THE ALL-ASSOCIATIVITY OF OCTONIONS AND ITS APPLICATIONS

Using an elementary method, we give a new proof of the all-associativity of octonions. As some applications, the known Taylor theorem is improved, and a new definition and new properties of octonionic determinant are also obtained.

Fanlian Huazhuo formula:A promising therapeutic approach for metabolic associated steatotic liver disease

This article reviews the study,“Fanlian huazhuo formula alleviates high-fat-dietinduced nonalcoholic fatty liver disease by modulating autophagy and lipid synthesis signaling pathway”published in the World Journal of Gastroenterology.The study explores the therapeutic potential of Fanlian Huazhuo formula(FLHZF)in treating metabolic-associated steatotic liver disease(MASLD),demonstrating that FLHZF reduces lipid accumulation,oxidative stress,and liver injury in MASLD models by modulating key signaling pathways involved in lipid metabolism and autophagy.This editorial emphasizes the potential of FLHZF as a treatment for MASLD and calls for further research to verify its clinical efficacy.

Predicting colorectal adenomatous polyps in patients with chronic liver disease: A novel nomogram

BACKGROUND Colorectal polyps are commonly observed in patients with chronic liver disease(CLD)and pose a significant clinical concern because of their potential for malignancy.AIM To explore the clinical characteristics of colorectal polyps in patients with CLD,a nomogram was established to predict the presence of adenomatous polyps(AP).METHODS Patients with CLD who underwent colonoscopy at Tianjin Second People’s Hospital from January 2020 to May 2023 were evaluated.Clinical data including laboratory results,colonoscopy findings,and pathology reports were collected.Key variables for the nomogram were identified through least absolute shrinkage and selection operator regression,followed by multivariate logistic regression.The performance of the model was evaluated using the area under the receiver area under curve,as well as calibration curves and decision curve analysis.RESULTS The study enrolled 870 participants who underwent colonoscopy,and the detection rate of AP in patients with CLD was 28.6%.Compared to individuals without polyps,six risk factors were identified as predictors for AP occurrence:Age,male sex,body mass index,alcohol consumption,overlapping metabolic dysfunction-associated steatotic liver disease,and serum ferritin levels.The novel nomogram(AP model)demonstrated an area under curve of 0.801(95%confidence interval:0.756-0.845)and 0.785(95%confidence interval:0.712-0.858)in the training and validation groups.Calibration curves indicated good agreement among predicted and actual probabilities(training:χ^(2)=11.860,P=0.157;validation:χ^(2)=7.055,P=0.530).The decision curve analysis underscored the clinical utility of the nomogram for predicting the risk of AP.CONCLUSION The AP model showed reasonable accuracy and provided a clinical foundation for predicting the occurrence of AP in patients with CLD,which has a certain predictive value.

A physical memristor model for Pavlovian associative memory

Brain-inspired intelligence is considered to be a computational model with the most promising potential to overcome the shortcomings of the von Neumann architecture,making it a current research hotspot.Due to advantages such as nonvolatility,high density,low power consumption,and high response ratio,memristors are regarded as devices with promising applications in brain-inspired intelligence.This paper proposes a physical Ag/HfO_(x)/FeO_(x)/Pt memristor model.The Ag/HfO_(x)/FeO_(x)/Pt memristor is first fabricated using magnetron sputtering,and its internal principles and characteristics are then thoroughly analyzed.Furthermore,we construct a corresponding physical memristor model which achieves a simulation accuracy of up to 99.72%for the physical memristor.We design a fully functional Pavlovian associative memory circuit,realizing functions including generalization,primary differentiation,secondary differentiation,and forgetting.Finally,the circuit is validated through PSPICE simulation and analysis.

Risk factors and a predictive model of diabetic foot in hospitalized patients with type 2 diabetes

BACKGROUND The risk factors and prediction models for diabetic foot(DF)remain incompletely understood,with several potential factors still requiring in-depth investigations.AIM To identify risk factors for new-onset DF and develop a robust prediction model for hospitalized patients with type 2 diabetes.METHODS We included 6301 hospitalized patients with type 2 diabetes from January 2016 to December 2021.A univariate Cox model and least absolute shrinkage and selection operator analyses were applied to select the appropriate predictors.Nonlinear associations between continuous variables and the risk of DF were explored using restricted cubic spline functions.The Cox model was further employed to evaluate the impact of risk factors on DF.The area under the curve(AUC)was measured to evaluate the accuracy of the prediction model.RESULTS Seventy-five diabetic inpatients experienced DF.The incidence density of DF was 4.5/1000 person-years.A long duration of diabetes,lower extremity arterial disease,lower serum albumin,fasting plasma glucose(FPG),and diabetic nephropathy were independently associated with DF.Among these risk factors,the serum albumin concentration was inversely associated with DF,with a hazard ratio(HR)and 95%confidence interval(CI)of 0.91(0.88-0.95)(P<0.001).Additionally,a U-shaped nonlinear relationship was observed between the FPG level and DF.After adjusting for other variables,the HRs and 95%CI for FPG<4.4 mmol/L and≥7.0 mmol/L were 3.99(1.55-10.25)(P=0.004)and 3.12(1.66-5.87)(P<0.001),respectively,which was greater than the mid-range level(4.4-6.9 mmol/L).The AUC for predicting DF over 3 years was 0.797.CONCLUSION FPG demonstrated a U-shaped relationship with DF.Serum albumin levels were negatively associated with DF.The prediction nomogram model of DF showed good discrimination ability using diabetes duration,lower extremity arterial disease,serum albumin,FPG,and diabetic nephropathy(Clinicaltrial.gov NCT05519163).

Critical assessment of the reported bidirectional associations between gallstone, non-alcoholic fatty liver, and kidney stone diseases

The recent article by Jiang et al published in World Journal of Gastroenterology reports substantial bidirectional associations between gallstone disease(GSD),non-alcoholic fatty liver disease(NAFLD),and kidney stone disease(KSD),based on multicenter cross-sectional studies and a systematic review with meta-analysis.While the findings have the potential to significantly impact clinical and pre-ventive strategies,several methodological issues merit closer examination.This letter critiques key aspects of the study,including sample population hetero-geneity,potential confounding variables,and the reliance on cross-sectional data that may limit causal inferences.We also discuss the generalizability of these results to broader populations given the study's focus on the Chinese demogra-phic.By addressing these concerns,we suggest a more nuanced interpretation of the associations between GSD,NAFLD,and KSD,advocating for longitudinal studies to validate these findings and enhance their applicability in global health contexts.

Transcriptome and single-cell profiling of the mechanism of diabetic kidney disease

BACKGROUND The NOD-like receptor thermal protein domain associated protein 3(NLRP3)inflammasome may play an important role in diabetic kidney disease(DKD).However,the exact link remains unclear.AIM To investigate the role of the NLRP3 inflammasome in DKD.METHODS Using datasets from the Gene Expression Omnibus database,30 NLRP3 inflammasome-related genes were identified.Differentially expressed genes were selected using differential expression analysis,whereas intersecting genes were selected based on overlapping differentially expressed genes and NLRP3 inflammasome-related genes.Subsequently,three machine learning algorithms were used to screen genes,and biomarkers were identified by overlapping the genes from the three algorithms.Potential biomarkers were validated by western blotting in a db/db mouse model of diabetes.RESULTS Two biomarkers,sirtuin 2(SIRT2)and caspase 1(CASP1),involved in the Leishmania infection pathway were identified.Both biomarkers were expressed in endothelial cells.Pseudo-temporal analysis based on endothelial cells showed that DKD mostly occurs during the mid-differentiation stage.Western blotting results showed that CASP1 expression was higher in the DKD group than in the control group(P<0.05),and SIRT2 content decreased(P<0.05).CONCLUSION SIRT2 and CASP1 provide a potential theoretical basis for DKD treatment.

Interface associativity and energy absorption capability of anti-vibration porous Al-MM alloy core with iron alloy skin structures

The interface associativity and energy absorption capability of composite structure with anti-vibration porous Al-MM（cerium-rich mischmetal）alloy core and iron alloy skin were investigated.Porous aluminum core/iron alloy skin structures were fabricated considering an iron alloy tube as its shell and closed-cell porous Al-MM alloy as its core.A peeling experiment was carried out to calculate the capacity of interfacial bonding and a compression test was carried out to determine the energy absorption capability.The results showed that the addition of MM significantly enhanced both the interfacial bonding and the energy absorption capacity.

Industrial Carbon Emission Distribution and Regional Joint Emission Reduction:A Case Study of Cities in the Pearl River Basin,China

China’s low-carbon development path will make significant contributions to achieving global sustainable development goals.Due to the diverse natural and economic conditions across different regions in China,there exists an imbalance in the distribution of car-bon emissions.Therefore,regional cooperation serves as an effective means to attain low-carbon development.This study examined the pattern of carbon emissions and proposed a potential joint emission reduction strategy by utilizing the industrial carbon emission intens-ity(ICEI)as a crucial factor.We utilized social network analysis and Local Indicators of Spatial Association(LISA)space-time trans-ition matrix to investigate the spatiotemporal connections and discrepancies of ICEI in the cities of the Pearl River Basin(PRB),China from 2010 to 2020.The primary drivers of the ICEI were determined through geographical detectors and multi-scale geographically weighted regression.The results were as follows:1)the overall ICEI in the Pearl River Basin is showing a downward trend,and there is a significant spatial imbalance.2)There are numerous network connections between cities regarding the ICEI,but the network structure is relatively fragile and unstable.3)Economically developed cities such as Guangzhou,Foshan,and Dongguan are in the center of the network while playing an intermediary role.4)Energy consumption,industrialization,per capita GDP,urbanization,science and techno-logy,and productivity are found to be the most influential variables in the spatial differentiation of ICEI,and their combination in-creased the explanatory power of the geographic variation of ICEI.Finally,through the analysis of differences and connections in urban carbon emissions under different economic levels and ICEI,the study suggests joint carbon reduction strategies,which are centered on carbon transfer,financial support,and technological assistance among cities.

Effects of excess high-normal alanine aminotransferase levels in relation to new-onset metabolic dysfunction-associated fatty liver disease:Clinical implications

In this editorial,we comment on the article by Chen et al recently published in 2024.We focus the debate on whether reducing the upper limit of normal of alanine aminotransferase(ALT)would effectively identify cases of fibrosis in metabolic-dysfunction associated fatty liver disease(MAFLD).This is important given the increasing prevalence of MAFLD and obesity globally.Currently,a suitable screening test to identify patients in the general population does not exist and most patients are screened after the finding of an abnormal ALT.The authors of this paper challenge the idea of what a normal ALT is and whether that threshold should be lowered,particularly as their study found that 83.12%of their study population with a diagnosis of MAFLD had a normal ALT.The main advantages of screening would be to identify patients and provide intervention early,the mainstay of this being changing modifiable risk factors and monitoring for liver fibrosis.However,there is not enough suitable therapeutic options available as of yet although this is likely to change in the coming years with more targets for therapy being discovered.Semaglutide is one example of this which has demonstrated benefit with an acceptable side effect profile for those patients with MAFLD and obesity,although studies have not yet shown a significant improvement in fibrosis regression.It would also require a huge amount of resource if a reduced ALT level alone was used as criteria;it is more likely that current scoring systems such as fibrosis-4 may be amended to represent this additional risk.Currently,there is not a good argument to recommend wide-spread screening with a reduced ALT level as this is unlikely to be cost-effective.This is compounded by the fact that there is a significant heterogeneity in what is considered a normal ALT between laboratories.Although studies previously have suggested a more pragmatic approach in screening those over the age of 60,this is likely to change with the increasing incidence of obesity within the younger age groups.The main message from this study is that those who have hypercholesterolemia and high body metabolic index should have these risk factors modified to maintain a lower level of ALT to reduce the risk of progression to fibrosis and cirrhosis.

Development of Machine Learning Methods for Accurate Prediction of Plant Disease Resistance

The traditional method of screening plants for disease resistance phenotype is both time-consuming and costly.Genomic selection offers a potential solution to improve efficiency,but accurately predicting plant disease resistance remains a challenge.In this study,we evaluated eight different machine learning(ML)methods,including random forest classification(RFC),support vector classifier(SVC),light gradient boosting machine(lightGBM),random forest classification plus kinship(RFC_K),support vector classification plus kinship(SVC_K),light gradient boosting machine plus kinship(lightGBM_K),deep neural network genomic prediction(DNNGP),and densely connected convolutional networks(DenseNet),for predicting plant disease resistance.Our results demonstrate that the three plus kinship(K)methods developed in this study achieved high prediction accuracy.Specifically,these methods achieved accuracies of up to 95%for rice blast(RB),85%for rice black-streaked dwarf virus(RBSDV),and 85%for rice sheath blight(RSB)when trained and applied to the rice diversity panel I(RDPI).Furthermore,the plus K models performed well in predicting wheat blast(WB)and wheat stripe rust(WSR)diseases,with mean accuracies of up to 90%and 93%,respectively.To assess the generalizability of our models,we applied the trained plus K methods to predict RB disease resistance in an independent population,rice diversity panel II(RDPII).Concurrently,we evaluated the RB resistance of RDPII cultivars using spray inoculation.Comparing the predictions with the spray inoculation results,we found that the accuracy of the plus K methods reached 91%.These findings highlight the effectiveness of the plus K methods(RFC_K,SVC_K,and lightGBM_K)in accurately predicting plant disease resistance for RB,RBSDV,RSB,WB,and WSR.The methods developed in this study not only provide valuable strategies for predicting disease resistance,but also pave the way for using machine learning to streamline genome-based crop breeding.

Identification of SSR markers linked to the abscission of cotton boll traits and mining germplasm in Cotton

Background Cotton is an economically important crop.It is crucial to find an effective method to improve cotton yield,and one approach is to decrease the abscission of cotton bolls and buds.However,the lack of knowledge of the genetic and molecular mechanisms underlying cotton boll abscission traits has hindered genetic improvements.Results Pearson’s correlation analysis revealed a significant positive correlation between boll abscission rates 1(AR1)and boll abscission rates 2(AR2).A genome-wide association study was conducted on 145 loci that exhibited high polymorphism and were uniformly distributed across 26 chromosomes(pair).The study revealed 18,46,and 62 markers that were significantly associated with boll abscission,fiber quality,and yield traits(P<0.05),explaining 1.75%–7.13%,1.16%–9.58%,and 1.40%–5.44%of the phenotypic variation,respectively.Notably,the marker MON_SHIN-1584b was associated with the cotton boll abscission trait,whereas MON_CGR5732a was associated with cotton boll abscission and fiber quality traits.Thirteen of the marker loci identified in this study had been previously reported.Based on phenotypic effects,six typical cultivars with elite alleles related to cotton boll abscission,fiber quality,and yield traits were identified.These cultivars hold great promise for widespread utilization in breeding programs.Conclusions These results lay the foundation for understanding the molecular regulatory mechanism of cotton boll abscission and provide data for the future improvement of cotton breeding.

Interplay between metabolic dysfunction-associated fatty liver disease and renal function: An intriguing pediatric perspective

Over recent years,the nomenclature of non-alcoholic fatty liver disease has undergone significant changes.Indeed,in 2020,an expert consensus panel proposed the term“Metabolic(dysfunction)associated fatty liver disease”(MAFLD)to underscore the close association of fatty liver with metabolic abnormalities,thereby highlighting the cardiometabolic risks(such as metabolic syndrome,type 2 diabetes,insulin resistance,and cardiovascular disease)faced by these patients since childhood.More recently,this term has been further replaced with metabolic associated steatotic liver disease.It is worth noting that emerging evidence not only supports a close and independent association of MAFLD with chronic kidney disease in adults but also indicates its interplay with metabolic impairments.However,comparable pediatric data remain limited.Given the progressive and chronic nature of both diseases and their prognostic cardiometabolic implications,this editorial aims to provide a pediatric perspective on the intriguing relationship between MAFLD and renal function in childhood.

The Genetic Association between CDKN1A and Heart Failure:Genome-Wide Exploration of m6A-SNPs and Mendelian Randomization

Objective N6-methyladenosine(m^(6)A)is a common epigenetic modification in eukaryotes.In this study,we explore the potential impact of m^(6)A-associated single nucleotide polymorphisms(m^(6)A-SNPs)on heart failure(HF).Methods Data from genome-wide association studies(GWAS)investigating HF in humans and from m^(6)A-SNPs datasets were used to identify HF-associated m^(6)A-SNPs.Their functions were explored using expression quantitative trait locus(eQTL),gene expression,and gene enrichment analyses.Mediation protein quantitative trait locus(pQTL)-Mendelian randomization(MR)was used to investigate the potential mechanism between critical protein levels and risk factors for HF.Results We screened 44 HF-associated m^(6)A-SNPs,including 10 m^(6)A-SNPs that showed eQTL signals and differential expressions in HF.The SNP rs1801270 in CDKN1A showed the strongest association with HF(P=7.75×10^(−6)).Additionally,MR verified the genetic association between the CDKN1A protein and HF,as well as the mediating effect of blood pressure(BP)in this pathway.Higher circulating level of CDKN1A was associated with a lower risk of HF(odds ratio[OR]=0.82,95%confidence interval[CI]:0.69 to 0.99).The proportions of hypertension,systolic BP,and diastolic BP were 48.10%,28.94%,and 18.02%,respectively.Associations of PDIA6(P=1.30×10^(−2))and SMAD3(P=4.80×10^(−2))with HF were also detected.Conclusion Multiple HF-related m^(6)A-SNPs were identified in this study.Genetic associations of CDKN1A and other proteins with HF and its risk factors were demonstrated,providing new ideas for further exploration of the molecular mechanisms of HF.

Unveiling DNA methylation in Alzheimer’s disease:a review of array-based human brain studies

The intricacies of Alzheimer’s disease pathogenesis are being increasingly illuminated by the exploration of epigenetic mechanisms,particularly DNA methylation.This review comprehensively surveys recent human-centered studies that investigate whole genome DNA methylation in Alzheimer’s disease neuropathology.The examination of various brain regions reveals distinctive DNA methylation patterns that associate with the Braak stage and Alzheimer’s disease progression.The entorhinal cortex emerges as a focal point due to its early histological alterations and subsequent impact on downstream regions like the hippocampus.Notably,ANK1 hypermethylation,a protein implicated in neurofibrillary tangle formation,was recurrently identified in the entorhinal cortex.Further,the middle temporal gyrus and prefrontal cortex were shown to exhibit significant hypermethylation of genes like HOXA3,RHBDF2,and MCF2L,potentially influencing neuroinflammatory processes.The complex role of BIN1 in late-onset Alzheimer’s disease is underscored by its association with altered methylation patterns.Despite the disparities across studies,these findings highlight the intricate interplay between epigenetic modifications and Alzheimer’s disease pathology.Future research efforts should address methodological variations,incorporate diverse cohorts,and consider environmental factors to unravel the nuanced epigenetic landscape underlying Alzheimer’s disease progression.

Associative Tasks Computing Offloading Scheme in Internet of Medical Things with Deep Reinforcement Learning

The Internet of Medical Things(Io MT) is regarded as a critical technology for intelligent healthcare in the foreseeable 6G era. Nevertheless, due to the limited computing power capability of edge devices and task-related coupling relationships, Io MT faces unprecedented challenges. Considering the associative connections among tasks, this paper proposes a computing offloading policy for multiple-user devices(UDs) considering device-to-device(D2D) communication and a multi-access edge computing(MEC)technique under the scenario of Io MT. Specifically,to minimize the total delay and energy consumption concerning the requirement of Io MT, we first analyze and model the detailed local execution, MEC execution, D2D execution, and associated tasks offloading exchange model. Consequently, the associated tasks’ offloading scheme of multi-UDs is formulated as a mixed-integer nonconvex optimization problem. Considering the advantages of deep reinforcement learning(DRL) in processing tasks related to coupling relationships, a Double DQN based associative tasks computing offloading(DDATO) algorithm is then proposed to obtain the optimal solution, which can make the best offloading decision under the condition that tasks of UDs are associative. Furthermore, to reduce the complexity of the DDATO algorithm, the cacheaided procedure is intentionally introduced before the data training process. This avoids redundant offloading and computing procedures concerning tasks that previously have already been cached by other UDs. In addition, we use a dynamic ε-greedy strategy in the action selection section of the algorithm, thus preventing the algorithm from falling into a locally optimal solution. Simulation results demonstrate that compared with other existing methods for associative task models concerning different structures in the Io MT network, the proposed algorithm can lower the total cost more effectively and efficiently while also providing a tradeoff between delay and energy consumption tolerance.

Analysis of the joint detection capability of the SMILE satellite and EISCAT-3D radar

The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)satellite is a small magnetosphere–ionosphere link explorer developed cooperatively between China and Europe.It pioneers the use of X-ray imaging technology to perform large-scale imaging of the Earth’s magnetosheath and polar cusp regions.It uses a high-precision ultraviolet imager to image the overall configuration of the aurora and monitor changes in the source of solar wind in real time,using in situ detection instruments to improve human understanding of the relationship between solar activity and changes in the Earth’s magnetic field.The SMILE satellite is scheduled to launch in 2025.The European Incoherent Scatter Sciences Association(EISCAT)-3D radar is a new generation of European incoherent scatter radar constructed by EISCAT and is the most advanced ground-based ionospheric experimental device in the high-latitude polar region.It has multibeam and multidirectional quasi-real-time three-dimensional(3D)imaging capabilities,continuous monitoring and operation capabilities,and multiple-baseline interferometry capabilities.Joint detection by the SMILE satellite and the EISCAT-3D radar is of great significance for revealing the coupling process of the solar wind–magnetosphere–ionosphere.Therefore,we performed an analysis of the joint detection capability of the SMILE satellite and EISCAT-3D,analyzed the period during which the two can perform joint detection,and defined the key scientific problems that can be solved by joint detection.In addition,we developed Web-based software to search for and visualize the joint detection period of the SMILE satellite and EISCAT-3D radar,which lays the foundation for subsequent joint detection experiments and scientific research.

Anti-tumor efficacy of Calculus bovis: Suppressing liver cancer by targeting tumor-associated macrophages

Despite significant advances in our understanding of the molecular pathogenesis of liver cancer and the availability of novel pharmacotherapies,liver cancer remains the fourth leading cause of cancer-related mortality worldwide.Tumor relapse,resistance to current anti-cancer drugs,metastasis,and organ toxicity are the major challenges that prevent considerable improvements in patient survival and quality of life.Calculus bovis(CB),an ancient Chinese medicinal drug,has been used to treat various pathologies,including stroke,convulsion,epilepsy,pain,and cancer.In this editorial,we discuss the research findings recently published by Huang et al on the therapeutic effects of CB in inhibiting the development of liver cancer.Utilizing the comprehensive transcriptomic analyses,in vitro experiments,and in vivo studies,the authors demonstrated that CB treatment inhibits the tumor-promoting M2 phenotype of tumor-associated macrophages via downregulating Wnt pathway.While multiple studies have been performed to explore the molecular mechanisms regulated by CB,this study uniquely shows its role in modulating the M2 phenotype of macrophages present within the tumor microenvironment.This study opens new avenues of future investigations aimed at investigating this drug’s efficacy in various mouse models including the effects of combination therapy,and against drug-resistant tumors.

Sedimentological evidence of climate-tectonic interaction in the upper Satluj catchment of NW Himalaya

Quaternary valley fill deposits in the Upper Satluj Valley of NW Himalaya act as archives of changing climate-tectonic dynamics in a region.Quaternary landforms help in decoding the relationship between climate and tectonics.Kinnaur region is traversed by several active faults and thrusts such as the Kaurik-Chango Fault(KCF)and Sangla Detachment(SD),thereby making upper Satluj Valley tectonically active.Morphotectonic parameters such as width of valley floor(Vfw),Normalized Steepness Index(KSn)and geomorphological evidences such as the presence of huge strath terraces,narrowing of the river valley and palaeolake deposits point towards the tectonically active nature of the terrain.This arid,high elevation region is also climatically sensitive as it falls in a transient climatic zone which receives rainfall only during abnormal monsoon months.Excessive rainfall causes outburst floods,a common phenomenon in the area due to the blocking of headwater in the upper reaches of the Satluj valley.As a result,the Quaternary sequence is modified from time to time.The transition from hypo concentrated deposits to channel deposits and ponding events are prominent in the depositional sequence,resulting from a response to climate.The studied Quaternary sediments reveal that the Trans-Himalayan region of the upper Satluj valley is affected by tectonic-climate variability,making it vulnerable to geohazards.

Quantitative assessment of self-management in patients with nonalcoholic fatty liver disease: An unmet clinical need

In this editorial we comment on the article titled“Establishment and validation of an adherence prediction system for lifestyle interventions in non-alcoholic fatty liver disease”by Zeng et al published in a recent issue of the World Journal of Gastroenterology.Non-alcoholic fatty liver disease(NAFLD)represents one of the current challenges in hepatology and public health,due to its continuous growing prevalence and the rising incidence of NAFLD-related fibrosis,non-alcoholic steatohepatitis and cirrhosis.The only effective therapeutic strategy for this dis-ease is represented by encouraging patients to improve their lifestyle through the modification of dietary intake and increased physical exercise,but the effective application of such modifications is often limited by various factors such as lack of information,psychological barriers or poor social support.While poor adherence to a healthy lifestyle can be decisive in determining the clinical outcome,in daily practice there is a lack of quantitative instruments aimed at identifying patients with the lowest adherence to lifestyle changes and higher risk of disease progre-ssion in the course of follow-up.In this article,Zeng et al propose a quantitative scale to assess the grade of adherence of patients with NAFLD to hea-lthy lifestyle intervention,called the Exercise and Diet Adherence Scale(EDAS).This scale,consisting of 33 items divided into 6 dimensions which relates to six subjective aspects in the self-management of NAFLD,has shown a good correlation with the identification of the sub-cohort of patients with the highest reduction in caloric intake,increase in physical exercise,probability of a reduction in liver stiffness measurement and alanine aminotransferase levels.The cor-relation among clinical outcomes and specific dimensions of this scale also highlights the pivotal role of a good and confidential doctor-patient relationship and of an effective communication.There is an urgent need for practical and effective instruments to assess the grade of self-management of NAFLD patients,together with the development of multidisciplinary teams with the aim of applying structured behavioral interventions.