Objective To analyze the spatial distribution pattern of the potential suitable habitats for the Tibetan medicinal plant Sinopodophyllum hexandrum under current climatic conditions and the factors influencing the spatial differentiation of the habitats.Methods Based on the maximum entropy model,a species distribution model was established using selected species distribution data and environmental variable data.The geographic detector and the interaction detector were applied to quantify the factors affecting the spatial differentiation of the suitable area.By overlaying the suitable area with land cover types,the distribution characteristics of potential arable land and forest land within the potential suitable area were quantified.Results Under the current climatic conditions,altitude,precipitation in July,precipitation during the warmest season,water vapor pressure in June,precipitation in December,and the highest temperature in February are the key environmental factors affecting the distribution of Sinopodophyllum hexandrum.Under the current climatic conditions,the potential geographical distribution range of Sinopodophyllum hexandrum covers an area of 1.30×106 km2.Considering land cover types,the actual suitable area for Sinopodophyllum hexandrum is 6.13×105 km2,including 4.25×105 km2 of forest land and 1.88×105 km2 of arable land.The highly suitable forest areas are mainly distributed in the Aba Tibetan and Qiang Autonomous Prefecture,Ganzi Tibetan Autonomous Prefecture of Sichuan Province,Diqing Tibetan Autonomous Prefecture,Nujiang Lisu Autonomous Prefecture of Yunnan Province and Linzhi City within the Tibet Autonomous Region.The highly suitable arable land areas are mainly distributed in the Linxia Hui Autonomous Prefecture,Dingxi City,Tianshui City,and Longnan City of Gansu Province,with sporadic belt-like distributions in Sichuan Province,Yunnan Province and the Tibet Autonomous Region.Conclusion The study can provide evidence for the protection of wild Sinopodophyllum hexandrum resources and the selection of optimal planting areas.

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.

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 pattern of potential suitable habitats and the influencing factors of habitat spatial differentiation of Gastrodiae Rhizoma under current climate conditions.Methods Based on 137 distribution records of Gastrodiae Rhizoma sourced from the Global Biodiversity Information Facility and 104 environmental variables acquired from the WorldClim dataset,a predictive model for the potential suitable habitat of Gastrodiae Rhizoma was developed using the MaxEnt model.The geodetector was applied to quantitatively analyze the environmental factors influencing the spatial heterogeneity of the suitable habitats.Subsequently,an overlay analysis with land cover types was conducted to obtain the distribution characteristics of forest land and cultivated land in the potential suitable habitats.Results Under current climate conditions,key environmental factors affecting the distribution of Gastrodiae Rhizoma included precipitation in July,average temperature in the coldest quarter,precipitation in the warmest quarter,water vapor pressure in September,altitude,and solar radiation in December.The potential geographical distribution range of Gastrodiae Rhizoma was 1.64×106 km2.Considering land cover types,the actual potential suitable area for Gastrodiae Rhizoma was 1.33×106 km2,of which the forest land area was 8.56×105 km2 and the cultivated land area was 4.74×105 km2.The highly suitable forest areas were mainly located within the provinces of Guizhou,Sichuan,Shaanxi,Hubei,Hunan and Gansu.The cultivated land suitable areas are mainly located within the provinces of Guizhou,Sichuan,Yunnan,Shaanxi and Hubei.Conclusion The highly suitable habitats of Gastrodiae Rhizoma are mainly located in provinces such as Guizhou,Sichuan,Shaanxi and Hubei,and are affected by factors such as solar radiation,water vapor pressure,temperature and precipitation.The research results can provide reference for the protection of wild Gastrodiae Rhizoma resources,artificial nurturing and optimal selection of ecological planting areas.

Objective To analyze the spatial distribution pattern of the potential suitable habitats for the Tibetan medicinal plant Sinopodophyllum hexandrum under current climatic conditions and the factors influencing the spatial differentiation of the habitats.Methods Based on the maximum entropy model,a species distribution model was established using selected species distribution data and environmental variable data.The geographic detector and the interaction detector were applied to quantify the factors affecting the spatial differentiation of the suitable area.By overlaying the suitable area with land cover types,the distribution characteristics of potential arable land and forest land within the potential suitable area were quantified.Results Under the current climatic conditions,altitude,precipitation in July,precipitation during the warmest season,water vapor pressure in June,precipitation in December,and the highest temperature in February are the key environmental factors affecting the distribution of Sinopodophyllum hexandrum.Under the current climatic conditions,the potential geographical distribution range of Sinopodophyllum hexandrum covers an area of 1.30×106 km2.Considering land cover types,the actual suitable area for Sinopodophyllum hexandrum is 6.13×105 km2,including 4.25×105 km2 of forest land and 1.88×105 km2 of arable land.The highly suitable forest areas are mainly distributed in the Aba Tibetan and Qiang Autonomous Prefecture,Ganzi Tibetan Autonomous Prefecture of Sichuan Province,Diqing Tibetan Autonomous Prefecture,Nujiang Lisu Autonomous Prefecture of Yunnan Province and Linzhi City within the Tibet Autonomous Region.The highly suitable arable land areas are mainly distributed in the Linxia Hui Autonomous Prefecture,Dingxi City,Tianshui City,and Longnan City of Gansu Province,with sporadic belt-like distributions in Sichuan Province,Yunnan Province and the Tibet Autonomous Region.Conclusion The study can provide evidence for the protection of wild Sinopodophyllum hexandrum resources and the selection of optimal planting areas.

Objective To study the efficacy and safety of less invasive surfactant administration(LISA)combined with budesonide and supported by nasal intermittent positive pressure ventilation(NIPPV)in preterm infants with respiratory distress syndrome(RDS).Methods Premature infants with RDS at the gestational age of 26-32 weeks in the neonatal ward of Xuzhou Central Hospital from Feb-ruary 2022 to March 2024 were divided into the observation group and the control group in this prospective randomized controlled trial.The control group suspended nasal continuous positive airway pressure(NCPAP),they were intubated and infused with PS into the lung through endotracheal tube and extubated(INSURE),then continued to receive NCPAP.In the observation group,a LISA tube was insert-ed through the vocal cords under direct vision with direct laryngoscope,then infused pulmonary surfactant(PS)and budesonide into the lung when NIPPV ventilation was applied.The results of blood gas analysis at 1h and 6h after intratracheal instillation of PS,medication administration,clinical efficacy,related complications of budesonide,bronchopulmonary dysplasia(BPD)were compared between the two groups.Results A total of 126 preterm infants with RDS were enrolled in the study,including 65 in the observation group and 61 in the control group.The incidence of regurgitation in the observation group were lower than those in the control group[(10.8％(7/65)vs 24.6％(15/61)],and the differences were statistically significant(P＜0.05).The PaO2/FiO2(P/F)in the observation group at 1h and 6h were higher than those in the control group,while PaCO2were lower than those in the control group,and the differences were statis-tically significant(all P＜0.05).The duration of non-invasive respiratory support(11.4±4.6 days vs 15.9±5.6 days),total oxygen inhaling(14.9±6.9 days vs 21.2±8.5 days),failure rate of machine withdrawal[(10.8％(7/65)vs 24.6％(15/61)],the rate of tracheal intubation within 72h[9.2％(6/65)vs 23.0％(14/61)],and re-administration of PS[18.5％(12/65)vs 34.4％(21/61)],the times of apnea[9.0(3.0-25.0)times vs 17.0(5.0-29.0)times]in the observation group were lower than those in the control group,and the differences were statistically significant(P＜0.05).The occurrence of BPD in the observational group were lower than those in the control group[15.4％(10/65)vs 34.4％(21/61)](P＜0.05).There were no significant differences between two groups in the related complications of budesonide(all P＞0.05).Conclusion LISA combined with budesonide and supported by NIPPV can effectively improve oxygenation,shorten the duration of non-invasive respiratory support,reduce the mechanical ventilation rate,and reduce the incidence of BPD in the treatment of premature infants with RDS at the gestational age of 26-32 weeks.

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 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 explore the application effectiveness of the large language model DeepSeek in the cultivation of clinical thinking skills for medical laboratory technology students.Methods:A non-randomized controlled study was conducted. In the 2024-2025 academic year, two classes of second-year medical laboratory technology students from Hubei University of Chinese Medicine were selected and divided into a DeepSeek-assisted teaching group (Class A, n=53) and a traditional teaching control group (Class B, n=53), totaling 106 students. Both groups followed a 20-week problem-based learning (PBL) framework with identical teaching content, instructors, and class hours. Class A utilized DeepSeek via the"Learning Pass AI"platform for case diagnosis reasoning, prompt construction training, test plan formulation, and result analysis, while Class B received traditional PBL instruction. Paired t-tests were used to compare pre-and post-teaching scores in clinical thinking skills, AI interaction literacy, and prompt construction in Class A. Independent samples t-tests and chi-square ( χ2) tests were used to evaluate differences in case reasoning scores, etiology analysis accuracy, and teaching satisfaction between groups. Structured questionnaires supplemented the evaluation of model-assisted teaching processes. Results:The comparison of pre-and post-teaching scores in Class A showed that post-teaching scores significantly improved in clinical thinking skills[(4.02±0.45) points vs. (3.09±0.50) points, t=2.23)] and AI interaction literacy [(4.62±0.41) points vs. (3.27±0.54) points, t=2.18]. Compared to Class B, Class A demonstrated superior performance in case reasoning scores [(81.1±3.8) points vs.(74.3±4.2) points, t=8.97], etiology analysis accuracy [94.3% (50/53) vs. 81.1% (43/53), χ2=4.29], and teaching satisfaction [(95.6±3.2)points vs. (82.6±4.8) points, t=11.86] ( P<0.05). The results of questionnaires indicated that during model application, the prompt construction improved in logic [(2.85±0.58) points to (4.25±0.50) points, t=14.23, P<0.01] and innovation [(2.60±0.53) points to (4.05±0.46) points, t=11.57, P<0.05], but question clarity (77.4%, 41/53) and medical terminology accuracy (43.4%, 23/53) remained primary shortcomings. Conclusion:Integrating large language models into AI-teacher collaborative learning pathways can effectively promote students′ autonomous inquiry and clinical reasoning skills, thereby enhancing medical laboratory technology students′ clinical thinking skills.

Objective To develop the Children's Screen Interaction Quality Questionnaire(CSIQ)suit-able for measuring Chinese children aged 0 to 4 years,and to test its reliability and validity.Methods The purposive sampling method was used,and the guardians of 30 normal children aged 0 to 4 years undergoing physical examinations in the Department of Child Health Care of Guiyang Maternal and Child Health Care Hospital from February to April 2023 were selected as the interview objects.25 initial items were constructed through literature review,semi-structured interviews,and the Delphi expert consultation method.With the convenience sampling method,2 242 guardians of children aged 0 to 4 years old in the small and middle classes of 9 kindergartens in Guiyang City,Zunyi City,and Renhuai City were surveyed for item analysis,exploratory factor analysis,confirmatory factor analysis,and reliability and validity analysis.Results Exploratory factor a-nalysis extracted three factors,namely screen content interaction,reality interaction,and media interaction,with a total of 12 items.The cumulative variance explained rate of the 3-factor model was 69.829％.Confirma-tory factor analysis supported the three-factor model of CSIQ:x2/df=4.424,root mean square error of ap-proximation(RMSEA)=0.066,normed fit index(NFI)=0.955,comparative fit index(CFI)=0.965,incre-mental fit index(IFI)=0.965,Tucker-Lewis index(TLI)=0.955,goodness-of-fit index(GFI)=0.955,and the CSIQ had good convergent validity and discriminant validity.Conclusion The CSIQ has good reliability and validity.