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Effect of the material-hardening mode on the springbacksimulation accuracy of V-free bendingXuechun Li a,*,Yuying Yang a ,Yongzhi Wang a ,Jun Bao a ,Shunping Li baSchool of Material Science and Engineering,Harbin Institute of Technology,435,Hei Longjiang,Harbin 150001,ChinabNorthwestern Polytechnical University,Xi’an,Shanxi 710072,ChinaReceived 2January 2001AbstractLower springback simulation accuracy is a common problem for large complex sheet metal parts with FE software.The springback of V-free bending is studied in this paper by using a self-developed 2D elasto-plastic finite element program.A linear-hardening model and an elasto-plastic power-exponent hardening model of the material are adopted in this study.The change of the material’s Young’s modulus with plastic deformation is also considered.The results show that the material-hardening mode directly affects the springback simulation accuracy,and the greater the veracity of the hardening mode,the greater the springback accuracy.#2002Published by Elsevier Science B.V .Keywords:Springback simulation;Hardening model;Young’s modulus1.IntroductionSpringback is severe during the unloading phase of bending and greatly affects the forming accuracy of the bent parts.To exactly and effectively forecast the springback is the basis of achieving a steady and precise shape of the formed part.Springback is related to many factors such as tooling geometry,material properties,friction and so on.Springback is so complicated that it is hard to simulate ually very low precision can be found in finite element codes for springback simulation [1].Springback is caused by the release of internal stress during the unloading phase in sheet metal forming,so factors affecting the stress calculation accuracy will affect the springback calculation.It is indicated that the finite element dimensions and the material’s hardening model have greater effects on the stress calculation.The material’s hardening model,viz the material’s stress–strain relationship,expresses the basic properties of the material during plastic deformation.It is important to cor-rectly select and reasonably pre-digest the stress–strain curve to enhance the accuracy of the springback simulation of bending with FE codes [2,3].It is common knowledge that Young’s modulus is an important parameter in a plastic-hardening model.The lit-erature shows that the value of Young’s modulus of cold-rolled plate varies when it is undergoing plastic deformation,therefore,to consider the change of Young’s modulus of the material can increase the springback simulation accuracy [4–6].In this paper,the springback of V-free bending is studied with three materials:LY12(M),LF21(M)and SPCC,and the change of the material’s Young’s modulus with plastic deformation is considered in a self-developed 2D elasto-plastic finite element code to study the effects of the materi-al’s hardening mode on springback accuracy.2.Material-hardening modelGenerally,when a sheet metal begins to deform plasti-cally,the stress–strain relationship is very complicated and hard to express.For the convenience of actual application,some material-hardening models and relevant empirical equations have been put forward for different metal materi-als.Among them,the linear-hardening model and the elasto-plastic power-exponent hardening model are two frequently used models for simulation analysis.The linear-hardening model is as follows:s ¼E e ðe <e S Þs s þE T e ðe !e S Þ (1)where e S is the strain at the yield point,E the Young’s modulus (elastic modulus),E T the tangent modulus after yielding,s s the yield stress,s the true stress and e the truestrain.Journal of Materials Processing Technology 123(2002)209–211*Corresponding author.Tel.:þ86-451-6415776;fax:þ86-451-6415776.E-mail address:youlf@ (X.Li).0924-0136/02/$–see front matter #2002Published by Elsevier Science B.V .PII:S 0924-0136(02)00055-9The elasto-plastic power-exponent hardening model has the form:s ¼E e ðe <e S ÞK e n ðe !e S Þ(2)where K and n represents the hardening coef ficient and the hardening exponent,respectively.The change of Young ’s modulus with plastic deforming can be expressed as [7]:E ¼E 0ð1þe p Þmwhere E 0is the initial Young ’s modulus and e p the equivalent plastic strain.Through the tensile test,the basic property parameters for three materials:LY12(M),LF21(M)and SPCC,were obtained,as shown in Table 1.And the Young ’s modulus –plastic strain relationships for the materials are shown in Fig.1.3.FEM for the springback simulation of V-free bending The static implicit algorithm is adopted in the FE code to simulate the V-free bending process.The counter node contact force at the end of forming phase is used as the initial acting force for springback calculation.Then an iteration algorithm begins until all the node contact forces becomes 0.The tooling dimensions for V-free bending are shown in Fig.2.In the developed FE code,an elasto-plastic algorithm is used in the loading phase and an elastic algo-rithm in springback,and the four nodes isoparametric plane element is adopted.Also,the change of Young ’s modulus with plastic deformation is considered.4.Results and analysisIn V-free bending simulation,different hardening modes result in different stress fields at the end of bending forming,viz the initial acting force for springback calculation will be different.In the simulation,the material ’s hardening mod-ulus H 0must be calculated to form a constitutive matrix,which can be expressed as:H 0¼d s d e p(3)or H 0¼EE T E ÀE T(4)where E T is the slope of the stress –strain curve after yielding,namely E T ¼d s d e(5)Table 1Basic property parameters Materials s (MPa)E 0(GPa)E T (MPa)K (MPa)n mLY12(M)91.4170.089386.668356.2250.206À0.0855LF21(M)60.0067.339148.15164.1170.183À0.1068SPCC 246.05159.048553.339551.6470.226À0.0351Fig.1.The change of Young ’s modulus with plasticdeformation.Fig.2.Tooling diagram:(1)punch;(2)blank;(3)die.Fig.3.Bending angle vs.springback angle for three materials without considering the change of Young ’s modulus with plastic deformation.BISO —linear-hardening model,MISO —elasto-plastic power-exponent hardening model.210X.Li et al./Journal of Materials Processing Technology 123(2002)209–211It is obvious that the stress obtained with the elasto-plastic power-exponent hardening model is more accurate than that with the linear-hardening model.As a result,the initial acting force for springback calculation is more accurate with the use of the elasto-plastic power-exponent hardening model.Fig.3is the relationship between the bending angle in the forming phase and the springback angle in the springback phase under the two material-hardening models.The bend-ing angle is the supplementary angle of the bent part ’s included angle.The figure shows that the springback calcu-lated with the elasto-plastic power-exponent hardening model is closer to the experiment results than that with the linear-hardening model.Figs.4–6show the relationships between the bending angle in the forming phase and the springback angle in the springback phase for the three materials,with the elasto-plastic power-exponent hardening model including the change of Young ’s modulus with plastic deformation.It has been proven by the experimental results that the value of Young ’s modulus changes along with plastic deformation,so considering the change of Young ’s modulus in the FE code can describe the deforming state of the material more truly,and the springback calculated is closer to the experiment value.5.Conclusions1.The material ’s hardening model directly affects the accuracy of springback calculation.The greater the veracity of the hardening model,the greater the springback accuracy.The springback calculated with the elasto-plastic power-exponent hardening model agrees better with experimental results than that calculated with the linear-hardening model.2.Young ’s modulus has a great effect on springback simulation ing the change of Young ’s modulus with plastic deformation can enhance the accuracy of springback simulation.References[1] D.B.Zhu,Newest progress on the springback ’s study of plate forming,J.Plas.Eng.1(2000)11–17.[2]Z.T.Zhang,D.Lee,Development of a new model for plane strainbending and springback analysis,J.Mater.Eng.Perform.4(3)(1995)291–300.[3]Z.T.Zhang,S.J.Hu,Stress and residual stress distributions in planestrain bending,Int.J.Mech.Sci.40(6)(1998)533–543.[4] A.Makinouchi,H.Ogawa,Use the ITAS-2D Program to Calculate theSpringback with Considering the Change in Young ’s Modulus due to Plastic Deformation,Unite Report Conference of Plastic Deformation,No.43,Tokyo,1992,pp.755–756.[5]L.J.Devin,A.H.Streppl,A process model for air bending,J.Mater.Process.Technol.57(1996)48–54.[6]S.Shima,M.Yang,A study of accuracy in an intelligent V-bendingprocess for sheet metals,Material 44(500)(1995)578–583.[7]X.C.Li,Y .Y .Yang,Discuss on the relationship between the Young ’smodulus and plastic deformation,J.Harbin Inst.Technol.32(5)(2000)54–56.Fig.4.Bending angle vs.springback angle for materialSPCC.Fig.5.Bending angle vs.springback angle for materialLY12(M).Fig.6.Bending angle vs.springback angle for material LF21(M).X.Li et al./Journal of Materials Processing Technology 123(2002)209–211211。
药物与临床China &Foreign Medical Treatment 中外医疗米非司酮周期疗法治疗对围绝经期异常子宫出血患者的影响分析梅娟，戴淑婷，张雪芳漳州招商局经济技术开发区第一医院妇产科，福建漳州 353100［摘要］ 目的 研讨米非司酮周期疗法治疗对围绝经期异常子宫出血（Abnormal Uterine Bleeding, AUB ）患者的影响。
方法 随机选取2021年5月—2023年5月漳州招商局经济技术开发区第一医院确诊为AUB 的100例患者为研究对象，依据随机数表法分组，对照组（n =50）接受米非司酮持续口服，观察组（n =50）接受米非司酮周期疗法治疗，比较两组方案疗效、性激素水平、临床相关指标以及用药安全性。
结果 观察组经3个周期用药后的疗效（96.00%）高于对照组（80.00%），差异有统计学意义（χ2=6.060，P <0.05）。
用药后，观察组各项性激素指标水平均低于对照组，差异有统计学意义（P 均<0.05）。
观察组用药后血红蛋白值高于对照组，子宫内膜厚度小于对照组，差异有统计学意义（P 均<0.05）。
两组间发生药物不良反应基本相当，差异无统计学意义（P >0.05）。
结论 对围绝经期AUB 患者实施米非司酮周期疗法用药，能够明显提升用药效果，调节患者机体性激素水平，提高血红蛋白值，缩小子宫内膜厚度，同时保障用药安全。
［关键词］ 围绝经期异常子宫出血；米非司酮；周期疗法；性激素；子宫内膜厚度［中图分类号］ R5 ［文献标识码］ A ［文章编号］ 1674-0742（2024）02(a)-0103-04Analysis of the Effect of Mifepristone Cycle Therapy on Perimenopausal Abnormal Uterine Bleeding PatientsMEI Juan, DAI Shuting, ZHANG XuefangDepartment of Obstetrics and Gynecology, Zhangzhou China Merchants Economic and Technological Development Zone First Hospital, Zhangzhou, Fujian Province, 353100 China[Abstract] Objective To study the effect of mifepristone cycle therapy on patients with perimenopausal abnormal uter⁃ine bleeding (AUB). Methods 100 patients diagnosed as perimenopausal AUB by Zhangzhou China Merchants Eco⁃nomic and Technological Development Zone First Hospital from May 2021 to May 2023 were randomly selected as the study objects and the group design was completed based on the random number table method. 50 cases in the control group received continuous oral mifepristone, and 50 cases in the observation group were treated with mifepristonecycle therapy. The efficacy, sex hormone levels, clinical indexes and drug safety of the two groups were compared. Results After 3 cycles of treatment, the therapeutic effect of the regimen in the observation group (96.00%) was higherthan that in the control group (80.00%), and the difference was statistically significant (χ2=6.060, P <0.05). After treat⁃ment, the levels of various sex hormone indexes in the observation group were lower than those in the control group, and the differences were statistically significant (all P <0.05). The hemoglobin value of the observation group was higher than that of the control group, and the endometrial thickness was lower than that of the control group, the differ⁃ences were statistically significant (both P <0.05). The incidence of adverse drug reactions between the two groups wassimilar, and there was no statistical significance difference (P >0.05). Conclusion The implementation of mifepristonecycle therapy for perimenopausal AUB patients can significantly enhance the effect of medication, regulate the level ofsex hormones in the patient's body, increase hemoglobin value, and reduce the thickness of the endometrium, as well DOI ：10.16662/ki.1674-0742.2024.04.103[作者简介] 梅娟（1983-），女，本科，主治医师，研究方向为妇产科临床。
Introduction to PhysiologyIntroductionPhysiology is the study of the functions of living matter. It is concerned with how an organism performs its varied activities: how it feeds, how it moves, how it adapts to changing circumstances, how it spawns new generations. The subject is vast and embraces the whole of life. The success of physiology in explaining how organisms perform their daily tasks is based on the notion that they are intricate and exquisite machines whose operation is governed by the laws of physics and chemistry.Although some processes are similar across the whole spectrum of biology—the replication of the genetic code for or example—many are specific to particular groups of organisms. For this reason it is necessary to divide the subject into various parts such as bacterial physiology, plant physiology, and animal physiology.To study how an animal works it is first necessary to know how it is built. A full appreciation of the physiology of an organism must therefore be based on a sound knowledge of its anatomy. Experiments can then be carried out to establish how particular parts perform their functions. Although there have been many important physiological investigations on human volunteers, the need for precise control over the experimental conditions has meant that much of our present physiological knowledge has been derived from studies on other animals such as frogs, rabbits, cats, and dogs. When it is clear that a specific physiological process has a common basis in a wide variety of animal species, it is reasonable to assume that the same principles will apply to humans. The knowledge gained from this approach has given us a great insight into human physiology and endowed us with a solid foundation for the effective treatment of many diseases.The building blocks of the body are the cells, which are grouped together to form tissues. The principal types of tissue are epithelial, connective, nervous, and muscular, each with its own characteristics. Many connective tissues have relatively few cells but have an extensive extracellular matrix. In contrast, smooth muscle consists of densely packed layers of muscle cells linked together via specific cell junctions. Organs such as the brain, the heart, the lungs, the intestines, and the liver are formed by the aggregation of different kinds of tissues. The organs are themselves parts of distinct physiological systems. The heart and blood vessels form the cardiovascular system; the lungs, trachea, and bronchi together with the chest wall and diaphragm form the respiratory system; the skeleton and skeletal muscles form the musculoskeletal system; the brain, spinal cord, autonomic nerves and ganglia, and peripheral somatic nerves form the nervous system, and so on.Cells differ widely in form and function but they all have certain common characteristics. Firstly, they are bounded by a limiting membrane, the plasma membrane. Secondly, they have the ability to break down large molecules to smaller ones to liberate energy for their activities.生理学简介介绍生理学是研究生物体功能的科学。
皮格马利翁效应英语作文The Pygmalion Effect, a psychological phenomenon, illustrates the profound impact of expectations on performance. It suggests that when individuals believe in their capabilities, they are more likely to achieve their goals.In classrooms, this effect is palpable. Teachers who hold high expectations for their students often witness remarkable progress. It's as if the belief in potential ignites a spark within the students, propelling them to excel.The workplace is another arena where the Pygmalion Effect thrives. Managers who express confidence in their team's abilities can foster an environment where employees thrive and exceed targets. It's a testament to the power of positive reinforcement.However, the Pygmalion Effect is not without its challenges. When expectations are set too high, it can lead to undue pressure and, in some cases, disappointment. It's crucial to strike a balance between aspiration and realism.In personal development, the Pygmalion Effect encourages self-belief. By setting high standards for oneself, individuals can push through barriers and achieve personal bests. It's a reminder that our own expectations can shape our reality.In conclusion, the Pygmalion Effect is a powerful tool that can drive success in various aspects of life. By fostering an atmosphere of belief and support, we can unlock the potential within ourselves and others.。
中国现代医生2020年11月第58卷第33期•临床研究-长筒弹力袜与屮筒弹力袜在小腿段浅静脉曲张患者屮的疗效比较及其对血流动力学的影响研究甄杰生广东省台山市人民医院肝胆乳腺甲状腺血管外科，广东台山529200［摘要］目的探讨长筒弹力袜与中筒弹力袜在小腿段浅静脉曲张患者中的疗效比较及其对血流动力学的影响研究。
方法选取2015年1月-2019年11月我院收治的小腿段浅静脉曲张患者157例，所有患者均接受大隐静脉高位结扎剥脱术治疗，依据术后使用的医用弹力袜长度不同进行分组，对照组78例,研究组79例，对所有患者的临床资料进行回顾性分析。
对照组应用中筒弹力袜，研究组应用长筒弹力袜。
比较两组临床治疗总有效率及相关血流动力学指标。
结果研究组辅助治疗总有效率为98.7%.,显著高于对照组的89.7%(P<0.05)。
研究组隐股交界远端股静脉的反流时间为(2.6±0.9)s，显著短于对照组的(4.1±0.5)s(P<0.05),研究组股静脉内径为(10.5±0.4)m m,显著低于对照组的(14.4±0.7)mm(P<0.05)。
结论小腿段浅静脉曲张患者在大隐静脉高位结扎剥脱术后使用医用弹力袜，可起到十分显著有效的辅助效果，且长筒弹力袜的辅助效果更加理想,可更为显著地改善患者患肢的血流动力学指标水平。
［关键词］静脉曲张；大隐静脉；弹力袜;血流动力学［中图分类号］R82［文献标识码］B［文章编号］1673-9701渊2020冤33-0123-03Comparative observation on the curative effect of long-barreled compression stockings and middle-barreled compression stockings in patients with superficial varicose veins of the calf and the effect on hemodynamicsZHEN JieshengDeparLmenL of HepaLobiliary,BreasL and Thyroid and Vascular Surgery,People's HospiLal of Taishan CiLy in Guangdong Province,Taishan529200,China［Abstract］Objective To invesLigaLe Lhe comparaLive observaLion on Lhe curaLive effecL of long-barreled compression sLockings and middle-barreled compression sLockings in paLienLs wiLh superficial varicose veins of Lhe calf and Lhe sLudy of Lheir effecLs on hemodynamics.Methods A LoLal of157paLienLs wiLh superficial varicose veins of Lhe calf who were admiLLed Lo our hospiLal from January2015Lo November2019were selecLed.All paLienLs received high saphenous vein ligaLion and sLripping,and were grouped according Lo Lhe lengLh of Lhe medical compression sLockings afLer Lhe operaLion,including78cases in Lhe conLrol group,and79cases in Lhe sLudy group.The clinical daLa of all paLienLs were reLrospecLively analyzed.The conLrol group used middle-barreled compression sLockings,and Lhe sLudy group used long-barreled compression sLockings.The clinical LreaLmenL LoLal efficiency and Lhe relevanL hemodynamic indexes be-Lween Lhe Lwo groups were observed and compared.Results The LoLal effective raLe of adjuvanL Lherapy in Lhe sLudy group was98.7%,which was significanLly higher Lhan89.7%in Lhe conLrol group(P<0.05).The reflux Lime of Lhe disLal femoral vein of Lhe saphenous femoral juncLion in Lhe sLudy group was(2.6±0.9)s,which was significantly shorLer Lhan(4.1±0.5)s of Lhe conLrol group(P<0.05).The inLernal diameLer of Lhe femoral vein in Lhe sLudy group was(10.5±0.4)mm,which was significanLly lower Lhan(14.4±0.7)mm of Lhe conLrol group(P<0.05).Conclusion The use of medical compression sLockings afLer Lhe high ligaLion and sLripping of Lhe greaL saphenous vein in paLienLs wiLh superficial varicose veins of Lhe calf can play a very significanL and effecLive auxiliary effecL,and Lhe long-barreled elasLic sLockings has more ideal auxiliary effecL,which can more significantly improve Lhe hemodynamic index level of Lhe paLienL's affecLed limb.［Key words］Varicose veins;GreaL saphenous vein;Compression sLockings;Hemodynamics•临床研究・中国现代医生2020年11月第58卷第33期下肢浅静脉曲张中最常见的一种就是大隐静脉曲张,主要是指下肢浅静脉发生瓣膜关闭不全,导致静脉中的血液发生反流，瘀滞远端静脉血管［1］。
Effects of aging on the human bodyIntroductionAging is a natural process that occurs in the human body as one grows older. This process affects all systems of the body and can lead to changes in physical appearance, function, and health. This article will discuss the effects of aging on the human body, including the skin, bones, muscles, organs, and immune system.Effects of Aging on the SkinThe skin is the largest organ in the body and is the first to show signs of aging. As one ages, the skin becomes thinner and less elastic, leading to wrinkles and sagging. Age spots, skin tags, and moles can also develop. The skin's ability to produce and hold moisture decreases, resulting in dryness and itching. It also becomes more susceptible to injury and infection.UV radiation from the sun plays a significant role in the skin's aging process. Exposure to the sun's rays can cause skin damage and increase the risk of skin cancer. Therefore, it is crucial to protect the skin from sun damage by wearing protective clothing, hats, and sunscreen with an SPF of 30 or higher.Effects of Aging on the Bones and MusclesAs one ages, bones may become weaker and more fragile, increasing the risk of osteoporosis, a condition in which bones become brittle and prone to fracture. Muscle mass also decreases, leading to reduced strength and mobility.Exercise is vital for maintaining bone density and muscle mass. Weight-bearing exercises, such as walking, running, and weight lifting, can help strengthen bones and muscles. It is also essential to eat a diet high in calcium and vitamin D to support bone health.Effects of Aging on the OrgansThe aging process can affect all organs in the body. The heart, which pumps blood throughout the body, can become weaker and less efficient with age. Blood vessels also become less elastic and more rigid, leading to high blood pressure. The digestive system may also become less efficient, leading to constipation and other digestive issues.The brain can also experience changes with age, including a decline in cognitive function. This decline may result in difficulty with memory, reasoning, and decision-making. However, it is important to note that cognitive decline is not an inevitable part of aging and can be delayed by engaging in mentally stimulating activities.Effects of Aging on the Immune SystemThe immune system is responsible for protecting the body from infections and disease. As one ages, the immune system may become less efficient, resulting in an increased risk of infections and a reduced response to vaccines. The body may also become less able to fight cancer cells, increasing the risk of cancer.To support the immune system, it is essential to maintain a healthy lifestyle. This includes eating a diet high in fruits and vegetables, exercising regularly, and getting adequate sleep.ConclusionIn conclusion, the aging process affects all systems of the body and can lead to changes in physical appearance, function, and health. While some of these changes are inevitable, engaging in a healthy lifestyle, including regular exercise and a healthy diet, can help delay the effects of aging and promote overall health and well-being.。
模板 1Dear Prof. XXXXX,Here within enclosed is our paper for consideration to be published on “(Journal name) ”. The further information about the paper is in the following:The Title: XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXThe Authors: XXXXXXXXXX XXXXXXXXXXXX and XXXXXXXXXXThe authors claim that none of the material in the paper hasbeen published or is under consideration for publication elsewhere.I am the corresponding author and my address and other information is as follows,？Address: Department of XXXXXXXXX,Tsinghua University,Beijing, 10084,E-mail:Tel: 86-Fax: 86-Thank you very much for consideration!Sincerely Yours,Dr. XXXXXXXXXXX模板 2Dear XX (Editor):Here is our paper submitted to "(XX Journal)".The Title: XXXXThe Authors: XXX XXX and XXXIn this paper, we ...The authors claim that none of the material in the paper has been published or is under consideration for publication elsewhere.The corresponding author is Dr. XXX and his address and other information is as following:Address: Department of XXX, XX University, ...,Tel: +86-xxx-xxxxxxxxFax: +86-xxx-xxxxxxxxThank you very much for consideration!Sincerely Yours,Dr. xxx模板 3Dear Mr. **We believe the paper may be of particular interest to the readersof your journal as it ........1.The work described has not been submitted elsewherefor publication, in whole or in part, and all the authors listed have approved the manuscript that is enclosed.2.I have read and have abided by the statement ofethical standards for manuscripts submitted to Neuroscience.kind regards.Your sincerely,通信作者Dear Prof. Gil:This is a manuscript by**and **entitled“.......”. It is submitted to be considered for publication as a“...” in your journal. This paper is new. Neither the entire paper nor any part ofits content has been published or has been accepted elsewhere. Itis not being submitted to any other journal.Correspondence should be addressed to **at the following address, phone and fax number, and email address:...Thanks very much for your attention to our paper.Sincerely yours,**投稿信模版四（实例）Case 1Dear Editor,We would like to submit the enclosed manuscript entitled "GDNF Acutely Modulates Neuronal Excitability and A-type Potassium Channels in Midbrain Dopaminergic Neurons", which we wish to be considered for publication in Nature Neuroscience.GDNF has long been thought to be a potent neurotrophic factor for the survival of midbrain dopaminergic neurons, which are degenerated in Parkinson ’s disease . In this paper, we report an unexpected, acute effect of GDNF on A-type potassium channels, leading to a potentiation of neuronal excitability, in the dopaminergic neurons in culture as well as in adult brain slices. Further, we show that GDNF regulates the K+ channels through a mechanism that involves activation of MAP kinase. Thus, this study has revealed, for thefirst time, an acute modulation of ion channels by GDNF. Our findings challenge the classic view of GDNF as a long-term survival factor for midbrain dopaminergic neurons, and suggest that the normal functionof GDNF is to regulate neuronal excitability, and consequently dopamine release. These results may also have implications in the treatment of Parkinson’s disease.Due to a direct competition and conflict of interest, we requestthat Drs. XXX of Harvard Univ., and YY of Yale Univ. not be considered as reviewers. With thanks for your consideration, I am Sincerely yours,case2Dear Editor,We would like to submit the enclosed manuscript entitled "Ca2+-binding protein frequenin mediates GDNF-induced potentiation of Ca2+ channels and transmitter release", which we wish to be considered for publication in Neuron.We believe that two aspects of this manuscript will make it interesting to general readers of Neuron. First, we report that GDNFhas a long-term regulatory effect on neurotransmitter release at the neuromuscular synapses. This provides the first physiologicalevidence for a role of this new family of neurotrophic factors in functional synaptic transmission. Second, we show that the GDNFeffect is mediated by enhancing the expression of the Ca2+-binding protein frequenin. Further, GDNF and frequenin facilitate synaptic transmission by enhancing Ca2+ channel activity, leading to an enhancement of Ca2+ influx. Thus, this study has identified, for thefirst time, a molecular target that mediates the long-term, synapticaction of a neurotrophic factor. Our findings may also have general implications in the cell biology of neurotransmitter release.HighlightsHighlights are a short collection of bullet points that convey the core findings and providereaders with a quick textual overview of the article. These three to five bullet pointsdescribe the essence of the research . results or conclusions) and highlight what isdistinctive about it.Highlights will be displayed in online search result lists, the contents list and in theonline article, but will not (yet) appear in the article PDF file or print.Author instructions:Highlights should be submitted as a separate file in EES by selecting "Highlights" from thedrop-down list when uploading files. Please adhere to the specifications below.Specifications:Include 3 to 5 highlights.There should be a maximum of85 characters , including spaces, per highlight.Only the core results of the paper should be covered.Examples ？？HighlightsWe model two hospitals which have regulated prices and compete on quality.We examine changes in the level of information about hospital quality.Increasing information will increase quality if hospital costs are similar.Increasing information will decrease quality if hospital costs are very different.Welfare effects depend on ex-ante or ex-post assumptions about quality information.？HighlightsHighly c -axis oriented ZnO nanowires were grown on glass using aqueous solutions.The growth temperature does not exceed 95°C in any step of the synthesis.The photocatalytic and wetting properties were studied upon UV irradiation.ZnO nanowires show superior photocatalytic activity.We report a reversible photo-induced transition from hydrophobic to super-hydrophilic.？HighlightsA conformational two-state mechanism for proton pumping complex I is proposed.The mechanism relies on stabilization changes of anionic ubiquinone intermediates.Electron-transfer and protonation should be strictly controlled during turnover.The mechanism explains the full reversibility of complex I.？HighlightsFading of a script alone does not foster domain-general strategy knowledge.Performance of the strategy declines during the fading of a script.Monitoring by a peer keeps performance of the strategy up during script fading.Performance of a strategy after fading fosters domain-general strategy knowledge.Fading and monitoring by a peer combined foster domain-general strategy knowledge.。
·综述·薄荷脑的药理作用及开发应用现状Δ朱帅鸣＊，骆芙瑶，麻浩，单俊杰 #（军事科学院军事医学研究院毒物药物研究所，北京 100850）中图分类号 R965文献标志码 A 文章编号 1001-0408（2023）13-1651-05DOI 10.6039/j.issn.1001-0408.2023.13.21摘要薄荷脑是薄荷挥发油的主要成分，是一种单萜类有机化合物。
本文对薄荷脑的药理作用及其在医药领域的开发应用现状进行系统归纳发现，薄荷脑可通过作用于瞬时受体电位（TRP）通道亚家族M成员8、5-羟色胺系统、γ-氨基丁酸系统等，保护中枢神经系统；可通过温感调节、缓解热应激压力等调节体温；可通过调控前列腺素E2、白三烯B4等炎症介质的产生和释放，以及TRP通道介导的细胞免疫效应发挥抗炎作用；可通过激活经典痛觉靶点，增强抑制性突触传递等发挥镇痛作用；可通过破坏角质层，促进透皮吸收；可通过调控肿瘤细胞增殖、凋亡和黏附途径等，发挥抗肿瘤作用。
薄荷脑既可作为药用辅料，用于药物矫味；也可作为活性成分，在疾病治疗过程中发挥重要药理作用，具有潜在的开发价值。
关键词薄荷脑；药理作用；开发应用Pharmacological effects of menthol and its present development and applicationZHU Shuaiming，LUO Fuyao，MA Hao，SHAN Junjie（Institute of Pharmacology and Toxicology，Academy of Military Medical Sciences， Beijing 100850， China）ABSTRACT Menthol is the main component of mint volatile oil and a monoterpenoid organic compound. This article systematically summarizes the pharmacological effects，present development and application status of menthol. It is found that menthol can protect the central nervous system through acting on the transient receptor potential （TRP）channel subfamily M member 8，5-hydroxytryptamine system，γ-aminobutyric acid system，etc. Menthol can regulate body temperature through temperature adjustment，relieving heat stress，and other means. It can play an anti-inflammatory role by regulating the production and release of inflammatory mediators such as prostaglandin E2and leukotriene B4，and exert anti-inflammatory effects through cellular immune effect mediated by TRP channel. It can play analgesic role by activating classic pain perception targets and enhancing inhibitory synaptic transmission. It can promote transdermal absorption by destroying the stratum corneum. It can exert anti-tumor effects by regulating tumor cell proliferation，apoptosis，and adhesion pathways. Menthol can be used as a medicinal excipient for correcting the taste of drugs；it can also serve as an active ingredient and play an important pharmacological role in the treatment of disease， with potential development value.KEYWORDS menthol； pharmacological effects； development and application薄荷脑，又称薄荷醇，是一种单萜类有机化合物，最早分离于唇形科薄荷属植物薄荷Mentha haplocalyx Briq.的茎和叶，是薄荷挥发油的主要成分，约占62%～87%[1]。
Effect of Asynchronous GABA Release on the Oscillatory Dynamics of Inhibitory CoupledNeuronsThomas Voegtlin and Dominique MartinezLORIA,Campus Scientifique-BP239,Vandoeuvre-Les-Nancy,54506,FranceAbstractNeuronal activities often exhibit rythmic patterns,with a frequency that changes from one band to another.These oscillations can be reproduced in network models of coupled inhibitors.However,the mechanism that controls the period of the os-cillations is not fully understood.Recent studies have shown that various types of inhibitory interneurons may release transmitters synchronously or asynchronously. Could this diversity explain changes in the rythm of the oscillation?To answer this,we studied the effect of synchronous versus asynchronous inhibi-tion,in a network of coupled inhibitory neurons.We observed that frequency and synchronization are reduced when release is asynchronous;the standard deviation of activity bursts increases linearly,while their period increases in a sublinear way.A mathematical analysis supports these observations.This suggests that the re-lease mode of inhibition could play an important role in setting up the oscillatory frequency of inhibitory coupled neurons.Key words:Oscillations,Synchronization,Asynchronous release1IntroductionRecorded electrical signals,such as electroencephalograms or localfield poten-tials,often exhibit rythmic activity patterns.It has been shown that inhibitory interneurons play a key role in generating these rythms;oscillations may result from interactions in a purely inhibitory coupled network or from the interplay Email addresses:Thomas.Voegtlin@loria.fr,Dominique.Martinez@loria.fr (Thomas Voegtlin and Dominique Martinez).Preprint submitted to Elsevier Science2October2006between inhibitory and excitatory neurons.However,the mechanism that con-trols the period of the oscillations is not fully understood.Analytical studies have predicted that this period linearly depends on the decay time of synaptic inhibition[4],but they fail to explain how oscillations may be generated in different frequency bands.Recent studies have shown that there are various types of inhibitory interneu-rons,and suggest that this diversity could explain the changes of rythm of the oscillation[13].More precisely,inhibitory cells may release transmitters syn-chronously or asynchronously[6].Could this have an effect on the underlying rythm?To address this question,we use a simplified computational model of the mammal olfactory bulb(OB)that allows for analytic calculations.The OB is a network mainly composed of excitatory neurons,the mitral cells (MCs),interconnected via local GABAergic neurons,the granule cells(GCs). In the mammal OB,oscillatory activity is observed both in the beta(15-30Hz) and the gamma(40-80Hz)frequency bands,both rythms occuring separately [3].Experimental and modeling studies have shown that oscillations result from inhibitory feedback by granule cells.Indeed,the gamma oscillations are disrupted when the GABAergic synapses from inhibitory to excitatory cells are pharmacologically blocked[7].However,GABAergic inhibition released by GCs and received by MCs can be asynchronous and variable across repeated trials[10,12].In this work,we study the effects of synchronous versus asyn-chronous inhibition on the network oscillations and the precise synchronization of relay neurons,using computer simulations and mathematical analysis.2Description of the modelWe consider here the quadratic integrate andfire(QIF)neuron,which is known to be a very good approximation of any type I neuron[5].The evolution of the membrane potential V is described by:C dVdt=q(V(t)−V T)2+I−I th−I gaba(t)(1)where I is a constant input current,I th denotes the minimal current required for repetitivefiring and I gaba is a synaptic inhibitory current.In the absence of synaptic current,the QIF neuron converges to the resting potential V rest when I=0andfires as soon as V reaches the threshold V th,when I≥I th. Right after the spike,V is reset to the value V reset.Parameters were chosen as to obtain a frequency-current response similar to the MC conductance based model by[11]:C=0.2nF,V rest=−65mV,V T =-60.68mV,q=0.00643mS.V−1,I th=0.12nA,V th=30mV and V reset= -70mv.In order to take into account the role of lateral inhibition through granule cells, we use a model of asynchronous release,inspired by[2].On each synapse,a pre-synaptic spike triggers a number of GABAergic post-synaptic events.These events are triggered asynchronously,according to an exponential distribution of varianceσ.The probability that a presynaptic spike at time t f produces a post-synaptic event at time t p is described by:P syn(t p|t f)=σ−1e−t p−t fσH(t p−t f)(2)where the Heavyside function H ensures causality.The total synaptic con-ductance results from the summation of these unitary synaptic events.The kinetics of unitary events are modeled by decaying exponentials:g syn(t)=g t p e−t−t pτH(t−t p)(3)where g=0.5nS the maximum conductance resulting from a unitary synaptic event,andτ=6ms is the synaptic time decay[9,8].The inhibitory synaptic current I gaba(t)in Eq.(1)is given byI gaba(t)=g syn(t)(V(t)−E gaba)(4) where E gaba=−70mV is the reversal potential of the synapse.3Results of computer simulationsWe simulated a network of100MCs with full connectivity.For each neuron, the transmission delay from soma to synapses was constant,equal toδ= 1ms.In addition,on each synapse,each presynaptic spike triggers10post-synaptic events,released asynchronously according to distribution(2).In order to investigate the effects of synchronous versus asynchronous inhibition,we varied the time constantσof the release distribution.High values ofσmodel the effect of asynchronous inhibition,where synaptic events may be released well after the arrival of an action potential on a synapse.Lower values ofσmodel the effect of synchronous inhibition.work activity over time,in two different conditions:synchronous release (top,σ=1ms)versus asynchronous release(bottom,σ=33ms).Left:Averaged mem-brane potential of the population(100neurons).Right:number of action potentials in the population(plotted as positive),and global number of synaptic events(plot-ted as negative and rescaled).The frequency of the oscillation,measured by Fast Fourier Transform of the average membrane potential,was f=50Hz in the syn-chronous condition,versus f=28Hz in the asynchronous condition.Figure1shows the activity histograms over time,recorded in two conditions:σ=1ms(top)andσ=33ms(bottom).It shows the evolution over time of the average membrane potential(left),action potentials and synaptic events (right).We observe that the frequency of oscillations greatly changes withσ. Forσ=1ms we observe an oscillation at a frequency(50Hz)that is within the gamma range.We also observe that,in this range of frequencies,synaptic events are released immediately after the burst.The temporal jitter of a burst, denoted byσT,is very small(≤1ms),which indicates that the population fires synchronously.In contrast,forσ=33ms,the frequency of the network is lower(28Hz,beta range).The histogram suggests that the synaptic release that follows a burst lasts much longer than the period of the oscillation,and that the resulting distribution over time of the synaptic events reaches a stable regime after a few cycles.Forσ=33ms,the fact that synaptic events may occur at any time within a cycle leads to a lower degree of synchrony(σT= 3.5ms).We repeated the same experiment for different values ofσin the interval [0;50ms].Figure2shows how the period of oscillations,T,and the standard deviation of the bursts,σT,change withσ.We see that the period T increases nonlinearly withσ.In contrast,the standard deviationσT increases linearly. The lowest frequency that can be obtained by increasingσis near25Hz (σ≈100ms);forσ≥100ms the network enters an asynchronous regime(data not shown).The dependency of the period of oscillations and the standard deviation of the bursts onσwill be determined mathematically in the next sections.Fig.2.Effect of the synaptic decay,σ,on the period of oscillations(left),and on the synchronization measured as the temporal dispersion(standard deviationσT) of the activity bursts(right).See sections4and5for explanations on the theoretical curves.4Standard deviation of the activity burstsThe standard deviationσT of the activity bursts increases with the variability of the received inhibition,as shown in Fig.2right.In order to characterize this dependency,we consider a neuron receiving k>>1asynchronous inhibitory synaptic events at random times t p.Itsfiring time T depends on the particular arrival times of the synaptic events and,thus,the spike output jitterσT is a function of the synaptic input jitterσt p.We have derived in[1]the following approximate analytical expression for the spike output jitter as a function of the variability of the received inhibitionσT≈σt p√k(5) Note that this approximation is valid forσt p small(see[1]for details).The arrival time of a unitary post-synaptic event is t p=t f+∆t.The time t f of the pre-synaptic spike is a random variable with standard deviationσT.The delay∆t=(t p−t f)is given by the exponential distribution with standarddeviationσ(Eq.2).Therefore,σ2t p=σ2T+σ2.Replacing this expression in Eq.(5)leads toσT≈σ√k(6)Figure2right compares the theoretical standard deviationσT given by Eq.(6) to the one obtained from simulations.We see a perfect match between theo-retical and experimental values whenσis small and for which Eq.(6)explains the linear dependancy betweenσT andσ.The discrepancy between theoretical and experimentalσT values,whenσincreases,is due to the approximationsmade for deriving Eq.(5).5Period of the oscillationsIn this section,we explain how frequency of the oscillations changes withσ.It should be emphasized that this change of rythm does not result from a differ-ence in the amount of inhibition;for any value ofσ,an activity burst always triggers1000unitary synaptic events on each neuron.Only the distribution of these events is changed.Therefore we need to investigate how the temporal distribution of inhibitory events affects the neural dynamics.We begin by expressing the distribution of synaptic inhibitory events,in the stable regime.Given the shape of bursts in Figure1,we make the assumption that spikes within a burst have a Gaussian distribution,of varianceσ2T.For simplicity,we will consider that this Gaussian is centered at t=0.P spike(t f)=1σT√2πe−t f22σ2T(7)5.1Synchronous synaptic release from a single activity burstWefirst derive the expression of the total synaptic conductance g syn(t)in the limit case of a synchronous release(σ=0such that t p=t f in Eq.3):g syn(t)=g t f e−t−t fτH(t−t f)(8) In this expression,it is possible to remove the Heavyside function,considering only causal spike times.This results in a modified summation index:g syn(t)=g t f≤t e−t−t fτ(9) On average,we haveg syn(t)=gt−∞P spike(t f)e−t−t fτdt f(10)This can be integrated analytically by using Eq.(7).We obtain:g syn(t)=g e−t−t0τf(t−2t0√2σT)(11)where t0=σ2T2τis a time constant,and f(x)=12(1+erf(x))is a sigmoid thattakes on values between0and1,defined using the error function:erf(x)= 2√π x0e−t2dt.Fig.3.Synaptic conductance g syn(t)resulting from a Gaussian burst of spikes,in the case of synchronous release.Left:match between theory and simulation.A burst of N spikes was centered in zero,and had a deviationσT=1ms.The time constant of the synapses wasτ=6ms.Right:Decomposition of g syn(t)as the product of a Gaussian and a sigmoid.The total conductance given by Eq.(11)is shown in Fig.3.It has a single maximum,and the shape of the curve depends onσT.For small values ofσT, this function has the shape of a decaying exponential.For higher values ofσT, it becomes more similar to a Gaussian.5.2Asynchronous synaptic release from a single activity burstWe now deal with the general case where each pre-synaptic spike triggers sev-eral post-synaptic events asynchronously.From Eq.(3),the total conductance readsg syn(t)=gt−∞P spike(t f)tt fP syn(t p|t f)e−(t−t p)/τdt p dt f(12)Replacing P spike(t f)and P syn(t p|t f)given by Eqs.(7)and(2)in the above equation leads tog syn(t)=gt−∞1σT√2πe−(t f)22σ2Ttt fσ−1e−t p−t fσe−t−t pτdt p dt f(13)The above equation can be integrated,in a similar way as in the synchronous case.This yields:g syn(t)=g1στ−1e−t−t1σf(t−2t1√2σT)−e−t−t0τf(t−2t0√2σT) (14)with t0=σ2T2τ,t1=σ2T2σ.The curves corresponding to the synchronous(eq.11)and to the asynchronous case(eq.14)are shown infigure4.In order to draw these curves,the value ofσT depended onσ,and it was chosen according to experimental measures from oursimulations.Fig.4.Difference between the synchronous and asynchronous cases.Left:forσsmall,the shape of the curve g syn(t)is similar to the curve in the synchronous case, but shifted to the right;g syn decays with a time constant approximately equal to τ.Right:forσhigher,the shape of the curve is different;g syn decays with a time constant approximately equal toσ.5.3Asynchronous synaptic release from several activity bursts(stable regime) In order to studyfiring frequency in the stable regime,we must take into account inhibitory events from previous bursts.This is because inhibition may last longer than the period of one oscillation,especially whenσis large(see Fig.1right).We therefore sum the conductances computed as above:G syn(t)=∞ n=0g syn(t+nT)(15)where T denotes the period of the oscillation.If G syn(t)is known,it is possible to numerically integrate Equation(1)for one single neuron,and to measure its spiking period.In turn,it is neces-sary to know the values of the period T and of the deviationσT,in order to compute G syn(t).In order to solve this,we used an initial estimate T est in the computation of G syn(t),and we measured the spike time T spike of a neuron initialized in the state V reset.In order to take into account synaptic transmission delays,G syn was shifted by the delayδ=1ms used in the sim-√k as explained in section4.We looked for afixed ulation.We usedσT=σ/point such that T spike=T est.Thisfixed point was found iteratively as follows: =0.5(T n est+T spike(T n est)),n→∞.T n+1estThe result is plotted in Figure2left.We observe that the period of the oscilla-tions in our network is correctly predicted,although we observe a constant dif-ference between theory and prediction,of about2ms.This discrepancy could be explained by the fact thatσT values approximated in Equation(6)were underestimated.Nevertheless,the shape of thefixed point curve matches that of the experimentally measured period,which demonstrates that the temporal distribution of inhibitory events is a key factor for controlling the period of the oscillation.6ConclusionOur results suggest that the release mode of GABA(synchronous vs.asyn-chronous)could play an important role in setting up the oscillatory frequency in inhibitory coupled neurons.In the mammal OB,oscillatory activity is ob-served both in the beta and the gamma frequency bands.Our results sug-gest that beta and gamma frequencies could result from synchronous and asynchronous release,respectively.Experimental studies have shown that in-hibitory cells in the OB may release GABA asynchronously[10,12].However, the transition between beta and the gamma frequencies remains to be under-stood.Feedback from the olfactory cortex plays a role in setting up the beta frequency,as this rythm disappears when the bulb is disconnected from the cortex.The switch from gamma to beta might result from the activation of anatomically different synapses by the olfactory cortex(teral inhibition vs recurrent inhibition)or different interneurons.References[1]M.Ambard and D.Martinez.Inhibitory control of spike timing precision.Neurocomputing,2006.[2] B.Bathellier,gier,P.Faure,and P-M.Lledo.Circuit properties generatinggamma oscillations in the mammalian olfactory bulb.J.Neurophysiol., doi:10.1152/jn.01141.200526(12),Dec.2005.[3]N.Buonviso,C.Amat,P.Litaudon,S.Roux,J-P.Royet,and V.Farget.Rythm sequence through the olfactory bulb layers during the time window of a respiratory cycle.European Journal of Neuroscience,17:1811–1819,2003.[4] C.C.Chow,J.A.White,J.Ritt,and N.Kopell.Frequency control insynchronized networks of inhibitory neurons.Journal of computational neuroscience,5:407–420,1998.[5] B.Ermentrout.Type1membranes,phase resetting curves,and synchrony.Neural computation,8:979–1001,1996.[6]S.Hefft and P.Jonas.Asynchronous gaba release generates long-lastinginhibition at a hippocampal interneuron-principal neuron synapse.Nature Neuroscience,8(10):1319–1328,2005.[7]gier,A.Carleton,and P-M.Lledo.Interplay between local gabaergicinterneurons and relay neurons generateγoscillations in the rat olfactory bulb.The Journal of Neuroscience,24:4382–4392,2004.[8]T.W.Margrie and A.T.Schaefer.Theta oscillation coupled spike latencies yieldcomputational vigour in a mammalian sensory system.J.Physiol,2002. [9]Z.Nusser.Release-independent short-term facilitation on gabaergic synapsesin the olfactory bulb.Neuropharmacology,43:573–583,2002.[10]N.Schoppa,J.M.Kinzie,Y.Sahara,T.P.Segerson,and G.L Westbrook.Dendrodendritic inhibition in the olfactory bulb is driven by nmda receptors.The Journal of Neuroscience,18:6790–6802,1998.[11]G.Y.Shen,W.R.Chen,J.Mitdgaard,G.M.Shepherd,and M.L.Hines.Computational analysis of action potential initiation in mitral cell soma and dendrites based on dual patch recordings.J.Neurophysiol.,82:3006–3020,1999.[12]N.Urban and B.Sakmann.Reciprocal intraglomerular excitation and intra-and interglomerular lateral inhibition between mouse olfactory bulb mitral cells.Journal of Physiology,pages355–367,2002.[13]M.A.Whittington and R.D.Traub.Interneuron diversity series:inhibitoryinterneurons and network oscillations in vitro.Trends in Neurosciences,26(12):676–682,2003.。
