The Good Wife is an American TV series that focuses on women’s independence,politics,and law.The drama has been remade in China,Japan,and South Korea.This research aims to use Nida’s Functional Equivalence Theory to...The Good Wife is an American TV series that focuses on women’s independence,politics,and law.The drama has been remade in China,Japan,and South Korea.This research aims to use Nida’s Functional Equivalence Theory to analyze the methods of its English-to-Chinese subtitle translation by considering social,cultural,and historic backgrounds between China and America.After data collection and case analysis,the study found that:(1)Five major translation methods are adopted in the subtitle translation of The Good Wife.They are free translation,variation,literal translation,addition,and omission.Among them,free translation is the most frequently used,while omission is used least.(2)The subtitle translation of films and TV series is limited by time and space restrictions,social-cultural differences,and other factors.When translating,translators should try to use humorous words,euphemism,intonation,and other ways,and combine different methods such as literal translation,free translation,variation,addition,omission,and other methods to seek equivalence both in the meaning and function of subtitles under the guidance of Functional Equivalence Theory.展开更多
The lysosomal enzyme β-glucocerebrosidase(GCase) belongs to the family of glycosidases and hydrolyses the glycosphingolipid glucosylceramide(GluCer) into glucose and ceramide. The enzyme is of central importance for ...The lysosomal enzyme β-glucocerebrosidase(GCase) belongs to the family of glycosidases and hydrolyses the glycosphingolipid glucosylceramide(GluCer) into glucose and ceramide. The enzyme is of central importance for two pathologies:(1) the lysosomal storage disorder Gaucher's disease(GD) and(2) the neurodegenerative disorder Parkinson's disease(PD).展开更多
The cosmetics industry operates on a global scale,making the accurate translation of ingredient terminology crucial for international trade and consumer comprehension.Cosmetic ingredient terms are characterized by the...The cosmetics industry operates on a global scale,making the accurate translation of ingredient terminology crucial for international trade and consumer comprehension.Cosmetic ingredient terms are characterized by their interdisciplinary nature,regulatory constraints,and function-oriented definitions.Based on real-world translation examples,this paper analyzes the challenges in translating cosmetics ingredient terminology for international trade and proposes targeted translation strategies.The study aims to facilitate the global marketing of cosmetic products while ensuring consumers can accurately understand product ingredient information.展开更多
Pathological scarring,manifested in the form of hypertrophic scars(HTS)and keloid scars(KS),represents a major clinical challenge due to its aesthetic and functional implications for patients.Understanding the molecul...Pathological scarring,manifested in the form of hypertrophic scars(HTS)and keloid scars(KS),represents a major clinical challenge due to its aesthetic and functional implications for patients.Understanding the molecular mechanisms involved in these types of scars and developing effective treatments requires the use of controlled ex-perimental models,especially animals,to overcome the limitations of clinical studies.The aim of this sistematic review is to critically analyze the animal models used in the last five years(2020-2025)for the study of pathological scars,highlighting their advantages,limitations and applicability in the development of new therapeutic strat-egies.Murine,rabbit and porcine models,as well as alternative models,offer varied perspectives on the formation and treatment of HTS and KS,with an emphasis on histological and molecular correlations with human pathology.By synthesizing recent data,the paper highlights the essential role of preclinical research in optimizing an-tifibrotic treatments and in advancing the translation of data into the clinical sphere.Overall,animal models remain essential for bridging mechanistic insights with clinical translation,supporting the development of more effective and personalized anti-scar therapies.展开更多
In this study,tropical cyclone(TC)translation speed was introduced as a new similarity factor within the generalized initial value(GIV)framework,enhancing the disaster preassessment capability of the dynamical statist...In this study,tropical cyclone(TC)translation speed was introduced as a new similarity factor within the generalized initial value(GIV)framework,enhancing the disaster preassessment capability of the dynamical statistical analog ensemble forecast model for landfalling TC disasters(DSAEF_LTD model).Three TC translation speed indicators most relevant to TC precipitation were incorporated:the maximum speed on Day 1(the first day of TC-induced precipitation and wind occurring on land)and the average and minimum speeds over All Days(all days of TC-induced precipitation and wind occurring on land),all classified using the Kmeans clustering algorithm.Simulation experiments showed that integrating TC translation speed enhanced the model's performance.The model provided a better optimal common scheme,with the TSS UM(sum of threat scores for severe and above and extremely severe and above disasters)increasing by 2.66%(from 0.5117 to 0.5253)compared with the original model.More importantly,its preassessment ability improved significantly,with the average TSS UM for independent samples increasing by 6.43%(from 0.6488 to0.6905).The modified model demonstrated greater accuracy in capturing disaster severity and distribution of TCs with significant speed characteristics or with regular tracks.This improvement stemmed from reduced false alarms due to the selection of analogs that are more similar to the target TC.The enhanced preassessment ability can be attributed to the key role of TC translation speed,which significantly influences TC precipitation patterns and improves TC precipitation forecasting.Since precipitation is one of the most crucial disaster-causing factors,better TC precipitation forecasting leads to improved disaster preassessment outcomes.These findings emphasize the promising potential of the DSAEF_LTD model for future TC disaster research and management,contributing to the achievement of the Sustainable Development Goals set by the United Nations 2030 Agenda by strengthening coastal resilience.展开更多
In multi-domain neural machine translation tasks,the disparity in data distribution between domains poses significant challenges in distinguishing domain features and sharing parameters across domains.This paper propo...In multi-domain neural machine translation tasks,the disparity in data distribution between domains poses significant challenges in distinguishing domain features and sharing parameters across domains.This paper proposes a Transformer-based multi-domain-aware mixture of experts model.To address the problem of domain feature differentiation,a mixture of experts(MoE)is introduced into attention to enhance the domain perception ability of the model,thereby improving the domain feature differentiation.To address the trade-off between domain feature distinction and cross-domain parameter sharing,we propose a domain-aware mixture of experts(DMoE).A domain-aware gating mechanism is introduced within the MoE module,simultaneously activating all domain experts to effectively blend domain feature distinction and cross-domain parameter sharing.A loss balancing function is then added to dynamically adjust the impact of the loss function on the expert distribution,enabling fine-tuning of the expert activation distribution to achieve a balance between domains.Experimental results on multiple Chinese-to-English and English-to-French datasets demonstrate that our proposed method significantly outperforms baseline models in both BLEU,chrF,and COMET metrics,validating its effectiveness in multi-domain neural machine translation.Further analysis of the probability distribution of expert activations shows that our method achieves remarkable results in both domain differentiation and cross-domain parameter sharing.展开更多
LargeLanguageModels(LLMs)are increasingly appliedinthe fieldof code translation.However,existing evaluation methodologies suffer from two major limitations:(1)the high overlap between test data and pretraining corpora...LargeLanguageModels(LLMs)are increasingly appliedinthe fieldof code translation.However,existing evaluation methodologies suffer from two major limitations:(1)the high overlap between test data and pretraining corpora,which introduces significant bias in performance evaluation;and(2)mainstream metrics focus primarily on surface-level accuracy,failing to uncover the underlying factors that constrain model capabilities.To address these issues,this paper presents TCode(Translation-Oriented Code Evaluation benchmark)—a complexity-controllable,contamination-free benchmark dataset for code translation—alongside a dedicated static feature sensitivity evaluation framework.The dataset is carefully designed to control complexity along multiple dimensions—including syntactic nesting and expression intricacy—enabling both broad coverage and fine-grained differentiation of sample difficulty.This design supports precise evaluation of model capabilities across a wide spectrum of translation challenges.The proposed evaluation framework introduces a correlation-driven analysis mechanism based on static program features,enabling predictive modeling of translation success from two perspectives:Code Form Complexity(e.g.,code length and character density)and Semantic Modeling Complexity(e.g.,syntactic depth,control-flow nesting,and type system complexity).Empirical evaluations across representative LLMs—including Qwen2.5-72B and Llama3.3-70B—demonstrate that even state-of-the-art models achieve over 80% compilation success on simple samples,but their accuracy drops sharply below 40% on complex cases.Further correlation analysis indicates that Semantic Modeling Complexity alone is correlated with up to 60% of the variance in translation success,with static program features exhibiting nonlinear threshold effects that highlight clear capability boundaries.This study departs fromthe traditional accuracy-centric evaluation paradigm and,for the first time,systematically characterizes the capabilities of large languagemodels in translation tasks through the lens of programstatic features.The findings provide actionable insights for model refinement and training strategy development.展开更多
“By successfully integrating artificial intelligence(AI)into research workflows,researchers could substantially increase scientific productivity”[1].In biofabrication,AI is dr iving a paradigm shift from empiricism ...“By successfully integrating artificial intelligence(AI)into research workflows,researchers could substantially increase scientific productivity”[1].In biofabrication,AI is dr iving a paradigm shift from empiricism toward intelligen t,data centric manufacturing[2].By integrating computation,automation,and biology,AI gives rise to self-evolving,adaptive systems that learn from data,predict complex behaviors,and autonomously optimize fabrication outcomes.Such systems translate experimental insights into patient-specific and clinically relevant solutions,bridging laboratory research and regenerative therapies[3].This emerging frontier is rapidly advancing from concept to application.This Special Column highlights how AI-driven advanc es in materials,design,and manufacturing are reshaping biof abrication for regenerative medicine and clinical translation.展开更多
Superoxide dismutase 1(SOD1)is a thermodynamically stable,zinc and copper binding homodimeric enzyme responsible for breaking down superoxide radicals.More than 200,mostly missense,mutations spread throughout the SOD1...Superoxide dismutase 1(SOD1)is a thermodynamically stable,zinc and copper binding homodimeric enzyme responsible for breaking down superoxide radicals.More than 200,mostly missense,mutations spread throughout the SOD1 gene are associated with the fatal neurodegenerative disease,amyotrophic lateral sclerosis(ALS).A unifying feature of ALS-associated SOD1 mutations is the destabilization of the SOD1 protein structure,increasing the propensity for misfolding and subsequent pathological aggregation.Post-mortem analysis of SOD1-associated ALS tissue shows the accumulation of misfolded SOD1 protein and ubiquitinated SOD1 inclusions within motor neurons.Misfolded SOD1 accumulation and aggregates are implicated in cellular dysfunction via a number of disparate but critical processes,including endoplasmic reticulum stress,oxidative damage,proteasome dysfunction,axonal transport abnormalities and synaptic dysfunction;culminating in motor neuron degeneration associated with ALS.展开更多
When performing English-to-Tamil Neural Machine Translation(NMT),end users face several challenges due to Tamil's rich morphology,free word order,and limited annotated corpora.Although available transformer-based ...When performing English-to-Tamil Neural Machine Translation(NMT),end users face several challenges due to Tamil's rich morphology,free word order,and limited annotated corpora.Although available transformer-based models offer strong baselines,they compromise syntactic awareness and the detection and man-agement of offensive content in cluttered,noisy,and informal text.In this paper,we present POSDEP-Offense-Trans,a multi-task NMT framework that combines Part-of-Speech(POS)and Dependency Parsing(DEP)methods with a robust offensive language classification module.Our architecture enriches the Transformer encoder with syntax-aware embeddings and provides syntax-guided attention mechanisms.The architecture incorporates a structure-aware contrastive loss that reinforces syntactic consistency and deploys auxiliary classification heads for POS tagging,dependency parsing,and multi-class offensive detection.The classifier for offensive words operates at both sentence and token levels and obtains guidance from syntactic features and formal finite automata rules that model offensive language structures-hate speech,profanity,sarcasm,and threats.Using this architecture,we construct a syntactically enriched,socially annotated corpus.Experimental results show improvements in translation quality,with a BLEU score of 33.5,UAS/LAS parsing accuracies of 92.4%and 90%,and a 4.5%Fl-score gain in offensive content detection compared with baseline POS+DEP+Offense models.Also,the proposed model achieved 92.3%in offensive content neutralization,as confirmed by ablation studies.This comprehensive English-Tamil NMT model that unifies syntactic modelling and ethical filtering-laying the groundwork for applications in social media moderation,hate speech mitigation,and policy-compliant multilingual content generation.展开更多
The metabolic enzyme isocitrate dehydrogenase 1(IDH1)catalyzes the oxidative decarboxylation of isocitrate to a-ketoglutarate(a-KG).Its mutation often leads to aberrant gene expression in cancer.IDH1 was reported to b...The metabolic enzyme isocitrate dehydrogenase 1(IDH1)catalyzes the oxidative decarboxylation of isocitrate to a-ketoglutarate(a-KG).Its mutation often leads to aberrant gene expression in cancer.IDH1 was reported to bind thousands of RNA transcripts in a sequence-dependent manner;yet,the functional significance of this RNA-binding activity remains elusive.Here,we report that IDH1 promotes mRNA translation via direct associations with polysome mRNA and translation machinery.Comprehensive proteomic analysis in embryonic stem cells(ESCs)revealed strikingenrichmentof ribosomal proteins and translation regulators in IDH1-bound protein interactomes.We performed ribosomal profiling and analyzed mRNA transcripts that are associated with actively translating polysomes.Interestingly,knockout of IDH1 in ESCs led to significant downregulation of polysome-bound mRNA in IDH1 targets and subtle upregulation of ribosome densities at the start codon,indicating inefficient translation initiation upon loss of IDH1.Tethering IDH1 to a luciferase mRNA via the MS2-MBP system promotes luciferase translation,independently of the catalytic activity of IDH1.Intriguingly,IDH1 fails to enhance luciferase translation driven by an internal ribosome entry site.Together,these results reveal an unforeseen role of IDH1 in fine-tuning cap-dependent translation via the initiation step.展开更多
Translation regulation is an important layer of gene expression:Generation of genome-wide expression datasets at multi-omics levels in spatial,temporal,and cell-type resolution is essential for deciphering brain compl...Translation regulation is an important layer of gene expression:Generation of genome-wide expression datasets at multi-omics levels in spatial,temporal,and cell-type resolution is essential for deciphering brain complexity.Regulation of gene expression is a highly dynamic process aiming at the production of precise levels of gene products to guarantee optimal cellular function,in response to physiological cues.Speedy advances in next-generation sequencing enabled the understanding of epigenomic and transcriptomic dynamic landscapes of different brain regions along development,aging,and disease progression.However,the correlation of the“transcriptome”with protein levels is poor because numerous mRNAs are subjected to manipulation of their translation efficiency,to warrant a favorable result under certain conditions.Hence,it is widely accepted that regulation at the translation level is a vital layer of gene expression.Quantification of actively translated mRNA populations(i.e.,“translatome”)is a more reliable predictor of the“proteome”(Wang et al.,2020).展开更多
Iron is an essential trace element in the human body,crucial in maintaining normal physiological functions.Recent studies have identified iron ions as a significant factor in initiating the ferroptosis process,a novel...Iron is an essential trace element in the human body,crucial in maintaining normal physiological functions.Recent studies have identified iron ions as a significant factor in initiating the ferroptosis process,a novel mode of programmed cell death characterized by iron overload and lipid peroxide accumulation.The iron metabolism pathway is one of the primary mechanisms regulating ferroptosis,as it maintains iron homeostasis within the cell.Numerous studies have demonstrated that abnormalities in iron metabolism can trigger the Fenton reaction,exacerbating oxidative stress,and leading to cell membrane rupture,cellular dysfunction,and damage to tissue structures.Therefore,regulation of iron metabolism represents a key strategy for ameliorating ferroptosis and offers new insights for treating diseases associated with iron metabolism imbalances.This review first summarizes the mechanisms that regulate iron metabolic pathways in ferroptosis and discusses the connections between the pathogenesis of various diseases and iron metabolism.Next,we introduce natural and synthetic small molecule compounds,hormones,proteins,and new nanomaterials that can affect iron metabolism.Finally,we provide an overview of the challenges faced by iron regulators in clinical translation and a summary and outlook on iron metabolism in ferroptosis,aiming to pave the way for future exploration and optimi-zation of iron metabolism regulation strategies.展开更多
Hepatocellular carcinoma(HCC)recurrence after liver transplantation(LT)presents a significant challenge,with recurrence rates ranging from 8%to 20%globally.Current biomarkers,such as alpha-fetoprotein(AFP)and des-gamm...Hepatocellular carcinoma(HCC)recurrence after liver transplantation(LT)presents a significant challenge,with recurrence rates ranging from 8%to 20%globally.Current biomarkers,such as alpha-fetoprotein(AFP)and des-gamma-carboxy prothrombin(DCP),lack specificity,limiting their utility in risk strati-fication.YKL-40,a glycoprotein involved in extracellular matrix remodeling,hepatic stellate cell activation,and immune modulation,has emerged as a promising biomarker for post-LT surveillance.Elevated serum levels of YKL-40 are associated with advanced liver disease,tumor progression,and poorer post-LT outcomes,highlighting its potential to address gaps in early detection and personalized management of HCC recurrence.This manuscript synthesizes clinical and mechanistic evidence to evaluate YKL-40’s predictive utility in post-LT care.While preliminary findings demonstrate its specificity for liver-related pathologies,challenges remain,including assay standardization,lack of pro-spective validation,and the need to distinguish between malignant and non-malignant causes of elevated levels.Integrating YKL-40 into multi-biomarker panels with AFP and DCP could enhance predictive accuracy and enable tailored therapeutic strategies.Future research should focus on multicenter studies to validate YKL-40’s clinical utility,address confounding factors like graft rejection and systemic inflammation,and explore its role in predictive models driven by emerging technologies such as artificial intelligence.YKL-40 holds transformative potential in reshaping post-LT care through precision medicine,providing a pathway for better outcomes and improved management of high-risk LT recipients.展开更多
A primary hallmark of pathological cardiac hypertrophy is excess protein synthesis due to enhanced translational activity.However,regulatory mechanisms at the translational level under cardiac stress remain poorly und...A primary hallmark of pathological cardiac hypertrophy is excess protein synthesis due to enhanced translational activity.However,regulatory mechanisms at the translational level under cardiac stress remain poorly understood.Here we examined the translational regulations in a mouse cardiac hypertrophy model induced by transaortic constriction(TAC)and explored the conservative networks versus the translatome pattern in human dilated cardiomyopathy(DCM).The results showed that the heart weight to body weight ratio was significantly elevated,and the ejection fraction and fractional shortening significantly decreased 8 weeks after TAC.Puromycin incorporation assay showed that TAC significantly increased protein synthesis rate in the left ventricle.RNAseq revealed 1,632 differentially expressed genes showing functional enrichment in pathways including extracellular matrix remodeling,metabolic processes,and signaling cascades associated with pathological cardiomyocyte growth.When combined with ribosome profiling analysis,we revealed that translation efficiency(TE)of 1,495 genes was enhanced,while the TE of 933 genes was inhibited following TAC.In DCM patients,1,354 genes were upregulated versus 1,213 genes were downregulated at the translation level.Although the majority of the genes were not shared between mouse and human,we identified 93 genes,including Nos3,Kcnj8,Adcy4,Itpr1,Fasn,Scd1,etc.,with highly conserved translational regulations.These genes were remarkably associated with myocardial function,signal transduction,and energy metabolism,particularly related to cGMP-PKG signaling and fatty acid metabolism.Motif analysis revealed enriched regulatory elements in the 5′untranslated regions(5′UTRs)of transcripts with differential TE,which exhibited strong cross-species sequence conservation.Our study revealed novel regulatory mechanisms at the translational level in cardiac hypertrophy and identified conserved translation-sensitive targets with potential applications to treat cardiac hypertrophy and heart failure in the clinic.展开更多
The second near-infrared window(NIR-II,900-1880 nm)overcomes critical limitations of visible(360-760 nm)and NIR-I(760-900 nm)imaging—including restricted penetration depth,low signal-to-back⁃ground ratio,and tissue a...The second near-infrared window(NIR-II,900-1880 nm)overcomes critical limitations of visible(360-760 nm)and NIR-I(760-900 nm)imaging—including restricted penetration depth,low signal-to-back⁃ground ratio,and tissue autofluorescence—establishing its pivotal role for in vivo deep-tissue bioimaging.With exponential growth in NIR-II photodiagnosis and phototherapy research over the past decade,bibliometric analy⁃sis is essential to map the evolving landscape and guide strategic priorities.We systematically analyzed 2,491 NIR-II-related publications(2009-2023)from the Web of Science Core Collection,employing scientometric tools for distinct analytical purposes:(a)VOSviewer,SCImago Graphica,and Gephi for co-authorship and co-occur⁃rence network mapping;(b)the R bibliometrix package for tracking field evolution and identifying high-impact publications/journals.The search retrieved 2491 studies from 359 journals originating from 54 countries.The country with the most published articles is China.Chinese institutions drive>60%of publications,with Stanford University(USA)and Nanyang Technological University(Singapore)ranked as the top two institutions by re⁃search quality.International cooperation is becoming increasingly frequent.Fan Quli,Tang Benzhong and Dai Hongjie are the top 3 productive authors in this field.Keyword evolution identifies"photodynamic therapy"and"immunotherapy"as pivotal future directions.We summarize the most cited literatures and NIR-II imaging clini⁃cal trials.This study delineates the NIR-II research trajectory,highlighting China's leadership,intensifying glob⁃al collaboration,and interdisciplinary convergence.Future efforts should prioritize the novel NIR-II probe devel⁃opment for NIR-II imaging and clinical translation of photodynamic/immunotherapy combinational platforms.展开更多
The sentence structure and syntax of the Mongolian heroic epic Jangar are diverse and rich in cultural connotations.Through the relentless efforts of generations of translators,Chinese readers can now appreciate this ...The sentence structure and syntax of the Mongolian heroic epic Jangar are diverse and rich in cultural connotations.Through the relentless efforts of generations of translators,Chinese readers can now appreciate this great heroic epic without hindrance.Studying the translation cases of epic lines of the Jangar holds significant importance for the translation of folk literature,including heroic epics.This paper takes the Chinese translations of the 70–chaptered edition of the epic Jangar as the research object,briefly discusses the characteristics of epic lines translation practices.The study reveals that translators employed relatively flexible methods when handling the original epic sentences,utilizing techniques such as altering sentence structures,transforming sentence components,integrating or splitting sentences,and adding or omitting words.展开更多
文摘The Good Wife is an American TV series that focuses on women’s independence,politics,and law.The drama has been remade in China,Japan,and South Korea.This research aims to use Nida’s Functional Equivalence Theory to analyze the methods of its English-to-Chinese subtitle translation by considering social,cultural,and historic backgrounds between China and America.After data collection and case analysis,the study found that:(1)Five major translation methods are adopted in the subtitle translation of The Good Wife.They are free translation,variation,literal translation,addition,and omission.Among them,free translation is the most frequently used,while omission is used least.(2)The subtitle translation of films and TV series is limited by time and space restrictions,social-cultural differences,and other factors.When translating,translators should try to use humorous words,euphemism,intonation,and other ways,and combine different methods such as literal translation,free translation,variation,addition,omission,and other methods to seek equivalence both in the meaning and function of subtitles under the guidance of Functional Equivalence Theory.
基金supported by the Michael J Fox Foundation (to PA and FZ)。
文摘The lysosomal enzyme β-glucocerebrosidase(GCase) belongs to the family of glycosidases and hydrolyses the glycosphingolipid glucosylceramide(GluCer) into glucose and ceramide. The enzyme is of central importance for two pathologies:(1) the lysosomal storage disorder Gaucher's disease(GD) and(2) the neurodegenerative disorder Parkinson's disease(PD).
基金funded by 2025 Graduate Teaching Construction Project of USST.
文摘The cosmetics industry operates on a global scale,making the accurate translation of ingredient terminology crucial for international trade and consumer comprehension.Cosmetic ingredient terms are characterized by their interdisciplinary nature,regulatory constraints,and function-oriented definitions.Based on real-world translation examples,this paper analyzes the challenges in translating cosmetics ingredient terminology for international trade and proposes targeted translation strategies.The study aims to facilitate the global marketing of cosmetic products while ensuring consumers can accurately understand product ingredient information.
基金Ministry of Research,Innovation and Digitization,CCCDI-UEFISCDI,Grant/Award Number:PN-IV-P7-7.1-PED-2024-1578,within PNCDI Ⅳ.
文摘Pathological scarring,manifested in the form of hypertrophic scars(HTS)and keloid scars(KS),represents a major clinical challenge due to its aesthetic and functional implications for patients.Understanding the molecular mechanisms involved in these types of scars and developing effective treatments requires the use of controlled ex-perimental models,especially animals,to overcome the limitations of clinical studies.The aim of this sistematic review is to critically analyze the animal models used in the last five years(2020-2025)for the study of pathological scars,highlighting their advantages,limitations and applicability in the development of new therapeutic strat-egies.Murine,rabbit and porcine models,as well as alternative models,offer varied perspectives on the formation and treatment of HTS and KS,with an emphasis on histological and molecular correlations with human pathology.By synthesizing recent data,the paper highlights the essential role of preclinical research in optimizing an-tifibrotic treatments and in advancing the translation of data into the clinical sphere.Overall,animal models remain essential for bridging mechanistic insights with clinical translation,supporting the development of more effective and personalized anti-scar therapies.
基金supported by the Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province(No.SCSF202307)the Basic Research Fund of CAMS(No.2023Z016)+1 种基金the National Natural Scientific Foundation of China(No.42275037)the Jiangsu Collaborative Innovation Center for Climate Change。
文摘In this study,tropical cyclone(TC)translation speed was introduced as a new similarity factor within the generalized initial value(GIV)framework,enhancing the disaster preassessment capability of the dynamical statistical analog ensemble forecast model for landfalling TC disasters(DSAEF_LTD model).Three TC translation speed indicators most relevant to TC precipitation were incorporated:the maximum speed on Day 1(the first day of TC-induced precipitation and wind occurring on land)and the average and minimum speeds over All Days(all days of TC-induced precipitation and wind occurring on land),all classified using the Kmeans clustering algorithm.Simulation experiments showed that integrating TC translation speed enhanced the model's performance.The model provided a better optimal common scheme,with the TSS UM(sum of threat scores for severe and above and extremely severe and above disasters)increasing by 2.66%(from 0.5117 to 0.5253)compared with the original model.More importantly,its preassessment ability improved significantly,with the average TSS UM for independent samples increasing by 6.43%(from 0.6488 to0.6905).The modified model demonstrated greater accuracy in capturing disaster severity and distribution of TCs with significant speed characteristics or with regular tracks.This improvement stemmed from reduced false alarms due to the selection of analogs that are more similar to the target TC.The enhanced preassessment ability can be attributed to the key role of TC translation speed,which significantly influences TC precipitation patterns and improves TC precipitation forecasting.Since precipitation is one of the most crucial disaster-causing factors,better TC precipitation forecasting leads to improved disaster preassessment outcomes.These findings emphasize the promising potential of the DSAEF_LTD model for future TC disaster research and management,contributing to the achievement of the Sustainable Development Goals set by the United Nations 2030 Agenda by strengthening coastal resilience.
基金supported by the NationalNatural Science Foundation of China(U2004163)Key Research and Development Program of Henan Province(No.251111211200).
文摘In multi-domain neural machine translation tasks,the disparity in data distribution between domains poses significant challenges in distinguishing domain features and sharing parameters across domains.This paper proposes a Transformer-based multi-domain-aware mixture of experts model.To address the problem of domain feature differentiation,a mixture of experts(MoE)is introduced into attention to enhance the domain perception ability of the model,thereby improving the domain feature differentiation.To address the trade-off between domain feature distinction and cross-domain parameter sharing,we propose a domain-aware mixture of experts(DMoE).A domain-aware gating mechanism is introduced within the MoE module,simultaneously activating all domain experts to effectively blend domain feature distinction and cross-domain parameter sharing.A loss balancing function is then added to dynamically adjust the impact of the loss function on the expert distribution,enabling fine-tuning of the expert activation distribution to achieve a balance between domains.Experimental results on multiple Chinese-to-English and English-to-French datasets demonstrate that our proposed method significantly outperforms baseline models in both BLEU,chrF,and COMET metrics,validating its effectiveness in multi-domain neural machine translation.Further analysis of the probability distribution of expert activations shows that our method achieves remarkable results in both domain differentiation and cross-domain parameter sharing.
文摘LargeLanguageModels(LLMs)are increasingly appliedinthe fieldof code translation.However,existing evaluation methodologies suffer from two major limitations:(1)the high overlap between test data and pretraining corpora,which introduces significant bias in performance evaluation;and(2)mainstream metrics focus primarily on surface-level accuracy,failing to uncover the underlying factors that constrain model capabilities.To address these issues,this paper presents TCode(Translation-Oriented Code Evaluation benchmark)—a complexity-controllable,contamination-free benchmark dataset for code translation—alongside a dedicated static feature sensitivity evaluation framework.The dataset is carefully designed to control complexity along multiple dimensions—including syntactic nesting and expression intricacy—enabling both broad coverage and fine-grained differentiation of sample difficulty.This design supports precise evaluation of model capabilities across a wide spectrum of translation challenges.The proposed evaluation framework introduces a correlation-driven analysis mechanism based on static program features,enabling predictive modeling of translation success from two perspectives:Code Form Complexity(e.g.,code length and character density)and Semantic Modeling Complexity(e.g.,syntactic depth,control-flow nesting,and type system complexity).Empirical evaluations across representative LLMs—including Qwen2.5-72B and Llama3.3-70B—demonstrate that even state-of-the-art models achieve over 80% compilation success on simple samples,but their accuracy drops sharply below 40% on complex cases.Further correlation analysis indicates that Semantic Modeling Complexity alone is correlated with up to 60% of the variance in translation success,with static program features exhibiting nonlinear threshold effects that highlight clear capability boundaries.This study departs fromthe traditional accuracy-centric evaluation paradigm and,for the first time,systematically characterizes the capabilities of large languagemodels in translation tasks through the lens of programstatic features.The findings provide actionable insights for model refinement and training strategy development.
文摘“By successfully integrating artificial intelligence(AI)into research workflows,researchers could substantially increase scientific productivity”[1].In biofabrication,AI is dr iving a paradigm shift from empiricism toward intelligen t,data centric manufacturing[2].By integrating computation,automation,and biology,AI gives rise to self-evolving,adaptive systems that learn from data,predict complex behaviors,and autonomously optimize fabrication outcomes.Such systems translate experimental insights into patient-specific and clinically relevant solutions,bridging laboratory research and regenerative therapies[3].This emerging frontier is rapidly advancing from concept to application.This Special Column highlights how AI-driven advanc es in materials,design,and manufacturing are reshaping biof abrication for regenerative medicine and clinical translation.
基金Motor Neuron Disease Research Australia in the form of a Bill Gole Postdoctoral Fellowship(PDF2307)FightMND in the form of Drug Development Grants(DDG-159 and DDG137 to JSL)。
文摘Superoxide dismutase 1(SOD1)is a thermodynamically stable,zinc and copper binding homodimeric enzyme responsible for breaking down superoxide radicals.More than 200,mostly missense,mutations spread throughout the SOD1 gene are associated with the fatal neurodegenerative disease,amyotrophic lateral sclerosis(ALS).A unifying feature of ALS-associated SOD1 mutations is the destabilization of the SOD1 protein structure,increasing the propensity for misfolding and subsequent pathological aggregation.Post-mortem analysis of SOD1-associated ALS tissue shows the accumulation of misfolded SOD1 protein and ubiquitinated SOD1 inclusions within motor neurons.Misfolded SOD1 accumulation and aggregates are implicated in cellular dysfunction via a number of disparate but critical processes,including endoplasmic reticulum stress,oxidative damage,proteasome dysfunction,axonal transport abnormalities and synaptic dysfunction;culminating in motor neuron degeneration associated with ALS.
文摘When performing English-to-Tamil Neural Machine Translation(NMT),end users face several challenges due to Tamil's rich morphology,free word order,and limited annotated corpora.Although available transformer-based models offer strong baselines,they compromise syntactic awareness and the detection and man-agement of offensive content in cluttered,noisy,and informal text.In this paper,we present POSDEP-Offense-Trans,a multi-task NMT framework that combines Part-of-Speech(POS)and Dependency Parsing(DEP)methods with a robust offensive language classification module.Our architecture enriches the Transformer encoder with syntax-aware embeddings and provides syntax-guided attention mechanisms.The architecture incorporates a structure-aware contrastive loss that reinforces syntactic consistency and deploys auxiliary classification heads for POS tagging,dependency parsing,and multi-class offensive detection.The classifier for offensive words operates at both sentence and token levels and obtains guidance from syntactic features and formal finite automata rules that model offensive language structures-hate speech,profanity,sarcasm,and threats.Using this architecture,we construct a syntactically enriched,socially annotated corpus.Experimental results show improvements in translation quality,with a BLEU score of 33.5,UAS/LAS parsing accuracies of 92.4%and 90%,and a 4.5%Fl-score gain in offensive content detection compared with baseline POS+DEP+Offense models.Also,the proposed model achieved 92.3%in offensive content neutralization,as confirmed by ablation studies.This comprehensive English-Tamil NMT model that unifies syntactic modelling and ethical filtering-laying the groundwork for applications in social media moderation,hate speech mitigation,and policy-compliant multilingual content generation.
基金This work was supported in part by the National Natural Science Foundation of China(31471219 and 31630095)the National Basic Research Program of China(2017YFA0504204)the Center for Life Sciences at Tsinghua University.
文摘The metabolic enzyme isocitrate dehydrogenase 1(IDH1)catalyzes the oxidative decarboxylation of isocitrate to a-ketoglutarate(a-KG).Its mutation often leads to aberrant gene expression in cancer.IDH1 was reported to bind thousands of RNA transcripts in a sequence-dependent manner;yet,the functional significance of this RNA-binding activity remains elusive.Here,we report that IDH1 promotes mRNA translation via direct associations with polysome mRNA and translation machinery.Comprehensive proteomic analysis in embryonic stem cells(ESCs)revealed strikingenrichmentof ribosomal proteins and translation regulators in IDH1-bound protein interactomes.We performed ribosomal profiling and analyzed mRNA transcripts that are associated with actively translating polysomes.Interestingly,knockout of IDH1 in ESCs led to significant downregulation of polysome-bound mRNA in IDH1 targets and subtle upregulation of ribosome densities at the start codon,indicating inefficient translation initiation upon loss of IDH1.Tethering IDH1 to a luciferase mRNA via the MS2-MBP system promotes luciferase translation,independently of the catalytic activity of IDH1.Intriguingly,IDH1 fails to enhance luciferase translation driven by an internal ribosome entry site.Together,these results reveal an unforeseen role of IDH1 in fine-tuning cap-dependent translation via the initiation step.
基金funded by the Israel Science Foundation(grants No.1036/12 and 1228/20)(to OES).
文摘Translation regulation is an important layer of gene expression:Generation of genome-wide expression datasets at multi-omics levels in spatial,temporal,and cell-type resolution is essential for deciphering brain complexity.Regulation of gene expression is a highly dynamic process aiming at the production of precise levels of gene products to guarantee optimal cellular function,in response to physiological cues.Speedy advances in next-generation sequencing enabled the understanding of epigenomic and transcriptomic dynamic landscapes of different brain regions along development,aging,and disease progression.However,the correlation of the“transcriptome”with protein levels is poor because numerous mRNAs are subjected to manipulation of their translation efficiency,to warrant a favorable result under certain conditions.Hence,it is widely accepted that regulation at the translation level is a vital layer of gene expression.Quantification of actively translated mRNA populations(i.e.,“translatome”)is a more reliable predictor of the“proteome”(Wang et al.,2020).
基金the Natural Science Foundation of Shaanxi Province(Grant No.:2023-JC-QN-0125)Yan'an Science andTechnology Bureau(Grant No.:2023-SFGG-141)+1 种基金ShaanxiProvincial Health Research(Grant No.:2022E010)Innovation and Entrepreneurship Training Program for College Students(Grant No.:202310719032).
文摘Iron is an essential trace element in the human body,crucial in maintaining normal physiological functions.Recent studies have identified iron ions as a significant factor in initiating the ferroptosis process,a novel mode of programmed cell death characterized by iron overload and lipid peroxide accumulation.The iron metabolism pathway is one of the primary mechanisms regulating ferroptosis,as it maintains iron homeostasis within the cell.Numerous studies have demonstrated that abnormalities in iron metabolism can trigger the Fenton reaction,exacerbating oxidative stress,and leading to cell membrane rupture,cellular dysfunction,and damage to tissue structures.Therefore,regulation of iron metabolism represents a key strategy for ameliorating ferroptosis and offers new insights for treating diseases associated with iron metabolism imbalances.This review first summarizes the mechanisms that regulate iron metabolic pathways in ferroptosis and discusses the connections between the pathogenesis of various diseases and iron metabolism.Next,we introduce natural and synthetic small molecule compounds,hormones,proteins,and new nanomaterials that can affect iron metabolism.Finally,we provide an overview of the challenges faced by iron regulators in clinical translation and a summary and outlook on iron metabolism in ferroptosis,aiming to pave the way for future exploration and optimi-zation of iron metabolism regulation strategies.
文摘Hepatocellular carcinoma(HCC)recurrence after liver transplantation(LT)presents a significant challenge,with recurrence rates ranging from 8%to 20%globally.Current biomarkers,such as alpha-fetoprotein(AFP)and des-gamma-carboxy prothrombin(DCP),lack specificity,limiting their utility in risk strati-fication.YKL-40,a glycoprotein involved in extracellular matrix remodeling,hepatic stellate cell activation,and immune modulation,has emerged as a promising biomarker for post-LT surveillance.Elevated serum levels of YKL-40 are associated with advanced liver disease,tumor progression,and poorer post-LT outcomes,highlighting its potential to address gaps in early detection and personalized management of HCC recurrence.This manuscript synthesizes clinical and mechanistic evidence to evaluate YKL-40’s predictive utility in post-LT care.While preliminary findings demonstrate its specificity for liver-related pathologies,challenges remain,including assay standardization,lack of pro-spective validation,and the need to distinguish between malignant and non-malignant causes of elevated levels.Integrating YKL-40 into multi-biomarker panels with AFP and DCP could enhance predictive accuracy and enable tailored therapeutic strategies.Future research should focus on multicenter studies to validate YKL-40’s clinical utility,address confounding factors like graft rejection and systemic inflammation,and explore its role in predictive models driven by emerging technologies such as artificial intelligence.YKL-40 holds transformative potential in reshaping post-LT care through precision medicine,providing a pathway for better outcomes and improved management of high-risk LT recipients.
基金supported by grants from National Natural Science Foundation of China(No.82370392)Shenzhen Medical Research Fund(No.B2302026)+4 种基金Science,Technology and Innovation Commission of Shenzhen Municipality(No.RCJC20210706091947009)National Key R&D Program of China(No.2022YFA1104500)CAMS Innovation Fund for Medical Sciences(No.2023-I2M-1-003 and 2022-I2M-2-001)Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences(No.2019PT320026)National High Level Hospital Clinical Research Funding(No.2022-GSP-GG-7)。
文摘A primary hallmark of pathological cardiac hypertrophy is excess protein synthesis due to enhanced translational activity.However,regulatory mechanisms at the translational level under cardiac stress remain poorly understood.Here we examined the translational regulations in a mouse cardiac hypertrophy model induced by transaortic constriction(TAC)and explored the conservative networks versus the translatome pattern in human dilated cardiomyopathy(DCM).The results showed that the heart weight to body weight ratio was significantly elevated,and the ejection fraction and fractional shortening significantly decreased 8 weeks after TAC.Puromycin incorporation assay showed that TAC significantly increased protein synthesis rate in the left ventricle.RNAseq revealed 1,632 differentially expressed genes showing functional enrichment in pathways including extracellular matrix remodeling,metabolic processes,and signaling cascades associated with pathological cardiomyocyte growth.When combined with ribosome profiling analysis,we revealed that translation efficiency(TE)of 1,495 genes was enhanced,while the TE of 933 genes was inhibited following TAC.In DCM patients,1,354 genes were upregulated versus 1,213 genes were downregulated at the translation level.Although the majority of the genes were not shared between mouse and human,we identified 93 genes,including Nos3,Kcnj8,Adcy4,Itpr1,Fasn,Scd1,etc.,with highly conserved translational regulations.These genes were remarkably associated with myocardial function,signal transduction,and energy metabolism,particularly related to cGMP-PKG signaling and fatty acid metabolism.Motif analysis revealed enriched regulatory elements in the 5′untranslated regions(5′UTRs)of transcripts with differential TE,which exhibited strong cross-species sequence conservation.Our study revealed novel regulatory mechanisms at the translational level in cardiac hypertrophy and identified conserved translation-sensitive targets with potential applications to treat cardiac hypertrophy and heart failure in the clinic.
基金Supported by National Natural Science Foundation of China(81874059 and 82102105)the Natural Science Foundation of Zhejiang Province(LQ22H160017)the China Postdoctoral Science Foundation(2021M702825).
文摘The second near-infrared window(NIR-II,900-1880 nm)overcomes critical limitations of visible(360-760 nm)and NIR-I(760-900 nm)imaging—including restricted penetration depth,low signal-to-back⁃ground ratio,and tissue autofluorescence—establishing its pivotal role for in vivo deep-tissue bioimaging.With exponential growth in NIR-II photodiagnosis and phototherapy research over the past decade,bibliometric analy⁃sis is essential to map the evolving landscape and guide strategic priorities.We systematically analyzed 2,491 NIR-II-related publications(2009-2023)from the Web of Science Core Collection,employing scientometric tools for distinct analytical purposes:(a)VOSviewer,SCImago Graphica,and Gephi for co-authorship and co-occur⁃rence network mapping;(b)the R bibliometrix package for tracking field evolution and identifying high-impact publications/journals.The search retrieved 2491 studies from 359 journals originating from 54 countries.The country with the most published articles is China.Chinese institutions drive>60%of publications,with Stanford University(USA)and Nanyang Technological University(Singapore)ranked as the top two institutions by re⁃search quality.International cooperation is becoming increasingly frequent.Fan Quli,Tang Benzhong and Dai Hongjie are the top 3 productive authors in this field.Keyword evolution identifies"photodynamic therapy"and"immunotherapy"as pivotal future directions.We summarize the most cited literatures and NIR-II imaging clini⁃cal trials.This study delineates the NIR-II research trajectory,highlighting China's leadership,intensifying glob⁃al collaboration,and interdisciplinary convergence.Future efforts should prioritize the novel NIR-II probe devel⁃opment for NIR-II imaging and clinical translation of photodynamic/immunotherapy combinational platforms.
文摘The sentence structure and syntax of the Mongolian heroic epic Jangar are diverse and rich in cultural connotations.Through the relentless efforts of generations of translators,Chinese readers can now appreciate this great heroic epic without hindrance.Studying the translation cases of epic lines of the Jangar holds significant importance for the translation of folk literature,including heroic epics.This paper takes the Chinese translations of the 70–chaptered edition of the epic Jangar as the research object,briefly discusses the characteristics of epic lines translation practices.The study reveals that translators employed relatively flexible methods when handling the original epic sentences,utilizing techniques such as altering sentence structures,transforming sentence components,integrating or splitting sentences,and adding or omitting words.
