Recent advances in enzymatic modification techniques to improve the quality of flour-based fried foods.

Flour-based fried foods are among the most commonly consumed foods worldwide. However, the sensory attributes and nutritional value of fried foods are inconsistent and unstable. Therefore, the creation of fried foods with desirable sensory attributes and good nutritional value remains a major challenge for the development of the fried food industry. The quality of flour-based fried foods can sometimes be improved by physical methods and the addition of chemical modifiers. However, enzyme modification is widely accepted by consumers due to its unique advantages of specificity, mild processing conditions and high safety. Therefore, it is important to elucidate the effects of enzyme treatments on the sensory attributes (color, flavor and texture), oil absorption and digestibility of flour-based fried foods. This paper reviews recent research progress in utilizing enzyme modification to improve the quality of flour-based fried foods. This paper begins with the effects of common enzymes on the physicochemical properties (rheological property, retrogradation property and specific volume) of dough. Based on the analysis of the mechanism of formation of sensory attributes and nutritional properties, it focuses on the application of amylase, protease, transglutaminase, and lipase in the regulation of sensory attributes and nutritional properties of flour-based fried foods.

Progress in using cross-linking technologies to increase the thermal stability of colloidal delivery systems.

In recent years, crosslinking technology has been found and widely used in food, textile, pharmaceutical, bioengineering and other fields. Crosslinking is a reaction in which two or more molecules bond to each other to form a stable three-dimensional network structure to improve the strength, heat resistance and other properties of substances. The researchers found that the cross-linking technology has a significant effect on improving the thermal stability of the colloidal delivery system. In this paper, crosslinking techniques that can be used to improve the thermal stability of colloidal delivery systems are reviewed, including enzyme-, ion-, chemical-, and combined cross-linking. Initially, the underlying mechanisms of these crosslinking technologies is reviewed. Then, the impacts of crosslinking on the heat-stability of colloidal delivery systems are discussed. Finally, the application of crosslinked delivery systems in improving the thermal stability of probiotics, polyphenols, pigments, and nutrients in foods and food packaging materials is introduced. The ability of proteins and polysaccharides to form heat-stable colloidal delivery systems can be improved by crosslinking. Nevertheless, more research is required to establish the impact of different crosslinking on the thermal stability of a broader range of different delivery systems, as well as to ensure their safety and efficacy.

Review of formation mechanisms and quality regulation of chewiness in staple foods: Rice, noodles, potatoes and bread.

Staple foods serve as vital nutrient sources for the human body, and chewiness is an essential aspect of food texture. Age, specific preferences, and diminished eating functions have broadened the chewiness requirements for staple foods. Therefore, comprehending the formation mechanism of chewiness in staple foods and exploring approaches to modulate it becomes imperative. This article reviewed the formation mechanisms and quality control methods for chewiness in several of the most common staple foods (rice, noodles, potatoes and bread). It initially summarized the chewiness formation mechanisms under three distinct thermal processing methods: water medium, oil medium, and air medium processing. Subsequently, proposed some effective approaches for regulating chewiness based on mechanistic changes. Optimizing raw material composition, controlling processing conditions, and adopting innovative processing techniques can be utilized. Nonetheless, the precise adjustment of staple foods' chewiness remains a challenge due to their diversity and technical study limitations. Hence, further in-depth exploration of chewiness across different staple foods is warranted.

Effect of magnetic fields on the structure, properties, baking performance of frozen wheat dough at different frozen stage.

As an emerging physical technology, magnetic fields have been used to improve the quality of frozen and refrigerated foods. This study compared the effect of applying a static magnetic field (2 mT) at different stages of freezing and storage on the quality of frozen dough. Results suggested that the magnetic field significantly impacted frozen dough quality. It not only prevented the formation of ice crystals during the pre-freezing stage but also inhibited ice crystal growth during the following frozen storage. This effect helped to maintain the integrity of gluten proteins and their adhesion to starch granules by preventing the breakage of disulfide bonds and the depolymerization of gluten macromolecules. It was also observed that yeast inactivation and glutathione release were reduced, resulting in improved air retention and air production capacity of the dough. This, in turn, led to a more appealing volume and texture quality of the finished bread.

Tailor-Made α-Glucans by Engineering the Processivity of α-Glucanotransferases via Tunnel-Cleft Active Center Interconversions.

The function of polysaccharides is intimately associated with their size, which is largely determined by the processivity of transferases responsible for their synthesis. A tunnel active center architecture has been recognized as a key factor that governs processivity of several glycoside hydrolases (GHs), e.g., cellulases and chitinases. Similar tunnel architecture is also observed in the Limosilactobacillus reuteri 121 GtfB (Lr121 GtfB) α-glucanotransferase from the GH70 family. The molecular element underpinning processivity of these transglucosylases remains underexplored. Here, we report the synthesis of the smallest (α1 → 4)-α-glucan interspersed with linear and branched (α1 → 6) linkages by a novel 4,6-α-glucanotransferase from L. reuteri N1 (LrN1 GtfB) with an open-clefted active center instead of the tunnel structure. Notably, the loop swapping engineering of LrN1 GtfB and Lr121 GtfB based on their crystal structures clarified the impact of the loop-mediated tunnel/cleft structure at the donor subsites -2 to -3 on processivity of these α-glucanotransferases, enabling the tailoring of both product sizes and substrate preferences. This study provides unprecedented insights into the processivity determinants and evolutionary diversification of GH70 α-glucanotransferases and offers a simple route for engineering starch-converting α-glucanotransferases to generate diverse α-glucans for different biotechnological applications.

Pea protein/carboxymethyl cellulose complexes prepared using a pH cycle strategy as stabilizers of high internal phase emulsions for 3D printing.

The development of food-grade high internal phase emulsions (HIPEs) for 3D printing and the replacement of animal fats have attracted considerable attention. In this study, in order to improve the rheological properties and stability of pea protein to prepare HIPE, pea protein/carboxymethyl cellulose (pH-PP/CMC) was prepared and subjected to pH cycle treatment to produce HIPEs. The results showed that pH cycle treatment and CMC significantly reduced the droplet size of HIPEs (from 143.33 to 12.10 µm). At higher CMC concentrations, the interfacial tension of the PP solution decreased from 12.84 to 11.71 mN/m without pH cycle treatment and to 10.79 mN/m with pH cycle treatment. The HIPEs with higher CMC concentrations subjected to pH cycle treatment showed shear thinning behavior and higher viscoelasticity and recovered their solid-like properties after being subjected to 50 % strain, indicating that they could be used for 3D printing. The 3D printing results showed that the pH-PP/CMC HIPE with 0.3 % CMC had the finest structure. Our work provides new insights into developing food-grade HIPEs and facilitating their use in 3D printing inks as nutrient delivery systems and animal fat substitutes.

Dynamic Mechanism of Cerebral Venous Disruption: Longitudinal Evidence From a Community-Based Cohort.

BACKGROUND: This study aims to investigate the temporal and spatial patterns of structural brain injury related to deep medullary veins (DMVs) damage. METHODS AND RESULTS: This is a longitudinal analysis of the population-based Shunyi cohort study. Baseline DMVs numbers were identified on susceptibility-weighted imaging. We assessed vertex-wise cortex maps and diffusion maps at both baseline and follow-up using FSL software and the longitudinal FreeSurfer analysis suite. We performed statistical analysis of global measurements and voxel/vertex-wise analysis to explore the relationship between DMVs number and brain structural measurements. A total of 977 participants were included in the baseline, of whom 544 completed the follow-up magnetic resonance imaging (age 54.97±7.83 years, 32% men, mean interval 5.56±0.47 years). A lower number of DMVs was associated with a faster disruption of white matter microstructural integrity, presented by increased mean diffusivity and radial diffusion (ß=0.0001 and SE=0.0001 for both, P=0.04 and 0.03, respectively), in extensive deep white matter (threshold-free cluster enhancement P<0.05, adjusted for age and sex). Of particular interest, we found a bidirectional trend association between DMVs number and change in brain volumes. Specifically, participants with mild DMVs disruption showed greater cortical enlargement, whereas those with severe disruption exhibited more significant brain atrophy, primarily involving clusters in the frontal and parietal lobes (multiple comparison corrected P<0.05, adjusted for age, sex, and total intracranial volume). CONCLUSIONS: Our findings posed the dynamic pattern of brain parenchymal lesions related to DMVs injury, shedding light on the interactions and chronological roles of various pathological mechanisms.

Predicting Invasiveness of Lung Adenocarcinoma at Chest CT with Deep Learning Ternary Classification Models.

Background Preoperative discrimination of preinvasive, minimally invasive, and invasive adenocarcinoma at CT informs clinical management decisions but may be challenging for classifying pure ground-glass nodules (pGGNs). Deep learning (DL) may improve ternary classification. Purpose To determine whether a strategy that includes an adjudication approach can enhance the performance of DL ternary classification models in predicting the invasiveness of adenocarcinoma at chest CT and maintain performance in classifying pGGNs. Materials and Methods In this retrospective study, six ternary models for classifying preinvasive, minimally invasive, and invasive adenocarcinoma were developed using a multicenter data set of lung nodules. The DL-based models were progressively modified through framework optimization, joint learning, and an adjudication strategy (simulating a multireader approach to resolving discordant nodule classifications), integrating two binary classification models with a ternary classification model to resolve discordant classifications sequentially. The six ternary models were then tested on an external data set of pGGNs imaged between December 2019 and January 2021. Diagnostic performance including accuracy, specificity, and sensitivity was assessed. The χ2 test was used to compare model performance in different subgroups stratified by clinical confounders. Results A total of 4929 nodules from 4483 patients (mean age, 50.1 years ± 9.5 [SD]; 2806 female) were divided into training (n = 3384), validation (n = 579), and internal (n = 966) test sets. A total of 361 pGGNs from 281 patients (mean age, 55.2 years ± 11.1 [SD]; 186 female) formed the external test set. The proposed strategy improved DL model performance in external testing (P < .001). For classifying minimally invasive adenocarcinoma, the accuracy was 85% and 79%, sensitivity was 75% and 63%, and specificity was 89% and 85% for the model with adjudication (model 6) and the model without (model 3), respectively. Model 6 showed a relatively narrow range (maximum minus minimum) across diagnostic indexes (accuracy, 1.7%; sensitivity, 7.3%; specificity, 0.9%) compared with the other models (accuracy, 0.6%-10.8%; sensitivity, 14%-39.1%; specificity, 5.5%-17.9%). Conclusion Combining framework optimization, joint learning, and an adjudication approach improved DL classification of adenocarcinoma invasiveness at chest CT. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Sohn and Fields in this issue.

Improving structural and functional properties of starch-catechin-based green nanofiber mats for active food packaging by electrospinning and crosslinking techniques.

The hydrophilic and low mechanical properties limited the application of starch-based films. In this work, a hydrophobic starch-based nanofiber mat was first successfully prepared from aqueous solution at room temperature by using electrospinning and glutaraldehyde (GTA) vapor phase crosslinking techniques for active packaging applications. Catechin (CAT) was immobilized in the nanofibers by electrospinning, resulting in higher thermal stability (Tdmax = 315.23 °C), antioxidant (DPPH scavenging activity = 94.31 ± 2.70 %) and antimicrobial (inhibition zone diameter = 15.6 ± 0.3 mm) of the fibers, which further demonstrated hydrogen bonding and electrostatic interaction between CAT and fibers. Nanofibers after GTA vapor phase crosslinking exhibited enhanced hydrophobicity (water contact angle: 15.6 ± 1.5° â†’ 93.5 ± 2.3°) and mechanical properties (tensile strength: 1.82 ± 0.06 MPa â†’ 7.64 ± 0.24 MPa, elastic modulus: 19.35 ± 0.63 MPa â†’ 45.34 ± 0.51 MPa). The results demonstrated that preparation of starch-based electrospun nanofiber mats in aqueous system at room temperature overcame the challenges of organic solvent pollution and thermosensitive material encapsulation, while GTA vapor phase crosslinking technique improved the hydrophobicity and mechanical properties of nanofiber mats, which facilitated the application of starch-based materials in the field of packaging.

An effective preserving strategy for strawberries by constructing pectin/starch coatings reinforced with functionalized eggshell fillers.

Food waste occurs frequently worldwide, though hunger and malnutrition issues have received global attention. Short-term spoilage of perishable foods causes a significant proportion of food waste. Developing simple, green, and low-cost strategies to preserve the freshness of perishable foods is important to address this issue and improving food safety. By using strawberries as the model perishable fruit, this study reported a pectin/carboxy methyl starch sodium (PC) based coating using epigallocatechin gallate-loaded eggshell powder (ES@EGCG) as the functional fillers. In comparison to PC coating, the PC-ES@EGCG coating displayed much-enhanced performance, such as enhanced mechanical (2 folds) and barrier (water vapor & oxygen) properties. This composite coating reduced the weight loss of strawberries from over 60% to around 30% after 7-day storage. Coated strawberries exhibit better freshness retention, which achieves the purpose of preserving strawberries during storage. This study provided a cost-effective and eco-friendly coating strategy for reducing food waste.

Fabrication and characterization of polydopamine-mediated zein-based nanoparticle for delivery of bioactive molecules.

In this study, a combination of whey protein (hydrophilic coating) and polydopamine (crosslinking agent) was used to improve the stability and functionality of quercetin-loaded zein nanoparticles. There are two key benefits of the core-shell nanoparticles formed. First, the ability of the polydopamine to bind to both zein and whey protein facilitates the formation of a stable core-shell structure, thereby protecting quercetin from any pro-oxidants in the aqueous surroundings. Second, neutral and hydrophilic whey proteins were used for the surface coating of the nanoparticles to further enhance the sustained and slow release of quercetin, facilitating its sustained release into the body at a slow and steady rate. The results of this study will promote the innovative development of precise nutritional delivery systems for zein and provide a theoretical basis for the design and development of dietary supplements based on hydrophobic food nutrient molecules.

Effect of different molecular weight ß-glucan hydrated with highland barley protein on the quality and in vitro starch digestibility of whole wheat bread.

Whole wheat bread has high nutritional value, but it has inferior baking quality and high glycemic index, which needs to be improved by methods such as adding protein and ß-glucan. This study investigated the effects of ß-glucan and highland barley protein of different molecular weights (2 × 104, 1 × 105, and 3 × 105 Da) and different hydrate methods (pre-hydrate and not pre-hydrate) on the characteristics of whole wheat dough and bread. The mixing properties and rheological properties demonstrated that ß-glucan pre-hydrated with highland barley protein were able to reduce the dough tan δ, reduce the dough viscoelasticity, while enhance the gluten network structure and dough deformation resistance. Compared to the control sample, the medium molecular weight pre-hydrate bread had a better specific volume of 3.21 mL/g, lower hardness of 527.28 g. In vitro starch digestion characteristics and ATR-FTIR showed that low and high molecular weight pre-hydrate increased the short-range ordered structure of starch and reduced the starch digestibility, while not pre-hydrated medium molecular weight hydrate had the lowest level of starch digestibility.

Diagnosis of a Familial Psittacosis Outbreak with Clinical Analysis and Metagenomic Next-Generation Sequencing Under COVID-19: A Case Series.

Purpose: To explore the clinical characteristics, diagnosis, and treatment of family outbreak of psittacosis and to improve the success rate of treatment. Patients and Methods: The clinical characteristics, diagnosis, treatment, and outcome of family outbreak of psittacosis, which consists three patients, diagnosed by clinical analysis and metagenomic next-generation sequencing (mNGS) in our hospital were analyzed retrospectively. Results: We report on three instances of clustered atypical pneumonia, which were caused by Chlamydia psittaci during the COVID-19 pandemic. All patients exhibited symptoms of fever and cough, while one patient also experienced gastrointestinal symptoms such as nausea, vomiting, and diarrhea. Laboratory tests indicated no significant increase in leukocytes and neutrophils, but a mild increase in C-reactive protein was observed in all three patients. Chest computed tomography (CT) scans revealed a consolidation shadow in a unilateral lung lobe in all three patients. Both patients were treated with empirical moxifloxacin, yielding unsatisfactory outcomes. mNGS was conducted on sputum samples from one adult patient, revealing the presence of Chlamydia psittaci. Additional doxycycline was prescribed immediately, and then the patients' temperatures were stabilized, and the lesion in chest CT was absorbed. The pediatric patient exhibited less severe symptoms compared to the adult patients and exhibited a favorable response to azithromycin administration. Conclusion: This study reports a cluster of a family outbreak of atypical pneumonia caused by C. psittaci in China. The occurrence of a family outbreak during the COVID-19 pandemic may be attributed to familial aggregation resulting from the epidemic. The three cases reported in this study did not experience severe complications, which can be attributed to the prompt medical intervention and swift diagnosis. This finding implies the need to enhance patients' awareness and vigilance towards their health. Additionally, mNGS emerges as a valuable technique for accurately identifying pathogens causing pulmonary infections.

Time-dependent CT score-based model for identifying severe/critical COVID-19 at a fever clinic after the emergence of Omicron variant.

Rationale and objectives: The computed tomography (CT) score has been used to evaluate the severity of COVID-19 during the pandemic; however, most studies have overlooked the impact of infection duration on the CT score. This study aimed to determine the optimal cutoff CT score value for identifying severe/critical COVID-19 during different stages of infection and to construct corresponding predictive models using radiological characteristics and clinical factors. Materials and methods: This retrospective study collected consecutive baseline chest CT images of confirmed COVID-19 patients from a fever clinic at a tertiary referral hospital from November 28, 2022, to January 8, 2023. Cohorts were divided into three subcohorts according to the time interval from symptom onset to CT examination at the hospital: early phase (0-3 days), intermediate phase (4-7 days), and late phase (8-14 days). The binary endpoints were mild/moderate and severe/critical infection. The CT scores and qualitative CT features were manually evaluated. A logistic regression analysis was performed on the CT score as determined by a visual assessment to predict severe/critical infection. Receiver operating characteristic analysis was performed and the area under the curve (AUC) was calculated. The optimal cutoff value was determined by maximizing the Youden index in each subcohort. A radiology score and integrated models were then constructed by combining the qualitative CT features and clinical features, respectively, using multivariate logistic regression with stepwise elimination. Results: A total of 962 patients (aged, 61.7 ± 19.6 years; 490 men) were included; 179 (18.6%) were classified as severe/critical COVID-19, while 344 (35.8%) had a typical Radiological Society of North America (RSNA) COVID-19 appearance. The AUCs of the CT score models reached 0.91 (95% confidence interval (CI) 0.88-0.94), 0.82 (95% CI 0.76-0.87), and 0.83 (95% CI 0.77-0.89) during the early, intermediate, and late phases, respectively. The best cutoff values of the CT scores during each phase were 1.5, 4.5, and 5.5. The predictive accuracies associated with the time-dependent cutoff values reached 88% (vs.78%), 73% (vs. 63%), and 87% (vs. 57%), which were greater than those associated with universal cutoff value (all P < 0.001). The radiology score models reached AUCs of 0.96 (95% CI 0.94-0.98), 0.90 (95% CI 0.87-0.94), and 0.89 (95% CI 0.84-0.94) during the early, intermediate, and late phases, respectively. The integrated models including demographic and clinical risk factors greatly enhanced the AUC during the intermediate and late phases compared with the values obtained with the radiology score models; however, an improvement in accuracy was not observed. Conclusion: The time interval between symptom onset and CT examination should be tracked to determine the cutoff value for the CT score for identifying severe/critical COVID-19. The radiology score combining qualitative CT features and the CT score complements clinical factors for identifying severe/critical COVID-19 patients and facilitates timely hierarchical diagnoses and treatment.

Quantitative MR imaging biomarkers for distinguishing inflammatory pancreatic mass and pancreatic cancer-a systematic review and meta-analysis.

OBJECTIVES: To evaluate the diagnostic performance of quantitative magnetic resonance (MR) imaging biomarkers in distinguishing between inflammatory pancreatic masses (IPM) and pancreatic cancer (PC). METHODS: A literature search was conducted using PubMed, Embase, the Cochrane Library, and Web of Science through August 2023. Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) was used to evaluate the risk of bias and applicability of the studies. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated using the DerSimonian-Laird method. Univariate meta-regression analysis was used to identify the potential factors of heterogeneity. RESULTS: Twenty-four studies were included in this meta-analysis. The two main types of IPM, mass-forming pancreatitis (MFP) and autoimmune pancreatitis (AIP), differ in their apparent diffusion coefficient (ADC) values. Compared with PC, the ADC value was higher in MFP but lower in AIP. The pooled sensitivity/specificity of ADC were 0.80/0.85 for distinguishing MFP from PC and 0.82/0.84 for distinguishing AIP from PC. The pooled sensitivity/specificity for the maximal diameter of the upstream main pancreatic duct (dMPD) was 0.86/0.74, with a cutoff of dMPD ≤ 4 mm, and 0.97/0.52, with a cutoff of dMPD ≤ 5 mm. The pooled sensitivity/specificity for perfusion fraction (f) was 0.82/0.68, and 0.82/0.77 for mass stiffness values. CONCLUSIONS: Quantitative MR imaging biomarkers are useful in distinguishing between IPM and PC. ADC values differ between MFP and AIP, and they should be separated for consideration in future studies. CLINICAL RELEVANCE STATEMENT: Quantitative MR parameters could serve as non-invasive imaging biomarkers for differentiating malignant pancreatic neoplasms from inflammatory masses of the pancreas, and hence help to avoid unnecessary surgery. KEY POINTS: • Several quantitative MR imaging biomarkers performed well in differential diagnosis between inflammatory pancreatic mass and pancreatic cancer. • The ADC value could discern pancreatic cancer from mass-forming pancreatitis or autoimmune pancreatitis, if the two inflammatory mass types are not combined. • The diameter of main pancreatic duct had the highest specificity for differentiating autoimmune pancreatitis from pancreatic cancer.

Design of colloid structure to realize gel salt reduction: a review.

Excessive consumption of salt is associated with increased incidence of cardiovascular diseases, hypertension, diabetes, and other health issues. However, it is challenging to find appropriate strategies that balance sensory qualities while achieving sodium reduction as salt plays a crucial role in providing desired appearance, texture, and taste. The impact of hydrocolloid properties (addition and type) on saltiness perception were reviewed. Additionally, considering the interactions between food components, both covalent and noncovalent, we propose designing specialized colloidal structures capable of binding sodium ions to enhance salt-taste perception. The effects of hydrocolloids on the physicochemical, structural, and sensory qualities of gel foods are then discussed. Finally, by addressing current issues with low-salt foods and consumer demands, we provide a future outlook for low-salt food development. The selection of suitable hydrocolloids and precise control of the addition are crucial considerations for achieving salt reduction. The interaction between hydrocolloids and other food components can be utilized to design specialized colloidal structures, thereby accomplishing gel-based salt reduction and enhancing properties. This review serves as a theoretical reference for developing healthy, nutritious, and flavorful low-salt foods that can aid in the prevention and mitigation of diseases associated with excessive salt consumption.

B1 Power Modification for Amide Proton Transfer Imaging in Parotid Glands: A Strategy for Image Quality Accommodation and Evaluation of Tumor Detection Feasibility.

BACKGROUND: In the application of APTw protocols for evaluating tumors and parotid glands, inhomogeneity and hyperintensity artifacts have remained an obstacle. This study aimed to improve APTw imaging quality and evaluate the feasibility of difference B1 values to detect parotid tumors. METHODS: A total of 31 patients received three APTw sequences to acquire 32 lesions and 30 parotid glands (one patient had lesions on both sides). Patients received T2WI and 3D turbo-spin-echo (TSE) APTw imaging on a 3.0 T scanner for three sequences (B1 = 2 µT, 1 µT, and 0.7 µT in APTw 1, 2, and 3, respectively). APTw image quality was evaluated using four-point Likert scales in terms of integrity and hyperintensity artifacts. Image quality was compared between the three sequences. An evaluable group and a trustable group were obtained for APTmean value comparison. RESULTS: Tumors in both APT2 and APT3 had fewer hyperintensity artifacts than in APT1. With B1 values decreasing, tumors had less integrity in APTw imaging. APTmean values of tumors were higher than parotid glands in traditional APT1 sequence though not significant, while the APTmean subtraction value was significantly different. CONCLUSIONS: Applying a lower B1 value could remove hyperintensity but could also compromise its integrity. Combing different APTw sequences might increase the feasibility of tumor detection.

Insights into the Structure-Function Relationship of GH70 GtfB α-Glucanotransferases from the Crystal Structure and Molecular Dynamic Simulation of a Newly Characterized Limosilactobacillus reuteri N1 GtfB Enzyme.

α-Glucanotransferases of the CAZy family GH70 convert starch-derived donors to industrially important α-glucans. Here, we describe characteristics of a novel GtfB-type 4,6-α-glucanotransferase of high enzyme activity (60.8 U mg-1) from Limosilactobacillus reuteri N1 (LrN1 GtfB), which produces surprisingly large quantities of soluble protein in heterologous expression (173 mg pure protein per L of culture) and synthesizes the reuteran-like α-glucan with (α1 → 6) linkages in linear chains and branch points. Protein structural analysis of LrN1 GtfB revealed the potential crucial residues at subsites -2∼+2, particularly H265, Y214, and R302, in the active center as well as previously unidentified surface binding sites. Furthermore, molecular dynamic simulations have provided unprecedented insights into linkage specificity hallmarks of the enzyme. Therefore, LrN1 GtfB represents a potent enzymatic tool for starch conversion, and this study promotes our knowledge on the structure-function relationship of GH70 GtfB α-glucanotransferases, which might facilitate the production of tailored α-glucans by enzyme engineering in future.

N1019D Mutant of Limosilactobacillus reuteri 121 4,6-α-Glucanotransferase GtfB Significantly Improved Catalytic Activity.

Limosilactobacillus reuteri 121 4,6-α-glucanotransferase GtfB (Lr 121 GtfB), belonging to glycoside hydrolase family 70 (GH70), synthesizes linear isomalto/malto polysaccharides having (α1→6) linkages attached to the nonreducing ends of (α1→4) linked maltose oligosaccharide segments using starch or maltodextrin as a substrate. Since Lr 121 GtfB has low catalytic activity and efficiency, it leads to substrate regeneration and reduced substrate utilization. In this study, we superimposed the crystal structure of Lr 121 GtfB-ΔNΔV with that of L. reuteri NCC 2613 GtfB-ΔNΔV (Lr 2613 GtfB-ΔNΔV) to identify the acceptor binding subsites +1 to +3 and constructed five single-residue mutants and a random mutagenesis of N1019. Compared with the wild-type, N1019D Lr 121 GtfB-ΔN did not alter the product specificity, increased the catalytic activity and efficiency by 420 and 590%, respectively, and maintained >80% relative activity in the pH 3.5-6.5 interval. The findings will contribute to the industrial application of Lr 121 GtfB and provide new solutions for starch synthesis of higher value derivatives.

Association of lower extremity peripheral arterial disease with quantitative muscle features from computed tomography angiography.

OBJECTIVES: To explore the association between lower extremity muscle features from CTA and peripheral arterial disease (PAD) severity using digital subtraction angiography (DSA) as reference standard. METHODS: Informed consent was waived for this Institutional Review Board approved retrospective study. PAD patients were recruited from July 2016 to September 2020. Two radiologists evaluated PAD severity on DSA and CTA using runoff score. The patients were divided into two groups: mild PAD (DSA score ≤ 7) vs. severe PAD (DSA score > 7). After segmenting lower extremity muscles from CTA, 95 features were extracted for univariable analysis, logistic regression model (LRM) analysis, and sub-dataset analysis (PAD prediction based on only part of the images). AUC of CTA score and LRMs for PAD prediction were calculated. Features were analyzed using Student's t test and chi-squared test. p < 0.05 was considered statistically significant. RESULTS: A total of 56 patients (69 ± 11 years; 38 men) with 56 lower legs were enrolled in this study. The lower leg muscles of mild PAD group (36 patients) showed higher CT values (44.6 vs. 39.5, p < 0.001) with smaller dispersion (35.6 vs. 41.0, p < 0.001) than the severe group (20 patients). The AUC of CTA score, LRM-I (constructed with muscle features), and LRM-II (constructed with muscle features and CTA score) for PAD severity prediction were 0.81, 0.84, and 0.89, respectively. The highest predictive performance was observed in the image subset of the middle and inferior segments of lower extremity (LRM-I, 0.83; LRM-II, 0.90). CONCLUSIONS: Lower extremity muscle features are associated with PAD severity and can be used for PAD prediction. CRITICAL RELEVANCE STATEMENT: Quantitative image features of lower extremity muscles are associated with the degree of lower leg arterial stenosis/occlusion and can be a beneficial supplement to the current imaging methods of vascular stenosis evaluation for the prediction of peripheral arterial disease severity. KEY POINTS: • Compared with severe PAD, lower leg muscles of mild PAD showed higher CT values (39.5 vs. 44.6, p < 0.001). • Models developed with muscle CT features had AUC = 0.89 for predicting PAD. • PAD severity prediction can be realized through the middle and inferior segment of images (AUC = 0.90).