Exploiting fly models to investigate rare human neurological disorders

Rare neurological diseases,while individually are rare,collectively impact millions globally,leading to diverse and often severe neurological symptoms.Often attributed to genetic mutations that disrupt protein function or structure,understanding their genetic basis is crucial for accurate diagnosis and targeted therapies.To investigate the underlying pathogenesis of these conditions,researchers often use non-mammalian model organisms,such as Drosophila(fruit flies),which is valued for their genetic manipulability,cost-efficiency,and preservation of genes and biological functions across evolutionary time.Genetic tools available in Drosophila,including CRISPR-Cas9,offer a means to manipulate gene expression,allowing for a deep exploration of the genetic underpinnings of rare neurological diseases.Drosophila boasts a versatile genetic toolkit,rapid generation turnover,and ease of large-scale experimentation,making it an invaluable resource for identifying potential drug candidates.Researchers can expose flies carrying disease-associated mutations to various compounds,rapidly pinpointing promising therapeutic agents for further investigation in mammalian models and,ultimately,clinical trials.In this comprehensive review,we explore rare neurological diseases where fly research has significantly contributed to our understanding of their genetic basis,pathophysiology,and potential therapeutic implications.We discuss rare diseases associated with both neuron-expressed and glial-expressed genes.Specific cases include mutations in CDK19 resulting in epilepsy and developmental delay,mutations in TIAM1 leading to a neurodevelopmental disorder with seizures and language delay,and mutations in IRF2BPL causing seizures,a neurodevelopmental disorder with regression,loss of speech,and abnormal movements.And we explore mutations in EMC1 related to cerebellar atrophy,visual impairment,psychomotor retardation,and gain-of-function mutations in ACOX1 causing Mitchell syndrome.Loss-of-function mutations in ACOX1 result in ACOX1 deficiency,characterized by very-long-chain fatty acid accumulation and glial degeneration.Notably,this review highlights how modeling these diseases in Drosophila has provided valuable insights into their pathophysiology,offering a platform for the rapid identification of potential therapeutic interventions.Rare neurological diseases involve a wide range of expression systems,and sometimes common phenotypes can be found among different genes that cause abnormalities in neurons or glia.Furthermore,mutations within the same gene may result in varying functional outcomes,such as complete loss of function,partial loss of function,or gain-of-function mutations.The phenotypes observed in patients can differ significantly,underscoring the complexity of these conditions.In conclusion,Drosophila represents an indispensable and cost-effective tool for investigating rare neurological diseases.By facilitating the modeling of these conditions,Drosophila contributes to a deeper understanding of their genetic basis,pathophysiology,and potential therapies.This approach accelerates the discovery of promising drug candidates,ultimately benefiting patients affected by these complex and understudied diseases.

Metabolic reprogramming: a new option for the treatment of spinal cord injury

Spinal cord injuries impose a notably economic burden on society,mainly because of the severe after-effects they cause.Despite the ongoing development of various therapies for spinal cord injuries,their effectiveness remains unsatisfactory.However,a deeper understanding of metabolism has opened up a new therapeutic opportunity in the form of metabolic reprogramming.In this review,we explore the metabolic changes that occur during spinal cord injuries,their consequences,and the therapeutic tools available for metabolic reprogramming.Normal spinal cord metabolism is characterized by independent cellular metabolism and intercellular metabolic coupling.However,spinal cord injury results in metabolic disorders that include disturbances in glucose metabolism,lipid metabolism,and mitochondrial dysfunction.These metabolic disturbances lead to corresponding pathological changes,including the failure of axonal regeneration,the accumulation of scarring,and the activation of microglia.To rescue spinal cord injury at the metabolic level,potential metabolic reprogramming approaches have emerged,including replenishing metabolic substrates,reconstituting metabolic couplings,and targeting mitochondrial therapies to alter cell fate.The available evidence suggests that metabolic reprogramming holds great promise as a next-generation approach for the treatment of spinal cord injury.To further advance the metabolic treatment of the spinal cord injury,future efforts should focus on a deeper understanding of neurometabolism,the development of more advanced metabolomics technologies,and the design of highly effective metabolic interventions.

Decoding the nexus:branched-chain amino acids and their connection with sleep,circadian rhythms,and cardiometabolic health

The sleep-wake cycle stands as an integrative process essential for sustaining optimal brain function and,either directly or indirectly,overall body health,encompassing metabolic and cardiovascular well-being.Given the heightened metabolic activity of the brain,there exists a considerable demand for nutrients in comparison to other organs.Among these,the branched-chain amino acids,comprising leucine,isoleucine,and valine,display distinctive significance,from their contribution to protein structure to their involvement in overall metabolism,especially in cerebral processes.Among the first amino acids that are released into circulation post-food intake,branched-chain amino acids assume a pivotal role in the regulation of protein synthesis,modulating insulin secretion and the amino acid sensing pathway of target of rapamycin.Branched-chain amino acids are key players in influencing the brain's uptake of monoamine precursors,competing for a shared transporter.Beyond their involvement in protein synthesis,these amino acids contribute to the metabolic cycles ofγ-aminobutyric acid and glutamate,as well as energy metabolism.Notably,they impact GABAergic neurons and the excitation/inhibition balance.The rhythmicity of branchedchain amino acids in plasma concentrations,observed over a 24-hour cycle and conserved in rodent models,is under circadian clock control.The mechanisms underlying those rhythms and the physiological consequences of their disruption are not fully understood.Disturbed sleep,obesity,diabetes,and cardiovascular diseases can elevate branched-chain amino acid concentrations or modify their oscillatory dynamics.The mechanisms driving these effects are currently the focal point of ongoing research efforts,since normalizing branched-chain amino acid levels has the ability to alleviate the severity of these pathologies.In this context,the Drosophila model,though underutilized,holds promise in shedding new light on these mechanisms.Initial findings indicate its potential to introduce novel concepts,particularly in elucidating the intricate connections between the circadian clock,sleep/wake,and metabolism.Consequently,the use and transport of branched-chain amino acids emerge as critical components and orchestrators in the web of interactions across multiple organs throughout the sleep/wake cycle.They could represent one of the so far elusive mechanisms connecting sleep patterns to metabolic and cardiovascular health,paving the way for potential therapeutic interventions.

Lipid droplets in the nervous system:involvement in cell metabolic homeostasis

Lipid droplets serve as primary storage organelles for neutral lipids in neurons,glial cells,and other cells in the nervous system.Lipid droplet formation begins with the synthesis of neutral lipids in the endoplasmic reticulum.Previously,lipid droplets were recognized for their role in maintaining lipid metabolism and energy homeostasis;however,recent research has shown that lipid droplets are highly adaptive organelles with diverse functions in the nervous system.In addition to their role in regulating cell metabolism,lipid droplets play a protective role in various cellular stress responses.Furthermore,lipid droplets exhibit specific functions in neurons and glial cells.Dysregulation of lipid droplet formation leads to cellular dysfunction,metabolic abnormalities,and nervous system diseases.This review aims to provide an overview of the role of lipid droplets in the nervous system,covering topics such as biogenesis,cellular specificity,and functions.Additionally,it will explore the association between lipid droplets and neurodegenerative disorders.Understanding the involvement of lipid droplets in cell metabolic homeostasis related to the nervous system is crucial to determine the underlying causes and in exploring potential therapeutic approaches for these diseases.

Aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders:progress of experimental models based on disease pathogenesis

Neuromyelitis optica spectrum disorders are neuroinflammatory demyelinating disorders that lead to permanent visual loss and motor dysfunction.To date,no effective treatment exists as the exact causative mechanism remains unknown.Therefore,experimental models of neuromyelitis optica spectrum disorders are essential for exploring its pathogenesis and in screening for therapeutic targets.Since most patients with neuromyelitis optica spectrum disorders are seropositive for IgG autoantibodies against aquaporin-4,which is highly expressed on the membrane of astrocyte endfeet,most current experimental models are based on aquaporin-4-IgG that initially targets astrocytes.These experimental models have successfully simulated many pathological features of neuromyelitis optica spectrum disorders,such as aquaporin-4 loss,astrocytopathy,granulocyte and macrophage infiltration,complement activation,demyelination,and neuronal loss;however,they do not fully capture the pathological process of human neuromyelitis optica spectrum disorders.In this review,we summarize the currently known pathogenic mechanisms and the development of associated experimental models in vitro,ex vivo,and in vivo for neuromyelitis optica spectrum disorders,suggest potential pathogenic mechanisms for further investigation,and provide guidance on experimental model choices.In addition,this review summarizes the latest information on pathologies and therapies for neuromyelitis optica spectrum disorders based on experimental models of aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders,offering further therapeutic targets and a theoretical basis for clinical trials.

Perfluoropentane-based oxygen-loaded nanodroplets reduce microglial activation through metabolic reprogramming

Microglia,the primary immune cells within the brain,have gained recognition as a promising therapeutic target for managing neurodegenerative diseases within the central nervous system,including Parkinson’s disease.Nanoscale perfluorocarbon droplets have been reported to not only possess a high oxygen-carrying capacity,but also exhibit remarkable anti-inflammatory properties.However,the role of perfluoropentane in microglia-mediated central inflammatory reactions remains poorly understood.In this study,we developed perfluoropentane-based oxygen-loaded nanodroplets(PFP-OLNDs)and found that pretreatment with these droplets suppressed the lipopolysaccharide-induced activation of M1-type microglia in vitro and in vivo,and suppressed microglial activation in a mouse model of Parkinson’s disease.Microglial suppression led to a reduction in the inflammatory response,oxidative stress,and cell migration capacity in vitro.Consequently,the neurotoxic effects were mitigated,which alleviated neuronal degeneration.Additionally,ultrahigh-performance liquid chromatography–tandem mass spectrometry showed that the anti-inflammatory effects of PFP-OLNDs mainly resulted from the modulation of microglial metabolic reprogramming.We further showed that PFP-OLNDs regulated microglial metabolic reprogramming through the AKT-mTOR-HIF-1αpathway.Collectively,our findings suggest that the novel PFP-OLNDs constructed in this study alleviate microglia-mediated central inflammatory reactions through metabolic reprogramming.

White-rot Fungus Growth Conditions and Its Metabolic Kinetic Models

To investigate the growth conditions of white-rot fungus and simulate its metabolism kinetic models, the rules how the factors such as biomass, culture fluid, pH value, glucose consumption and exopolysaccharides generation, etc., changed during the batch culture process of white-rot fungi by using an air-lift fermenter, as well as metabolic kinetics of white-rot fungi were studied. Based on Logistic equation, Luedeking-Piret equation and experimental data, the correlation model parameters of mycelia biomass, glucose consumption and exopolysaccharide generation were obtained and found to be change with time in metabolism process. Detailedly, μm=0.071 8 h-1,α= 0.831 8 g/(g·h), β= 0.002 g/(g·h), b1=0.016 3 g/(g·h) and b2=3.023 3 g/(g·h). Hence the mycelial growth kinetic model, exopolysaccharide generation kinetic model and substrate consumption kinetic model which describe fermentation process of white-rot fungi were established. Meanwhile, the experimental data were verified by this model, and a good fitting result with an average relative error less than 10% between the data obtained from experiments and the model was yielded. The results show that these models can predict the growth and metabolic rules of white-rot fungus, the fermentation process of exopolysaccharides and the kinetic mechanism of white-rot fungus accurately.

Analysis of Data on Xanthan Fermentation in Stationary Phase Using Black Box and Metabolic Network Models

The xanthan fermentation data in the stationary phase was analyzed using the black box and the metabolic network models. The data consistency is checked through the elemental balance in the black box model. In the metabolic network model, the metabolic flux distribution in the cell is calculated using the metabolic flux analysis method, then the maintenance coefficients is calculated.

Rapid metabolic fingerprinting with the aid of chemometric models to identify authenticity of natural medicines: Turmeric, Ocimum, and Withania somnifera study

Herbal medicines are popular natural medicines that have been used for decades.The use of alternative medicines continues to expand rapidly across the world.The World Health Organization suggests that quality assessment of natural medicines is essential for any therapeutic or health care applications,as their therapeutic potential varies between different geographic origins,plant species,and varieties.Classification of herbal medicines based on a limited number of secondary metabolites is not an ideal approach.Their quality should be considered based on a complete metabolic profile,as their pharmacological activity is not due to a few specific secondary metabolites but rather a larger group of bioactive compounds.A holistic and integrative approach using rapid and nondestructive analytical strategies for the screening of herbal medicines is required for robust characterization.In this study,a rapid and effective quality assessment system for geographical traceability,species,and variety-specific authenticity of the widely used natural medicines turmeric,Ocimum,and Withania somnifera was investigated using Fourier transform near-infrared(FT-NIR)spectroscopy-based metabolic fingerprinting.Four different geographical origins of turmeric,five different Ocimum species,and three different varieties of roots and leaves of Withania somnifera were studied with the aid of machine learning approaches.Extremely good discrimination(R^(2)>0.98,Q^(2)>0.97,and accuracy=1.0)with sensitivity and specificity of 100%was achieved using this metabolic fingerprinting strategy.Our study demonstrated that FT-NIR-based rapid metabolic fingerprinting can be used as a robust analytical method to authenticate several important medicinal herbs.

FibroScan-aspartate transaminase:A superior non-invasive model for diagnosing high-risk metabolic dysfunction-associated steatohepatitis

BACKGROUND Non-alcoholic fatty liver disease(NAFLD)with hepatic histological NAFLD activity score≥4 and fibrosis stage F≥2 is regarded as“at risk”non-alcoholic steatohepatitis(NASH).Based on an international consensus,NAFLD and NASH were renamed as metabolic dysfunction-associated steatotic liver disease(MASLD)and metabolic dysfunction-associated steatohepatitis(MASH),respectively;hence,we introduced the term“high-risk MASH”.Diagnostic values of seven non-invasive models,including FibroScan-aspartate transaminase(FAST),fibrosis-4(FIB-4),aspartate transaminase to platelet ratio index(APRI),etc.for high-risk MASH have rarely been studied and compared in MASLD.AIM To assess the clinical value of seven non-invasive models as alternatives to liver biopsy for diagnosing high-risk MASH.METHODS A retrospective analysis was conducted on 309 patients diagnosed with NAFLD via liver biopsy at Beijing Ditan Hospital,between January 2012 and December 2020.After screening for MASLD and the exclusion criteria,279 patients wereincluded and categorized into high-risk and non-high-risk MASH groups.Utilizing threshold values of each model,sensitivity,specificity,positive predictive value(PPV),and negative predictive values(NPV),were calculated.Receiver operating characteristic curves were constructed to evaluate their diagnostic efficacy based on the area under the curve(AUROC).RESULTS MASLD diagnostic criteria were met by 99.4%patients with NAFLD.The MASLD population was analyzed in two cohorts:Overall population(279 patients)and the subgroup(117 patients)who underwent liver transient elastography(FibroScan).In the overall population,FIB-4 showed better diagnostic efficacy and higher PPV,with sensitivity,specificity,PPV,NPV,and AUROC of 26.9%,95.2%,73.5%,72.2%,and 0.75.APRI,Forns index,and aspartate transaminase to alanine transaminase ratio(ARR)showed moderate diagnostic efficacy,whereas S index and gamma-glutamyl transpeptidase to platelet ratio(GPR)were relatively weaker.In the subgroup,FAST had the highest diagnostic efficacy,its sensitivity,specificity,PPV,NPV,and AUROC were 44.2%,92.3%,82.1%,67.4%,and 0.82.The FIB-4 AUROC was 0.76.S index and GPR exhibited almost no diagnostic value for high-risk MASH.CONCLUSION FAST and FIB-4 could replace liver biopsy as more effectively diagnostic methods for high-risk MASH compared to APRI,Forns index,ARR,S index,and GPR;FAST is superior to FIB-4.

Role of gut-liver axis and glucagon-like peptide-1 receptor agonists in the treatment of metabolic dysfunction-associated fatty liver disease

Metabolic dysfunction-associated fatty liver disease(MAFLD)is a hepatic manifestation of the metabolic syndrome.It is one of the most common liver diseases worldwide and shows increasing prevalence rates in most countries.MAFLD is a progressive disease with the most severe cases presenting as advanced fibrosis or cirrhosis with an increased risk of hepatocellular carcinoma.Gut microbiota play a significant role in the pathogenesis and progression of MAFLD by disrupting the gut-liver axis.The mechanisms involved in maintaining gut-liver axis homeostasis are complex.One critical aspect involves preserving an appropriate intestinal barrier permeability and levels of intestinal lumen metabolites to ensure gutliver axis functionality.An increase in intestinal barrier permeability induces metabolic endotoxemia that leads to steatohepatitis.Moreover,alterations in the absorption of various metabolites can affect liver metabolism and induce liver steatosis and fibrosis.Glucagon-like peptide-1 receptor agonists(GLP-1 RAs)are a class of drugs developed for the treatment of type 2 diabetes mellitus.They are also commonly used to combat obesity and have been proven to be effective in reversing hepatic steatosis.The mechanisms reported to be involved in this effect include an improved regulation of glycemia,reduced lipid synthesis,β-oxidation of free fatty acids,and induction of autophagy in hepatic cells.Recently,multiple peptide receptor agonists have been introduced and are expected to increase the effectiveness of the treatment.A modulation of gut microbiota has also been observed with the use of these drugs that may contribute to the amelioration of MAFLD.This review presents the current understanding of the role of the gutliver axis in the development of MAFLD and use of members of the GLP-1 RA family as pleiotropic agents in the treatment of MAFLD.

Experimental models of metabolic and alcoholic fatty liver disease

Non-alcoholic fatty liver disease(NAFLD)is a multi-systemic disease that is considered the hepatic manifestation of metabolic syndrome(MetS).Because alcohol consumption in NAFLD patients is common,there is a significant overlap in the pathogenesis of NAFLD and alcoholic liver disease(ALD).Indeed,MetS also significantly contributes to liver injury in ALD patients.This“syndrome of metabolic and alcoholic steatohepatitis”(SMASH)is thus expected to be a more prevalent presentation in liver patients,as the obesity epidemic continues.Several pre-clinical experimental models that couple alcohol consumption with NAFLDinducing diet or genetic obesity have been developed to better understand the pathogenic mechanisms of SMASH.These models indicate that concomitant MetS and alcohol contribute to lipid dysregulation,oxidative stress,and the induction of innate immune response.There are significant limitations in the applicability of these models to human disease,such as the ability to induce advanced liver injury or replicate patterns in human food/alcohol consumption.Thus,there remains a need to develop models that accurately replicate patterns of obesogenic diet and alcohol consumption in SMASH patients.

Metabolic and hepatic effects of liraglutide,obeticholic acid and elafibranor in diet-induced obese mouse models of biopsy-confirmed nonalcoholic steatohepatitis

AIM To evaluate the pharmacodynamics of compounds in clinical development for nonalcoholic steatohepatitis(NASH) in obese mouse models of biopsy-confirmedNASH.METHODS Male wild-type C57 BL/6 J mice(DIO-NASH) and Lep^(ob/ob)(ob/ob-NASH) mice were fed a diet high in trans-fat(40%), fructose(20%) and cholesterol(2%) for 30 and 21 wk, respectively. Prior to treatment, all mice underwent liver biopsy for confirmation and stratification of liver steatosis and fibrosis, using the nonalcoholic fatty liver disease activity score(NAS) and fibrosis staging system. The mice were kept on the diet and received vehicle, liraglutide(0.2 mg/kg, SC, BID), obeticholic acid(OCA, 30 mg/kg PO, QD), or elafibranor(30 mg/kg PO, QD) for eight weeks. Within-subject comparisons were performed on changes in steatosis, inflammation, ballooning degeneration, and fibrosis scores. In addition, compound effects were evaluated by quantitative liver histology, including percent fractional area of liver fat, galectin-3, and collagen 1 a1.RESULTS Liraglutide and elafibranor, but not OCA, reduced body weight in both models. Liraglutide improved steatosis scores in DIO-NASH mice only. Elafibranor and OCA reduced histopathological scores of hepatic steatosis and inflammation in both models, but only elafibranor reduced fibrosis severity. Liraglutide and OCA reduced total liver fat, collagen 1 a1, and galectin-3 content, driven by significant reductions in liver weight. The individual drug effects on NASH histological endpoints were supported by global gene expression(RNA sequencing) and liver lipid biochemistry.CONCLUSION DIO-NASH and ob/ob-NASH mouse models show distinct treatment effects of liraglutide, OCA, and elafibranor, being in general agreement with corresponding findings in clinical trials for NASH. The present data therefore further supports the clinical translatability and utility of DIO-NASH and ob/ob-NASH mouse models of NASH for probing the therapeutic efficacy of compounds in preclinical drug development for NASH.

Metabolic disease and the liver: A review

Metabolic dysfunction-associated steatotic liver disease(MASLD)is the most common liver disease worldwide,with an estimated prevalence of 31%in Latin America.The presence of metabolic comorbidities coexisting with liver disease varies substantially among populations.It is acknowledged that obesity is boosting the type 2 diabetes mellitus“epidemic,”and both conditions are significant contributors to the increasing number of patients with MASLD.Nonalcoholic steatohepatitis represents a condition of chronic liver inflammation and is considered the most severe form of MASLD.MASLD diagnosis is based on the presence of steatosis,noninvasive scores and altered liver tests.Noninvasive scores of liver fibrosis,such as serum biomarkers,which should be used in primary care to rule out advanced fibrosis,are simple,inexpensive,and widely available.Currently,guidelines from international hepatology societies recommend using noninvasive strategies to simplify case finding and management of high-risk patients with MASLD in clinical practice.Unfortunately,there is no definite pharmacological treatment for the condition.Creating public health policies to treat patients with risk factors for MASLD prevention is essential.

Relating models of activity metabolism to the metabolic efficiency of steady swimming

Power-law ( ) and exponential power-law ( ) functional forms model activity metabolism ( ) for fully submerged swimming animals, and are special cases of the power-law polynomial equation, in which?? is the observed total metabolic rate measured at an observed steady swimming speed,? . The relationship between the metabolic efficiency of steady swimming and the exponents of?? is addressed in this paper to establish the use of?? () and?? () as optimal efficiencies for comparing the hydrodynamic and muscle metabolic efficiencies among fully submerged animals that engage in steady swimming activities. The metabolic efficiency of steady swimming is transformed into its ideal form ( ) from which??? the optimal hydrodynamic efficiency ( ) and the optimal muscle metabolic efficiency ( ) are derived. These optimal efficiencies are therefore ideal metabolic efficiencies measured at different optimal steady speeds. Subsequently, linear ( ) and exponential ( ) models are approximations with divergent optimal muscle metabolic efficiencies ( and , respectively), but with a similar optimal hydrodynamic efficiency ( ).

Anisotropic time-dependent behaviors of shale under direct shearing and associated empirical creep models

Understanding the anisotropic creep behaviors of shale under direct shearing is a challenging issue.In this context,we conducted shear-creep and steady-creep tests on shale with five bedding orientations (i.e.0°,30°,45°,60°,and 90°),under multiple levels of direct shearing for the first time.The results show that the anisotropic creep of shale exhibits a significant stress-dependent behavior.Under a low shear stress,the creep compliance of shale increases linearly with the logarithm of time at all bedding orientations,and the increase depends on the bedding orientation and creep time.Under high shear stress conditions,the creep compliance of shale is minimal when the bedding orientation is 0°,and the steady-creep rate of shale increases significantly with increasing bedding orientations of 30°,45°,60°,and 90°.The stress-strain values corresponding to the inception of the accelerated creep stage show an increasing and then decreasing trend with the bedding orientation.A semilogarithmic model that could reflect the stress dependence of the steady-creep rate while considering the hardening and damage process is proposed.The model minimizes the deviation of the calculated steady-state creep rate from the observed value and reveals the behavior of the bedding orientation's influence on the steady-creep rate.The applicability of the five classical empirical creep models is quantitatively evaluated.It shows that the logarithmic model can well explain the experimental creep strain and creep rate,and it can accurately predict long-term shear creep deformation.Based on an improved logarithmic model,the variations in creep parameters with shear stress and bedding orientations are discussed.With abovementioned findings,a mathematical method for constructing an anisotropic shear creep model of shale is proposed,which can characterize the nonlinear dependence of the anisotropic shear creep behavior of shale on the bedding orientation.

Metabolic dysfunction-associated steatotic liver disease:Navigating terminological evolution,diagnostic frontiers and therapeutic horizon-an editorial exploration

Metabolic dysfunction-associated steatotic liver disease(MASLD),once known as non-alcoholic fatty liver disease(NAFLD),represents a spectrum of liver disorders characterized by lipid accumulation within hepatocytes.The redefinition of NAFLD in 2023 marked a significant reposition in terminology,emphasizing a broader understanding of liver steatosis and its associated risks.MASLD is now recognized as a major risk factor for liver cirrhosis,hepatocellular carcinoma,and systemic complications such as cardiovascular diseases or systemic inflammation.Diagnostic challenges arise,particularly in identifying MASLD in lean individuals,necessitating updated diagnostic protocols and investing in non-invasive diagnostic tools.Therapeutically,there is an urgent need for effective treatments targeting MASLD,with emerging pharmacological options focusing on,among others,carbohydrate and lipid metabolism.Additionally,understanding the roles of bile acid metabolism,the microbiome,and dietary interventions in MASLD pathogenesis and management holds promise for innovative therapeutic approaches.There is a strong need to emphasize the importance of collaborative efforts in understanding,diagnosing,and managing MASLD to improve physicians’approaches and patient outcomes.

Cumulative effects of excess high-normal alanine aminotransferase levels in relation to new-onset metabolic dysfunction-associated fatty liver disease in China

BACKGROUND Within the normal range,elevated alanine aminotransferase(ALT)levels are associated with an increased risk of metabolic dysfunction-associated fatty liver disease(MAFLD).AIM To investigate the associations between repeated high-normal ALT measurements and the risk of new-onset MAFLD prospectively.METHODS A cohort of 3553 participants followed for four consecutive health examinations over 4 years was selected.The incidence rate,cumulative times,and equally and unequally weighted cumulative effects of excess high-normal ALT levels(ehALT)were measured.Cox proportional hazards regression was used to analyse the association between the cumulative effects of ehALT and the risk of new-onset MAFLD.RESULTS A total of 83.13%of participants with MAFLD had normal ALT levels.The incidence rate of MAFLD showed a linear increasing trend in the cumulative ehALT group.Compared with those in the low-normal ALT group,the multivariate adjusted hazard ratios of the equally and unequally weighted cumulative effects of ehALT were 1.651[95%confidence interval(CI):1.199-2.273]and 1.535(95%CI:1.119-2.106)in the third quartile and 1.616(95%CI:1.162-2.246)and 1.580(95%CI:1.155-2.162)in the fourth quartile,respectively.CONCLUSION Most participants with MAFLD had normal ALT levels.Long-term high-normal ALT levels were associated with a cumulative increased risk of new-onset MAFLD.

Evolution and Prospects of Foundation Models: From Large Language Models to Large Multimodal Models

Since the 1950s,when the Turing Test was introduced,there has been notable progress in machine language intelligence.Language modeling,crucial for AI development,has evolved from statistical to neural models over the last two decades.Recently,transformer-based Pre-trained Language Models(PLM)have excelled in Natural Language Processing(NLP)tasks by leveraging large-scale training corpora.Increasing the scale of these models enhances performance significantly,introducing abilities like context learning that smaller models lack.The advancement in Large Language Models,exemplified by the development of ChatGPT,has made significant impacts both academically and industrially,capturing widespread societal interest.This survey provides an overview of the development and prospects from Large Language Models(LLM)to Large Multimodal Models(LMM).It first discusses the contributions and technological advancements of LLMs in the field of natural language processing,especially in text generation and language understanding.Then,it turns to the discussion of LMMs,which integrates various data modalities such as text,images,and sound,demonstrating advanced capabilities in understanding and generating cross-modal content,paving new pathways for the adaptability and flexibility of AI systems.Finally,the survey highlights the prospects of LMMs in terms of technological development and application potential,while also pointing out challenges in data integration,cross-modal understanding accuracy,providing a comprehensive perspective on the latest developments in this field.

Omics-based biomarkers as useful tools in metabolic dysfunctionassociated steatotic liver disease clinical practice:How far are we?

Unmet needs exist in metabolic dysfunction-associated steatotic liver disease(MASLD)risk stratification.Our ability to identify patients with MASLD with advanced fibrosis and at higher risk for adverse outcomes is still limited.Incorporating novel biomarkers could represent a meaningful improvement to current risk predictors.With this aim,omics technologies have revolutionized the process of MASLD biomarker discovery over the past decades.While the research in this field is thriving,much of the publication has been haphazard,often using single-omics data and specimen sets of convenience,with many identified candidate biomarkers but lacking clinical validation and utility.If we incorporate these biomarkers to direct patients’management,it should be considered that the roadmap for translating a newly discovered omics-based signature to an actual,analytically valid test useful in MASLD clinical practice is rigorous and,therefore,not easily accomplished.This article presents an overview of this area’s current state,the conceivable opportunities and challenges of omics-based laboratory diagnostics,and a roadmap for improving MASLD biomarker research.