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Herpes zoster (HZ), or shingles, is caused by reactivation of the varicella-zoster virus (VZV), which remains latent in the sensory ganglia until immunity wanes with age. The representative HZ vaccine, Shingrix is efficacious but causes side effects due to vaccine adjuvants. Therefore, the development of highly efficacious vaccines with minimal side effects is required. We developed chimeric adenovirus vector (ChimAd)-based HZ vaccine candidates encoding the VZV glycoprotein E (gE). These candidates include ChimAd-tPAgE, in which the signal peptide is replaced with tissue plasminogen activator (tPA), and ChimAd-WTgE, which retains the original signal peptide. C57BL/6 mice were immunized with VZV-vaccine candidates, and cellular and humoral immune responses were evaluated using interferon-γ ELISPOT and ELISA. The ChimAd-based HZ vaccines induced high levels of gE-specific antibodies and cell-mediated immunity. ChimAd-tPAgE (optimal dose: 1 × 107 IFU) elicited a more robust gE-specific T-cell response than Shingrix and Zostavax, showing potential as HZ prophylactic vaccines.

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BACKGROUND: This study aims to identify distinct microbial and functional biomarkers characteristic of body-first or brain-first subtypes of Parkinson's disease (PD). This could illuminate the unique pathogenic mechanisms within these subtypes. METHODS: In this cross-sectional study, we classified 36 well-characterized PD patients into body-first, brain-first, or undetermined subtypes based on the presence of premotor REM sleep behavior disorder (RBD) and cardiac meta-iodobenzylguanidine (MIBG) uptake. We then conducted an in-depth shotgun metagenomic analysis of the gut microbiome for each subtype and compared the results with those from age- and sex-matched healthy controls. RESULTS: Significant differences were found in the gut microbiome of body-first PD patients (n = 15) compared to both brain-first PD patients (n = 9) and healthy controls. The gut microbiome in body-first PD showed a distinct profile, characterized by an increased presence of Escherichia coli and Akkermansia muciniphila, and a decreased abundance of short-chain fatty acid-producing commensal bacteria. These shifts were accompanied by a higher abundance of microbial genes associated with curli protein biosynthesis and a lower abundance of genes involved in putrescine and spermidine biosynthesis. Furthermore, the combined use of premotor RBD and MIBG criteria was more strongly correlated with these microbiome differences than the use of each criterion independently. CONCLUSIONS: Our findings highlight the significant role of dysbiotic and pathogenic gut microbial alterations in body-first PD, supporting the body-first versus brain-first hypothesis. These insights not only reinforce the gut microbiome's potential as a therapeutic target in PD but also suggest the possibility of developing subtype-specific treatment strategies.

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With the continued evolution of DNA sequencing technologies, the role of genome sequence data has become more integral in the classification and identification of Bacteria and Archaea. Six years after introducing EzBioCloud, an integrated platform representing the taxonomic hierarchy of Bacteria and Archaea through quality-controlled 16S rRNA gene and genome sequences, we present an updated version, that further refines and expands its capabilities. The current update recognizes the growing need for accurate taxonomic information as defining a species increasingly relies on genome sequence comparisons. We also incorporated an advanced strategy for addressing underrepresented or less studied lineages, bolstering the comprehensiveness and accuracy of our database. Our rigorous quality control protocols remain, where whole-genome assemblies from the NCBI Assembly Database undergo stringent screening to remove low-quality sequence data. These are then passed through our enhanced identification bioinformatics pipeline which initiates a 16S rRNA gene similarity search and then calculates the average nucleotide identity (ANI). For genome sequences lacking a 16S rRNA sequence and without a closely related genomic representative for ANI calculation, we apply a different ANI approach using bacterial core genes for improved taxonomic placement (core gene ANI, cgANI). Because of the increase in genome sequences available in NCBI and our newly introduced cgANI method, EzBioCloud now encompasses a total of 109 835 species, of which 21 964 have validly published names. 47 896 are candidate species identified either through 16S rRNA sequence similarity (phylotypes) or through whole genome ANI (genomospecies), and the remaining 39 975 were positioned in the taxonomic tree by cgANI (species clusters). Our EzBioCloud database is accessible at www.ezbiocloud.net/db.

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Understanding the relationship between the gut microbiome and autism spectrum disorder (ASD) is challenging due to the heterogeneous nature of ASD. Here, we analyzed the microbial and clinical characteristics of individuals with ASD using enterotypes. A total of 456 individuals participated in the study, including 249 participants with ASD, 106 typically developing siblings, and 101 controls. The alpha and beta diversities of the ASD, sibling, and control groups did not show significant differences. Analysis revealed a negative association between the Bifidobacterium longum group and the Childhood Autism Rating Scale, as well as a negative association between the Streptococcus salivarus group and the Social Responsiveness Scale (SRS) within the ASD group. When clustered based on microbial composition, participants with ASD exhibited two distinct enterotypes, E1 and E2. In the E2 group, the SRS score was significantly higher, and the Vineland Adaptive Behavior Scale score was significantly lower compared to the E1 group. Machine learning results indicated that the microbial species predicting SRS scores were distinct between the two enterotypes. Our study suggests that the microbial composition in individuals with ASD exhibits considerable variability, and the patterns of associations between the gut microbiome and clinical symptoms may vary depending on the enterotype.

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Biopsy is the clinical standard for diagnosing lymph node (LN) metastasis, but it is invasive and poses significant risk to patient health. Magnetic resonance imaging (MRI) has been utilized as a noninvasive alternative but is limited by low sensitivity, with only ∼35% of LN metastases detected, as clinical contrast agents cannot discriminate between healthy and metastatic LNs due to nonspecific accumulation. Nanoparticles targeted to the C-C chemokine receptor 2 (CCR2), a biomarker highly expressed in metastatic LNs, have the potential to guide the delivery of contrast agents, improving the sensitivity of MRI. Additionally, cancer cells in metastatic LNs produce monocyte chemotactic protein 1 (MCP1), which binds to CCR2+ inflammatory monocytes and stimulates their migration. Thus, the molecular targeting of CCR2 may enable nanoparticle hitchhiking onto monocytes, providing an additional mechanism for metastatic LN targeting and early detection. Hence, we developed micelles incorporating gadolinium (Gd) and peptides derived from the CCR2-binding motif of MCP1 (MCP1-Gd) and evaluated the potential of MCP1-Gd to detect LN metastasis. When incubated with migrating monocytes in vitro, MCP1-Gd transport across lymphatic endothelium increased 2-fold relative to nontargeting controls. After administration into mouse models with initial LN metastasis and recurrent LN metastasis, MCP1-Gd detected metastatic LNs by increasing MRI signal by 30-50% relative to healthy LNs. Furthermore, LN targeting was dependent on monocyte hitchhiking, as monocyte depletion decreased accumulation by >70%. Herein, we present a nanoparticle contrast agent for MRI detection of LN metastasis mediated by CCR2-targeting and demonstrate the potential of monocyte hitchhiking for enhanced nanoparticle delivery.

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OBJECTIVE: While a significant link between emotional well-being (EWB) and the gut microbiome has been reported recently, their temporal relationships remain elusive. This study aims to fill this gap by examining the longitudinal associations between EWB and the Shannon Index (SI), an indicator of gut microbiome diversity. METHOD: The analysis focused on a dataset that collected participants' current EWB and fecal samples in both 2019 and 2022 (N = 57, 56.1% female, Mage = 52.47 years, SD = 12.65). Gut microbiome profiles were generated by sequencing the 16S rRNA gene, from which SI was subsequently calculated. RESULTS: The cross-lagged panel analysis revealed significant positive cross-sectional associations between EWB and SI in both 2019 (ß = .296, SE = 0.121, p = .014) and 2022 (ß = .324, SE = 0.119, p = .006). However, no significant longitudinal associations were found between 2019 EWB and 2022 SI (ß = .068, SE = 0.138, p = .623), nor between 2019 SI and 2022 EWB (ß = -.016, SE = 0.13, p = .899). CONCLUSIONS: Our findings indicate that emotional happiness may be associated with gut microbiome profiles at a particular time point, but they may not serve as predictive factors for each other over time. Future research is needed to establish causal relationships between them. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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BACKGROUND AND AIM: The gut microbiome of patients with clinically stable ulcerative colitis (UC) differs from that of healthy individuals depending on the state of the colonic mucosa, especially with or without advanced scarring; however, the underlying mechanism is unclear. Therefore, this study examined the gut microbiome compositional signatures in patients with significant mucosal scarring and UC-related symptoms. METHODS: Stool samples for gut microbiome analysis were prospectively collected from 57 patients with clinically stable UC between January 1 and December 31, 2022. Data from 57 individuals without inflammatory bowel disease (non-IBD) paired by age and sex were selected from our previous study as the control group. The fecal samples were subjected to 16S rRNA gene sequencing. Associations between gut microbiome profiles and clinical or colonoscopic assessments were examined using diversity and differential abundance analyses. RESULTS: Gut microbiome compositions between the patients with clinically stable UC and non-IBD controls differed significantly. Furthermore, gut microbiome compositions varied between the preserved and altered mucosa groups identified based on mucosal changes in the UC group. Differential abundance test of patients with UC for symptomatic remission based on stool frequency from the two-item patient-reported outcome identified several overlapping taxa specified as gut microbiome signatures, including the Enterobacteriaceae unknown genera (Enterobacteriaceae_g), Klebsiella, and several Lachnospiraceae spp. both in mucosal and symptom change analyses. CONCLUSIONS: The gut microbiome can change with mucosal changes, even in clinically stable UC, and some gut microbial signatures may explain the symptom manifestations in patients with UC showing significant mucosal changes.

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Background: The SoUth Korean study to PrEvent cognitive impaiRment and protect BRAIN health through lifestyle intervention in at-risk elderly people (SUPERBRAIN) is a part of the World-Wide Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (WW-FINGERS) network. This study aimed to demonstrate the effects of the SUPERBRAIN-based multidomain intervention with nutritional supplements in amyloid positive emission tomography (PET) proven early symptomatic Alzheimer's disease patients. Methods: Forty-six participants who were diagnosed with mild cognitive impairment or mild dementia and were positive in the amyloid PET study randomized into three groups: group A, the multidomain intervention with nutritional supplements; group B, nutritional supplements only; and a control group. The primary outcome was a change in the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) total scale index score after an 8-week intervention. Secondary outcomes, including gut microbiome data, were also analyzed. Results: The RBANS total scale index score improved significantly in group A compared with group B (p < 0.032) and compared with the control group (p < 0.001). After intervention, beta diversity of the gut microbiome between group A and the control group increased, and patients in group A were more enriched with Bifidobacterium. Conclusion: SUPERBRAIN-based multidomain intervention with nutritional supplements improves cognition and gut microbiota in patients with early symptomatic Alzheimer's disease who were amyloid-positive by PET.

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Purpose: To investigate whether CT-based tumor regression grade (ctTRG) can be used to predict the response to neoadjuvant chemotherapy (NAC) in colon cancer. Materials and Methods: A total of 53 patients were enrolled. Two radiologists independently assessed the ctTRG using the length, thickness, layer pattern, and luminal and extraluminal appearance of the tumor. Changes in tumor volume were also analyzed using the 3D Slicer software. We evaluated the association between pathologic TRG (pTRG) and ctTRG. Patients with Rödel's TRG of 2, 3, or 4 were classified as responders. In terms of predicting responder and pathologic complete remission (pCR), receiver operating characteristic was compared between ctTRG and tumor volume change. Results: There was a moderate correlation between ctTRG and pTRG (ρ = -0.540, p < 0.001), and the interobserver agreement was substantial (weighted κ = 0.672). In the prediction of responder, there was no significant difference between ctTRG and volumetry (Az = 0.749, criterion: ctTRG ≤ 3 for ctTRG, Az = 0.794, criterion: ≤ -27.1% for volume, p = 0.53). Moreover, there was no significant difference between the two methods in predicting pCR (p = 0.447). Conclusion: ctTRG might predict the response to NAC in colon cancer. The diagnostic performance of ctTRG was comparable to that of CT volumetry.

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Semaglutide, one of the most potent glucagon-like peptide (GLP)-1 analogs, has widely been used to treat type II diabetes mellitus and obesity. Recent studies have shown that semaglutide also works on the brain, suggesting its potential utility for various diseases, including Parkinson's disease and Alzheimer's disease. This study aimed to develop a novel liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of semaglutide in both plasma and brain to characterize the pharmacokinetics and brain distribution in rats. Semaglutide was extracted by simple protein precipitation with methanol from plasma and by solid phase extraction from brain tissue. Liraglutide was used as an internal standard. Gradient elution profiles with mobile phases comprising 0.1 % formic acid in water and acetonitrile were used for chromatographic separation. The lower limit of quantification (LLOQ) of the LC-MS/MS assay was 0.5 ng/mL for both rat plasma and brain. Intra- and inter-day accuracy ranged 89.20-109.50 % in the plasma and 92.00-105.00 % in the brain. Precision was within 8.92 % in the plasma and 7.94 % in the brain. Sprague-Dawley rats were given semaglutide by intravenous (IV, 0.02 mg/kg) and subcutaneous (SC, 0.1 and 0.2 mg/kg) injection. Plasma concentrations of semaglutide showed a multi-exponential decline with an average half-life of 7.22-9.26 hr in rats. The subcutaneous bioavailability of semaglutide was 76.65-82.85 %. The brain tissue to plasma partition coefficient (Kp) value of semaglutide was estimated as <0.01. Among the different regions of the brain, semaglutide concentrations were significantly higher in the hypothalamus. The analytical method and pharmacokinetic information may be helpful toward a better understanding of the effect of semaglutide in the brain and further development of GLP-1 analogs for various brain diseases.

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Emerging evidence reveals a close association between gut microbiota and human neurological disorders. The present study aimed to assess whether the composition of gut microbiota in participants with episodic migraine (EM) and chronic migraine (CM) was altered in comparison to that of the controls. This study was a cross-sectional, case-control study. The gut microbiota were evaluated by the partial, targeted sequencing of the 16S rRNA V3-V4 region. This study enrolled 42 and 45 participants with EM and CM, respectively, and 43 controls. Alpha and beta diversities revealed no significant difference among the three groups; however, the microbiota composition at the class, order, family, and genus levels differed significantly between EM and the control, CM and the control, and the EM and CM groups. Moreover, higher composition of PAC000195_g was significantly associated with a lower headache frequency among the five genera that exhibited significantly different microbiota composition in EM and CM. Agathobacter revealed a significant negative association with severe headache intensity. The findings of the present study provide evidence of altered gut microbiota in EM and CM. These findings will help in understanding the course and treatment of migraine.

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The majority of clear cell renal cell carcinomas (ccRCCs) are characterized by mutations in the Von Hippel−Lindau (VHL) tumor suppressor gene, which leads to the stabilization and accumulation of the HIF2α transcription factor that upregulates key oncogenic pathways that promote glucose metabolism, cell cycle progression, angiogenesis, and cell migration. Although FDA-approved HIF2α inhibitors for treating VHL disease-related ccRCC are available, these therapies are associated with significant toxicities such as anemia and hypoxia. To improve ccRCC-specific drug delivery, peptide amphiphile micelles (PAMs) were synthesized incorporating peptides targeted to the CD70 marker expressed by ccRCs and anti-HIF2α siRNA, and the ability of HIF2α-CD27 PAMs to modulate HIF2α and its downstream targets was evaluated in human ccRCC patient-derived cells. Cell cultures were derived from eight human ccRCC tumors and the baseline mRNA expression of HIF2A and CD70, as well as the HIF2α target genes SLC2A1, CCND1, VEGFA, CXCR4, and CXCL12 were first determined. As expected, each gene was overexpressed by at least 63% of all samples compared to normal kidney proximal tubule cells. Upon incubation with HIF2α-CD27 PAMs, a 50% increase in ccRCC-binding was observed upon incorporation of a CD70-targeting peptide into the PAMs, and gel shift assays demonstrated the rapid release of siRNA (>80% in 1 h) under intracellular glutathione concentrations, which contributed to ~70% gene knockdown of HIF2α and its downstream genes. Further studies demonstrated that knockdown of the HIF2α target genes SLC2A1, CCND1, VEGFA, CXCR4, and CXCL12 led to inhibition of their oncogenic functions of glucose transport, cell proliferation, angiogenic factor release, and cell migration by 50−80%. Herein, the development of a nanotherapeutic strategy for ccRCC-specific siRNA delivery and its potential to interfere with key oncogenic pathways is presented.

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The disruption of the human gut microbiota has been linked to host health conditions, including various diseases. However, no reliable index for measuring and predicting a healthy microbiome is currently available. Here, the sequencing data of 1,663 Koreans were obtained from three independent studies. Furthermore, we pooled 3,490 samples from public databases and analyzed a total of 5,153 fecal samples. First, we analyzed Korean gut microbiome covariates to determine the influence of lifestyle on variation in the gut microbiota. Next, patterns of microbiota variations across geographical locations and disease statuses were confirmed using a global cohort and di-sease data. Based on comprehensive comparative analysis, we were able to define three enterotypes among Korean cohorts, namely, Prevotella type, Bacteroides type, and outlier type. By a thorough categorization of dysbiosis and the evaluation of microbial characteristics using multiple datasets, we identified a wide spectrum of accuracy levels in classifying health and disease states. Using the observed microbiome patterns, we devised an index named the gut microbiome index (GMI) that could consistently predict health conditions from human gut microbiome data. Compared to ecological metrics, the microbial marker index, and machine learning approaches, GMI distinguished between healthy and non-healthy individuals with a higher accuracy across various datasets. Thus, this study proposes a potential index to measure health status of gut microbiome that is verified from multiethnic data of various diseases, and we expect this model to facilitate further clinical application of gut microbiota data in future.

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BACKGROUND: Dysbiosis of ulcerative colitis (UC) has been frequently investigated using readily accessible stool samples. However, stool samples might insufficiently represent the mucosa-associated microbiome status. We hypothesized that luminal contents including loosely adherent luminal bacteria after bowel preparation may be suitable for diagnosing the dysbiosis of UC. METHODS: This study included 16 patients with UC (9 men and 7 women, mean age: 52.13 ± 14.09 years) and 15 sex- and age-matched healthy individuals (8 men and 7 women, mean age: 50.93 ± 14.11 years). They donated stool samples before colonoscopy and underwent luminal content aspiration and endoscopic biopsy during the colonoscopy. Then, the composition of each microbiome sample was analyzed by 16S rRNA-based next-generation sequencing. RESULTS: The microbiome between stool, luminal contents, and biopsy was significantly different in alpha and beta diversities. However, a correlation existed between stool and luminal contents in the Procrustes test (p = 0.001) and Mantel test (p = 0.0001). The stool microbiome was different between patients with UC and the healthy controls. Conversely, no difference was found in the microbiome of luminal content and biopsy samples between the two subject groups. The microbiome of stool and lavage predicted UC, with AUC values of 0.85 and 0.81, respectively. CONCLUSION: The microbiome of stool, luminal contents, and biopsy was significantly different. However, the microbiome of luminal contents during colonoscopy can predict UC, with AUC values of 0.81. Colonoscopic luminal content aspiration analysis could determine microbiome differences between patients with UC and the healthy control, thereby beneficial in screening dysbiosis via endoscopy. TRIAL REGISTRATION: This trial was registered at http://cris.nih.go.kr . Registration No.: KCT0003352), Date: 2018-11-13.

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The Zika virus (ZIKV) outbreak in 2015-2016 raised public health concerns and created a pressing need for vaccine development. However, no vaccine has been developed and most of the ones under development use a single serotype of ZIKV. In this study, we established a Vero cell-adapted ZIKV strain (GMZ-002) and developed a purified inactivated virus (PIV) vaccine. GMZ-002 presented significantly increased productivity in Vero cells, and IFNAR1-blocked C57BL/6 mice administered two doses of the PIV were fully protected against lethal challenge. Vaccine efficacy was illustrated by the high level of serum neutralizing antibodies and strong innate immune response, along with an absence of detectable viremia in vaccinated mice. Furthermore, anti-sera neutralized both African and Asian genetic lineages of the virus in vitro. Our results suggest that GMZ-002 PIV elicited robust and persistent protective immunity, and therefore represents a promising vaccine candidate for ZIKV.

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The causes of snapping knee include meniscal instability, but dynamic ultrasonographic findings have rarely been reported. Here, we report a case of snapping knee due to direct trauma to the right knee of a 79-year-old woman. Dynamic ultrasonography is used to confirm the snapping phenomenon caused by the anterosuperior displacement of the truncated posterior horn and body of the right medial meniscus.

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We demonstrate the mechanism by which C3G, a major dietary anthocyanin, regulates energy metabolism and insulin sensitivity. Oral administration of C3G reduced hepatic and plasma triglyceride levels, adiposity, and improved glucose tolerance in mice fed high-fat diet. Hepatic metabolomic analysis revealed that C3G shifted metabolite profiles towards fatty acid oxidation and ketogenesis. C3G increased glucose uptake in HepG2 cells and C2C12 myotubes and induced the rate of hepatic fatty acid oxidation. C3G directly interacted with and activated PPARs, with the highest affinity for PPARα. The ability of C3G to reduce plasma and hepatic triglycerides, glucose tolerance, and adiposity and to induce oxygen consumption and energy expenditure was abrogated in PPARα-deficient mice, suggesting that PPARα is the major target for C3G. These findings demonstrate that the dietary anthocyanin C3G activates PPARs, a master regulators of energy metabolism. C3G is an agonistic ligand of PPARs and stimulates fuel preference to fat.

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Shotgun metagenomics is of great importance in order to understand the composition of the microbial community associated with a sample and the potential impact it may exert on its host. For clinical metagenomics, one of the initial challenges is the accurate identification of a pathogen of interest and ability to single out that pathogen within a complex community of microorganisms. However, in absence of an accurate identification of those microorganisms, any kind of conclusion or diagnosis based on misidentification may lead to erroneous conclusions, especially when comparing distinct groups of individuals. When comparing a shotgun metagenomic sample against a reference genome sequence database, the classification itself is dependent on the contents of the database. Focusing on the genus Streptococcus, we built four synthetic metagenomic samples and demonstrated that shotgun taxonomic profiling using the bacterial core genes as the reference database performed better in both taxonomic profiling and relative abundance prediction than that based on the marker gene reference database included in MetaPhlAn2. Additionally, by classifying sputum samples of patients suffering from chronic obstructive pulmonary disease, we showed that adding genomes of genomospecies to a reference database offers higher taxonomic resolution for taxonomic profiling. Finally, we show how our genomospecies database is able to identify correctly a clinical stool sample from a patient with a streptococcal infection, proving that genomospecies provide better taxonomic coverage for metagenomic analyses.

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Strategies involving metastable phases have been the basis of the design of numerous alloys, yet research on metastable high-entropy alloys is still in its infancy. In dual-phase high-entropy alloys, the combination of local chemical environments and loading-induced crystal structure changes suggests a relationship between deformation mechanisms and chemical atomic distribution, which we examine in here in a Cantor-like Cr20Mn6Fe34Co34Ni6 alloy, comprising both face-centered cubic (fcc) and hexagonal closed packed (hcp) phases. We observe that partial dislocation activities result in stable three-dimensional stacking-fault networks. Additionally, the fraction of the stronger hcp phase progressively increases during plastic deformation by forming at the stacking-fault network boundaries in the fcc phase, serving as the major source of strain hardening. In this context, variations in local chemical composition promote a high density of Lomer-Cottrell locks, which facilitate the construction of the stacking-fault networks to provide nucleation sites for the hcp phase transformation.

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Shape memory effect, the ability to recover a pre-deformed shape on heating, results from a reversible martensitic transformation between austenite and martensite phases. Here, we demonstrate a strategy of designing high-entropy alloys (HEAs) with high-temperature shape memory effect in the CrMnFeCoNi alloy system. First, we calculate the difference in Gibbs free energy between face-centered-cubic (FCC) and hexagonal-close-packed (HCP) phases, and find a substantial increase in thermodynamic equilibrium temperature between the FCC and HCP phases through composition tuning, leading to thermally- and stress-induced martensitic transformations. As a consequence, the shape recovery temperature in non-equiatomic CrMnFeCoNi alloys can be increased to 698 K, which is much higher than that of conventional shape memory alloys (SMAs) and comparable to that of B2-based multi-component SMAs containing noble metals (Pd, Pt, etc.) or refractory metals (Zr, Hf, etc.). This result opens a vast field of applications of HEAs as a novel class of cost-effective high-temperature SMAs.