on two-dimensional (2D) materials. In this study, we discovered that the adsorption of silica precursors in rapid silicification can prevent the distortion caused by graphene and generates a high shape-fidelity DNA origami-silica composite on a graphene interface. We found that an incubation time of 1 min and silicification time of 16 h resulted in the formation of DNA origami-silica composites with the highest shape fidelity of 99%. By comparing the distortion of the DNA origami on the graphene interface with and without silicification, we observed that rapid silicification effectively preserved the integrity of the DNA origami. Statistical analysis of scanning electron microscopy data indicates that compared to bare DNA origami, the DNA origami-silica composite has an increased shape fidelity by more than two folds. Furthermore, molecular dynamics simulations revealed that rapid silicification effectively suppresses the distortion of the DNA origami through the interhelical insertion of silica precursors. Our strategy provides a simple yet effective solution to maintain the shape-fidelity DNA origami on interfaces that have strong interaction with DNA molecules, expanding the applicable interfaces for patterning 2D DNA origamis.

Alcalase-hydrolyzed insoluble soybean meal hydrolysate aggregates: Structure, bioactivity, function properties, and influences on the stability of oil-in-water emulsions.

We studied the influences of hydrolysis time on the structure, functional properties, and emulsion stability of insoluble soybean meal hydrolysate aggregates (ISMHAs). We assume that the ISMHAs produced by soybean meal can be used as emulsifiers to prepare stable emulsions. The molecular weights of these ISMHAs were below 53 kDa. After hydrolysis, a decrease in α-helices and an increase in random coils indicated that the soybean meal proteins were unfolding. Moreover, the fluorescence intensity, UV absorption, and surface hydrophobicity of ISMHAs increased. These results would contribute to their antioxidant activity and functional properties. Additionally, the 90-min ISMHA sample exhibited the highest ABTS+• scavenging activity (80.02 ± 4.55 %), foaming stability (52.92 ± 8.06 %), and emulsifying properties (emulsifying activity index of 97.09 m2/g; emulsifying stability index of 371.47 min). The 90-min ISMHA emulsion exhibited the smallest particle size and excellent storage stability. Soybean meal peptide by-product emulsifier has potential for sustainable application.

Chinese national clinical practice guidelines on the prevention, diagnosis, and treatment of early gastric cancer.

BACKGROUND: Gastric cancer is one of the most common malignant tumors in the digestive system in China. Few comprehensive practice guidelines for early gastric cancer in China are currently available. Therefore, we created the Chinese national clinical practice guideline for the prevention, diagnosis, and treatment of early gastric cancer. METHODS: This clinical practice guideline (CPG) was developed in accordance with the World Health Organization's recommended process and with the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) in assessing evidence quality. We used the Evidence to Decision framework to formulate clinical recommendations to minimize bias and increase transparency in the CPG development process. We used the Reporting Items for practice Guidelines in HealThcare (RIGHT) statement and the Appraisal of Guidelines for Research and Evaluation II (AGREE II) as reporting and conduct guidelines to ensure completeness and transparency of the CPG. RESULTS: This CPG contains 40 recommendations regarding the prevention, screening, diagnosis, treatment, and follow-up of early gastric cancer based on available clinical studies and guidelines. We provide recommendations for the timing of Helicobacter pylori eradication, screening populations for early gastric cancer, indications for endoscopic resection and surgical gastrectomy, follow-up interval after treatment, and other recommendations. CONCLUSIONS: This CPG can lead to optimum care for patients and populations by providing up-to-date medical information. We intend this CPG for widespread adoption to increase the standard of prevention, screening, diagnosis, treatment, and follow-up of early gastric cancer; thereby, contributing to improving national health care and patient quality of life.