Knee osteoarthritis:A review of animal models and intervention of traditional Chinese medicine

Background:Knee osteoarthritis(KOA)characterized by degeneration of knee cartilage and subsequent bone hyperplasia is a prevalent joint condition primarily affecting aging adults.The pathophysiology of KOA remains poorly understood,as it involves complex mechanisms that result in the same outcome.Consequently,researchers are interested in studying KOA and require appropriate animal models for basic research.Chinese herbal compounds,which consist of multiple herbs with diverse pharmacological properties,possess characteristics such as multicomponent,multipathway,and multitarget effects.The potential benefits in the treatment of KOA continue to attract attention.Purpose:This study aims to provide a comprehensive overview of the advantages,limitations,and specific considerations in selecting different species and methods for KOA animal models.This will help researchers make informed decisions when choosing an animal model.Methods:Online academic databases(e.g.,PubMed,Google Scholar,Web of Science,and CNKI)were searched using the search terms“knee osteoarthritis,”“animal models,”“traditional Chinese medicine,”and their combinations,primarily including KOA studies published from 2010 to 2023.Results:Based on literature retrieval,this review provides a comprehensive overview of the methods of establishing KOA animal models;introduces the current status of advantages and disadvantages of various animal models,including mice,rats,rabbits,dogs,and sheep/goats;and presents the current status of methods used to establish KOA animal models.Conclusion:This study provides a review of the animal models used in recent KOA research,discusses the common modeling methods,and emphasizes the role of traditional Chinese medicine compounds in the treatment of KOA.

Structural similarity of lithospheric velocity models of Chinese mainland

Existing lithospheric velocity models exhibit similar structures typically associated with the first-order tectonic features,with dissimilarities due to different data and methods used in model generation.The quantification of model structural similarity can help in interpreting the geophysical properties of Earth's interior and establishing unified models crucial in natural hazard assessment and resource exploration.Here we employ the complex wavelet structural similarity index measure(CW-SSIM)active in computer image processing to analyze the structural similarity of four lithospheric velocity models of Chinese mainland published in the past decade.We take advantage of this method in its multiscale definition and insensitivity to slight geometrical distortion like translation and scaling,which is particularly crucial in the structural similarity analysis of velocity models accounting for uncertainty and resolution.Our results show that the CW-SSIM values vary in different model pairs,horizontal locations,and depths.While variations in the inter-model CW-SSIM are partly owing to different databases in the model generation,the difference of tomography methods may significantly impact the similar structural features of models,such as the low similarities between the full-wave based FWEA18 and other three models in northeastern China.We finally suggest potential solutions for the next generation of tomographic modeling in different areas according to corresponding structural similarities of existing models.

Model informed precision medicine of Chinese herbal medicines formulas-A multi-scale mechanistic intelligent model

Recent trends suggest that Chinese herbal medicine formulas(CHM formulas)are promising treatments for complex diseases.To characterize the precise syndromes,precise diseases and precise targets of the precise targets between complex diseases and CHM formulas,we developed an artificial intelligence-based quantitative predictive algorithm(DeepTCM).DeepTCM has gone through multilevel model calibration and validation against a comprehensive set of herb and disease data so that it accurately captures the complex cellular signaling,molecular and theoretical levels of traditional Chinese medicine(TCM).As an example,our model simulated the optimal CHM formulas for the treatment of coronary heart disease(CHD)with depression,and through model sensitivity analysis,we calculated the balanced scoring of the formulas.Furthermore,we constructed a biological knowledge graph representing interactions by associating herb-target and gene-disease interactions.Finally,we experimentally confirmed the therapeutic effect and pharmacological mechanism of a novel model-predicted intervention in humans and mice.This novel multiscale model opened up a new avenue to combine“disease syndrome”and“macro micro”system modeling to facilitate translational research in CHM formulas.

The enlightenment of artificial intelligence large-scale model on the research of intelligent eye diagnosis in traditional Chinese medicine

Eye diagnosis is a method for inspecting systemic diseases and syndromes by observing the eyes.With the development of intelligent diagnosis in traditional Chinese medicine(TCM);artificial intelligence(AI)can improve the accuracy and efficiency of eye diagnosis.However;the research on intelligent eye diagnosis still faces many challenges;including the lack of standardized and precisely labeled data;multi-modal information analysis;and artificial in-telligence models for syndrome differentiation.The widespread application of AI models in medicine provides new insights and opportunities for the research of eye diagnosis intelli-gence.This study elaborates on the three key technologies of AI models in the intelligent ap-plication of TCM eye diagnosis;and explores the implications for the research of eye diagno-sis intelligence.First;a database concerning eye diagnosis was established based on self-su-pervised learning so as to solve the issues related to the lack of standardized and precisely la-beled data.Next;the cross-modal understanding and generation of deep neural network models to address the problem of lacking multi-modal information analysis.Last;the build-ing of data-driven models for eye diagnosis to tackle the issue of the absence of syndrome dif-ferentiation models.In summary;research on intelligent eye diagnosis has great potential to be applied the surge of AI model applications.

Factors Influencing the Spatial Variability of Air Temperature Urban Heat Island Intensity in Chinese Cities

Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling factors.In this study,the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers.A total of 355 urban clusters were used.We performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its formation.The results show that the midday AUHI is negatively correlated with climate wetness(humid:0.34 K;semi-humid:0.50 K;semi-arid:0.73 K).The annual mean midnight AUHI does not show discernible spatial patterns,but is generally stronger than the midday AUHI.The urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid(0.32±0.09 K)and the semi-arid(0.36±0.11 K)climate zones.The release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate zones.The rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations.A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.

Developments in the study of Chinese herbal medicine's assessment index and action mechanism for diabetes mellitus

In traditional Chinese medicine(TCM),based on various pathogenic symptoms and the‘golden chamber’medical text,Huangdi Neijing,diabetes mellitus falls under the category‘collateral disease’.TCM,with its wealth of experience,has been treating diabetes for over two millennia.Different antidiabetic Chinese herbal medicines re-duce blood sugar,with their effective ingredients exerting unique advantages.As well as a glucose lowering effect,TCM also regulates bodily functions to prevent diabetes associated complications,with reduced side effects compared to western synthetic drugs.Chinese herbal medicine is usually composed of polysaccharides,saponins,al-kaloids,flavonoids,and terpenoids.These active ingredients reduce blood sugar via various mechanism of actions that include boosting endogenous insulin secretion,enhancing insulin sensitivity and adjusting key enzyme activity and scavenging free radicals.These actions regulate glycolipid metabolism in the body,eventually achiev-ing the goal of normalizing blood glucose.Using different animal models,a number of molecular markers are available for the detection of diabetes induction and the molecular pathology of the disease is becoming clearer.Nonetheless,there is a dearth of scientific data about the pharmacology,dose-effect relationship,and structure-activity relationship of TCM and its constituents.Further research into the efficacy,toxicity and mode of action of TCM,using different metabolic and molecular markers,is key to developing novel TCM antidiabetic formulations.

A Survey on Chinese Sign Language Recognition:From Traditional Methods to Artificial Intelligence

Research on Chinese Sign Language(CSL)provides convenience and support for individuals with hearing impairments to communicate and integrate into society.This article reviews the relevant literature on Chinese Sign Language Recognition(CSLR)in the past 20 years.Hidden Markov Models(HMM),Support Vector Machines(SVM),and Dynamic Time Warping(DTW)were found to be the most commonly employed technologies among traditional identificationmethods.Benefiting from the rapid development of computer vision and artificial intelligence technology,Convolutional Neural Networks(CNN),3D-CNN,YOLO,Capsule Network(CapsNet)and various deep neural networks have sprung up.Deep Neural Networks(DNNs)and their derived models are integral tomodern artificial intelligence recognitionmethods.In addition,technologies thatwerewidely used in the early days have also been integrated and applied to specific hybrid models and customized identification methods.Sign language data collection includes acquiring data from data gloves,data sensors(such as Kinect,LeapMotion,etc.),and high-definition photography.Meanwhile,facial expression recognition,complex background processing,and 3D sign language recognition have also attracted research interests among scholars.Due to the uniqueness and complexity of Chinese sign language,accuracy,robustness,real-time performance,and user independence are significant challenges for future sign language recognition research.Additionally,suitable datasets and evaluation criteria are also worth pursuing.

A CMIP6-based assessment of regional climate change in the Chinese Tianshan Mountains

Climate warming profoundly affects hydrological changes,agricultural production,and human society.Arid and semi-arid areas of China are currently displaying a marked trend of warming and wetting.The Chinese Tianshan Mountains(CTM)have a high climate sensitivity,rendering the region particularly vulnerable to the effects of climate warming.In this study,we used monthly average temperature and monthly precipitation data from the CN05.1 gridded dataset(1961-2014)and 24 global climate models(GCMs)of the Coupled Model Intercomparison Project Phase 6(CMIP6)to assess the applicability of the CMIP6 GCMs in the CTM at the regional scale.Based on this,we conducted a systematic review of the interannual trends,dry-wet transitions(based on the standardized precipitation index(SPI)),and spatial distribution patterns of climate change in the CTM during 1961-2014.We further projected future temperature and precipitation changes over three terms(near-term(2021-2040),mid-term(2041-2060),and long-term(2081-2100))relative to the historical period(1961-2014)under four shared socio-economic pathway(SSP)scenarios(i.e.,SSP1-2.6,SSP2-4.5,SSP3-7.0,and SSP5-8.5).It was found that the CTM had experienced significant warming and wetting from 1961 to 2014,and will also experience warming in the future(2021-2100).Substantial warming in 1997 was captured by both the CN05.1 derived from interpolating meteorological station data and the multi-model ensemble(MME)from the CMIP6 GCMs.The MME simulation results indicated an apparent wetting in 2008,which occurred later than the wetting observed from the CN05.1 in 1989.The GCMs generally underestimated spring temperature and overestimated both winter temperature and spring precipitation in the CTM.Warming and wetting are more rapid in the northern part of the CTM.By the end of the 21st century,all the four SSP scenarios project warmer and wetter conditions in the CTM with multiple dry-wet transitions.However,the rise in precipitation fails to counterbalance the drought induced by escalating temperature in the future,so the nature of the drought in the CTM will not change at all.Additionally,the projected summer precipitation shows negative correlation with the radiative forcing.This study holds practical implications for the awareness of climate change and subsequent research in the CTM.

Application of multidisciplinary team-based integrated traditional Chinese medicine and Western medicine in rotator cuff injury patients undergoing arthroscopic surgery

BACKGROUND Arthroscopic rotator cuff repair is a common surgical treatment for rotator cuff injuries(RCIs).Although this procedure has certain clinical advantages,it requires rehabilitation management interventions to ensure therapeutic efficacy.AIM To investigate the effect of integrated traditional Chinese medicine and Western medicine(TCM-WM)under the multidisciplinary team(MDT)model on the postoperative recovery of patients undergoing arthroscopic surgery for RCIs.METHODS This study enrolled 100 patients who underwent arthroscopic rotator cuff repair for RCIs at the Seventh People’s Hospital of Shanghai University of Traditional Chinese Medicine between June 2021 and May 2024.They were divided into a control group(n=48)that received routine rehabilitation treatment and an experimental group(n=52)that received TCM-WM under the MDT model(e.g.,acupuncture,TCM traumatology and orthopedics,and rehabilitation).The results of the Constant–Murley Shoulder Score(CMS),Visual Analogue Scale(VAS),Shoulder Pain and Disability Index(SPADI),muscular strength evaluation,and shoulder range of motion(ROM)assessments were analyzed.RESULTS After treatment,the experimental group showed significantly higher CMS scores in terms of pain,functional activity,shoulder joint mobility,and muscular strength than the baseline and those of the control group.The experimental group also exhibited significantly lower VAS and SPADI scores than the baseline and those of the control group.In addition,the experimental group showed significantly enhanced muscular strength(forward flexor and external and internal rotator muscles)and shoulder ROM(forward flexion,abduction,and lateral abduction)after treatment compared with the control group.CONCLUSION TCM-WM under the MDT model improved shoulder joint function,relieved postoperative pain,promoted postoperative functional recovery,and facilitated the recovery of muscular strength and shoulder ROM in patients with RCIs who underwent arthroscopic rotator cuff repair.

Study on the Photosynthetic Characteristics of Six Varieties(Strains)in Chinese Chestnut

[Objectives]This study was conducted to investigate the differences of photosynthetic physiological characteristics of different varieties(strains),which will provide a theoretical basis for high photosynthesis efficiency breeding and application in Chinese chestnut.[Methods]Six Chinese chestnut varieties of Castanea mollissima‘Yanbao’,C.mollissima‘Yanqiu’,C.mollissima‘Yanchang’,C.mollissima‘Yanjia’,C.mollissima‘Qianxi 37’,and C.mollissima‘Hybrid 22’were used as the materials.Using the portable photosynthesis system Li-6400,we measured the photosynthetic characteristics and diurnal variation of leaf samples of six different chestnut varieties or strains.We fitted the light response curves and photosynthetic parameters using the leaf floating model.Additionally,we determined the chlorophyll content in the leaves using a UV-visible spectrophotometer.[Results]Among the six chestnut varieties or strains,‘Yanqiu’exhibited a significantly higher photosynthetic light saturation point(P LSP)compared to other five varieties,and‘Hybrid 22’ranked second,indicating that these two varieties had the strongest adaptation to high light intensity.The photosynthetic light compensation point(P LCP)of‘Yanchang’was significantly higher than other five varieties,and"Qianxi 37"ranked second,indicating that these two varieties had the strongest adaptation to low light intensity.Additionally,they exhibited higher chlorophyll content and maintained good photosynthetic characteristics even in shaded environments with weak light stress.Varieties‘Yanbao’and‘Yanjia’showed higher P LSP and lower P LCP,indicating that these two varieties have a wider range of adaptation to light intensity.They were capable of efficiently utilizing light across a broader spectrum of intensities.‘Yanqiu’had the highest maximum net photosynthetic rate(P n,max)and the lowest dark respiration rate(R d),along with the highest chlorophyll content.It indicated that‘Yanqiu’has strong photosynthetic capacity and organic matter accumulation ability.It also had the highest P LSP,enabling it to fully utilize the high light environment of the Yanshan Mountains and possessed high light efficiency characteristics.The P n,max of‘Yanqiu’was significantly higher than other varieties.‘Hybrid 22’and‘Yanbao’also exhibited significantly higher P n,max compared with‘Yanjia’and‘Qianxi 37’.‘Yanchang’had the lowest P n,max.The order of P n,max among the six chestnut varieties or strains was as follows:‘Yanqiu’>‘Hybrid 22’>‘Yanbao’>‘Yanjia’>‘Qianxi 37’>‘Yanchang’.[Conclusions]

Construction of competency evaluation system for infection control personnel in traditional Chinese medicine hospitals

Background:This study uses a literature review and the Delphi expert consultation method to construct a competency evaluation model for infection control personnel in traditional Chinese medicine(TCM)hospitals.The aim is to strengthen infection control management in TCM hospitals,assess the competency of infection control personnel in their positions,and assist them in identifying the competencies that need improvement.Methods:Based on the literature research method and the Delphi expert consultation method,a competency model for the position was constructed through two rounds of expert consultations,analyzing the relationships between various factors and establishing a hierarchical structure model.Pairwise comparisons were made among the elements at the same level to construct a judgment matrix.Through the analytic hierarchy process,the weight coefficients of the indicators at each level in the competency model were obtained.Results:This study conducted a comprehensive assessment of various capabilities and practices related to hospital infection control.The survey results indicate that participants excelled in multiple areas,with a high overall satisfaction rate.95.28%of participants were able to develop hospital infection monitoring plans based on national infection control policies,demonstrating a good understanding and execution of these policies.94.09%of participants were familiar with high-risk populations and key departments in the hospital.91.73%of participants were able to establish monitoring scopes based on the trends of multidrug-resistant bacteria and conduct information monitoring,reflecting strong response capabilities.92.91%of participants were able to collaborate with relevant departments to conduct bacterial resistance monitoring,showing a good team spirit.94.49%of participants were able to perform targeted monitoring,including surgical site infections,indicating that they have effective monitoring strategies.91.34%of participants were able to collect and organize monitoring data and establish a systematic database,demonstrating good data management skills.90.16%of participants were able to interpret laws and regulations related to hospital infection management,indicating a high level of legal knowledge.89.37%of participants generally possessed good communication skills.92.52%of participants were able to guide medical staff on occupational safety and protective knowledge,showing an emphasis on occupational health.Participants demonstrated a strong desire to learn and innovate,with 87.01%actively participating in continuing education and research activities,reflecting a pursuit of professional development.Conclusion:Based on the results of the two rounds of expert consultations,a competency evaluation model for infection control personnel in TCM hospitals was formed.Through the analytic hierarchy process,the weight coefficients of various indicators at different levels in the model were obtained,and the research results have good scientific validity and reliability.

Machine learning models for stroke detection by observing the eye-movement features under five-color visual stimuli in traditional Chinese medicine

Objective:To develop a novel diagnostic modality to identify and diagnose stroke in daily life scenarios for improving the therapeutic effects and prognoses of patients.Methods:In this study,16 stroke patients and 24 age-matched healthy participants as controls were recruited for comparative analysis.Leveraging a portable eye-tracking device and integrating traditional Chinese medicine theory with modern color psychology principles,we recorded the eye movement signals and calculated eye movement features.Meanwhile,the stroke recognition models based on eye movement features were further trained by using random forest(RF),k-nearest neighbors(KNN),decision tree(DT),gradient boosting classifier(GBC),XGBoost,and CatBoost.Results:The stroke group and the healthy group showed significant differences in some eye movement features(P<.05).The models trained based on eye movement characteristics had good performances in recognizing stroke individuals,with accuracies ranging from 77.40%to 88.45%.Under the red stimulus,the eye movement model trained by RF became the best machine learning model with a recall of 84.65%,a precision of 86.48%,a F1 score of 85.47%.Among the six algorithms,RF and CatBoost performed better in classification.Conclusion:This study pioneers the application of traditional Chinese medicine's five-color stimuli to visual observation tasks.On the basis of the combined design,the eye-movement models can accurately identify stroke,and the developed high-performance models may be used in daily life scenarios.

Price linkage between Chinese and international nonferrous metals commodity markets based on VAR-DCC-GARCH models

Using VAR-DCC-GARCH model,the literature on commodity price was extended by exploring the co-movement between Chinese nonferrous metal prices and global nonferrous metal prices represented by the nonferrous metal prices from London Metal Exchange(LME).The results show that LME nonferrous metals prices still have a greater impact on Chinese nonferrous metals prices.However,the impact of Chinese nonferrous metals prices on LME nonferrous metals prices is still weak except for lead price.The co-movement of nonferrous metal prices between LME and China presents hysteretic nature,and it lasts for 7-8trading days.Furthermore,the co-movement between LME nonferrous metals prices and Chinese nonferrous metals prices has the characteristics of time-varying,and the correlation of lead prices between LME and China is the more stable than all other nonferrous metals prices.

“CHINESE”复元模式对高校心理育人工作的启示

根据2020年心理健康蓝皮书,青少年的抑郁检出率随着年级增长呈上升趋势,抑郁状态进入大学前抵达峰值。该研究采取系统整体论的观点聚焦心理疾病学生的整体分布情况和发病规律,将心理疾病学生清晰定位为高校心理育人的重点与难点。“CHINESE”复元模式与高校的心理育人工作本质上存在很好的契合度,复元模式关注高校社区环境下生活的个体,从社会工作视角进一步整合高校心理工作的资源从多个层面为心理疾病学生提供帮助和支持,这是心理疾病学生恢复大学学习与生活的良好契机。“CHINESE”复元模式的社区工作思路不仅启发高校心理育人工作的提升路径,并且有效地避免仅以危机干预方式应对心理疾病学生的工作误区。

Narrative Medicine Under the Guidance of Traditional Chinese Medicine Theory

This paper is an exploration into the practice of narrative medicine in the clinical setting guided by the theory and approaches of traditional Chinese medicine(TCM).By adopting the theory of TCM,the author attempted to provide the patients with systematic treatment from the perspective of society-psychology-biology under the guidance of both the unity of Heaven and Man,and the unity of Xing(Body)and Shen(Mind/Spirit)through his clinical practice.Guided by yin-yang and Wu Xing(Five Elements)theory and focusing on the social relations of the patients for any possible relationships between patients’social,psychological and biological state,the author took the patients’emotion management as a point of departure and helped the patients recover both physically and psychologically by promoting positive transformation in patients’social,psychological,and biological state.A clinical case was provided at the end of this paper to demonstrate how the above theory was put into practice.Narrative medicine under the guidance of TCM theory can supplement modern medical humanity practices as well as extend the scope of modern medical treatment from the perspective of the unity of Heaven and Man,by enriching the content of narrative medicine,and promoting the medical model from biological medical model toward social-psychological-biological model.

基于ChineseBert的中文拼写纠错方法

中文拼写错误主要集中在拼音相似和字形相似两个方面,而通用的预训练语言模型只考虑文本的语义信息,忽略了中文的拼音和字形特征.最新的中文拼写纠错(Chinese Spelling Correction,CSC)方法在预训练模型的基础上利用额外的网络来融入拼音和字形特征,但和直接微调预训练模型相比,改进的模型没有显著提高模型的性能,因为由小规模拼写任务语料训练的拼音和字形特征,和预训练模型获取的丰富语义特征相比,存在严重的信息不对等现象.将多模态预训练语言模型ChineseBert应用到CSC问题上,由于ChineseBert已将拼音和字形信息放到预训练模型构建阶段,基于ChineseBert的CSC方法不仅无须构建额外的网络,还解决了信息不对等的问题.由于基于预训练模型的CSC方法普遍不能很好地处理连续错误的问题,进一步提出SepSpell方法.首先利用探测网络检测可能错误的字符,再对可能错误的字符保留拼音特征和字形特征,掩码对应的语义信息进行预测,这样能降低预测过程中错误字符带来的干扰,更好地处理连续错误问题.在三个官方评测数据集上进行评估,提出的两个方法都取得了非常不错的结果.

Creating animal models, why not use the Chinese tree shrew ( Tupaia belangeri chinensis)？

The Chinese tree shrew （Tupaia belangeri chinensis） a squirrel-like and rat-sized mammal, has a wide distribution in Southeast Asia, South and Southwest China and has many unique characteristics that make it suitable for use as an experimental animal. There have been many studies using the tree shrew （Tupaia belangeri） aimed at increasing our understanding of fundamental biological mechanisms and for the modeling of human diseases and therapeutic responses. The recent release of a publicly available annotated genome sequence of the Chinese tree shrew and its genome database （www.treeshrewdb.org） has offered a solid base from which it is possible to elucidate the basic biological properties and create animal models using this species. The extensive characterization of key factors and signaling pathways in the immune and nervous systems has shown that tree shrews possess both conserved and unique features relative to primates. Hitherto, the tree shrew has been successfully used to create animal models for myopia, depression, breast cancer, alcohol-induced or non-alcoholic fatty liver diseases, herpes simplex virus type 1 （HSV-1） and hepatitis C virus （HCV） infections, to name a few. The recent successful genetic manipulation of the tree shrew has opened a new avenue for the wider usage of this animal in biomedical research. In this opinion paper, I attempt to summarize the recent research advances that have used the Chinese tree shrew, with a focus on the new knowledge obtained by using the biological properties identified using the tree shrew genome, a proposal for the genome-based approach for creating animal models, and the genetic manipulation of the tree shrew. With more studies using this species and the application of cutting-edge gene editing techniques, the tree shrew will continue to be under the spot light as a viable animal model for investigating the basis of many different human diseases.

Asian Summer Monsoon Onset in Simulations and CMIP5 Projections Using Four Chinese Climate Models

The reproducibility and future changes of the onset of the Asian summer monsoon were analyzed based on the simulations and projections under the Representative Concentration Pathways （RCP） scenario in which anthropogenic emissions continue to rise throughout the 21 st century （i.e. RCP8.5） by all realizations from four Chinese models that participated in the Coupled Model Intercomparison Project Phase 5 （CMIP5）. Delayed onset of the monsoon over the Arabian Sea was evident in all simulations for present-day climate, which was associated with a too weak simulation of the low-level Somali jet in May. A consistent advanced onset of the monsoon was found only over the Arabian Sea in the projections, where the advanced onset of the monsoon was accompanied by an increase of rainfall and an anomalous anticyclone over the northern Indian Ocean. In all the models except FGOALS-g2, the enhanced low-level Somali jet transported more water vapor to the Arabian Sea, whereas in FGOALS-g2 the enhanced rainfall was determined more by the increased wind convergence. Furthermore, and again in all models except FGOALS-g2, the equatorial SST warming, with maximum increase over the eastern Pacific, enhanced convection in the central West Pacific and reduced convection over the eastern Indian Ocean and Maritime Continent region, which drove the anomalous anticyclonic circulation over the western Indian Ocean. In contrast, in FGOALS-g2, there was minimal （near-zero） warming of projected SST in the central equatorial Pacific, with decreased convection in the central West Pacific and enhanced convection over the Maritime Continent. The broader-scale differences among the models across the Pacific were related to both the differences in the projected SST pattern and in the present-day simulations.

Stand basal area modelling for Chinese fir plantations using an artificial neural network model

Artificial neural network models are a popular estimation tool for fitting nonlinear relationships because they require no assumptions about the form of the fitting function,non-Gaussian distributions,multicollinearity,outliers and noise in the data.The problems of backpropagation models using artificial neural networks include determination of the structure of the network and overlearning courses.According to data from 1981 to 2008 from 15 permanent sample plots on Dagangshan Mountain in Jiangxi Province,a back-propagation artificial neural network model(BPANN)and a support vector machine model(SVM)for basal area of Chinese fir(Cunninghamia lanceolata)plantations were constructed using four kinds of prediction factors,including stand age,site index,surviving stem numbers and quadratic mean diameters.Artificial intelligence methods,especially SVM,could be effective in describing stand basal area growth of Chinese fir under different growth conditions with higher simulation precision than traditional regression models.SVM and the Chapman–Richards nonlinear mixed-effects model had less systematic bias than the BPANN.

Development of a human rotavirus induced diarrhea model in Chinese mini-pigs

AIM: to establish a new animal model for the research of human rotavirus(HRV) infection, its pathogenesis and immunity and evaluation of potential vaccines.METHODS: 5-d, 30-d and 60-d-old Chinese mini-pigs, Guizhou and bamma, were inoculated with a single oral dose of attenuated strain Wa, G1, G3 of HRV, and PbS(control), respectively, and fecal samples of pigs from 0 to 7 d post infection(DPI) were collected individually. Enzyme linked immunosorbent assay was used to detect HRV antigen in feces. the HRV was tested by real-time PCR(Rt-PCR). the sections of the intestinal tissue were stained with hematoxylin and eosin to observe the morphologic variation by microscopy. Immunofluorescence was used to determine the HRV in intestinal tissue. HRV particles in cells of the ileum were observed by electron micrography.RESULTS: When inoculated with HRV, mini-pigs younger than 30 d developed diarrhea in an agedependent manner and shed HRV antigen of the sameinoculum, as demonstrated by Rt- PCR.Histopathological changes were observed in HRV inoculated mini-pigs including small intestinal cell tumefaction and necrosis. HRV that was distributed in the small intestine was restricted to the top part of the villi on the internal wall of the ileum, which was observed by immunofluorescence and transmission electron microscopy. Virus particles were observed in Golgi like follicles in HRV-infected neonatal minipigs. Guizhou mini-pigs were more sensitive to HRV than bamma with respect to RV antigen shedding and clinical diarrhea.CONCLUSION: these results indicate that we have established a mini-pig model of HRV induced diarrhea. Our findings are useful for the understanding of the pathogenic mechanisms of HRV infection.