ObjectiveBiochemistry and Molecular Biology, a discipline that elucidates life phenomena at the molecular level, serves as a core foundational course in medical education. It provides the theoretical basis for studying other basic and clinical medical subjects, as well as for understanding pathogenesis, disease diagnosis, and treatment. However, its complex content and highly abstract concepts have posed a dual challenge to traditional teaching models: “inefficient instruction” and “inadequate learning outcomes”. Within limited classroom hours, how to engage students and stimulate their intrinsic motivation, and how to help them recognize, understand, and develop a passion for biochemistry from the perspective of the discipline’s essence, have long been key focuses of curriculum research. MethodsUsing the lipid metabolism chapter as an example, this study employs “Rain Classroom”, a generative artificial intelligence (AI)-assisted platform, to support education in four dimensions: teaching, learning, evaluation, and research. In teaching, it assists instructors through virtual experiments, lesson preparation support, knowledge mapping, and assignment design. For learning, it serves as an intelligent study assistant for students, providing automated assignment review, enabling educational resource sharing, and facilitating personalized learning pathways. In evaluation, the platform automates assignment grading, analyzes student performance data, and offers diagnostic feedback and teaching recommendations. In research, it aids educators in collecting and analyzing teaching data, as well as searching for and summarizing relevant literature. ResultsThe results indicate that an educational model integrating teacher-led instruction, student-centered learning, and generative AI assistance significantly enhances teaching quality, students’ self-directed learning abilities, and knowledge mastery. Furthermore, with the support of generative AI, curriculum-based ideological education—focusing on cutting-edge disciplinary advances and topical medical issues—helps cultivate students’ medical spirit of “honoring life and healing the wounded”, thereby fostering the establishment of appropriate professional values. Finally, while generative AI presents both opportunities and challenges for higher education, this study also analyzes potential risks in its teaching applications, emphasizing the need for both instructors and students to avoid over-reliance and to ensure that technological tools consistently serve the fundamental goals of education. ConclusionThis study demonstrates that integrating generative AI, specifically via the “Rain Classroom” platform, can effectively enhance biochemistry education. By supporting teaching, learning, evaluation, and research, this approach improves both educational effectiveness and student outcomes. It also facilitates the incorporation of cutting-edge knowledge and professional ethics, nurturing a patient-centered mindset. Additionally, the study addresses potential implementation risks to ensure that such technological tools remain aligned with the core purpose of education.

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*

Autophagy is a fundamental biological metabolic process involved in immune defense, material metabolism, and homeostasis and closely linked to immune regulation. Systemic lupus erythematosus (SLE) is a widespread connective tissue disorder primarily resulting from immune system imbalance. Due to the immune system's failure to recognize its own substances, it generates autoantibodies that can affect various tissues and organs, leading to diverse clinical manifestations. The pathogenesis and treatment of SLE are currently under extensive investigation. In normal metabolic processes, autophagy engages in both innate and adaptive immunity, regulates the immune response, and is crucial for maintaining normal immune function and the body's internal homeostasis. Research has indicated that SLE patients exhibit immune dysfunction and altered autophagy levels. Modulating autophagy expression can influence immune system functionality and alleviate SLE symptoms. Additionally, autophagy aids in the innate immune response and adaptive immunity by clearing metabolites and regulating the life cycle of immune cells. Studies suggest that drugs targeting autophagy can positively influence the progression of SLE. This article reviews advancements in research regarding the impact of autophagy on the pathogenesis of SLE through the regulation of immune system functions.
Lupus Erythematosus, Systemic/pathology* ; Autophagy/immunology* ; Humans ; Animals ; Immunity, Innate ; Adaptive Immunity ; Disease Progression ; Immune System/immunology*

Ovarian tumor (OT) is the most lethal form of gynecologic malignancy, with minimal improvements in patient outcomes over the past several decades. Metastasis is the leading cause of ovarian cancer-related deaths, yet the underlying mechanisms remain poorly understood. Psychological stress is known to activate the glucocorticoid receptor (NR3C1), a factor associated with poor prognosis in OT patients. However, the precise mechanisms linking NR3C1 signaling and metastasis have yet to be fully elucidated. In this study, we demonstrate that chronic restraint stress accelerates epithelial-mesenchymal transition (EMT) and metastasis in OT through an NR3C1-dependent mechanism involving nuclear protein 1 (NUPR1). Mechanistically, NR3C1 directly regulates the transcription of NUPR1, which in turn increases the expression of snail family transcriptional repressor 2 (SNAI2), a key driver of EMT. Clinically, elevated NR3C1 positively correlates with NUPR1 expression in OT patients, and both are positively associated with poorer prognosis. Overall, our study identified the NR3C1/NUPR1 axis as a critical regulatory pathway in psychological stress-induced OT metastasis, suggesting a potential therapeutic target for intervention in OT metastasis.

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 analyze the spatial distribution patterns and influencing factors of potential suitable habitats for Saussurea medusa under current climatic conditions.Methods The maximum entropy(MaxEnt)model with 125 selected distribution spots data and 9 environmental factors data of Saussurea medusa as input variables for modeling.Quantitative analysis was conducted on the influencing factors of spatial differentiation in the suitable habitat area of Saussurea medusa using geographic detector factor detection and interaction detection tools.Based on land use type data and national nature reserve distribution data,the distribution range of each land use type in the suitable habitat areas for Saussurea medusa,as well as the distribution pattern of high,medium and low suitable habitat areas in national nature reserves were refined.Results Key environmental determinants included elevation,precipitation in the warmest quarter,and solar radiation in April and May.The total potential suitable habitat area spanned 1.33×106 km2,accounting for 13.89%of China's mainland.Grasslands(67.70%),forests(19.19%),barren land(5.90%),snow-covered areas(2.59%)and croplands(2.08%)dominated the suitable habitats,with 34.98%overlapping national nature reserves.Conclusion The results of this study can provide basis for understanding the ecological needs and resource conservation of Saussurea medusa.

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.

AIM To establish a GC-MS/MS method for the analysis of volatile components in Yinhu Ganmao Powder,and to determine the contents of α-pinene,camphene,sabinene,β-pinene,α-terpinene,(+)-limonene,p-cymene,1,8-cineole,linalool,L-menthol,terpinen-4-ol,DL-menthol,α-terpineol,tridecane,pulegone,caryophyllene,humulene,n-hexadecane and patchouli alcohol.METHODS The analysis was performed on a DB-624 UI capillary column(30 m×0.25 mm×1.40 μm ),and electron ionization source was adopted with multiple reaction monitoring mode.RESULTS Fifty volatile components and twenty-five liposoluble components were identified in volatile oils and medicinal material powder,respectively.Nineteen constituents showed good linear relationships within their own ranges(r ≥ 0.999 0),whose average recoveries were 84.43％-113.31％with the RSDs of less than 9.15％.CONCLUSION This stable,accurate and reproducible method can provide a reference for the quality evaluation of Yinhu Ganmao Powder.