Climate and land use changes may significantly impact the habitat distribution of Gastrodia elata, an endangered traditional medicinal plant. Accurately predicting its future potential suitable habitats is crucial for its conservation and sustainable development. This study integrates current distribution data of G. elata with 56 environmental variables and uses the MaxEnt model to predict changes in its suitable habitats under current climate conditions and four future climate scenarios(SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). The results show that October precipitation and December minimum temperature are key environmental factors influencing its distribution. Under the current climate, optimal habitats for G. elata are concentrated in montane forest areas in Sichuan, Yunnan, Guizhou, and Hubei, which meet the species' requirements for understory growth. Across all future scenarios, the suitable habitat of G. elata consistently shows a stable northward shift, with a steady increase in suitable areas, extending to the middle and lower reaches of the Yangtze River and the Huang-Huai region, and even expanding into Liaoning, Jilin, and southern Heilongjiang. Land use analysis, taking into account the protection of arable land and the utilization of forest resources, indicates that by 2100, under future climate conditions, arable land in medium-to high-suitability areas is expected to increase by 30%-124%. While the conversion of non-suitable forest land into suitable habitats is projected to increase by 5%-52%, the growth of medium-to high-suitability areas within forests is relatively modest, ranging from 1% to 24%. These findings highlight the need to balance agricultural expansion with forest resource conservation to ensure the long-term sustainability of G. elata and provide scientific guidance for future suitable habitat management.
Ecosystem ; China ; Climate Change ; Gastrodia/growth & development* ; Conservation of Natural Resources ; Plants, Medicinal/growth & development*

The left maxilla of a patient was resected because of tumor,and the defect was reconstruted with fibular transplantation.The autonomous dental implant robot technology was used to achieve precise implantation of multiple implants and immediate denture restoration within the limited left maxilla.The surgery was minimally invasive and efficient,and significantly reducing patient post-operative discomfort.The final restoration was completed 6 months after surgery.

Objective To analyze the spatial distribution patterns of the potential suitable habitats for Cremastrae Pseudobulbus Pleiones Pseudobulbus,including Cremastra appendiculata(D.Don)Makino,Pleione bulbocodioides(Franch.)Rolfe and Pleione yunnanensis Rolfe under current climatic conditions,and the factors influencing the spatial differentiation of their habitats.Methods Based on the maximum entropy(MaxEnt)model,a species distribution model was established using the screened species distribution data and environmental variable data.The factor detection and interaction detection of geographical detector were applied to quantify the factors influencing the spatial differentiation of the suitable areas.By overlaying the suitable areas with land cover types,the distribution characteristics of forest land and arable land in the potential suitable areas were quantified.Results Under the current climatic scenario,environmental variables such as solar radiation intensity,precipitation and temperature were closely related to the spatial distribution of Cremastrae Pseudobulbus Pleiones Pseudobulbus.The potential suitable areas for Cremastra appendiculata(D.Don)Makino,Pleione bulbocodioides(Franch.)Rolfe and Pleione yunnanensis Rolfe were 2.20×106 km2,2.75×106 km2 and 7.22×105 km2,respectively.Considering land cover types,the actual possible suitable areas for Cremastra appendiculata(D.Don)Makino,Pleione bulbocodioides(Franch.)Rolfe and Pleione yunnanensis Rolfe were 1.86×106 km2,2.20×106 km2 and 5.77×105 km2,respectively.Among these,the area of forest land was 1.17×106 km2,1.34×106 km2 and 3.67×105 km2,respectively,and the area of arable land was 6.95×105 km2,8.64×105 km2 and 2.10×105 km2,respectively.Conclusion This study can provide a basis for the protection and sustainable utilization of wild resources of the original plant materials of Cremastrae Pseudobulbus Pleiones Pseudobulbus.

Objective To investigate the spatial distribution pattern of the suitable habitats for Codonopsis pilosula(Franch.)Nannf.and the factors influencing the spatial differentiation of its habitat under current climatic conditions in China.Methods Based on maximum entropy(MaxEnt)model,a species distribution model was established with filtered species occurrence data and environmental variable data.The geographical detector was applied to quantify the factors influencing the spatial differentiation of the suitable areas,employing both factor detection and interaction detection functionalities.Additionally,an overlay analysis with land cover types was conducted to quantify the distribution characteristics of arable land and forest land within the potential suitable areas for Codonopsis pilosula(Franch.)Nannf..Results Based on the contribution rate of environmental factors and the Jackknife method,average solar radiation intensity in December,precipitation in July,and highest temperature in December were identified as key environmental factors affecting the suitability of Codonopsis pilosula(Franch.)Nannf.habitats,which were further validated by the geographical detector.The total suitable area for Codonopsis pilosula(Franch.)Nannf.in China under current climatic conditions was approximately 4.46×106 km2,with the areas of high,moderate,and low suitability being 1.08×106 km2,1.70×106 km2,and 1.68×106 km2,respectively.After overlaying with arable and forest lands,the potentially suitable total forest area for Codonopsis pilosula(Franch.)Nannf.was 1.55×106 km2,and the arable land area was 1.63×106 km2.Conclusion This study provides reference for the optimization of cultivation areas for Codonopsis pilosula(Franch.)Nannf.and the conservation of its wild resources.

Objective To analyze the spatial distribution pattern of the potential suitable habitats for Cordyceps under current climatic conditions in China based on space characteristics and biological traits;To explore the key environmental factors affecting the spatial differentiation of its habitats.Methods The Maximum Entropy model was utilized as a predictive tool to synthesize the distribution data of Cordyceps and its associated species Polygonum viviparum and Polygonum macrophyllum,along with environmental variable data.Factor detectors and interaction detectors of geographic detectors were used to conduct geographic exploration of spatial differentiation factors in the suitable habitats of Cordyceps.Furthermore,by overlaying the potential suitable habitats of Cordyceps with surface cover types and the suitable areas of Polygonum viviparum and Polygonum macrophyllum,the specific distribution range of the potential suitable habitats for Cordyceps was refined.Results Under the current climatic conditions,altitude,the precipitation amount of the warmest season,the highest temperature in February,and the precipitation in July are the key environmental factors influencing the distribution of Cordyceps.The potential suitable habitats for Cordyceps reaches 1.18×106 km2,and considering surface cover types,the actual potential suitable habitats for Cordyceps is 7.33×105 km2.Taking into account the associated relationships between species,the actual potential suitable habitats for Cordyceps is 7.27×105 km2.Conclusion The results of this study can reflect the ecological needs of Cordyceps,promote its sustainable utilization of resources,and provide reference for maintaining biodiversity and ecosystem integrity.

Objective To investigate the geographical distribution patterns and influencing factors of suitable habitats for the desert medicinal plant Cynomorium songaricum Rupr under current climatic conditions;To provide a basis for its resource conservation and sustainable utilization.Methods The MaxEnt model was used to analyze potential suitable habitats for Cynomorium songaricum Rupr.Geographical Detector model was used to identify key environmental factors affecting habitat suitability.Surface cover data were overlaid to assess the distribution of sandy and Gobi regions within suitable habitats,enabling a quantitative evaluation of actual potential suitable areas.Results Model predictions indicated a total suitable habitat area of approximately 2.98×106 km2,representing 30.99%of China's mainland area.Highly suitable habitats are concentrated in desert and Gobi regions of Gansu,Xinjiang,Inner Mongolia,Qinghai and Ningxia.Among climatic factors,precipitation of the coldest quarter(bio19),solar radiation in August(srad8),and mean temperature of the coldest quarter(bio11)significantly influence Cynomorium songaricum Rupr distribution.The interaction between temperature and solar radiation intensity exhibited the highest explanatory power for habitat distribution patterns(q=0.82).Overlay analysis with surface cover data estimated the actual potential suitable area at approximately 9.70×105 km2,with sandy regions comprising 5.73×105 km2 and Gobi regions 3.98×105 km2.Conclusion By integrating multi-source data and modeling approaches,this study delineates the potential suitable habitats for Cynomorium songaricum Rupr across China and evaluates the spatial distribution characteristics and influencing factors of suitable habitats in Cynomorium songaricum Rupr.These findings offer a foundation for conserving wild Cynomorium songaricum Rupr resources,optimizing ecological planting regions,and promoting sustainable industry development.

Objective:To investigate the technical application pathways of artificial intelligence(AI)in laboratory information management systems(LIMS)and its role in promoting laboratory management efficiency and intelli-gence.Methods:Through the integration of traditional AI technologies(e.g.,machine learning,computer vision)with large language models,this study demonstrated the application of various AI technologies in scenarios such as intelligent Q&A for local knowledge bases,comprehensive review of inspection processes,intelligent data visualization,and image recognition.Results:Through the implementation of AI applications in laboratory settings,AI significantly enhanced management efficiency:the intelligent Q&A system achieved over 90％accuracy,auto-mated inspection processes reduced manual workload by 40％,and image recognition precision reached 89％-100％.Conclusion:AI provides efficient and precise solutions for laboratory management via multimodal integration and process optimization.Future efforts should focus on strengthening data security and model interpret-ability to promote comprehensive intelligent development.

Objective To develop and validate a nomogram prediction model for residual stone risk after flexible ureteroscopic lithotripsy(FURL)in patients with 2-3 cm renal calculi,so as to provide reference for treatment options.Methods Clinical data of 342 patients with renal calculi measuring 2-3 cm undergoing FURL in our hospital during Jun.2017 and Apr.2024 were retrospectively collected.At a 3∶1 randomization ratio,patients were allocated to the training cohort(n=257)and validation cohort(n=85).Patients in the training cohort were stratified into two subgroups based on postoperative stone-free status:residual stone group(n=63)and stone-free group(n=194).Logistic regression analysis was employed to identify factors influencing stone retention and construct the nomogram prediction model.Bootstrapped resampling was applied to validate the model internally,model performance was assessed with calibration curves,Hosmer-Lemeshow test was used to test the degree of fitting,receiver operating characteristic(ROC)curve was plotted to evaluate the predictive accuracy,and decision curve analysis was used to determine the clinical net benefit.The model's generalization capability was evaluated with 10-fold cross-validation of the training set.Results Multivariate logistic regression revealed that stone size,CT value,lower calyx stones,multiple stones,renal infundibulum length(RIL),and renal infundibulum width(RIW)were independent predictors of residual stones(P＜0.05).The nomogram based on the above mentioned parameters demonstrated excellent discrimination,with Bootstrap-validated concordance indices of 0.876(training cohort)and 0.948(validation cohort).Hosmer-Lemeshow tests showed good calibration in both cohorts(P＞0.05).ROC analysis yielded the area under the curve(AUC)of 0.876 and 0.948 for the training and validation cohorts,respectively.The optimal cutoff value was 0.253,with corresponding sensitivity of 84.13％,specificity of 78.35％,and total score of nomogram of 143.The decision curve analysis showed when the threshold probability of the training cohort and verification cohort was 0-0.81 and 0-0.97,respectively,the nomogram could obtain good clinical net benefit in predicting the risk of residual stones.The average accuracy of 10-fold cross-validation was 0.814,and the average AUC was 0.865.Conclusion The nomogram model effectively predicts residual stone risk following FURL for 2-3 cm renal calculi.It is suggested that patients with a total score of ≤143 may consider undergoing FURL.

Objective:To evaluate the long-term outcomes and predictors of coronary atherosclerotic lesions deemed functionally non-ischemic (quantitative flow ratio(QFR)>0.80) and deferred from intervention.Methods:This study is a post-hoc analysis of the FAVOR Ⅲ China trial, which enrolled 3 825 patients with stable or unstable angina pectoris or with myocardial infarction occurring at least 72 hours prior to screening, between December 5, 2018 and January 9, 2020 from 26 research centers in China. Coronary vessels with QFR>0.80 and without interventional treatment were analyzed in this study. The primary endpoint was 3-year target vessel revascularization. Vessels with revascularization (revascularized group) during follow-up were matched 1∶1 using propensity score matching to comparable vessels without revascularization (non-revascularized group). Multivariate Cox regression analysis was used to identify the risk factors for target vessel revascularization (TVR).Results:A total of 6 212 functionally negative vessels with deferred intervention were included in the final analysis, among which 153 vessels (2.5%) underwent TVR during a 3-year follow-up. Prior to propensity score matching, 6 059 vessels comprised the non-revascularized group. At the vessel level, compared to the non-revascularized group, the revascularized group exhibited a significantly higher proportion of males (79.1% (121/153) vs. 70.2% (4 253/6 059), P=0.018), higher body mass index ((25.6±4.0) kg/m2 vs. (24.3±5.2) kg/m2, P=0.003), and a higher prevalence of hypertension (73.9% (113/153) vs. 65.1% (3 944/6 059), P=0.025). And 152 pairs of vessels were successfully matched. Multivariate Cox regression analysis identified in-stent restenosis lesions ( HR=2.59, 95% CI 1.28-5.23, P=0.008) as an independent risk factor for target vessel revascularization. Conclusions:Coronary lesions classified as functionally non-ischemic at baseline are not entirely stable and may progress to lesions that requiring revascularization over time. In-stent restenosis emerges as a critical independent predictor of revascularization.

Objective: To understand the moderating effect of cohabitation with parents on the association between peer dating behavior and sexual behaviors among secondary vocational school students, so as to provide a scientific basis for preventing sexual behaviors among secondary vocational school students. Methods: From March to April 2021, an electronic questionnaire survey was conducted among 3 180 students from 6 vocational schools in Shanghai (urban, suburban, exurban) and Shaanxi (Shangluo, Ankang, Baoji) using cluster sampling. Spearman correlation analysis was used to investigate the relationship of cohabitation with parents, peer dating behavior and sexual behaviors among secondary vocational school students. Binary Logistic regression analysis was performed to investigate the role of cohabitation with parents on peer dating behavior and sexual behaviors among secondary vocational students. Results: There was a significant negative between cohabitation with parents and sexual ( r =-0.04); and there was a positive correlation between peer dating behavior and sexual behaviors ( r =0.24), as well as cohabitation with parents and peer dating behavior ( r =0.04)( P <0.05). Multivariable Logistic regression analysis showed an association between peer dating behavior and the occurrence of sexual behaviors ( OR=2.79-12.95, P <0.05). Cohabitation with parents played a moderating role in the association between peer dating behavior and sexual behaviors, and a signification interaction was found between cohabitation with parents and reporting that a small part or about half of their peers had dating behavior ( OR =0.48, P <0.05). Conclusions The more peers dating behavior are associated with a higher risk of sexual behaviors among secondary vocational school students, and cohabitation with parents can partly reduce this risk. School and family sexuality education for secondary vocational students should be strengthened to improve their interpersonal skills and decision-making, and ability to resist peer pressure, so as to reduce their risk of sexual behaviors.