Association between biological aging and diabetic retinopathy.

The impact of aging on diabetic retinopathy (DR) remains underestimated. The current study aimed to investigate the association between biological aging and DR, in contrast to chronological age (CA). Using the National Health and Nutrition Survey data from 2005 to 2008. Biological aging was evaluated through the biological age (BA) and phenotypic age (PA), which were calculated from clinical markers. DR was identified in participants with diabetes mellitus (DM) when they exhibited one or more retinal microaneurysms or retinal blot hemorrhages under retinal imaging, with or without the presence of more severe lesions. Survey-weighted multivariable logistic regression was performed, and the regression model was further fitted using restricted cubic splines. The discriminatory capability and clinical utility of the model were evaluated using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Based on weighted analyses, of the 3100 participants included in this study, of which 162 had DR. In the adjusted model, BA (odds ratio [OR] = 1.12, 95% CI, 1.06-1.18) and PA (OR = 1.11, 95% CI, 1.07-1.14) were associated with DR, while CA was not significantly (OR = 1.01, 95% CI, 0.99-1.03). Narrowing the analysis to DM participants and adjusting for factors like insulin showed similar results. ROC and DCA analyses indicate that BA/PA predicted DR better than CA and offer greater clinical utility. The positive association between BA/PA and DR was consistent across subgroups despite potential interactions. Biological aging heightens DR risk, with BA/PA showing a stronger association than CA. Our findings underscored the importance of timely anti-aging interventions for preventing DR.

Adherence to Life's Essential 8 is associated with delayed biological aging: a population-based cross-sectional study.

INTRODUCTION AND OBJECTIVES: The aim of this study was to explore the potential of adhering to the American Heart Association's updated Life's Essential 8 (LE8) scores in delaying biological aging amid growing concerns about aging populations and related diseases. METHODS: A total of 18 261 adults (≥ 20 years old) were examined using National Health and Nutrition Examination Survey data from 2005-2010 and 2015-2018. The LE8 includes 8 components, covering health behaviors and factors. Acceleration of biological aging was defined as an excess of biological/phenotypic age over chronological age, assessed by using clinical biomarkers. The association between LE8 score and biological aging was explored through regression analyses. RESULTS: Each 10-point increase in LE8 scores was associated with a 1.19-year decrease in biological age and a 1.63-year decrease in phenotypic age. Individuals with high cardiovascular health (CVH) had a 90% reduction in their risk of accelerated aging based on biological age and an 81% reduction based on phenotypic age compared with individuals with low CVH. Bootstrap-based model estimates and weighted quantile sum regression suggested that health factors, particularly blood glucose, had strong impact on delaying aging. The association between smoking and biological aging seemed to differ depending on the definition of aging used. Among all subgroups, LE8 consistently correlated negatively with biological aging, despite observed interactions. Three sensitivity analyses confirmed the robustness of our conclusions. CONCLUSIONS: A higher CVH is associated with a lower risk of biological aging. Maintaining elevated LE8 levels across demographics, regardless of cardiovascular history, is recommended to delay aging and promote healthy aging, with significant implications for primary health care.

Measurable residual disease monitoring by ddPCR in the early posttransplant period complements the traditional MFC method to predict relapse after HSCT in AML/MDS: a multicenter retrospective study.

BACKGROUND: Droplet digital PCR (ddPCR) is widely applied to monitor measurable residual disease (MRD). However, there are limited studies on the feasibility of ddPCR-MRD monitoring after allogeneic hematopoietic stem cell transplantation (allo-HSCT), especially targeting multiple molecular markers simultaneously. METHODS: Our study collected samples from patients with acute myeloid leukemia (AML) or high-risk myelodysplastic syndrome (MDS) in complete remission after allo-HSCT between January 2018 and August 2021 to evaluate whether posttransplant ddPCR-MRD monitoring can identify patients at high risk of relapse. RESULTS: Of 152 patients, 58 (38.2%) were MRD positive by ddPCR within 4 months posttransplant, with a median variant allele frequency of 0.198%. The detectable DTA mutations (DNMT3A, TET2, and ASXL1 mutations) after allo-HSCT were not associated with an increased risk of relapse. After excluding DTA mutations, patients with ddPCR-MRD positivity had a significantly higher cumulative incidence of relapse (CIR, 38.7% vs. 9.7%, P < 0.001) and lower rates of relapse-free survival (RFS, 55.5% vs. 83.7%, P < 0.001) and overall survival (OS, 60.5% vs. 90.5%, P < 0.001). In multivariate analysis, ddPCR-MRD positivity of non-DTA genes was an independent adverse predictor for CIR (hazard ratio [HR], 4.02; P < 0.001), RFS (HR, 2.92; P = 0.002) and OS (HR, 3.12; P = 0.007). Moreover, the combination of ddPCR with multiparameter flow cytometry (MFC) can further accurately identify patients at high risk of relapse (F+/M+, HR, 22.44; P < 0.001, F+/M-, HR, 12.46; P < 0.001 and F-/M+, HR, 4.51; P = 0.003). CONCLUSION: ddPCR-MRD is a feasible approach to predict relapse after allo-HSCT in AML/MDS patients with non-DTA genes and is more accurate when combined with MFC. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT06000306. Registered 17 August 2023 -Retrospectively registered ( https://clinicaltrials.gov/study/NCT06000306?term=NCT06000306&rank=1 ).

Accelerated First-Principles Calculations Based on Machine Learning for Interfacial Modification Element Screening of SiCp/Al Composites.

SiCp/Al composites offer the advantages of lightweight construction, high strength, and corrosion resistance, rendering them extensively applicable across various domains such as aerospace and precision instrumentation. Nonetheless, the interfacial reaction between SiC and Al under high temperatures leads to degradation in material properties. In this study, the interface segregation energy and interface binding energy subsequent to the inclusion of alloying elements were computed through a first-principle methodology, serving as a dataset for machine learning. Feature descriptors for machine learning undergo refinement via feature engineering. Leveraging the theory of machine-learning-accelerated first-principle computation, six machine learning models-RBF, SVM, BPNN, ENS, ANN, and RF-were developed to train the dataset, with the ANN model selected based on R2 and MSE metrics. Through this model, the accelerated computation of interface segregation energy and interface binding energy was achieved for 89 elements. The results indicate that elements including B, Si, Fe, Co, Ni, Cu, Zn, Ga, and Ge exhibit dual functionality, inhibiting interfacial reactions while bolstering interfacial binding. Furthermore, the atomic-scale mechanism elucidates the interfacial modulation of these elements. This investigation furnishes a theoretical framework for the compositional design of SiCp/Al composites.

A Study of the Adsorption Properties of Individual Atoms on the Graphene Surface: Density Functional Theory Calculations Assisted by Machine Learning Techniques.

In this research, the adsorption performance of individual atoms on the surface of monolayer graphene surface was systematically investigated using machine learning methods to accelerate density functional theory. The adsorption behaviors of over thirty different atoms on the graphene surface were computationally analyzed. The adsorption energy and distance were extracted as the research targets, and the basic information of atoms (such as atomic radius, ionic radius, etc.) were used as the feature values to establish the dataset. Through feature engineering selection, the corresponding input feature values for the input-output relationship were determined. By comparing different models on the dataset using five-fold cross-validation, the mathematical model that best fits the dataset was identified. The optimal model was further fine-tuned by adjusting of the best mathematical ML model. Subsequently, we verified the accuracy of the established machine learning model. Finally, the precision of the machine learning model forecasts was verified by the method of comparing and contrasting machine learning results with density functional theory. The results suggest that elements such as Zr, Ti, Sc, and Si possess some potential in controlling the interfacial reaction of graphene/aluminum composites. By using machine learning to accelerate first-principles calculations, we have further expanded our choice of research methods and accelerated the pace of studying element-graphene interactions.

No evidence of a causal relationship between miscarriage and 25-hydroxyvitamin D: a Mendelian randomization study.

STUDY QUESTION: Is there a causal relationship between 25-hydroxyvitamin D (25OHD) and miscarriage? SUMMARY ANSWER: In this study, little evidence of a causal relationship was found between low serum 25OHD concentration or vitamin D deficiency and the risk of miscarriages. WHAT IS KNOWN ALREADY: Associations between low vitamin D levels and increased risk of miscarriage have been reported, but causality is unclear. STUDY DESIGN SIZE DURATION: The latest and largest genome-wide association studies (GWAS) for serum 25OHD concentration (n = 417 580), vitamin D deficiency (426 cases and 354 812 controls), miscarriage (16 906 cases and 149 622 controls), and the number of miscarriages (n = 78 700) were used to explore the causal association between serum vitamin D levels and miscarriage by two-sample Mendelian randomization analysis. PARTICIPANTS/MATERIALS SETTING METHODS: This study was based on summary GWAS results from the FinnGen database and the UK Biobank. The random-effect inverse-variance weighted method was regarded as the primary analysis; MR-Egger, weighted median, weighted mode, simple mode, and MR-pleiotropy residual sum and outlier (MR-PRESSO) were further employed as complementary methods. MR-Egger intercept analysis and MR-PRESSO were employed to test pleiotropy, and Cochran's Q statistic and leave-one-out sensitivity analysis were used to determine the heterogeneity and robustness of the overall estimates, respectively. MAIN RESULTS AND THE ROLE OF CHANCE: There was insufficient evidence of causal associations between serum 25OHD concentration and miscarriage (odds ratio (OR) = 0.995, 95% CI: 0.888 to 1.114, P = 0.927), or the number of miscarriages (ß = -0.004, 95% CI: -0.040 to 0.032, P = 0.829). Furthermore, little evidence of causality between genetically determined vitamin D deficiency to miscarriage (OR = 0.993, 95% CI: 0.966 to 1.021, P = 0.624), or the number of miscarriages (ß = 0.001, 95% CI: -0.009 to 0.011, P = 0.828), was observed. The results of the sensitivity analysis were robust, and no significant heterogeneity or horizontal pleiotropy was found. LIMITATIONS REASONS FOR CAUTION: This study is limited by the absence of female-specific GWAS data and the limited amount of GWAS data available for this study, as well as the need for caution in generalizing the findings to non-European ethnic groups. WIDER IMPLICATIONS OF THE FINDINGS: These findings enhance the current understanding of the intricate association between vitamin D and pregnancy outcomes, challenging prevailing beliefs regarding the strong association with miscarriage. The results provide a special perspective that may prompt further exploration and potentially offer insights for guiding future research and informing clinical guidelines pertaining to the management of miscarriage. STUDY FUNDING/COMPETING INTERESTS: This project was supported by the Hubei Provincial Natural Science Foundation Program General Surface Project (2022CFB200), the Key Research & Developmental Program of of Hubei Province (2022BCA042), the Fundamental Research Funds for the Central Universities (2042022gf0007, 2042022kf1210), and the Interdisciplinary Innovative Talents Foundation from Renmin Hospital of Wuhan University (JCRCWL-2022-001, JCRCYG-2022-009). All authors have no conflicts of interest to declare. TRIAL REGISTRATION NUMBER: N/A.

Chiral Assembly of Perovskite Nanocrystals: Sensitive Discrimination of Amino Acid Enantiomers.

Chirality is a widespread phenomenon in nature and in living organisms and plays an important role in living systems. The sensitive discrimination of chiral molecular enantiomers remains a challenge in the fields of chemistry and biology. Establishing a simple, fast, and efficient strategy to discriminate the spatial configuration of chiral molecular enantiomers is of great significance. Chiral perovskite nanocrystals (PNCs) have attracted much attention because of their excellent optical activity. However, it is a challenge to prepare perovskites with both chiral and fluorescence properties for chiral sensing. In this work, we synthesized two chiral fluorescent perovskite nanocrystal assembly (PNA) enantiomers by using l- or d-phenylalanine (Phe) as chiral ligands. PNA exhibited good fluorescence recognition for l- and d-proline (Pro). Homochiral interaction led to fluorescence enhancement, while heterochiral interaction led to fluorescence quenching, and there is a good linear relationship between the fluorescence changing rate and l- or d-Pro concentration. Mechanism studies show that homochiral interaction-induced fluorescence enhancement is attributed to the disassembly of chiral PNA, while no disassembly of chiral PNA was found in heterochiral interaction-induced fluorescence quenching, which is attributed to the substitution of Phe on the surface of chiral PNA by heterochiral Pro. This work suggests that chiral perovskite can be used for chiral fluorescence sensing; it will inspire the development of chiral nanomaterials and chiral optical sensors.

Early T-cell reconstitution predicts risk of EBV reactivation after allogeneic hematopoietic stem cell transplantation.

The quality of immune reconstitution (IR) is crucial for the outcome of patients who received allogeneic hematopoietic stem cell transplantation (allo-HSCT), and is closely connected with infection, relapse and graft-versus-host disease (GvHD) which are the most important causes for transplantation failure. However, the IR pattern in the early stage after allo-HSCT, particularly haploidentical (HID) HSCT, remains unclear. In this retrospective study, we examined the T cell reconstitution of patients within the initial 30 days (n = 173) and 100 days (n = 122) after allo-HSCT with myeloablative condition (MAC), of which > 70% were HID HSCT, to assess the influence of IR on the transplant outcomes. By comparing 78 patients with good IR (GIR) to 44 patients with poor IR (PIR), we observed that GIR was associated with lower risk for Epstein-Barr virus (EBV) reactivation and cytomegalovirus (CMV) reactivation, but had no significant impacts on the survival outcomes (i.e., overall survival, event-free survival) and cumulative incidences of GvHD. Importantly, we found lymphocyte reconstitution pattern at day 30 after allo-HSCT would be a surrogate for IR evaluated at day 100. In the Cox proportional hazard model, early reconstitution of CD4+, CD4+CD25+, CD4+CD45RO+, CD4+CD25+CD27low, and CD8+ T cells at day 30 was reversely correlated with risk of EBV reactivation. Finally, we constructed a predictive model for EBV reactivation with CD8+ and CD4+CD45RO+ T cell proportions of the training cohort (n = 102), which was validated with a validation cohort (n = 37). In summary, our study found that the quality of IR at day 30 had a predictive value for the risk of EBV reactivation, and might provide guidance for close monitoring for EBV reactivation.

COVID-19 in immunocompromised patients after hematopoietic stem cell transplantation: a pilot study.

Data on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in patients at early stage of immune reconstitution after hematopoietic stem cell transplantation (HSCT) are limited. In the present study, we retrospectively investigated the incidence and clinical features of SARS-CoV-2 infection in patients who underwent HSCT in 2022. Patients (allo-HSCT, n = 80; auto-HSCT, n = 37) were consecutively included in the study. The SARS-CoV-2 infection rate was 59.8%, and the median interval of HSCT to coronavirus disease 2019 (COVID-19) was 4.8 (range: 0.5-12) months. Most patients were categorized as mild (41.4%) or moderate (38.6%), and 20% as severe/critical. No deaths were attributable to COVID-19. Further analysis showed that lower circulating CD8+ T-cell counts and calcineurin inhibitor administration increased the risk of SARS-CoV-2 infection. Exposure to rituximab significantly increased the probability of severe or critical COVID-19 compared with that of mild/moderate illness (P < .001). In the multivariate analysis, rituximab use was associated with severe COVID-19. Additionally, COVID-19 had no significant effect on immune reconstitution. Furthermore, it was found that Epstein-Barr virus infection and rituximab administration possibly increase the risk of developing severe illness. Our study provides preliminary insights into the effect of SARS-CoV-2 on immune reconstitution and the outcomes of allo-HSCT recipients.

Synthesis of a water-stable CsPbBr3 perovskite for selective detection of mercury ion in water.

By using the method of low-temperature crystallization, CsPbBr3 perovskite nanocrystals (PNCs) coated with trifluoroacetyl lysine (Tfa-Lys) and oleamine (Olam) were synthesized in aqueous solution. The structure of the CsPbBr3 PNCs was characterized by many methods, such as ultraviolet (UV)-visible absorption spectrophotometer, fluorescence spectrophotometer, transmission electron microscopy (TEM), and X-ray diffraction (XRD) pattern. The fluorescence emission of the CsPbBr3 PNCs is stable in water for about 1 day at room temperature. It was also found that the fluorescence of the PNCs could be obviously and selectively quenched after the addition of mercury ion (Hg2+ ), allowing a visual detection of Hg2+ by the naked eye under UV light illumination. The fluorescence quenching rate (I0 /I) has a good linear relationship with the addition of Hg2+ in the concentration range 0.075 to 1.5 mg/L, with a correlation coefficient (R2 ) of 0.997, and limit of detection of 0.046 mg/L. The fluorescence quenching mechanism of the PNCs was determined by the fluorescence lifetime and X-ray photoelectron spectroscopy (XPS) of the PNCs. Overall, the synthesis method for CsPbBr3 PNCs is simple and rapid, and the as-prepared PNCs are stable in water that could be conveniently used for selective detection of Hg2+ in the water environment.

Association of Dietary Live Microbes and Nondietary Prebiotic/Probiotic Intake With Cognitive Function in Older Adults: Evidence From NHANES.

BACKGROUND: The current study aims to examine association of dietary live microbes and nondietary prebiotic/probiotic intake with cognitive function among older U.S. adults, examining heterogeneity across demographic characteristics and diseases. METHODS: Participants from the National Health and Nutrition Examination Survey 2011-2014 cycles were selected and administered 3 cognitive function tests: the Consortium to Establish a Registry for Alzheimer's Disease Word Learning subtest (CERAD W-L, including immediate [CERAD-IRT] and delayed [CERAD-DRT] memory), the Animal Fluency Test (AFT), and the Digit Symbol Substitution Test (DSST). Test-specific and global cognition z-score was created. Based on their estimated dietary live microbes intake, participants were categorized into three groups: low, medium, and high. Text mining was employed to identify nondietary prebiotic/probiotic usage by examining the names and ingredients of dietary supplements or drugs. RESULTS: Participants in the medium (including AFT) and high (including global cognition, AFT, DSST, and CERAD-IRT) dietary live microbes intake group had significantly higher z-score of cognitive function compared to those in the low intake group. Among participants with cardiovascular disease history, nondietary prebiotic intake was associated with higher z-score in global cognition and CERAD-DRT compared to those who did not consume prebiotic. Additionally, probiotic intake was linked to higher z-score in global cognition, AFT, and DSST, particularly in participants with diabetes mellitus or hypertension. CONCLUSIONS: Our study suggests that the intake of dietary live microbes and nondietary probiotic/prebiotic was associated with better cognitive function in older adults, particularly in specific disease states.

The Evolution of a Microstructure during Tempering and Its Influence on the Mechanical Properties of AerMet 100 Steel.

In order to provide guidance for furthering the balance of strength and toughness of AerMet 100 steel through tempering treatment, the effects of the tempering time on microstructure and mechanical properties are investigated. The microstructure evolution, especially M2C precipitates and austenite in AerMet 100 tempered at 482 °C for 1~20 h, was characterized, and its influences on the mechanical properties were studied. The tensile strength decreases gradually, the yield strength increases first and then decreases, and the fracture toughness KIC increases gradually with an increasing tempering time. The strength and toughness matching of AerMet 100 steel is achieved by tempering at 482 °C for 5~7 h. Without considering the martensitic size effect, the influence of the dislocation density on the tensile strength is more significant during tempering at 482 °C. The precipitation strengthening mechanism plays a dominant role in the yield strength when tempering for 5 h or less, and the combined influence of carbide coarsening and a sharp decrease in the dislocation density resulted in a significant decrease in tensile strength when tempering for 8 h or more. The fracture toughness KIC is primarily influenced by the reverted austenite, so that KIC increases gradually with the prolongation of the tempering time. However, a significant decrease in the dislocation density resulting from long-term tempering has a certain impact on KIC, giving rise to a decrease in the rising amplitude in KIC after tempering for 8 h or more.

Exploration of Solid Solutions and the Strengthening of Aluminum Substrates by Alloying Atoms: Machine Learning Accelerated Density Functional Theory Calculations.

In this paper, we studied the effects of a series of alloying atoms on the stability and micromechanical properties of aluminum alloy using a machine learning accelerated first-principles approach. In our preliminary work, high-throughput first-principles calculations were explored and the solution energy and theoretical stress of atomically doped aluminum substrates were extracted as basic data. By comparing five different algorithms, we found that the Catboost model had the lowest RMSE (0.24) and lowest MAPE (6.34), and this was used as the final prediction model to predict the solid solution strengthening of the aluminum matrix by the elements. Calculations show that alloying atoms such as K, Na, Y and Tl are difficult to dissolve in the aluminum matrix, whereas alloy atoms like Sc, Cu, B, Zr, Ni, Ti, Nb, V, Cr, Mn, Mo, and W exerted a strengthening influence. Theoretical studies on solid solutions and the strengthening effect of various alloy atoms in an aluminum matrix can offer theoretical guidance for the subsequent selection of suitable alloy elements. The theoretical investigation of alloy atoms in an aluminum matrix unveils the fundamental aspects of the solution strengthening effect, contributing significantly to the expedited development of new aluminum alloys.

Life's Essential 8 and Mortality in US Adults with Chronic Kidney Disease.

INTRODUCTION: The current prevalence of chronic kidney disease (CKD) is substantial, and CKD individuals face a heightened risk of mortality, encompassing both all-cause and cause-specific outcomes. The current study aims to investigate the potential impact of adhering to Life's Essential 8 (LE8) on reducing mortality among CKD individuals. METHODS: Using the National Health and Nutrition Survey (NHANES) data from 2005 to 2018, we analyzed 22,420 US adults (≥20 years old). CKD is defined by urinary albumin-to-creatinine ratio (≥30 mg/g or 3 mg/mmol) and estimated glomerular filtration rate (<60 mL/min/1.73 m2). The components of LE8, including diet, physical activity (PA), nicotine exposure, sleep, body mass index, blood lipids, blood glucose, and blood pressure (BP), were measured and given a score of 0-100. The total LE8 score was the unweighted average of all components and was divided into low cardiovascular health (CVH) (0-49), moderate CVH (50-79), and high CVH (80-100). A Cox proportional hazards regression model was used to explore the associations of LE8 with all-cause, cardiovascular disease (CVD), and cancer mortality, which were followed prospectively by the National Center for Health Statistics until December 31, 2019. RESULTS: In the overall population, individuals with moderate CVH had a 47% lower risk of CKD, while high CVH was linked to a 55% lower risk compared to low CVH. During a median follow-up of 7.58 years, CKD individuals had a 93% higher all-cause mortality rate and a 149% higher CVD mortality rate compared to those without CKD. Among the CKD individuals, every 10-point increase in the LE8 score was associated with reduced risks of 17% for all-cause mortality (especially PA, nicotine exposure, blood glucose, and BP), 18% for CVD mortality (especially PA), and 12% for cancer mortality (especially PA and sleep health). In additional and sensitivity analysis, the results remained significant after further consideration of potential confounding of renal function. Additionally, LE8 demonstrated superior risk stratification for CVD mortality among CKD patients compared with LS7. Interaction was observed between LE8 and age, education level, marital status, and drinking status. CONCLUSION: The current study demonstrates that adherence to higher LE8 levels within CKD individuals is associated with a reduced risk of both all-cause and cause-specific mortality.

Femtosecond Laser-Driven Phase Engineering of WS2 for Nano-Periodic Phase Patterning and Sub-ppm Ammonia Gas Sensing.

Laser-driven phase transition of 2D transition metal dichalcogenides has attracted much attention due to its high flexibility and rapidity. However, there are some limitations during the laser irradiation process, especially the unsatisfied surface ablation, the inability of nanoscale phase patterning, and the unexploited physical properties of new phase. In this work, the well-controlled femtosecond (fs) laser-driven transformation from the metallic 2M-WS2 to the semiconducting 2H-WS2 is reported, which is confirmed to be a single-crystal to single-crystal transition without layer thinning or obvious ablation. Moreover, a highly ordered 2H/2M nano-periodic phase transition with a resolution of ≈435 nm is achieved, breaking through the existing size bottleneck of laser-driven phase transition, which is attributed to the selective deposition of plasmon energy induced by fs laser. It is also demonstrated that the achieved 2H-WS2 after laser irradiation contains rich sulfur vacancies, which exhibits highly competitive ammonia gas sensing performance, with a detection limit below 0.1 ppm and a fast response/recovery time of 43/67 s at room temperature. This study provides a new strategy for the preparation of the phase-selective transition homojunction and high-performance applications in electronics.

The interplay between N6-methyladenosine and precancerous liver disease: molecular functions and mechanisms.

N6-methyladenosine(m6A) is one of the most abundant modifications of mammalian cellular RNAs. m6A regulates various biological functions in epitranscriptomic ways, including RNA stability, decay, splicing, translation and nuclear export. Recent studies have indicated the growing importance of m6A modification in precancerous disease, influencing viral replication, immune escape, and carcinogenesis. Here, we review the role of m6A modification in HBV/HCV infection, NAFLD and liver fibrosis, and its function in liver disease pathogenesis. Our review will provide a new sight for the innovative treatment strategy for precancerous liver disease.

Effect of Temperatures and Graphene on the Mechanical Properties of the Aluminum Matrix: A Molecular Dynamics Study.

Graphene has become an ideal reinforcement for reinforced metal matrix composites due to its excellent mechanical properties. However, the theory of graphene reinforcement in graphene/aluminum matrix composites is not yet well developed. In this paper, the effect of different temperatures on the mechanical properties of the metal matrix is investigated using a classical molecular dynamics approach, and the effects of the configuration and distribution of graphene in the metal matrix on the mechanical properties of the composites are also described in detail. It is shown that in the case of a monolayer graphene-reinforced aluminum matrix, the simulated stretching process does not break the graphene as the strain increases, but rather, the graphene and the aluminum matrix have a shearing behavior, and thus, the graphene "pulls out" from the aluminum matrix. In the parallel stretching direction, the tensile stress tends to increase with the increase of the graphene area ratio. In the vertical stretching direction, the tensile stress tends to decrease as the percentage of graphene area increases. In the parallel stretching direction, the tensile stress of the system tends to decrease as the angle between graphene and the stretching direction increases. It is important to investigate the effect of a different graphene distribution in the aluminum matrix on the mechanical properties of the composites for the design of high-strength graphene/metal matrix composites.