Xylose Metabolism Perturbation in Yarrowia lipolytica for Efficient Succinic Acid Bioproduction from Lignocellulosic Biomass.

Lignocellulosic biomass is a sustainable feedstock for biorefineries, but inefficient xylose utilization limits microbial bioproduction. Here, the oleaginous yeast Yarrowia lipolytica was engineered to produce succinic acid (SA) from xylose by resolving metabolic and regulatory conflicts. Initial overexpression of xylose catabolic genes (XR, XDH, XK) in an SA-hyperproducing strain did not activate xylose utilization, indicating underlying cryptic constraints.

Radiomics-clinical integration guides prophylactic cranial irradiation decisions in limited-stage small cell lung cancer: a brain metastasis risk stratification model.

Background: Limited-stage small-cell lung cancer (LS-SCLC) is highly aggressive and prone to brain metastasis (BM). Early identification of BM risk is crucial for devising personalized prophylactic cranial irradiation (PCI) strategies. This study aimed to develop a multimodal model integrating radiomic and clinical features to stratify BM risk in LS-SCLC patients and guide personalized PCI strategies.

Novel Umami Peptides from : Evaluation of the Umami Enhancing Effect Using Biosensors and Molecular Simulation.

are edible fungi with a unique aroma and umami flavor. The current study sought to identify novel umami peptides in while investigating their umami-enhancing properties. We conducted a virtual screening of 12 potential umami peptides from the ultrasound-assisted hydrolysate of , and five potential umami peptides were finally obtained.

Relative Binding Free Energy Methods Based on the Alchemical Transformation Framework: An Effective Strategy for Predicting the Umami Recognition Threshold of Umami Peptide Derivatives.

Umami peptides integrating both flavor and nutritional properties possess numerous derivatives that pose challenges for prediction using absolute free energy prediction tools and peptide classification models. While relative binding free energy (RBFE) methods based on the alchemical transformation framework have demonstrated excellent performance in drug activity prediction, their application in taste activity prediction remains unexplored. Through scientific literature analysis, 611 umami peptides and derivatives were systematically organized and cataloged with their structures and recognition thresholds then clustered into eight clusters.

Engineering of CO recycling and formate metabolism for succinic acid production in Yarrowia lipolytica.

Succinic acid (SA), a key platform chemical in biorefineries, faces industrial production challenges stemming from inefficient CO fixation and redox imbalances in microbial cell factories. Here, we report a novel strategy to enhance SA biosynthesis in unconventional yeast Yarrowia lipolytica by cooperatively integrating carbonic anhydrase (CA)-mediated CO recycling with formate metabolism. Initially, the expression of CA improved the carboxylation efficiency of reductive TCA (rTCA) pathway, resulting in the strain Hi-SA-YlCA, which produced 89.

Machine learning discrimination of quality grades of base liquor integrating GC-TOF/MS and GC-IMS data analysis: Case study of strong-flavor Chinese baijiu.

The flavor of base liquor is critical to the grading quality of Baijiu. This study focuses on the base liquor grades of five different strong-flavor Baijiu brands. Headspace Solid-phase Microextraction Gas Chromatography Time-of-flight Mass spectrometry (HS-SPME-GC-TOF/MS) and Headspace Gas Chromatography Ion Mobility Spectrometry (HS-GC-IMS) identified 313 and 188 compounds respectively.

Umami_IP: An integrated model and explanatory analysis for quantitative prediction of Umami recognition threshold.

Umami peptides have gained considerable attention due to high nutritional value and distinct flavor. However, because of experimental complexity and time cost, the identification of umami peptides encounters obstacles. Based on the recognition threshold documented in TastePeptidesDB (http://tastepeptides-meta.

Expanding the genetic toolkit of Yarrowia lipolytica: Dynamic promoter engineering enables high-titer biosynthesis of 3-hydroxypropionic acid.

The oleaginous yeast Yarrowia lipolytica has emerged as a promising microbial chassis for biosynthesis of platform chemicals such as 3-hydroxypropionic acid (3-HP). However, its industrial potential has been limited by the scarcity of precisely regulated genetic tools. To address this gap, we developed a comprehensive promoter toolkit for Y.

TastePeptides-Meta: A One-Stop Platform for Taste Peptides and Their Structural Derivatives, Including Taste Properties, Interactions, and Prediction Models.

Taste peptides have nutritional and sensory properties, and their structural derivatives show unique taste modulation effects. The increasing number of taste peptide candidates requires a fast and accurate screening methodology using advanced detection tools. Notably, existing platforms lack integrated bioinformatics solutions to provide accurate retrieval and prediction capabilities.

Umami peptide synergy unveiled: A comprehensive study from molecular simulation to practical validation of sensing strategy.

Synergistic effect is one of the main properties of umami substances, as a new natural umami agent, umami peptide synergy has not been systematically explored. Presently, conventional methods relying on human sensory evaluation and intelligent instrument analysis pose challenges due to their time-consuming and lack of high throughput. This research provides a detailed molecular-level understanding of multiple umami peptides interact with T1R1-VFT simultaneous, revealing that multiple umami peptides promotes stronger binding affinity and more effective receptor activation (from -7.

Chitin nanocrystal-reinforced chitin/collagen composite hydrogels for annulus fibrosus repair after discectomy.

Discectomy is a widely utilized approach for alleviating disc herniation; however, effective repair of postoperative annulus fibrosus (AF) defects remains a significant challenge. This study introduces a hydrogel patch with enhanced mechanical properties for AF repair fabricated using chitin (Ch), collagen (Col), and chitin nanocrystals (ChNCs) through a freeze-thaw cycling technique. The Ch and Col components constitute the matrix of the hydrogel patch, while uniformly dispersed ChNCs act as a nanofiller, markedly improving the mechanical performance (compression strain: 95 %; compression modulus: 0.

A dataset for cyber threat intelligence modeling of connected autonomous vehicles.

Cyber attacks pose significant threats to connected autonomous vehicles in intelligent transportation systems. Cyber threat intelligence (CTI), which involves collecting and analyzing cyber threat information, offers a promising approach to addressing emerging vehicle cyber threats and enabling proactive security defenses. Obtaining valuable information from enormous cybersecurity data using knowledge extraction technologies to achieve CTI modeling is an effective means to ensure automotive cybersecurity.

Fruit wines classification enabled by combing machine learning with comprehensive volatiles profiles of GC-TOF/MS and GC-IMS.

Fruit wines, produced through the fermentation of various fruits, are well-documented for their distinct flavor profiles. Intelligent sensory analysis, GC-TOF/MS and GC-IMS were used for the analysis of the volatile profile of eight types of fruit wines including 5 grape wine (SJ, LS, HY, TJ, FT), 1 fermented plum wine (FZ), 1 blueberry wine (HZ), as well as 1 configured plum wine (LM). A total of 281 compounds were identified through GC-TOF/MS, with esters and acids constituting over 80% of all samples.

Isolation, purification and identification of antibacterial peptides from Jinhua ham broth and molecular simulation analyses of their interaction with bacterial porins.

The bioactive peptides in Jinhua ham could be released into the broth during cooking. After comparing peptide antibacterial activity from Jinhua ham broth with varying cooking durations, the cooking-2-h broths were selected for further analysis using cation-exchange and reverse-phase-liquid chromatography. The purified peptide sequences were subsequently synthesized and tested for their antibacterial activity.

Artificial intelligence and food flavor: How AI models are shaping the future and revolutionary technologies for flavor food development.

The food flavor science, traditionally reliant on experimental methods, is now entering a promising era with the help of artificial intelligence (AI). By integrating existing technologies with AI, researchers can explore and develop new flavor substances in a digital environment, saving time and resources. More and more research will use AI and big data to enhance product flavor, improve product quality, meet consumer needs, and drive the industry toward a smarter and more sustainable future.

Preparation of Microelectrolysis Filler Using Coal Slag for the Removal of Hazardous Substances in Contaminated Water.

Presently, the utilization of gasification slag in the context of wastewater treatment is constrained. Furthermore, the presence of dye wastewater and wastewater containing hazardous metals represents a significant threat to human health. Accordingly, the present study prepared a microelectrolytic filler (MF) from gasification slag via a high-temperature roasting method and evaluated its degradation performance in water containing organic matter and harmful metal ions.

Real-time accident anticipation for autonomous driving through monocular depth-enhanced 3D modeling.

The primary goal of traffic accident anticipation is to foresee potential accidents in real time using dashcam videos, a task that is pivotal for enhancing the safety and reliability of autonomous driving technologies. In this study, we introduce an innovative framework, AccNet, which significantly advances the prediction capabilities beyond the current state-of-the-art 2D-based methods by incorporating monocular depth cues for sophisticated 3D scene modeling. Addressing the prevalent challenge of skewed data distribution in traffic accident datasets, we propose the Binary Adaptive Loss for Early Anticipation (BA-LEA).

[Advances in synthesis of succinic acid using yeast cell factories].

Succinic acid is an important C4 platform compound that serves as a raw material for the production of 1,4-butanediol, tetrahydrofuran, and biodegradable plastics such as polybutylene succinate (PBS). Compared to the traditional petrochemical-based route that uses maleic anhydride as a raw material, the microbial fermentation method for producing succinic acid offers more sustainable economic value and environmental friendliness. Yeasts with good acid tolerance can achieve low-pH fermentation of succinic acid, significantly reducing the cost of product extraction.

Sustainable succinic acid production from lignocellulosic hydrolysates by engineered strains of Yarrowia lipolytica at low pH.

Succinic acid (SA) is a valuable C4 platform chemical with diverse applications. Lignocellulosic biomass represents an abundant and renewable carbon resource for microbial production of SA. However, the presence of toxic compounds in pretreated lignocellulosic hydrolysates poses challenges to cell metabolism, leading to inefficient SA production.

Novel Umami Peptides from Mushroom () and Their Umami Enhancing Effect via Virtual Screening and Molecular Simulation.

This study aimed to identify novel umami peptides in and investigate their umami enhancing effect. We virtually screened 155 potential umami peptides from the ultrasound-assisted hydrolysate according to values, iUmami-SCM, Umami_YYDS, and Tastepeptides_DM models, and molecular docking. Five peptides (AGKNTNGSQF, DEAVARGATF, REESDFQSSF, SEETTTGVHH, and WNNDAFQSSTN) were synthesized for sensory evaluation and kinetic analysis.

A β-Primeverosidase-like Enzyme in Soybean [ (L.) Merr] Hypocotyls: Specificity toward 1-Octen-3-yl and 3-Octanyl β-Primeverosides.

A novel β-primeverosidase-like enzyme, originating from the hypocotyl of soybeans, was isolated and characterized. This enzyme, with an estimated molecular weight of 44 kDa, was identified as a monomer and exhibited peak activity at 55 °C and pH 5.5.

From Molecular Dynamics to Taste Sensory Perception: A Comprehensive Study on the Interaction of Umami Peptides with the T1R1/T1R3-VFT Receptor.

The research on the umami receptor-ligand interaction is crucial for understanding umami perception. This study integrated molecular simulations, sensory evaluation, and biosensor technology to analyze the interaction between umami peptides and the umami receptor T1R1/T1R3-VFT. Molecular dynamics simulations were used to investigate the dissociation process of seven umami peptides with the umami receptor T1R1/T1R3-VFT, and by calculating the potential mean force curve using the Jarzynski equation, it was found that the binding free energy of umami peptide is between -58.