With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective To understand the epidemiological characteristics of a clustered outbreak of severe fever with thrombocytopenia syndrome(SFTS)as well as the ecological tick monitoring results for Zibo City, and to provide a scientific basis for formulating prevention and control strategies. Methods A case definition was cited before epidemic investigations were performed. Epidemiological investigations were performed on the index cases and their close contacts. Blood samples were collected from cases and close contacts, and quantitative real-time RT-PCR was used to detect SFTS virus(SFTSV)nucleic acid sequences. A retrospective cohort study was conducted to analyze risk factors and develop prevention and control strategies. Results This clustered outbreak involved two index cases and six close contacts with no deaths. Case A exhibited symptom onset on July 26. SFTS was confirmed on August 2. Case B exhibited symptom onset on August 1, and SFTS was confirmed on August 3. Patient B reported a recent history of tick bites. In both index cases, the incubation period for SFTS was inferred to be 7-12 days. The time interval from symptom onset to clinical diagnosis in the two cases ranged from 2-8 days, with an average period of 5 days. SFTSV nucleic acid test result were positive for both patients, whereas all six close contacts tested negative. All captured ticks tested negative for SFTSV using quantitative real-time RT-PCR. The densities of parasitic and free-living ticks in the emergency monitoring area around the cases were 12.60 and 4.65 ticks/(flag·100 m). In 2024, the average parasitic tick index and free-living tick density index were 4.21 and 2.43 ticks/(flag ·100 m)in Yiyuan County, respectively. Conclusions No evidence of human-to-human transmission was found in the assessed SFTS clusters. The infections were likely acquired through tick bites during fieldwork, and the risk of a subsequent outbreak spreading was low.

Objective To examine the impact of climate, land use and their interaction effect on the population density of Oncomelania hupensis. Methods O. hupensis snail surveillance data in Yunnan Province from 2013 to 2022 were obtained from the National Information System for Parasitic Diseases Prevention and Control of Chinese Information System for Disease Control and Prevention, and the density of living snails was calculated in each county-level administrative district. Climate data were obtained from the China Meteorological Forcing Dataset version 2.0, and land use data were captured from the China Land Cover Dataset. The raster climate data and land use data were clipped to the administrative border of Yunnan Province in the R package version 4.5, and the climate data were resampled to a spatial resolution of 30 m × 30 m consistent with the land use data using bilinear interpolation. Annual meteorological indicators were extracted from each county-level schistosomiasis surveillance administrative area in Yunnan Province from 2013 to 2022, including average temperature, maximum temperature, minimum temperature, temperature difference, average precipitation rate, maximum precipitation rate, minimum precipitation rate, downward shortwave radiation flux, downward longwave radiation flux, air pressure, wind speed, specific humidity and relative humidity. Annual land use structure and landscape pattern index in each county-level schistosomiasis surveillance administrative area in Yunnan Province from 2013 to 2022 were extracted and calculated, including the proportion of areas occupied by each type of land use, patch density, largest patch index, landscape separation index, landscape fragmentation index, landscape segmentation index, contagion index, patch cohesion index, edge density, and shape index. Land use entropy index was introduced to represent the degree of habitat fragmentation and ecological niche breadth. The density of living snails and environmental factors were subjected to rank correlation analysis, and variables with no statistically significant correlation (P>0.1) were excluded. Then, a correlation coefficient matrix was constructed, and |r_s| of 0.85 and greater was defined as the threshold of high collinearity. For highly correlated variables in each group, indicators with a more biological explanatory power or a better statistical efficiency were retained. A generalized additive model (GAM) was constructed with O. hupensis snail density as a response variable and screened environmental variables as independent variables, and the model performance was evaluated using the variance explained. Results The area occupied by O. hupensis snail habitats was 1 056 to 1 680 hm² in Yunnan Province from 2013 to 2022, appearing an overall tendency towards a decline; however, the density of living snails appeared a tendency towards a slight rise. Based on the correlation coefficient matrix, 14 core explanatory variables were retained, including farmland, water bodies, bare land, impervious surface, landscape separation index, landscape fragmentation index, edge density, shape index, land use entropy index, downward longwave radiation flux, downward shortwave radiation flux, maximum temperature, minimum precipitation rate and specific humidity. Two types of GAM were constructed, including the main-effects model without interaction terms and the interaction model with interaction terms. The corrected Akaike information criterion (AICc) of the optimal main-effects model was −285.223, and the core variables included bare land, impervious surface, landscape separation index, edge density, shape index, land use entropy index and downward shortwave radiation flux. Following introduction of second-order interaction terms, the AICc value of the optimal interaction model was −345.526, and the significant interaction combinations included: farmland × impervious surface, farmland × landscape separation index, farmland × shape index, farmland × land use entropy index, impervious surface × landscape separation index, impervious surface × edge density, and shape index × downward shortwave radiation flux. The proportion of the main-effects model explaining the variation of O. hupensis snail density was 39.8%, and the explanatory power of GAM increased to 79.0% following introduction of interaction terms. Conclusion Landscape separation index, edge density, shape index and other landscape pattern indicators pose significant impacts on the intensity and direction of changes in O. hupensis snail density in Yunnan Province.

This study identified 8 members including NjBIN2 of the GSK3 family in Nardostachys jatamansi by bioinformatics analysis. Moreover, the phylogenetic tree revealed that the GKS3 family members of N. jatamansi had a close relationship with those of Arabidopsis. RT-qPCR results showed that NjBIN2 presented a tissue-specific expression pattern with the highest expression in roots, suggesting that NjBIN2 played a role in root growth and development. In addition, the application of epibrassinolide or the brassinosteroid(BR) synthesis inhibitor(brassinazole) altered the expression pattern of NjBIN2 and influenced the photomorphogenesis(cotyledon opening) and root development of N. jatamansi, which provided direct evidence about the functions of NjBIN2. In conclusion, this study highlights the roles of BIN2 in regulating the growth and development of N. jatamansi by analyzing the expression pattern and biological function of NjBIN2. It not only enriches the understanding about the regulatory mechanism of the growth and development of N. jatamansi but also provides a theoretical basis and potential gene targets for molecular breeding of N. jatamansi with improved quality in the future.
Brassinosteroids/metabolism* ; Steroids, Heterocyclic/metabolism* ; Gene Expression Regulation, Plant/drug effects* ; Plant Proteins/metabolism* ; Phylogeny ; Nardostachys/metabolism* ; Plant Growth Regulators/pharmacology* ; Plant Roots/drug effects*

The chemical constituents were systematically separated from the roots of Berberis polyantha by various chromatographic methods, including silica gel column chromatography, HP20 column chromatography, polyamide column chromatography, reversed-phase C_(18) column chromatography, and preparative high-performance liquid chromatography. The structures of the compounds were identified by physicochemical properties and spectroscopic techniques(1D NMR, 2D NMR, UV, MS, and CD). Four phenylpropanoids were isolated from the methanol extract of the roots of B. polyantha, and they were identified as(2R)-1-(4-hydroxy-3,5-dimethoxyphenyl)-1-propanone-O-β-D-glucopyranoside(1), methyl 4-hydroxy-3,5-dimethoxybenzoate(2),(+)-syringaresinol(3), and syringaresinol-4-O-β-D-glucopyranoside(4). Compound 1 was a new compound, and other compounds were isolated from this plant for the first time. The anti-inflammatory activity of these compounds was evaluated based on the release of nitric oxide(NO) in the culture of lipopolysaccharide(LPS)-induced RAW264.7 macrophages. At a concentration of 10 μmol·L~(-1), all the four compounds inhibited the LPS-induced release of NO in RAW264.7 cells, demonstrating potential anti-inflammatory properties.
Plant Roots/chemistry* ; Animals ; Mice ; Berberis/chemistry* ; RAW 264.7 Cells ; Macrophages/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; Nitric Oxide/metabolism* ; Molecular Structure ; Anti-Inflammatory Agents/isolation & purification*

A high performance liquid chromatography-tandem mass spectrometry(HPLC-MS/MS) method was established for the simultaneous determination of 498 farm chemical residues in Atractylodis Macrocephalae Rhizoma. Furthermore, the established method was used to determine the residues in 30 batches of Atractylodis Macrocephalae Rhizoma samples from different habitats. The samples were extracted with acetonitrile containing 1% glacial acetic acid, and the extract was purified by dispersive solid-phase extraction with sorbents of magnesium sulfate, primary secondary amine(PSA), C_(18), silica gel, and graphitized carbon black(GCB). The prepared samples were then analyzed by HPLC-MS/MS, and the internal standard method was used to quantify the residues. The experimental results showed that the 498 farm chemicals presented good linear relationship within the range of 5-400 ng·mL~(-1), with correction coefficients greater than 0.990. Within the linear ranges, the recovery of 495 farm chemicals(except daimuron, chinomethionat, and emamectin benzoate) at three spiked levels(0.05, 0.10, and 0.20 mg·kg~(-1)) was in the range of 61.18%-132.1%, with the RSD of 0.24%-15%. A total of 16 farm chemicals were detected in 30 batches of samples. Among them, difenoconazole and tebuconazole showed higher detection rates, and the detection rate of difenoconazole was 76.7%. The residues of 4 batches of samples exceeded the limits of quantitation of 33 banned farm chemicals stipulated in the Chinese Pharmacopoeia. The theoretical maximum residue limits of the farm chemicals except banned farm cheimicals were used as the judgment standard of safety risks, under which the detected residues of clothianidin, difenoconazole, and pirimiphos-methyl exceeded the theoretical maximum residue limits. The new method established in this paper is simple and reliable, and it can thus be used for qualitative and quantitative analyses of farm chemical residues in Atractylodis Macrocephalae Rhizoma.
Tandem Mass Spectrometry/methods* ; Chromatography, High Pressure Liquid/methods* ; Atractylodes/chemistry* ; Rhizome/chemistry* ; Drugs, Chinese Herbal/analysis* ; Pesticide Residues/analysis* ; Liquid Chromatography-Mass Spectrometry

Qualitative and quantitative analysis methods for chemical components of different processed products of Corni Fructus were established to systematically characterize and identify these components, and the content of the main differential components was determined. The chemical components of different processed products of Corni Fructus were collected using ultra-high performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS). Through analysis of self-built databases, literature, and reference standards, a total of 93 components were obtained, including 19 iridoids, 15 flavonoids, 16 organic acids, eight triterpenoids, eight tannins, four amino acids, two polysaccharides, five olefins, and 16 other compounds. Additionally, by using multivariate statistical methods, the differential components between different processed products of Corni Fructus were screened under the conditions of VIP>1.0 and FC<0.5 or FC>2.0 and P<0.05. The PCA and OPLS-DA results showed differences in the chemical components between different processed products of Corni Fructus. A total of 21 differential components were screened, including tartaric acid, morroniside, and rutin. On this basis, ultra-high performance liquid chromatography-triple quadrupole tandem mass spectrometry(UPLC-QqQ-MS/MS) was used to determine the content of 10 main common differential components, including gallic acid, morroniside, ursolic acid, loganin, swertiamarin, rutin, 5-hydroxymethylfurfural, cornuside Ⅰ, quercetin, and oleanolic acid. The above 10 components showed a good linear relationship within the determined concentration range, with the precision, stability, repeatability, and sample recovery rate all meeting the requirements. Compared with that in Corni Fructus, the content of iridoid glycosides in wine-prepared Corni Fructus and wine-and honey-prepared Corni Fructus decreased, while the content of gallic acid, rutin, quercetin, 5-hydroxymethylfurfural, ursolic acid, and oleanolic acid increased. Compared with wine-prepared Corni Fructus, wine-and honey-prepared Corni Fructus showed varying degrees of increase in all other components, except for a slight decrease in gallic acid content. In summary, this study clarified the influence of different processing methods on the chemical components of Corni Fructus, providing a theoretical basis for the scientific connotation, overall quality evaluation, and clinically rational application of Corni Fructus processing in the future.
Tandem Mass Spectrometry/methods* ; Chromatography, High Pressure Liquid/methods* ; Cornus/chemistry* ; Drugs, Chinese Herbal/chemistry* ; Fruit/chemistry*

Syringa pinnatifolia, belonging to the family Oleaceae, is a species endemic to China. It is predominantly distributed in the Helan Mountains region of Inner Mongolia and Ningxia of China. The peeled roots, stems, and thick branches have been used as a distinctive Mongolian medicinal material known as "Shan-chen-xiang", which has effects such as suppressing "khii", clearing heat, and relieving pain and is employed for the treatment of cardiovascular and pulmonary diseases and joint pain. Over the past five years, significant increase was achieved in research on chemical constituents and pharmacological effects. There were a total of 130 new constituents reported, covering sesquiterpenoids, lignans, and alkaloids. Its effects of anti-myocardial ischemia, anti-cerebral ischemia/reperfusion, sedation, and analgesia were revealed, and the mechanisms of agarwood formation were also investigated. To better understand its medical value and potential of clinical application, this review updates the research progress in recent five years focusing on the chemical constituents and pharmacological effects of S. pinnatifolia, providing reference for subsequent research on active ingredient and support for its innovative application in modern medicine system.
Medicine, Mongolian Traditional ; Humans ; Drugs, Chinese Herbal/pharmacology* ; Animals ; Syringa/chemistry*

The traditional Chinese medicine(TCM) industry is a crucial part of China's pharmaceutical sector and plays a strategic role in ensuring public health and promoting economic and social development. In response to the practical demand for high-quality development of the TCM industry, this paper focused on the bottlenecks encountered during the digital and intelligent transformation of TCM production systems. Specifically, it explored technical strategies and methodologies for constructing the best TCM production mode. An innovative artificial intelligence(AI)-centered technical architecture for TCM production was proposed, focusing on key aspects of production management including process modeling, state evaluation, and decision optimization. Furthermore, a series of critical technologies were developed to realize the best TCM production mode. Finally, a novel AI-driven TCM production mode characterized by a closed-loop system of "measurement-modeling-decision-execution" was presented through engineering case studies. This study is expected to provide a technological pathway for developing new quality productive forces within the TCM industry.
Artificial Intelligence ; Drugs, Chinese Herbal ; Medicine, Chinese Traditional/methods* ; Humans

Melicope pteleifolia is a plant belonging to the Melicope genus of the Rutaceae family. Known for a bitter taste and cold nature, its stems and tender branches with leaves possess properties of clearing heat, detoxifying, dispelling wind, and removing dampness and can be used to treat sore throat, malaria, jaundice hepatitis, rheumatic bone pain, eczema, dermatitis, and sores and ulcers. In this study, 19 compounds were isolated from the chloroform and n-butanol extracts of M. pteleifolia leaves by using liquid chromatography-mass spectrometry(LC-MS) and proton nuclear magnetic resonance(~1H-NMR)-guided separation techniques. The compounds were identified as isoleptonol(1), leptaones B-E(2-5), friedelin(6), evodionol(7), ethyl p-hydroxybenzoate(8), litseachromolaevane A(9), quercetin-7,3',4'-trimethyl ether(10), kokusaginin(11), 8-(1-hydroxyethyl)-5,6,7-trimethoxy-2,2-dimethyl-2H-1-benzopyran(12), ethyl p-hydroxycinnamate(13), 3-hydroxy-9-methyl-6H-benzo\[c\]chromen-6-one(14), agrimonolide(15), 7-hydroxycoumarin(16), scopoletin(17), isoscutellarein(18), and agrimonolide 6-O-glucoside(19). Among these, the new compounds included one chromene and four meroterpenoid(1-5). The anti-inflammatory activities of the newly identified compounds 1-5 were screened in vitro, showing that the five compounds(1-5) exhibited inhibitory effects on nitric oxide(NO) production in BV2 cells induced by lipopolysaccharide(LPS)/interferon(IFN)-γ, with IC_(50) values ranging from 12.25 to 36.48 μmol·L~(-1).
Anti-Inflammatory Agents/isolation & purification* ; Mice ; Animals ; Rutaceae/chemistry* ; Drugs, Chinese Herbal/isolation & purification* ; Macrophages/immunology* ; Nitric Oxide/immunology*