Current Status of Shared Decision-Making in Intraocular Lens Selection for Cataract Surgery: A Cross-Sectional Study.

Purpose: To explore 1) the level of shared decision-making (SDM) participation in intraocular lens (IOL) selection in cataract patients and the factors that influence this participation and 2) the relationships between preparation for decision-making (PrepDM)and the level of SDM participation and satisfaction with the decision (SWD). Provide guidance for improving SDM in ophthalmology. Patients and Methods: 176 cataract patients were asked to complete the PrepDM scale, the 9-item Shared Decision Making Questionnaire (SDM-Q-9) and the SWD instrument in IOL decision-making process. Multiple linear regression was used to analyze the influencing factors of the level of SDM. The Process program and bootstrap sampling method was used to test whether the level of participation in SDM was a mediating variable among the three. Results: The SDM-Q-9 median score was 77.78 (IQR 31.11-88.89). Patients with a history of surgery in the operative eye (P=0.022) or PrepDM <60 points (P<0.001) had lower SDM-Q-9 scores than patients with no history of surgery in the operative eye or PrepDM ≥60 points. Patients with an education level lower than primary school had lower SDM-Q-9 scores than patients with other education levels (P<0.05). The PrepDM of cataract patients was positively correlated with the level of SDM (r=0.768, P<0.001) and with the SWD (r=0.727, P<0.001), and the level of SDM was positively correlated with the SWD (r=0.856, P<0.001). The level of SDM fully mediated PrepDM and SDW, with a mediating effect value of 0.128 and a mediating effect of 86.66% of the total effect. Conclusion: The SDM of cataract patients involved in IOL selection was in the upper middle range. Education, history of surgery in the operated eye, and PrepDM were factors that influenced the level of SDM. The level of participation in SDM fully mediated the relationship between PrepDM and SWD.

QTL mapping and genomic selection of stem and branch diameter in soybean (Glycine max L.).

Introduction: Soybean stem diameter (SD) and branch diameter (BD) are closely related traits, and genetic clarification of SD and BD is crucial for soybean breeding. Methods: SD and BD were genetically analyzed by a population of 363 RIL derived from the cross between Zhongdou41 (ZD41) and ZYD02878 using restricted two-stage multi-locus genome-wide association, inclusive composite interval mapping, and three-variance component multi-locus random SNP effect mixed linear modeling. Then candidate genes of major QTLs were selected and genetic selection model of SD and BD were constructed respectively. Results and discussion: The results showed that SD and BD were significantly correlated (r = 0.74, P < 0.001). A total of 93 and 84 unique quantitative trait loci (QTL) were detected for SD and BD, respectively by three different methods. There were two and ten major QTLs for SD and BD, respectively, with phenotypic variance explained (PVE) by more than 10%. Within these loci, seven genes involved in the regulation of phytohormones (IAA and GA) and cell proliferation and showing extensive expression of shoot apical meristematic genes were selected as candidate genes. Genomic selection (GS) analysis showed that the trait-associated markers identified in this study reached 0.47-0.73 in terms of prediction accuracy, which was enhanced by 6.56-23.69% compared with genome-wide markers. These results clarify the genetic basis of SD and BD, which laid solid foundation in regulation gene cloning, and GS models constructed could be potentially applied in future breeding programs.

Multichannel Nanogenerator-Driven Collaborative Metabolic Fingerprint Diagnostic Strategy for Early Screening and Risk Evaluation of Nonalcoholic Fatty Liver Disease.

Nonalcoholic fatty liver disease (NAFLD), along with its progressive forms nonalcoholic steatohepatitis (NASH) and NASH fibrosis, has emerged as a global health crisis. However, the absence of robust screening and risk evaluation tools contributes to the underdiagnosis of NAFLD. Herein, we reported a multichannel nanogenerator-assisted laser desorption/ionization mass spectrometry (LDI-MS) platform for early screening and risk evaluation of NAFLD. Specifically, titanium oxide nanosheets (TiNS) and covalent-organic framework nanosheets (COFNS) were employed as nanogenerators with excellent optical properties and exhibited efficient desorption/ionization during the LDI-MS process. Only ∼0.025 µL of serum without pretreatments and separation, serum metabolic fingerprints (SMFs) can be extracted within seconds. Notably, integrated SMFs from TiNS and COFNS significantly improved diagnostic performance and achieved the area under the curve (AUC) values of 1.000 with 100% sensitivity and 100% specificity for the validation sets of global diagnosis, early diagnosis, high-risk NASH, and NASH fibrosis evaluation. Additionally, four biomarker panels were identified, and their diagnostic AUC values were more than 0.944. Ultimately, key metabolic pathways indicating the change from simple NAFLD to high-risk NASH and NASH fibrosis were uncovered. This work provided a noninvasive and high-throughput screening and risk evaluation strategy for NAFLD healthcare management, thus contributing to the precise treatment of the NALFD.

Red Blood Cell Membrane-Coated Nanoparticles Enable Incompatible Blood Transfusions.

Blood transfusions save lives and improve health every day. Despite the matching of blood types being stricter than it ever has been, emergency transfusions among incompatible blood types are still inevitable in the clinic when there is a lack of acceptable blood types for recipients. Here to overcome this, a counter measure nanoplatform consisting of a polymeric core coated by a red blood cell (RBC) membrane is developed. With A-type or B-type RBC membrane camouflaging, the nanoplatform is capable of specifically capturing anti-A or anti-B IgM antibodies within B-type or A-type whole blood, thereby decreasing the corresponding IgM antibody levels and then allowing the incompatible blood transfusions. In addition to IgM, the anti-RBC IgG antibody in a passive immunization murine model can likewise be neutralized by this nanoplatform, leading to prolonged circulation time of incompatible donor RBCs. Noteworthily, nanoplatform made by expired RBCs (>42 days stored hypothermically) and then subjected to lyophilization does not impair their effect on antibody neutralization. Most importantly, antibody-captured RBC-NP do not exacerbate the risk of inflammation, complement activation, and coagulopathy in an acute hemorrhagic shock murine model. Overall, this biomimetic nanoplatform can safely neutralize the antibody to enable incompatible blood transfusion.

In Situ Array Microextraction and Metabolic Profiling of Small Extracellular Vesicles to Guide and Monitor Maternal Delivery.

The advantages of small extracellular vesicles (sEV) in disease management have become increasingly prominent, with the main challenge lying in meeting the demands of large-scale extraction and high-throughput analysis, a crucial aspect in the realm of precision medicine. To overcome this challenge, an engineered on-plate aptamer array (16×24 spots) is developed for continuous scale-up microextraction of plasma sEV and their in situ metabolic analysis using mass spectrometry. With this integrated array strategy, metabolic profiles of sEV are acquired from the plasma of 274 antenatal or postpartum women, reducing analysis time by half (7.5 h) and sample volume by 95% (only 0.125 µL usage) compared to the traditional suspension method. Moreover, using machine learning algorithms on sEV metabolic profiles, a risk score system is constructed that accurately assesses the need for epidural analgesia during childbirth and the likelihood of post-administration fever. The system, based on admission samples, achieves an impressive 94% accuracy. Furthermore, post-administration fever can be identified from delivery samples, reaching an overall accuracy rate of 88%. This work offers real-time monitoring of the childbirth process that can provide timely guidance for maternal delivery, underscoring the significance of sEV detection in large-scale clinical samples for medicine innovation and advancement.

Metal-support spin orders: Crucial effect on electrocatalytic oxygen reduction.

Magnetic property (e.g. spin order) of support is of great importance in the rational design of heterogeneous catalysts. Herein, we have taken the Ni-supported ferromagnetic (FM) CrBr3 support (Nix/CrBr3) to thoroughly investigate the effect of spin-order on electrocatalytic oxygen reduction reaction (ORR) via spin-polarized density functional theory calculations. Specifically, Ni loading induces anti-FM coupling in Ni-Cr, leading to a transition from FM-to-ferrimagnetic (FIM) properties, while Ni-Ni metallic bonds create a robust FM direct exchange, benefiting the improvement of the phase transition temperature. Interestingly, with the increase in Ni loading, the easy magnetic axis changes from out-of-plane (2D-Heisenberg) to in-plane (2D-XY). The adsorption properties of Nix/CrBr3, involving O2 adsorption energy and configuration, are not governed by the d-band center but strongly correlate with magnetic anisotropy. It is noteworthy that the applied potential and electrolyte acidity triggers spin-order transition phenomena during the ORR and induces the catalytic pathway change from 4e- ORR to 2e- ORR with the excellent onset potential of 0.93 V/reversible hydrogen electrode, comparable to the existing most excellent noble-metal catalysts. Generally, these findings offer new avenues to understand and design heterogeneous catalysts with magnetic support.

KinomeMETA: a web platform for kinome-wide polypharmacology profiling with meta-learning.

Kinase-targeted inhibitors hold promise for new therapeutic options, with multi-target inhibitors offering the potential for broader efficacy while minimizing polypharmacology risks. However, comprehensive experimental profiling of kinome-wide activity is expensive, and existing computational approaches often lack scalability or accuracy for understudied kinases. We introduce KinomeMETA, an artificial intelligence (AI)-powered web platform that significantly expands the predictive range with scalability for predicting the polypharmacological effects of small molecules across the kinome. By leveraging a novel meta-learning algorithm, KinomeMETA efficiently utilizes sparse activity data, enabling rapid generalization to new kinase tasks even with limited information. This significantly expands the repertoire of accurately predictable kinases to 661 wild-type and clinically-relevant mutant kinases, far exceeding existing methods. Additionally, KinomeMETA empowers users to customize models with their proprietary data for specific research needs. Case studies demonstrate its ability to discover new active compounds by quickly adapting to small dataset. Overall, KinomeMETA offers enhanced kinome virtual profiling capabilities and is positioned as a powerful tool for developing new kinase inhibitors and advancing kinase research. The KinomeMETA server is freely accessible without registration at https://kinomemeta.alphama.com.cn/.

Magnetic Order Transition of a Two-Dimensional Square-Lattice Electrocatalyst Assembled by Fe-N4 Units: Crucial Role on Oxygen Reduction.

Herein, we theoretically investigate the effect of magnetic orders on electrocatalytic oxygen reduction reaction (ORR) properties on the Fe-N4 site-embedded two-dimensional (2D) covalent organic framework (Fe-N4@COF-C3N2) under realistic environments. The Fe-N4@COF-C3N2 shows a 2D square-lattice (sql) topology with three magnetic order states: one ferromagnetic state (FM) and two antiferromagnetic states (AFM1 and AFM2). Specially, the electrocatalyst in the AFM2 state shows a remarkable onset potential of 0.80 V/reversible hydrogen electrode (RHE) at pH 1, superior to the existing most excellent noble-metal catalysts. Thermodynamically, the onset potential for the 4e- ORR is 0.64 V/RHE at pH 1, with a magnetic state transition process of FM → AFM1 → FM → FM → FM, while at pH 13, the onset potential for the 4e- ORR is 0.54 V/RHE, with the magnetic transition process of FM → FM → AFM1 → FM → FM. Generally, this finding will provide new avenues to rationally design the Fe-N4 electrocatalyst.

A Prospective Multicenter Study on the Additive Value of Contrast-Enhanced Ultrasound for Biopsy Decision of Ultrasound BI-RADS 4 Breast Lesions.

OBJECTIVE: The main aim of this study was to determine whether the use of contrast-enhanced ultrasound (CEUS) could improve the categorization of suspicious breast lesions based on the Breast Imaging Reporting and Data System (BI-RADS), thereby reducing the number of benign breast lesions referred for biopsy. METHODS: This prospective study, conducted between January 2017 and December 2018, enrolled consenting patients from eight teaching hospitals in China, who had been diagnosed with solid breast lesions classified as BI-RADS 4 using conventional ultrasound. CEUS was performed within 1 wk of diagnosis for reclassification of breast lesions. Histopathological results obtained from core needle biopsies or surgical excision samples served as the reference standard. The simulated biopsy rate and cancer-to-biopsy yield were used to compare the accuracy of CEUS and conventional ultrasound (US). RESULTS: Among the 1490 lesions diagnosed as BI-RADS 4 with conventional ultrasound, 486 malignant and 1004 benign lesions were confirmed based on histology. Following CEUS, 2, 395, and 211 lesions were reclassified as CEUS-based BI-RADS 2, 3, and 5, respectively, while 882 (59%) remained as BI-RADS 4. The actual cancer-to-biopsy yield based on US was 32.6%, which increased to 43.4% when CEUS-based BI-RADS 4A was used as the cut-off point to recommend biopsy. The simulated biopsy rate decreased to 73.4%. Overall, in this preselected BI-RADS 4 population, only 2.5% (12/486) of malignant lesions would have been miscategorized as BI-RADS 3 using CEUS-based reclassification. The diagnostic accuracy, sensitivity, and specificity of contrast-enhanced ultrasound reclassification were 57.65%, 97.53%, and 38.35%, respectively. CONCLUSION: Our collective findings indicate that CEUS is a valuable tool in further triage of BI-RADS category 4 lesions and facilitates a reduction in the number of biopsies while increasing the cancer-to-biopsy yield.

Nomogram Based on US and Clinicopathologic Characteristics: Axillary Nodal Evaluation Following Neoadjuvant Chemotherapy in Patients With Node-Positive Breast Cancer.

BACKGROUND: To develop a convenient modality to predict axillary response to neoadjuvant chemotherapy (NAC) in breast cancer patients. MATERIALS AND METHODS: In this multi-center study, a total of 1019 breast cancer patients with biopsy-proven positive lymph node (LN) receiving NAC were randomly assigned to the training and validation groups at a ratio of 7:3. Clinicopathologic and ultrasound (US) characteristics of both primary tumors and LNs were used to develop corresponding prediction models, and a nomogram integrating clinicopathologic and US predictors was generated to predict the axillary response to NAC. RESULTS: Axillary pathological complete response (pCR) was achieved in 47.79% of the patients. The expression of estrogen receptor, human epidermal growth factor receptor -2, Ki-67 score, and clinical nodal stage were independent predictors for nodal response to NAC. Location and radiological response of primary tumors, cortical thickness and shape of LNs on US were also significantly associated with nodal pCR. In the validation cohort, the discrimination of US model (area under the curve [AUC], 0.76) was superior to clinicopathologic model (AUC, 0.68); the combined model (AUC, 0.85) demonstrates strong discriminatory power in predicting nodal pCR. Calibration curves of the nomogram based on the combined model demonstrated that substantial agreement can be observed between the predictions and observations. This nomogram showed a false-negative rates of 16.67% in all patients and 10.53% in patients with triple negative breast cancer. CONCLUSION: Nomogram incorporating routine clinicopathologic and US characteristics can predict nodal pCR and represents a tool to aid in treatment decisions for the axilla after NAC in breast cancer patients.

Apoptotic Bodies Derived from Fibroblast-Like Cells in Subcutaneous Connective Tissue Inhibit Ferroptosis in Ischaemic Flaps via the miR-339-5p/KEAP1/Nrf2 Axis.

Preventing and treating avascular necrosis at the distal end of the flaps are critical to surgery success, but current treatments are not ideal. A recent study shows that apoptotic bodies (ABs) generated near the site of apoptosis can be taken up and promote cell proliferation. The study reveals that ABs derived from fibroblast-like cells in the subcutaneous connective tissue (FSCT cells) of skin flaps promoted ischaemic flap survival. It is also found that ABs inhibited cell death and oxidative stress and promoted M1-to-M2 polarization in macrophages. Transcriptome sequencing and protein level testing demonstrated that ABs promoted ischaemic flap survival in endothelial cells and macrophages by inhibiting ferroptosis via the KEAP1-Nrf2 axis. Furthermore, microRNA (miR) sequencing data and in vitro and in vivo experiments demonstrated that ABs inhibited KEAP1 by delivering miR-339-5p to exert therapeutic effects. In conclusion, FSCT cell-derived ABs inhibited ferroptosis, promoted the macrophage M1-to-M2 transition via the miR-339-5p/KEAP1/Nrf2 axis and promoted ischaemic flap survival. These results provide a potential therapeutic strategy to promote ischaemic flap survival by administering ABs.

Global insights into endophytic bacterial communities of terrestrial plants: Exploring the potential applications of endophytic microbiota in sustainable agriculture.

Endophytic microorganisms are indispensable symbionts during plant growth and development and often serve functions such as growth promotion and stress resistance in plants. Therefore, an increasing number of researchers have applied endophytes for multifaceted phytoremediation (e.g., organic pollutants and heavy metals) in recent years. With the availability of next-generation sequencing technologies, an increasing number of studies have shifted the focus from culturable bacteria to total communities. However, information on the composition, structure, and function of bacterial endophytic communities is still not widely synthesized. To explore the general patterns of variation in bacterial communities between plant niches, we reanalyzed data from 1499 samples in 30 individual studies from different continents and provided comprehensive insights. A group of bacterial genera were commonly found in most plant roots and shoots. Our analysis revealed distinct variations in the diversity, composition, structure, and function of endophytic bacterial communities between plant roots and shoots. These variations underscore the sophisticated mechanisms by which plants engage with their endophytic microbiota, optimizing these interactions to bolster growth, health, and resilience against stress. Highlighting the strategic role of endophytic bacteria in promoting sustainable agricultural practices and environmental stewardship, our study not only offers global insights into the endophytic bacterial communities of terrestrial plants but also underscores the untapped potential of these communities as invaluable resources for future research.

Straightforward Creation of Multishell Hollow Hybrids for an Integrated Metabolic Monitoring System in Disease Management.

Multidimensional metabolic analysis has become a new trend in establishing efficient disease monitoring systems, as the constraints associated with relying solely on a single dimension in refined monitoring are increasingly pronounced. Here, coordination polymers are employed as derivative precursors to create multishell hollow hybrids, developing an integrated metabolic monitoring system. Briefly, metabolic fingerprints are extracted from hundreds of serum samples and urine samples, encompassing not only membranous nephropathy but also related diseases, using high-throughput mass spectrometry. With optimized algorithm and initial feature selection, the established combined panel demonstrates enhanced accuracy in both subtype differentiation (over 98.1%) and prognostic monitoring (over 95.6%), even during double blind test. This surpasses the serum biomarker panel (≈90.7% for subtyping, ≈89.7% for prognosis) and urine biomarker panel (≈94.4% for subtyping, ≈76.5% for prognosis). Moreover, after attempting to further refine the marker panel, the blind test maintains equal sensitivity, specificity, and accuracy, showcasing a comprehensive improvement over the single-fluid approach. This underscores the remarkable effectiveness and superiority of the integrated strategy in discriminating between MN and other groups. This work has the potential to significantly advance diagnostic medicine, leading to the establishment of more effective strategies for patient management.

Study on the Thermal Stability of the Sweet-Tasting Protein Brazzein Based on Its Structure-Sweetness Relationship.

Brazzein (Brz) is a sweet-tasting protein composed of 54 amino acids and is considered as a potential sugar substitute. The current methods for obtaining brazzein are complicated, and limited information is available regarding its thermal stability. In this study, we successfully expressed recombinant brazzein, achieving a sweetness threshold of 15.2 µg/mL. Subsequently, we conducted heat treatments at temperatures of 80, 90, 95, and 100 °C for a duration of 2 h to investigate the structural changes in the protein. Furthermore, we employed hydrogen-deuterium exchange coupled to mass spectrometry (HDX-MS) to analyze the effect of heating on the protein structure-sweetness relationships. Our results indicated that the thermal inactivation process primarily affects residues 6-14 and 36-45 of brazzein, especially key residues Tyr8, Tyr11, Ser14, Glu36, and Arg43, which are closely associated with its sweetness. These findings have significant implications for improving the thermal stability of brazzein.

Phosphocholine-induced energy source shift alleviates mitochondrial dysfunction in lung cells caused by geospecific PM2.5 components.

Fine particulate matter (PM2.5) is globally recognized for its adverse implications on human health. Yet, remain limited the individual contribution of particular PM2.5 components to its toxicity, especially considering regional disparities. Moreover, prevention solutions for PM2.5-associated health effects are scarce. In the present study, we comprehensively characterized and compared the primary PM2.5 constituents and their altered metabolites from two locations: Taiyuan and Guangzhou. Analysis of year-long PM2.5 samples revealed 84 major components, encompassing organic carbon, elemental carbon, ions, metals, and organic chemicals. PM2.5 from Taiyuan exhibited higher contamination, associated health risks, dithiothreitol activity, and cytotoxicities than Guangzhou's counterpart. Applying metabolomics, BEAS-2B lung cells exposed to PM2.5 from both cities were screened for significant alterations. A correlation analysis revealed the metabolites altered by PM2.5 and the critical toxic PM2.5 components in both regions. Among the PM2.5-down-regulated metabolites, phosphocholine emerged as a promising intervention for PM2.5 cytotoxicities. Its supplementation effectively attenuated PM2.5-induced energy metabolism disorder and cell death via activating fatty acid oxidation and inhibiting Phospho1 expression. The highlighted toxic chemicals displayed combined toxicities, potentially counteracted by phosphocholine. Our study offered a promising functional metabolite to alleviate PM2.5-induced cellular disorder and provided insights into the geo-based variability in toxic PM2.5 components.

Effect of early dexamethasone on outcomes of COVID-19: A quasi-experimental study using propensity score matching.

BACKGROUND: The RECOVERY trial demonstrated that the use of dexamethasone is associated with a 36% lower 28-day mortality in hospitalized patients with COVID-19 on invasive mechanical ventilation. Nevertheless, the optimal timing to start dexamethasone remains uncertain. METHODS: We conducted a quasi-experimental study at National Taiwan University Hospital (Taipei, Taiwan) using propensity score matching to simulate a randomized controlled trial to receive or not to receive early dexamethasone (6 mg/day) during the first 7 days following the onset of symptoms. Treatment was standard protocol-based, except for the timing to start dexamethasone, which was left to physicians' decision. The primary outcome is 28-day mortality. Secondary outcomes include secondary infection within 60 days and fulfilling the criteria of de-isolation within 20 days. RESULTS: A total of 377 patients with COVID-19 were enrolled. Early dexamethasone did not decrease 28-day mortality in all patients (adjusted odds ratio [aOR], 1.03; 95% confidence interval [CI], 0.97-1.10) or in patients who required O2 for severe/critical disease at admission (aOR, 1.05; 95%CI, 0.94-1.18); but is associated with a 24% increase in superinfection in all patients (aOR, 1.24; 95% CI, 1.12-1.37) and a 23% increase in superinfection in patients of O2 for several/critical disease at admission (aOR, 1.23; 95% CI, 1.02-1.47). Moreover, early dexamethasone is associated with a 42% increase in likelihood of delayed clearance of SARS-CoV-2 virus (adjusted hazard ratio, 1.42; 95% CI, 1.01-1.98). CONCLUSION: An early start of dexamethasone (within 7 days after the onset of symptoms) could be harmful to hospitalized patients with COVID-19.

Designed Directional Growth of Ti-Metal-Organic Frameworks for Decoding Alzheimer's Disease-Specific Exosome Metabolites.

Exosomes, a growing focus for liquid biopsies, contain diverse molecular cargos. In particular, exosome metabolites with valuable information have exhibited great potential for improving the efficiency of liquid biopsies for addressing complex medical conditions. In this work, we design the directional growth of Ti-metal-organic frameworks on polar-functionalized magnetic particles. This design facilitates the rapid synergistic capture of exosomes with the assistance of an external magnetic field and additionally synergistically enhances the ionization of their metabolites during mass spectrometry detection. Benefiting from this dual synergistic effect, we identified three high-performance exosome metabolites through the differential comparison of a large number of serum samples from individuals with Alzheimer's disease (AD) and normal cognition. Notably, the accuracy of AD identification ranges from 93.18 to 100% using a single exosome metabolite and reaches a flawless 100% with three metabolites. These findings emphasize the transformative potential of this work to enhance the precision and reliability of AD diagnosis, ushering in a new era of improved diagnostic accuracy.

Physicochemical Quantitative Analysis of the Oil-Water Interface as Affected by the Mutual Interactions between Pea Protein Isolate and Mono- and Diglycerides.

As a commercially available ingredient, the mono- and diglycerides (MDG) were widely used in a plant protein-based emulsion to provide effective, functional, emulsifying properties. The simultaneous addition of the MDG and pea protein isolate (PPI) was investigated by the methods of interfacial rheology and quantitative protein proteomics. The physicochemical quantitative analysis of the oil-water interface revealed an interfacial stability mechanism for the protein adsorption layer. For a low MDG concentration, the interfacial quantities of vicilin and albumin were increased, which could be attributed to the adsorption rate. For a high MDG concentration, both vicilin and albumin were displaced by MDG and desorbed from the interface, while legumin was more difficult to displace due to its slow adsorption and the complex structure of protein molecules. The protein molecules with the structural rearrangement interacted with MDG, exhibiting potential effects on the interfacial film structure. Combined with some nanotechnologies, the new comprehension of protein-emulsifier interactions may promote food delivery systems. The research aims to develop an in-depth analysis of interfacial proteins, and provide more innovative and tailored functionalities for the application of the plant protein emulsion.

Formulations and assessments of structure, physical properties, and sensory attributes of soy yogurts: Effect of carboxymethyl cellulose content and degree of substitution.

Soy yogurts present challenges, including absence of tender and slipperiness mouthfeel, and poor stability. This study aimed to investigate the impacts of carboxymethyl cellulose (CMC) with degrees of substitution of 0.7 (CMC0.7) and 1.2 (CMC1.2) at concentrations ranging from 0 % to 1.1 % on the stability, microstructure, rheology, tribology, and mouthfeel of soy yogurts. As the CMC concentration increased from 0 % to 0.3 %, soy yogurts displayed a coarser microstructure, decreased stability, and increased gel strength. As the concentration of CMC further increased from 0.5 % to 1.1 %, soy yogurts exhibited trends of a smoother microstructure, increased stability, and softer gel strength. Notably, soy yogurts with CMC0.7 demonstrated a superior water holding capacity (WHC) than soy yogurts with CMC1.2. Tribological measurements indicated that soy yogurts with CMC0.7 at a 0.7 % concentration had the lowest coefficient of friction (COF) value among most sliding speeds, showing a 23 % reduction compared to soy yogurts without CMC at a sliding speed of 10 mm/s. Moreover, sensory evaluation showed that soy yogurts with CMC0.7 at a 0.7 % concentration had the highest total score in mouthfeel evaluation. Therefore, the addition of CMC0.7 within the concentration range of 0.5 % to 1.1 % may produce stable and delicate yogurts.

Expression of Ice Nucleation Protein in Bacillus amyloliquefaciens and Its Application in Food Freezing Process.

To produce food-grade ice nucleators, a 3.77 kb ice nucleation gene (iceE) isolated from Pantoea agglomerans (Erwinia herbicola) was introduced into the Gram-positive microorganism Bacillus amyloliquefaciens for the first time. The differential scanning calorimetry (DSC) results indicated that recombined strain B9-INP was an effective ice nucleator for controlling the supercooling point of distilled water at low concentrations. In the presence of B9-INP cells, model food systems, including sucrose solution and sodium chloride solution, different pH solutions froze at a relatively high subzero temperature, thus increasing the supercooling point by 5.8~16.7 °C. Moreover, B9-INP also facilitated model and real food systems to freeze at -6 °C. This recombinant strain not only improved the freezing temperature of food systems but also shortened the total freezing time, thus saving energy and reducing consumption. The results suggest that B9-INP has great application potential in the frozen food industry.