Nutritional and medicinal characteristics of Chinese giant salamander (Andrias davidianus) for applications in healthcare industry by artificial cultivation: A review

Andrias davidianus,i.e.Chinese giant salamander(CGS),is one of the largest and oldest amphibians existing in the world and is also one of the valuable biological resources of China.Wild CGS has been threatened with extinction in the past decades due to over capturing,deterioration of natural environment,the slow breeding and growth of the wild species in nature.However,in the past twenty years,with the breakthrough and progress of artificial breeding technology by artificial insemination,the number of artificially cultivated CGS has increased rapidly.Artificially cultivated CGS can either be released to the CGS living environment to increase the population in nature or legally applied in food and medicinal industry as a feedstock due to the unique nutritional and medicinal values of CGS as recorded historically.In this review,the nutritional components,bioactive components and medicinal activities of the artificially cultivated CGS will be summarized.The mucus,skin,meat and bone of CGS contain many different bioactive substances thereby having various medicinal activities including anti-aging,anti-fatigue,anti-tumor,therapy of burn and anti-infection and other physiological functions.This paper will further discuss the potential applications of the artificially cultivated CGS in healthcare industry and prospects of future technological development.

Comparison of Nutritional Components in the Muscle of Juvenile Siganus guttatus Fed with Enteromorpha prolifera and Artificial Feed

[ Objective] This experiment was conducted to analyze and compare the nutritional components in the muscle of juvenile Siganus guttatus fed with Enteromorpha prolifera and artificial feed. [ Method] A total of 180 healthy S. guttatus juveniles with similar body size were assigned into two groups： one fed with E. prolifera, and the other fed with artificial feed, respectively. There were three replicates in each group, and 30 fish in each replicate. And the experiment lasted for 90 d. [ Result] The results showed that the weight gain rate, specific growth rate and relative growth rate of E. prolifera-fed group were significantly lower than those of artificial feed-fed group （P 〈0.05） ; the contents of crude protein and crude ash of E. prolifera-fed group were significantly higher than those of artificial feed-fed group （P 〈 0.05 ）. However, the content of crude fat of E. prolifera-fed group was significantly lower than that of artificial feed-fed group （P 〈 0.05 ）. The moisture content had no significant difference between the two groups （P 〉 0.05 ）. The amino acid composition was similar between the two groups. Seventeen amino acids were found in both groups, and the essential amino acid index （EAAI） was 76.71 in E. prolifera-fed group and 70.05 in artificial feed-fed group, both of which met the criteria set by the Food and Agriculture Organization of the United Nations （FAO）/World Health Organization （WHO）. The content of eicosapentaenoic acid （EPA） ＋ docosahexaenoic acid （DHA） and the content of to-3 polyunsaturated fatty acids （ to-3 PUFAs） of E. prolifera-fed group were significantly higher than those of artificial feed-fed group （ P 〈 0.05 ）. [ Conclusion ] In conclusion, the juvenile S. guttatus in both groups contains a variety of nutritional components. S. guttatus fed with E. prolifera has higher levels of essential amino acids, more balanced composition of polyunsaturated fatty acids, higher nutritive val- ue and better taste than that fed with artificial feed.

Transfer of disulfide bond formation modules via yeast artificial chromosomes promotes the expression of heterologous proteins in Kluyveromyces marxianus

Kluyveromyces marxianus is a food-safe yeast with great potential for producing heterologous proteins.Improving the yield in K.marxianus remains a challenge and incorporating large-scale functional modules poses a technical obstacle in engineering.To address these issues,linear and circular yeast artificial chromosomes of K.marxianus(KmYACs)were constructed and loaded with disulfide bond formation modules from Pichia pastoris or K.marxianus.These modules contained up to seven genes with a maximum size of 15 kb.KmYACs carried telomeres either from K.marxianus or Tetrahymena.KmYACs were transferred successfully into K.marxianus and stably propagated without affecting the normal growth of the host,regardless of the type of telomeres and configurations of KmYACs.KmYACs increased the overall expression levels of disulfide bond formation genes and significantly enhanced the yield of various heterologous proteins.In high-density fermentation,the use of KmYACs resulted in a glucoamylase yield of 16.8 g/l,the highest reported level to date in K.marxianus.Transcriptomic and metabolomic analysis of cells containing KmYACs suggested increased flavin adenine dinucleotide biosynthesis,enhanced flux entering the tricarboxylic acid cycle,and a preferred demand for lysine and arginine as features of cells overexpressing heterologous proteins.Consistently,supplementing lysine or arginine further improved the yield.Therefore,KmYAC provides a powerful platform for manipulating large modules with enormous potential for industrial applications and fundamental research.Transferring the disulfide bond formation module via YACs proves to be an efficient strategy for improving the yield of heterologous proteins,and this strategy may be applied to optimize other microbial cell factories.

The Application of Bilayer Artificial Dermis Combined with VSD Technology in Chronic Wounds

Background: Bilayer artificial dermis promotes wound healing and offers a treatment option for chronic wounds. Aim: Examine the clinical efficacy of bilayer artificial dermis combined with Vacuum Sealing Drainage (VSD) technology in the treatment of chronic wounds. Method: From June 2021 to December 2023, our hospital treated 24 patients with chronic skin tissue wounds on their limbs using a novel tissue engineering product, the bilayer artificial dermis, in combination with VSD technology to repair the wounds. The bilayer artificial dermis protects subcutaneous tissue, blood vessels, nerves, muscles, and tendons, and also promotes the growth of granulation tissue and blood vessels to aid in wound healing when used in conjunction with VSD technology for wound dressing changes in chronic wounds. Results: In this study, 24 cases of chronic wounds with exposed bone or tendon larger than 1.0 cm2 were treated with a bilayer artificial skin combined with VSD dressing after wound debridement. The wounds were not suitable for immediate skin grafting. At 2 - 3 weeks post-treatment, good granulation tissue growth was observed. Subsequent procedures included thick skin grafting or wound dressing changes until complete wound healing. Patients were followed up on average for 3 months (range: 1 - 12 months) post-surgery. Comparative analysis of the appearance, function, skin color, elasticity, and sensation of the healed chronic wounds revealed superior outcomes compared to traditional skin fl repairs, resulting in significantly higher satisfaction levels among patients and their families. Conclusion: The application of bilayer artificial dermis combined with VSD technology for the repair of chronic wounds proves to be a viable method, yielding satisfactory therapeutic effects compared to traditional skin flap procedures.

Explainable Artificial Intelligence(XAI)Model for Cancer Image Classification

The use of Explainable Artificial Intelligence(XAI)models becomes increasingly important for making decisions in smart healthcare environments.It is to make sure that decisions are based on trustworthy algorithms and that healthcare workers understand the decisions made by these algorithms.These models can potentially enhance interpretability and explainability in decision-making processes that rely on artificial intelligence.Nevertheless,the intricate nature of the healthcare field necessitates the utilization of sophisticated models to classify cancer images.This research presents an advanced investigation of XAI models to classify cancer images.It describes the different levels of explainability and interpretability associated with XAI models and the challenges faced in deploying them in healthcare applications.In addition,this study proposes a novel framework for cancer image classification that incorporates XAI models with deep learning and advanced medical imaging techniques.The proposed model integrates several techniques,including end-to-end explainable evaluation,rule-based explanation,and useradaptive explanation.The proposed XAI reaches 97.72%accuracy,90.72%precision,93.72%recall,96.72%F1-score,9.55%FDR,9.66%FOR,and 91.18%DOR.It will discuss the potential applications of the proposed XAI models in the smart healthcare environment.It will help ensure trust and accountability in AI-based decisions,which is essential for achieving a safe and reliable smart healthcare environment.

Teaching Design of Course Building Decoration Materials Based on Generative Artificial Intelligence

With the digital transformation of global education and China's emphasis on education digital,generative AI technology has been widely used in the field of higher education.In this paper,the development of generative AI technology and its potential in personalized learning,interactive content creation and adaptive assessment in education were introduced firstly.Then,the application case of generative AI tools in teaching content creation,scenario-based teaching content development,visual teaching content development,complex concept deconstruction and analogy,student-led application practice and other aspects in the teaching of Building Decoration Materials was discussed.Through the teaching experiment and effect evaluation,the positive influence of generative AI technology on the improvement of students'learning effect and teaching efficiency was verified.Finally,some thoughts and inspirations on the combination of educational theory and generative AI technology,the integration of teaching design and generative AI technology,and the practice cases and effect evaluation were put forward,and the importance of teacher role transformation and personalized learning path design was emphasized to provide theoretical and practical support for the innovative development of higher education.

Hybrid Hierarchical Particle Swarm Optimization with Evolutionary Artificial Bee Colony Algorithm for Task Scheduling in Cloud Computing

Task scheduling plays a key role in effectively managing and allocating computing resources to meet various computing tasks in a cloud computing environment.Short execution time and low load imbalance may be the challenges for some algorithms in resource scheduling scenarios.In this work,the Hierarchical Particle Swarm Optimization-Evolutionary Artificial Bee Colony Algorithm(HPSO-EABC)has been proposed,which hybrids our presented Evolutionary Artificial Bee Colony(EABC),and Hierarchical Particle Swarm Optimization(HPSO)algorithm.The HPSO-EABC algorithm incorporates both the advantages of the HPSO and the EABC algorithm.Comprehensive testing including evaluations of algorithm convergence speed,resource execution time,load balancing,and operational costs has been done.The results indicate that the EABC algorithm exhibits greater parallelism compared to the Artificial Bee Colony algorithm.Compared with the Particle Swarm Optimization algorithm,the HPSO algorithmnot only improves the global search capability but also effectively mitigates getting stuck in local optima.As a result,the hybrid HPSO-EABC algorithm demonstrates significant improvements in terms of stability and convergence speed.Moreover,it exhibits enhanced resource scheduling performance in both homogeneous and heterogeneous environments,effectively reducing execution time and cost,which also is verified by the ablation experimental.

Optimal Location and Sizing ofMulti-Resource Distributed Generator Based onMulti-Objective Artificial Bee Colony Algorithm

Distribution generation(DG)technology based on a variety of renewable energy technologies has developed rapidly.A large number of multi-type DG are connected to the distribution network(DN),resulting in a decline in the stability of DN operation.It is urgent to find a method that can effectively connect multi-energy DG to DN.photovoltaic(PV),wind power generation(WPG),fuel cell(FC),and micro gas turbine(MGT)are considered in this paper.A multi-objective optimization model was established based on the life cycle cost(LCC)of DG,voltage quality,voltage fluctuation,system network loss,power deviation of the tie-line,DG pollution emission index,and meteorological index weight of DN.Multi-objective artificial bee colony algorithm(MOABC)was used to determine the optimal location and capacity of the four kinds of DG access DN,and compared with the other three heuristic algorithms.Simulation tests based on IEEE 33 test node and IEEE 69 test node show that in IEEE 33 test node,the total voltage deviation,voltage fluctuation,and system network loss of DN decreased by 49.67%,7.47%and 48.12%,respectively,compared with that without DG configuration.In the IEEE 69 test node,the total voltage deviation,voltage fluctuation and system network loss of DN in the MOABC configuration scheme decreased by 54.98%,35.93%and 75.17%,respectively,compared with that without DG configuration,indicating that MOABC can reasonably plan the capacity and location of DG.Achieve the maximum trade-off between DG economy and DN operation stability.

A Discussion of Artificial Intelligence in Visual Art Education

Since ChatGPT emerged on November 30, 2022, Artificial Intelligence (AI) has been increasingly discussed as a radical force that will change our world. People have become used to AI in which such ubiquitous technologies as Siri, Google, and Netflix deploy AI algorithms to answer questions, impart information, and provide recommendations. However, many individuals including originators and backers of AI have recently expressed grave concerns. In this paper, the authors will assess what is occurring with AI in Visual Arts Education, outline positives and negatives, and provide recommendations addressed specifically for teachers working in the field regarding emerging AI usage from kindergarten to grade twelve levels as well as in higher education.

Simultaneous Identification of Thermophysical Properties of Semitransparent Media Using a Hybrid Model Based on Artificial Neural Network and Evolutionary Algorithm

A hybrid identification model based on multilayer artificial neural networks(ANNs) and particle swarm optimization(PSO) algorithm is developed to improve the simultaneous identification efficiency of thermal conductivity and effective absorption coefficient of semitransparent materials.For the direct model,the spherical harmonic method and the finite volume method are used to solve the coupled conduction-radiation heat transfer problem in an absorbing,emitting,and non-scattering 2D axisymmetric gray medium in the background of laser flash method.For the identification part,firstly,the temperature field and the incident radiation field in different positions are chosen as observables.Then,a traditional identification model based on PSO algorithm is established.Finally,multilayer ANNs are built to fit and replace the direct model in the traditional identification model to speed up the identification process.The results show that compared with the traditional identification model,the time cost of the hybrid identification model is reduced by about 1 000 times.Besides,the hybrid identification model remains a high level of accuracy even with measurement errors.

Cultivation of Critical Thinking Skills: Exploring the Impact of Generative Artificial Intelligence- Enabled Instruction in English Essay Writing

This study explores the impact of generative artificial intelligence(AI)-enabled instruction on critical thinking in English essay writing among 1,050 first-year English majors across four colleges.Pedagogical strategies,including facilitating critical responses and emphasizing real-world application,are identified to enhance generative AI’s impact.Both qualitative and quantitative analyses reveal significant post-intervention improvements in critical thinking skills.This research contributes to understanding how generative AI can effectively foster critical thinking in educational settings.

A Review of Artificial Waterfalls in Gardens

When artificial waterfalls are built in gardens,leaves from trees or vegetation often fall into the water storage pool and block the pipelines,requiring regular cleaning of pipelines.This not only increases the manpower needed for maintenance but also disrupts the use of the waterfalls.Therefore,it is necessary to design a new type of artificial waterfall that is suitable for gardens.The waterfall should incorporate features that make cleaning easier,including filter plates and water funnels to prevent clogging caused by fallen leaves and debris.

Exploration of Industrial Internet Security Technology and Application from the Perspective of Generative Artificial Intelligence

In recent years,artificial intelligence technology has developed rapidly around the world is widely used in various fields,and plays an important role.The integration of industrial Internet security with new technologies such as big models and generative artificial intelligence has become a hot research issue.In this regard,this paper briefly analyzes the industrial Internet security technology and application from the perspective of generative artificial intelligence,hoping to provide some valuable reference and reference for readers.

Revisiting Educational Issues in the Age of Generative Artificial Intelligence

The emergence of generative artificial intelligence(AI)has had a huge impact on all areas of life,including the field of education.AI can assist teachers in cultivating talents and promoting personalized learning and teaching,but it also prevents individuals from thinking independently and creatively.In the era of generative AI,the rapid development of technology and its significant impact on the field of education are inevitable.There are many educational issues related to it,such as teaching methods,student training goals,teaching philosophy and purposes,and other educational issues,that require re-conceptualization and review.

Exploring Pedagogical Ideologies and Strategies for College English Writing Instruction from a Generative Artificial Intelligence Perspective

This study,drawing on the commonalities between generative artificial intelligence and foreign language writing instruction,outlines the core ideology of digital humanities-based college English writing instruction,including auxiliary use of generative artificial intelligence tools,primary focus on humanistic education,and the re-production of knowledge,aiming to foster students’critical thinking,collaborative skills,and creativity.Building on this foundation,the study delves into generative artificial intelligence tools applicable to different stages of process-genre writing and their strategic applications.The use of generative artificial intelligence tools is beneficial for students to present,discuss,and share writing content,encouraging them to enhance their writing,collaboration,critical thinking,and creative abilities through deep interaction with model essays and creative discourses.

Advances in Cervical Artificial Disc Replacement for Cervical Spondylosis

Anterior cervical decompression and fusion(ACDF)treatment for cervical spondylosis has been more than half a century,and achieved good clinical results.However,with the continuous extension of follow-up time,the fusion segment-associated postoperative complications emerged gradually.Reserved cervical stability and activity,the concept of non-fusion was born.As a non-fusion technique,cervical artificial disc replacement(CADR)developed rapidly.With the continuous development of artificial prosthesis materials and design concepts,and specification and proficiency of surgical procedures,CADR has achieved better short and mid-term clinical efficacy than ACDF.Compared with ACDF,the main advantages of CADR are that the postoperative recovery is quick,the activity and stability of cervical vertebra are maintained,the height of cervical intervertebral space is restored,and the stress of adjacent segments and the rate of surgical renovation are reduced.In clinical work,as an emerging technology,CADR requires spine surgeons to control the surgical indications,contraindications,and patients'conditions strictly.This article reviews the research progress of CADR in order to provide new ideas for clinical treatment of cervical spondylosis.

Toward a Learnable Climate Model in the Artificial Intelligence Era

Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related challenges.Amid this AI-driven transformation,the foundational role of physics in climate science has occasionally been overlooked.Our perspective suggests that the future of climate modeling involves a synergistic partnership between AI and physics,rather than an“either/or”scenario.Scrutinizing controversies around current physical inconsistencies in large AI models,we stress the critical need for detailed dynamic diagnostics and physical constraints.Furthermore,we provide illustrative examples to guide future assessments and constraints for AI models.Regarding AI integration with numerical models,we argue that offline AI parameterization schemes may fall short of achieving global optimality,emphasizing the importance of constructing online schemes.Additionally,we highlight the significance of fostering a community culture and propose the OCR(Open,Comparable,Reproducible)principles.Through a better community culture and a deep integration of physics and AI,we contend that developing a learnable climate model,balancing AI and physics,is an achievable goal.

Concept of Artificial Intelligence (AI) and Its Use in Orthopaedic Practice: Applications and Pitfalls: A Narrative Review

Background: The growth and use of Artificial Intelligence (AI) in the medical field is rapidly rising. AI is exhibiting a practical tool in the healthcare industry in patient care. The objective of this current review is to assess and analyze the use of AI and its use in orthopedic practice, as well as its applications, limitations, and pitfalls. Methods: A review of all relevant databases such as EMBASE, Cochrane Database of Systematic Reviews, MEDLINE, Science Citation Index, Scopus, and Web of Science with keywords of AI, orthopedic surgery, applications, and drawbacks. All related articles on AI and orthopaedic practice were reviewed. A total of 3210 articles were included in the review. Results: The data from 351 studies were analyzed where in orthopedic surgery. AI is being used for diagnostic procedures, radiological diagnosis, models of clinical care, and utilization of hospital and bed resources. AI has also taken a chunk of share in assisted robotic orthopaedic surgery. Conclusions: AI has now become part of the orthopedic practice and will further increase its stake in the healthcare industry. Nonetheless, clinicians should remain aware of AI’s serious limitations and pitfalls and consider the drawbacks and errors in its use.

Application of artificial hibernation technology in acute brain injury

Controlling intracranial pressure,nerve cell regeneration,and microenvironment regulation are the key issues in reducing mortality and disability in acute brain injury.There is currently a lack of effective treatment methods.Hibernation has the characteristics of low temperature,low metabolism,and hibernation rhythm,as well as protective effects on the nervous,cardiovascular,and motor systems.Artificial hibernation technology is a new technology that can effectively treat acute brain injury by altering the body’s metabolism,lowering the body’s core temperature,and allowing the body to enter a state similar to hibernation.This review introduces artificial hibernation technology,including mild hypothermia treatment technology,central nervous system regulation technology,and artificial hibernation-inducer technology.Upon summarizing the relevant research on artificial hibernation technology in acute brain injury,the research results show that artificial hibernation technology has neuroprotective,anti-inflammatory,and oxidative stress-resistance effects,indicating that it has therapeutic significance in acute brain injury.Furthermore,artificial hibernation technology can alleviate the damage of ischemic stroke,traumatic brain injury,cerebral hemorrhage,cerebral infarction,and other diseases,providing new strategies for treating acute brain injury.However,artificial hibernation technology is currently in its infancy and has some complications,such as electrolyte imbalance and coagulation disorders,which limit its use.Further research is needed for its clinical application.

Application of artificial intelligence in the diagnosis and treatment of Kawasaki disease

This editorial provides commentary on an article titled"Potential and limitationsof ChatGPT and generative artificial intelligence(AI)in medical safety education"recently published in the World Journal of Clinical Cases.AI has enormous potentialfor various applications in the field of Kawasaki disease(KD).One is machinelearning(ML)to assist in the diagnosis of KD,and clinical prediction models havebeen constructed worldwide using ML;the second is using a gene signalcalculation toolbox to identify KD,which can be used to monitor key clinicalfeatures and laboratory parameters of disease severity;and the third is using deeplearning(DL)to assist in cardiac ultrasound detection.The performance of the DLalgorithm is similar to that of experienced cardiac experts in detecting coronaryartery lesions to promoting the diagnosis of KD.To effectively utilize AI in thediagnosis and treatment process of KD,it is crucial to improve the accuracy of AIdecision-making using more medical data,while addressing issues related topatient personal information protection and AI decision-making responsibility.AIprogress is expected to provide patients with accurate and effective medicalservices that will positively impact the diagnosis and treatment of KD in thefuture.