Combined deep learning and radiomics in pretreatment radiation esophagitis prediction for patients with esophageal cancer underwent volumetric modulated arc therapy.

PURPOSE: To develop a combined radiomics and deep learning (DL) model in predicting radiation esophagitis (RE) of a grade ≥ 2 for patients with esophageal cancer (EC) underwent volumetric modulated arc therapy (VMAT) based on computed tomography (CT) and radiation dose (RD) distribution images. MATERIALS AND METHODS: A total of 273 EC patients underwent VMAT were retrospectively reviewed and enrolled from two centers and divided into training (n = 152), internal validation (n = 66), and external validation (n = 55) cohorts, respectively. Radiomic and dosiomic features along with DL features using convolutional neural networks were extracted and screened from CT and RD images to predict RE. The performance of these models was evaluated and compared using the area under curve (AUC) of the receiver operating characteristic curves (ROC). RESULTS: There were 5 and 10 radiomic and dosiomic features were screened, respectively. XGBoost achieved a best AUC of 0.703, 0.694 and 0.801, 0.729 with radiomic and dosiomic features in the internal and external validation cohorts, respectively. ResNet34 achieved a best prediction AUC of 0.642, 0.657 and 0.762, 0.737 for radiomics based DL model (DLR) and RD based DL model (DLD) in the internal and external validation cohorts, respectively. Combined model of DLD + Dosiomics + clinical factors achieved a best AUC of 0.913, 0.821 and 0.805 in the training, internal, and external validation cohorts, respectively. CONCLUSION: Although the dose was not responsible for the prediction accuracy, the combination of various feature extraction methods was a factor in improving the RE prediction accuracy. Combining DLD with dosiomic features was promising in the pretreatment prediction of RE for EC patients underwent VMAT.

Deoxycholic acid inducing chronic atrophic gastritis with colonic mucosal lesion correlated to mucosal immune dysfunction in rats.

The present study aimed to explore the underlying mechanism of bile reflux-inducing chronic atrophic gastritis (CAG) with colonic mucosal lesion. The rat model of CAG with colonic mucosal lesion was induced by free-drinking 20 mmol/L sodium deoxycholate to simulate bile reflux and 2% cold sodium salicylate for 12 weeks. In comparison to the control group, the model rats had increased abundances of Bacteroidetes and Firmicutes but had decreased abundances of Proteobacteria and Fusobacterium. Several gut bacteria with bile acids transformation ability were enriched in the model group, such as Blautia, Phascolarctobacter, and Enterococcus. The cytotoxic deoxycholic acid and lithocholic acid were significantly increased in the model group. Transcriptome analysis of colonic tissues presented that the down-regulated genes enriched in T cell receptor signaling pathway, antigen processing and presentation, Th17 cell differentiation, Th1 and Th2 cell differentiation, and intestinal immune network for IgA production in the model group. These results suggest that bile reflux-inducing CAG with colonic mucosal lesion accompanied by gut dysbacteriosis, mucosal immunocompromise, and increased gene expressions related to repair of intestinal mucosal injury.

Crystal structure of lipase from Pseudomonas aeruginosa reveals an unusual catalytic triad conformation.

The Pseudomonas aeruginosa lipase PaL catalyzes the stereoselective hydrolysis of menthyl propionate to produce L-menthol. The lack of a three-dimensional structure of PaL has so far prevented a detailed understanding of its stereoselective reaction mechanism. Here, the crystal structure of PaL was determined at a resolution of 1.80 Å by single-wavelength anomalous diffraction. In the apo-PaL structure, the catalytic His302 is located in a long loop on the surface that is solvent exposed. His302 is distant from the other two catalytic residues, Asp274 and Ser164. This configuration of catalytic residues is unusual for lipases. Using metadynamics simulations, we observed that the enzyme undergoes a significant conformational change upon ligand binding. We also explored the catalytic and stereoselectivity mechanisms of PaL by all-atom molecular dynamics simulations. These findings could guide the engineering of PaL with an improved diastereoselectivity for L-menthol production.

Radiation pneumonitis prediction with dual-radiomics for esophageal cancer underwent radiotherapy.

BACKGROUND: To integrate radiomics and dosiomics features from multiple regions in the radiation pneumonia (RP grade ≥ 2) prediction for esophageal cancer (EC) patients underwent radiotherapy (RT). METHODS: Total of 143 EC patients in the authors' hospital (training and internal validation: 70%:30%) and 32 EC patients from another hospital (external validation) underwent RT from 2015 to 2022 were retrospectively reviewed and analyzed. Patients were dichotomized as positive (RP+) or negative (RP-) according to CTCAE V5.0. Models with radiomics and dosiomics features extracted from single region of interest (ROI), multiple ROIs and combined models were constructed and evaluated. A nomogram integrating radiomics score (Rad_score), dosiomics score (Dos_score), clinical factors, dose-volume histogram (DVH) factors, and mean lung dose (MLD) was also constructed and validated. RESULTS: Models with Rad_score_Lung&Overlap and Dos_score_Lung&Overlap achieved a better area under curve (AUC) of 0.818 and 0.844 in the external validation in comparison with radiomics and dosiomics models with features extracted from single ROI. Combining four radiomics and dosiomics models using support vector machine (SVM) improved the AUC to 0.854 in the external validation. Nomogram integrating Rad_score, and Dos_score with clinical factors, DVH factors, and MLD further improved the RP prediction AUC to 0.937 and 0.912 in the internal and external validation, respectively. CONCLUSION: CT-based RP prediction model integrating radiomics and dosiomics features from multiple ROIs outperformed those with features from a single ROI with increased reliability for EC patients who underwent RT.

Enhancing the Thermostability and Catalytic Activity of the Lipase from Rhizopus oryzae via Introducing N-Glycosylation.

Lipase from Rhizopus oryzae (ROL) exhibits remarkable sn-1,3 stereoselectivity and catalytic activity, but its poor thermostability limits its applications in the production of 1,3-dioleoyl-2-palmitoyl glycerol (OPO, a high-quality substitute for human milk fat). In this work, a semirational method was proposed to engineer the thermostability and catalytic activity of 4M (ROL mutant in our previous study). First, a computer-aided design is performed using 4M as a template, and N-glycosylation mutants are then recombinantly expressed and screened in Pichia pastoris, the optimal mutant N227 exhibited a half-life of 298.8 h at 45 °C, which is 7.23-folds longer than that of 4M. Its catalytic activity also reached 1043.80 ± 61.98 U/mg, representing a 29.2% increase compared to 4M (808.02 ± 47.02 U/mg). Molecular dynamics simulations of N227 suggested that the introduction of glycan enhanced the protein rigidity, while the strong hydrogen bonds formed between the glycan and the protein stabilized the lipase structure, thereby improving its thermostability. The acidolysis reaction between oleic acid (OA) and glycerol tripalmitate (PPP) was successfully carried out using immobilized N227, achieving a molar conversion rate of 90.2% for PPP. This engineering strategy guides the modification of lipases, while the glycomutants obtained in this study have potential applications in the biosynthesis of OPO.

Ovalbumin Hydrolysates Enhance Skeletal Muscle Insulin-Dependent Signaling Pathway in High-Fat Diet-Fed Mice.

Egg white hydrolysates (EWH) and ovotransferrin-derived peptides have distinct beneficial effects on glucose metabolism. This research aims to investigate whether ovalbumin hydrolysates (OVAHs), without ovotransferrin can improve insulin signaling pathway in high-fat diet (HFD)-fed mice. Two types of ovalbumin hydrolysates were produced, either using thermoase (OVAT), or thermoase + pepsin (OVATP). Both OVAHs-supplemented groups exhibited lower body weight gain (P < 0.001) and enhanced oral glucose tolerance (P < 0.05) compared with HFD. Moreover, diet supplementation with either hydrolysate increased the insulin-stimulated activation of protein kinase B (AKT) and insulin receptor ß (IRß) (P < 0.0001) in skeletal muscle. In conclusion, OVAHs improved glucose tolerance and insulin-dependent signaling pathway in HFD-fed mice.

Multi-omics deep learning for radiation pneumonitis prediction in lung cancer patients underwent volumetric modulated arc therapy.

BACKGROUND AND OBJECTIVE: To evaluate the feasibility and accuracy of radiomics, dosiomics, and deep learning (DL) in predicting Radiation Pneumonitis (RP) in lung cancer patients underwent volumetric modulated arc therapy (VMAT) to improve radiotherapy safety and management. METHODS: Total of 318 and 31 lung cancer patients underwent VMAT from First Affiliated Hospital of Wenzhou Medical University (WMU) and Quzhou Affiliated Hospital of WMU were enrolled for training and external validation, respectively. Models based on radiomics (R), dosiomics (D), and combined radiomics and dosiomics features (R+D) were constructed and validated using three machine learning (ML) methods. DL models trained with CT (DLR), dose distribution (DLD), and combined CT and dose distribution (DL(R+D)) images were constructed. DL features were then extracted from the fully connected layers of the best-performing DL model to combine with features of the ML model with the best performance to construct models of R+DLR, D+DLD, R+D+DL(R+D)) for RP prediction. RESULTS: The R+D model achieved a best area under curve (AUC) of 0.84, 0.73, and 0.73 in the internal validation cohorts with Support Vector Machine (SVM), XGBoost, and Logistic Regression (LR), respectively. The DL(R+D) model achieved a best AUC of 0.89 and 0.86 using ResNet-34 in training and internal validation cohorts, respectively. The R+D+DL(R+D) model achieved a best performance in the external validation cohorts with an AUC, accuracy, sensitivity, and specificity of 0.81(0.62-0.99), 0.81, 0.84, and 0.67, respectively. CONCLUSIONS: The integration of radiomics, dosiomics, and DL features is feasible and accurate for the RP prediction to improve the management of lung cancer patients underwent VMAT.

In silico mining and identification of a novel lipase from Paenibacillus larvae: Rational protein design for improving catalytic performance.

Lipases play a vital role in various biological processes, from lipid metabolism to industrial applications. However, the ever-evolving challenges and diverse substrates necessitate the continual exploration of novel high-performance lipases. In this study, we employed an in silico mining approach to search for lipases with potential high sn-1,3 selectivity and catalytic activity. The identified novel lipase, PLL, from Paenibacillus larvae subsp. larvae B-3650 exhibited a specific activity of 111.2 ± 5.5 U/mg towards the substrate p-nitrophenyl palmitate (pNPP) and 6.9 ± 0.8 U/mg towards the substrate olive oil when expressed in Escherichia coli (E. coli). Computational design of cysteine mutations was employed to enhance the catalytic performance of PLL. Superior stability was achieved with the mutant K7C/A386C/H159C/K108C (2M3/2M4), showing an increase in melting temperature (Tm) by 1.9°C, a 2.05-fold prolonged half-life at 45°C, and no decrease in enzyme activity. Another mutant, K7C/A386C/A174C/A243C (2M1/2M3), showed a 4.9-fold enhancement in specific activity without compromising stability. Molecular dynamics simulations were conducted to explore the mechanisms of these two mutants. Mutant 2M3/2M4 forms putative disulfide bonds in the loop region, connecting the N- and C-termini of PLL, thus enhancing overall structural rigidity without impacting catalytic activity. The cysteines introduced in mutant 2M1/2M3 not only form new intramolecular hydrogen bonds but also alter the polarity and volume of the substrate-binding pocket, facilitating the entry of large substrate pNPP. These results highlight an efficient in silico exploration approach for novel lipases, offering a rapid and efficient method for enhancing catalytic performance through rational protein design.

Treatment of telangiectasias with a 595-nm pulsed dye laser following hemangioma involution: a retrospective analysis.

Telangiectasias are the most frequent type of sequelae of infantile hemangiomas after involution. Few studies have reported the treatment of telangiectasias with 595-nm pulsed dye lasers. Therefore, the objective of this study was to assess the efficacy and safety of a 595-nm pulsed dye laser for treating residual telangiectasias following hemangioma involution. This is a retrospective case series that analyzes the medical records and reviews the charts of 22 patients who had undergone 595-nm pulsed dye laser treatment for residual telangiectasias. Pre- and post-treatment digital images were independently assessed, and the changes were scored to ascertain the efficacy of the treatment (0 = no change, 4 = complete improvement). Of the 22 patients, 59.1% experienced complete resolution of telangiectasias following treatment. No serious complications or side effects were reported. The observations indicate that the 595-nm pulsed dye laser is effective and safe for treating residual telangiectasias following hemangioma involution.

Cross-sectional Relationship Between Dietary Protein Intake, Energy Intake and Protein Energy Wasting in Chronic Kidney Disease Patients.

The potential threshold for dietary energy intake (DEI) that might prevent protein-energy wasting (PEW) in chronic kidney disease (CKD) is uncertain. The subjects were non-dialysis CKD patients aged ≥ 14 years who were hospitalized from September 2019 to July 2022. PEW was measured by subjective global assessment (SGA). DEI and dietary protein intake (DPI) were obtained by 3-days diet recalls. Patients were divided into adequate DEI group and inadequate DEI group according to DEI ≥ 30 or < 30 kcal/kg/d. Logistic regression analysis and restricted cubic spline (RCS) were used in this study. We enrolled 409 patients, with 53.8% had hypertension and 18.6% had diabetes. The DEI and DPI was 27.63 ± 5.79 kcal/kg/day and 1.00 (0.90,1.20) g/kg/day, respectively. 69.2% of participants in inadequate DEI group. Malnutrition occurred in 18.6% of patients. Comparing to patients in adequate DEI group, those in inadequate DEI group had significantly lower total lymphocyte count (TLC), serum cholesterol (Chol) and low-density cholesterol (LDL), and a higher prevalence of PEW. For every 1kcal/kg/day increase in DEI, the incidence of PEW was reduced by 12.0% [odds ratio (OR): 0.880, 95% confidence interval (CI): 0.830 to 0.933, P < 0.001]. There was a nonlinear curve relationship between DEI and PEW (overall P < 0.001), and DEI ≥ 27.6 kcal/kg/d may have a preventive effect on PEW in CKD. Low DPI was also significantly associated with malnutrition, but not when DEI was adequate. Decreased energy intake may be a more important factor of PEW in CKD than protein intake.

Enantiodivergent kinetic resolution of 4-substituted 1,2,3,4-tetrahydroquinolines employing amine oxidase.

Optically pure 1,2,3,4-tetrahydroquinolines (THQs) represent a class of important motifs in many natural products and pharmaceutical agents. While recent advances on redox biocatalysis have demonstrated the great potential of amine oxidases, all the transformations focused on 2-substituted THQs. The corresponding biocatalytic method for the preparation of chiral 4-substituted THQs is still challenging due to the poor activity and stereoselectivity of the available enzyme. Herein, we developed a biocatalytic kinetic resolution approach for enantiodivergent synthesis of 4-phenyl- or alkyl-substituted THQs. Through structure-guided protein engineering of cyclohexylamine oxidase derived from Brevibacterium oxidans IH-35 A (CHAO), the variant of CHAO (Y215H/Y214S) displayed improved specific activity toward model substrate 4-phenyl substituted THQ (0.14 U/mg, 13-fold higher than wild-type CHAO) with superior (R)-stereoselectivity (E > 200). Molecular dynamics simulations show that CHAO Y215H/Y214S allows a suitable substrate positioning in the expanded binding pocket to be facilely accessed, enabling enhanced activity and stereoselectivity. Furthermore, a series of 4-alkyl-substituted THQs can be transformed by CHAO Y215H/Y214S, affording R-isomers with good yields (up to 50 %) and excellent enantioselectivity (up to ee > 99 %). Interestingly, the monoamine oxidase from Pseudomonas fluorescens Pf0-1 (PfMAO1) with opposite enantioselectivity was also mined. Together, this system enriches the kinetic resolution methods for the synthesis of chiral THQs.

Are novel plant-based meat alternatives the healthier choice?

The global market for plant-based meat alternatives (PBMAs) is expanding quickly. In this narrative review, analysis of the most recent scientific literature was achieved to understand the nutritional profile, health implications, and the challenges faced by PBMAs. On the positive side, most PBMAs are good sources of dietary fiber, contain phytochemicals, have comparable levels of iron, and are lower in calories, saturated fat, and cholesterol than meat. However, PBMAs frequently contain anti-nutrients, have less protein, iron, and vitamin B12, are lower in protein quality, and also have higher amounts of sodium. Substituting PBMAs for meats may cause iron, vitamin B12, and less likely protein deficiency for these vulnerable population such as women, older adults, and individuals with disorders. PBMAs fall into the category of ultra-processed foods, indicating a need to develop minimally processed, clean-label products. Replacing red meat with healthy plant-based foods is associated with lower risks of cardiovascular diseases, type 2 diabetes, and total mortality. There is a lack of robust, long-term evidence on the role of PBMAs consumption in health. As the nutrient contents of PBMAs can vary, consumers must read nutrition facts labels and ingredient lists to select a product that best fits their nutritional and health objectives.

Sequence-Guided Redesign of an Omega-Transaminase from Bacillus megaterium for the Asymmetric Synthesis of Chiral Amines.

ω-Transaminases (ω-TAs) are attractive biocatalysts asymmetrically catalyzing ketones to chiral amines. However, poor non-native catalytic activity and substrate promiscuity severely hamper its wide application in industrial production. Protein engineering efforts have generally focused on reshaping the substrate-binding pockets of ω-TAs. However, hotspots around the substrate tunnel as well as distant sites outside the pockets may also affect its activity. In this study, the ω-TA from Bacillus megaterium (BmeTA) was selected for engineering. The tunnel mutation Y164F synergy with distant mutation A245T which was acquired through a multiple sequence alignment showed improved soluble expression, a 3.7-fold higher specific activity and a 19.9-fold longer half-life at 45 °C. Molecule Dynamics simulation explains the mechanism of improved catalytic activity, enhanced thermostability and improved soluble expression of BmeTAY164F/A245T(2 M). Finally, the resting cells of 2 M were used for biocatalytic processes. 450 mM of S-methoxyisopropylamine (S-MOIPA) was obtained with an ee value of 97.3 % and a conversion rate of 90 %, laying the foundation for its industrial production. Mutant 2 M was also found to be more advantageous in catalyzing the transamination of various ketones. These results demonstrated that sites that are far away from the active center also play an important role in the redesign of ω-TAs.

Food-Derived Up-Regulators and Activators of Angiotensin Converting Enzyme 2: A Review.

Angiotensin-converting enzyme 2 (ACE2) is a key enzyme in the renin-angiotensin system (RAS), also serving as an amino acid transporter and a receptor for certain coronaviruses. Its primary role is to protect the cardiovascular system via the ACE2/Ang (1-7)/MasR cascade. Given the critical roles of ACE2 in regulating numerous physiological functions, molecules that can upregulate or activate ACE2 show vast therapeutic value. There are only a few ACE2 activators that have been reported, a wide range of molecules, including food-derived compounds, have been reported as ACE2 up-regulators. Effective doses of bioactive peptides range from 10 to 50 mg/kg body weight (BW)/day when orally administered for 1 to 7 weeks. Protein hydrolysates require higher doses at 1000 mg/kg BW/day for 20 days. Phytochemicals and vitamins are effective at doses typically ranging from 10 to 200 mg/kg BW/day for 3 days to 6 months, while Traditional Chinese Medicine requires doses of 1.25 to 12.96 g/kg BW/day for 4 to 8 weeks. ACE2 activation is linked to its hinge-bending region, while upregulation involves various signaling pathways, transcription factors, and epigenetic modulators. Future studies are expected to explore novel roles of ACE2 activators or up-regulators in disease treatments and translate the discovery to bedside applications.

Soil fungal community has higher network stability than bacterial community in response to warming and nitrogen addition in a subtropical primary forest.

Global change factors are known to strongly affect soil microbial community function and composition. However, as of yet, the effects of warming and increased anthropogenic nitrogen deposition on soil microbial network complexity and stability are still unclear. Here, we examined the effects of experimental warming (3°C above ambient soil temperature) and nitrogen addition (5 g N m-2 year-1) on the complexity and stability of the soil microbial network in a subtropical primary forest. Compared to the control, warming increased |negative cohesion|:positive cohesion by 7% and decreased network vulnerability by 5%; nitrogen addition decreased |negative cohesion|:positive cohesion by 10% and increased network vulnerability by 11%. Warming and decreased soil moisture acted as strong filtering factors that led to higher bacterial network stability. Nitrogen addition reduced bacterial network stability by inhibiting soil respiration and increasing resource availability. Neither warming nor nitrogen addition changed fungal network complexity and stability. These findings suggest that the fungal community is more tolerant than the bacterial community to climate warming and nitrogen addition. The link between bacterial network stability and microbial community functional potential was significantly impacted by nitrogen addition and warming, while the response of soil microbial network stability to climate warming and nitrogen deposition may be independent of its complexity. Our findings demonstrate that changes in microbial network structure are crucial to ecosystem management and to predict the ecological consequences of global change in the future. IMPORTANCE: Soil microbes play a very important role in maintaining the function and health of forest ecosystems. Unfortunately, global change factors are profoundly affecting soil microbial structure and function. In this study, we found that climate warming promoted bacterial network stability and nitrogen deposition decreased bacterial network stability. Changes in bacterial network stability had strong effects on bacterial community functional potentials linked to metabolism, nitrogen cycling, and carbon cycling, which would change the biogeochemical cycle in primary forests.

Using UAV images and deep learning in investigating potential breeding sites of Aedes albopictus.

Aedes albopictus (Diptera: Culicidae) plays a crucial role as a vector for mosquito-borne diseases like dengue and zika. Given the limited availability of effective vaccines, the prevention of Aedes-borne diseases mainly relies on extensive efforts in vector surveillance and control. In multiple mosquito control methods, the identification and elimination of potential breeding sites (PBS) for Aedes are recognized as effective methods for population control. Previous studies utilizing unmanned aerial vehicles (UAVs) and deep learning to identify PBS have primarily focused on large, regularly-shaped containers. However, there has been a small amount of empirical research into their practical application in the field. We have thus constructed a PBS dataset specifically tailored for Ae. albopictus, including items such as buckets, bowls, bins, aquatic plants, jars, lids, pots, boxes, and sinks that were common in the Yangtze River Basin in China. Then, a YOLO v7 model for identifying these PBS was developed. Finally, we recognized and labeled the area with the highest PBS density, as well as the subarea with the most urgent need for source reduction in the empirical region, by calculating the kernel density value. Based on the above research, we proposed a UAV-AI-based methodological framework to locate the spatial distribution of PBS, and conducted empirical research on Jinhulu New Village, a typical model community. The results revealed that the YOLO v7 model achieved an excellent result on the F1 score and mAP(both above 0.99), with 97% of PBS correctly located. The predicted distribution of different PBS categories in each subarea was completely consistent with true distribution; the five houses with the most PBS were correctly located. The results of the kernel density map indicate the subarea 4 with the highest density of PBS, where PBS needs to be removed or destroyed with immediate effect. These results demonstrate the reliability of the prediction results and the feasibility of the UAV-AI-based methodological framework. It can minimize repetitive labor, enhance efficiency, and provide guidance for the removal and destruction of PBS. The research can shed light on the investigation of mosquito PBS investigation both methodologically and practically.

Reconstructing dynamics correlation network to simultaneously improve activity and stability of 2,3-butanediol dehydrogenase by design of distal interchain disulfide bonds.

The complete enzyme catalytic cycle includes substrate binding, chemical reaction and product release, in which different dynamic conformations are adopted. Due to the complex relationship among enzyme activity, stability and dynamics, the directed evolution of enzymes for improved activity or stability commonly leads to a trade-off in stability or activity. It hence remains a challenge to engineer an enzyme to have both enhanced activity and stability. Here, we have attempted to reconstruct the dynamics correlation network involved with active center to improve both activity and stability of a 2,3-butanediol dehydrogenase (2,3-BDH) by introducing inter-chain disulfide bonds. A computational strategy was first applied to evaluate the effect of introducing inter-chain disulfide bond on activity and stability of three 2,3-BDHs, and the N258C mutation of 2,3-BDH from Corynebacterium glutamicum (CgBDH) was proved to be effective in improving both activity and stability. In the results, CgBDH-N258C showed a different unfolding curve from the wild type, with two melting temperatures (Tm) of 68.3 °C and 50.8 °C, 19.7 °C and 2 °C higher than 48.6 °C of the wild type. Its half-life was also improved by 14.8-fold compared to the wild type. Catalytic efficiency (kcat/Km) of the mutant was increased by 7.9-fold toward native substrate diacetyl and 8.8-fold toward non-native substrate 2,5-hexanedione compared to the wild type. Molecular dynamics simulations revealed that an interaction network formed by Cys258, Arg162, Ala144 and the catalytic residues was reconstructed in the mutant and the dynamics change caused by the disulfide bond could be propagated through the interactions network. This improved the enzyme stability and activity by decreasing the flexibility and locking more "reactive" pose, respectively. Further construction of mutations including A144G showing a 44-fold improvement in catalytic efficiency toward meso-2,3-BD confirmed the role of modifying dynamics correlation network in tunning enzyme activity and selectivity. This study provided important insights into the relationship among dynamics, enzyme catalysis and stability, and will be useful in the designing new enzymes with co-evolution of stability, activity and selectivity.

Bioavailability and Metabolism of Bioactive Peptide IRW with Angiotensin-Converting Enzyme 2 (ACE2) Upregulatory Activity in Spontaneously Hypertensive Rats.

Peptide IRW is the first food-derived angiotensin-converting enzyme 2 (ACE2) upregulator. This study aimed to investigate the pharmacokinetic characteristics of IRW and identify the metabolites contributing to its antihypertensive activity in spontaneously hypertensive rats (SHRs). Rats were administered 100 mg of IRW/kg of the body weight via an intragastric or intravenous route. The bioavailability (F %) was determined to be 11.7%, and the half-lives were 7.9 ± 0.5 and 28.5 ± 6.8 min for gavage and injection, respectively. Interestingly, significant blood pressure reduction was not observed until 1.5 h post oral administration, or 2 h post injection, indicating that the peptide's metabolites are likely responsible for the blood pressure-lowering activity. Time-course metabolomics revealed a significant increase in the level of kynurenine, a tryptophan metabolite, in blood after IRW administration. Kynurenine increased the level of ACE2 in cells. Oral administration of tryptophan (W), but not dipeptide IR, lowered the blood pressure and upregulated aortic ACE2 in SHRs. Our study supports the key role of tryptophan and its metabolite, kynurenine, in IRW's blood pressure-lowering effects.