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.

Owing to its inherent advantages—such as being non-destructive, rapid, highly molecule-specific, and minimally interfered with by moisture—Raman spectroscopy has been widely adopted in the fields of skin barrier function assessment, monitoring the transdermal penetration of active cosmetic ingredients, and the identification and quality control of cosmetic products. Despite these strengths, the practical application of this technique faces a significant bottleneck: the strong fluorescence background generated by endogenous skin components and exogenous cosmetic additives. Endogenous skin substances, such as structural proteins (e.g., collagen and elastin), metabolic coenzymes (e.g., nicotinamide adenine dinucleotide), and pigments (e.g., melanin), together with exogenous cosmetic constituents like organic colorants, chemical sunscreens, and fragrances, often possess strong absorption and emission characteristics. When excited by lasers, these components produce a fluorescence background that can be 10⁶ to 10⁸ times stronger than the Raman scattering signals, effectively masking the inherently weak vibrational fingerprint information. In recent years, driven by the rapid development of optoelectronic hardware and artificial intelligence algorithms, fluorescence suppression strategies have evolved from isolated, single-method approaches into comprehensive, multi-level synergistic systems. These systems are categorized into three distinct tiers: sample preparation, signal acquisition, and data processing. At the sample preparation level, techniques such as photobleaching and surface-enhanced Raman spectroscopy (SERS) are employed to eliminate or bypass the generation of fluorescence at the source. At the signal acquisition level, instrumental improvements—including the use of long-wavelength near-infrared excitation (typically 785 nm or 1 064 nm), confocal spatial filtering, and shifted excitation Raman difference spectroscopy (SERDS)— are utilized to physically isolate Raman signals from the fluorescence background. Furthermore, at the data processing level, numerical baseline correction methods such as polynomial fitting, penalized least squares (e.g., airPLS, arPLS), wavelet transform, and derivative algorithms are increasingly integrated into the analytical pipeline to extract Raman spectral features from mixed signals without increasing hardware costs or acquisition time. This review provides a systematic categorization and critical evaluation of these fluorescence suppression methods, detailing their underlying principles, technical advantages, and inherent limitations in diverse experimental setups. By focusing on critical application scenarios—including skin barrier assessment, percutaneous absorption monitoring, the routine quality control of cosmetics, and the emerging field of portable on-site detection—this paper explores the current state of technique selection and optimization. Finally, the article discusses future development trends, emphasizing the necessity of constructing adaptive, tiered suppression strategies, developing intelligent and automated data processing algorithms, and promoting the integration of portable, multi-modal diagnostic devices. The objective of this review is to provide a comprehensive technical reference to facilitate the transition of Raman spectroscopy from a specialized laboratory tool into a routine, robust analytical platform for advancements in skin science and cosmetic research.

BACKGROUND: This study aimed to investigate programmed death-ligand 1 tumor proportion score in predicting the safety and efficacy of PD-1/PD-L1 antibody-based therapy in treating patients with advanced non-small cell lung cancer (NSCLC) in a real-world setting. METHODS: This retrospective, multicenter, observational study enrolled adult patients who received PD-1/PD-L1 antibody-based therapy in China and met the following criteria: (1) had pathologically confirmed, unresectable stage III-IV NSCLC; (2) had a baseline PD-L1 tumor proportion score (TPS); and (3) had confirmed efficacy evaluation results after PD-1/PD-L1 treatment. Logistic regression, Kaplan-Meier analysis, and Cox regression were used to assess the progression-free survival (PFS), overall survival (OS), and immune-related adverse events (irAEs) as appropriate. RESULTS: A total of 409 patients, 65.0% ( n = 266) with a positive PD-L1 TPS (≥1%) and 32.8% ( n = 134) with PD-L1 TPS ≥50%, were included in this study. Cox regression confirmed that patients with a PD-L1 TPS ≥1% had significantly improved PFS (hazard ratio [HR] 0.747, 95% confidence interval [CI] 0.573-0.975, P = 0.032). A total of 160 (39.1%) patients experienced 206 irAEs, and 27 (6.6%) patients experienced 31 grade 3-5 irAEs. The organs most frequently associated with irAEs were the skin (52/409, 12.7%), thyroid (40/409, 9.8%), and lung (34/409, 8.3%). Multivariate logistic regression revealed that a PD-L1 TPS ≥1% (odds ratio [OR] 1.713, 95% CI 1.054-2.784, P = 0.030) was an independent risk factor for irAEs. Other risk factors for irAEs included pretreatment absolute lymphocyte count >2.5 × 10 9 /L (OR 3.772, 95% CI 1.377-10.329, P = 0.010) and pretreatment absolute eosinophil count >0.2 × 10 9 /L (OR 2.006, 95% CI 1.219-3.302, P = 0.006). Moreover, patients who developed irAEs demonstrated improved PFS (13.7 months vs. 8.4 months, P <0.001) and OS (28.0 months vs. 18.0 months, P = 0.007) compared with patients without irAEs. CONCLUSIONS A positive PD-L1 TPS (≥1%) was associated with improved PFS and an increased risk of irAEs in a real-world setting. The onset of irAEs was associated with improved PFS and OS in patients with advanced NSCLC receiving PD-1/PD-L1-based therapy.
Humans ; Carcinoma, Non-Small-Cell Lung/metabolism* ; Male ; Female ; Retrospective Studies ; Middle Aged ; Lung Neoplasms/metabolism* ; Aged ; B7-H1 Antigen/metabolism* ; Programmed Cell Death 1 Receptor/metabolism* ; Adult ; Aged, 80 and over ; Immune Checkpoint Inhibitors/therapeutic use*

In order to clarify the effects of drought stress training on the quality and drought resistance of Codonopsis pilosula, this study used PEG to simulate drought stress and employed potting with water control for the drought stress training of C. pilosula plants. The polysaccharide content, secondary metabolites, antioxidant system, and photosynthetic pigment system of C. pilosula after drought stress training were analyzed. The results showed that the content of fructans in the root of C. pilosula increased after two rounds of drought stress treatment, and it was significantly higher than that of the control group. The accumulation of fructans in the root of C. pilosula showed an upward trend during the rehydration treatment. The content of lobetyolin and tangshenoside Ⅰ increased after drought stress treatment compared with that of the control group. The rehydration treatment caused first increasing and then decreasing in the content of lobetyolin, while it had no significant effect on the tangshenoside Ⅰcontent. The content of photosynthetic pigments decreased after drought stress treatment, and it gradually increased during the first round of rehydration and the second round of rehydration. Moreover, the increase was faster in the second round of rehydration than in the first round of rehydration. The content of the peroxidation product malondialdehyde(MDA) and the activities of superoxide dismutase(SOD), peroxidase(POD), and catalase(CAT) increased after drought stress treatment compared with those of the control group, and they showed a tendency of decreasing during rehydration. Moreover, the decrease was faster in the second round of rehydration than in the first round of rehydration. When the plants of C. pilosula after drought stress training were again subjected to severe drought stress, the wilting rate decreased significantly, and the biomass increases significantly. This study showed that the drought stress training could promote the accumulation of polysaccharides and secondary metabolites in the root of C. pilosula. When encountering drought stress again, C. pilosula plants could quickly regulate the antioxidant system and delay the decomposition of chlorophyll to respond to drought stress. The findings provide a theoretical basis for the ecological cultivation of C. pilosula in arid and semi-arid areas.
Codonopsis/growth & development* ; Droughts ; Polysaccharides/metabolism* ; Stress, Physiological ; Water/metabolism* ; Antioxidants/metabolism* ; Photosynthesis ; Drought Resistance

Guided by the concept of quality by design(QbD), this study optimizes the calcination and quenching process of calcined Magnetitum and establishes the XRD characteristic spectra of calcined Magnetitum, providing a scientific basis for the formulation of quality standards. Based on the processing methods and quality requirements of Magnetitum in the Chinese Pharmacopoeia, the critical process parameters(CPPs) identified were calcination temperature, calcination time, particle size, laying thickness, and the number of vinegar quenching cycles. The critical quality attributes(CQAs) included Fe mass fraction, Fe~(2+) dissolution, and surface color. The weight coefficients were determined by combining Analytic Hierarchy Process(AHP) and the criteria importance though intercrieria correlation(CRITIC) method, and the calcination process was optimized using orthogonal experimentation. Surface color was selected as a CQA, and based on the principle of color value, the surface color of calcined Magnetitum was objectively quantified. The vinegar quenching process was then optimized to determine the best processing conditions. X-ray diffraction(XRD) was used to establish the characteristic spectra of calcined Magnetitum, and methods such as similarity evaluation, cluster analysis, and orthogonal partial least squares-discriminant analysis(OPLS-DA) were used to evaluate the quality of the spectra. The optimized calcined Magnetitum preparation process was found to be calcination at 750 ℃ for 1 h, with a laying thickness of 4 cm, a particle size of 0.4-0.8 cm, and one vinegar quenching cycle(Magnetitum-vinegar ratio 10∶3), which was stable and feasible. The XRD characteristic spectra analysis method, featuring 9 common peaks as fingerprint information, was established. The average correlation coefficient ranged from 0.839 5-0.988 1, and the average angle cosine ranged from 0.914 4 to 0.995 6, indicating good similarity. Cluster analysis results showed that Magnetitum and calcined Magnetitum could be grouped together, with similar compositions. OPLS-DA discriminant analysis identified three key characteristic peaks, with Fe_2O_3 being the distinguishing component between the two. The final optimized processing method is stable and feasible, and the XRD characteristic spectra of calcined Magnetitum was initially established, providing a reference for subsequent quality control and the formulation of quality standards for calcined Magnetitum.
X-Ray Diffraction/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Particle Size

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

As a new type of production factor that can empower the development of new quality productivity, the data element is an important engine to promote the high quality development of the industry. Traditional Chinese medicine(TCM) dispensing is the most basic work of TCM clinical pharmacy, and its quality directly affects the clinical efficacy of TCM. The integration of data elements and TCM dispensing can stimulate the innovation and vitality of the TCM dispensing industry and promote the high-quality and sustainable development of the industry. A large-scale, detailed, and systematic study on TCM dispensing was conducted. The innovative practice path of data fusion construction in the whole process of TCM dispensing was investigated by integrating the digital resources "nine full activities" of TCM dispensing, creating the digital dictionary of "TCM clinical information data elements", and exploring innovative applications of TCM dispensing driven by data and technology, so as to promote the standardized, digital, and intelligent development of TCM dispensing in medical health services. The research content of this project was successfully selected as the second batch of "Data element×" typical cases of National Data Administration in 2024, which is the only selected case in the field of TCM.
Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal ; Humans

This study aims to explore the scientific connotation of sinking Rehmanniae Radix has the best quality and compare the quality between floating and sinking fresh Rehmanniae Radix samples. Ultra-performance liquid chromatography tandem quadrupole electrostatic field Orbitrap high-resolution mass spectrometry(UHPLC-Q-Orbitrap HRMS) was employed to detect the chemical components in floating and sinking fresh Rehmanniae Radix samples. The fingerprint of fresh Rehmanniae Radix was established by high performance liquid chromatography(HPLC), and four index components were determined simultaneously. The cluster analysis, principal component analysis(PCA), and orthogonal partial least squares-discriminant analysis(OPLS-DA) were conducted to compare the quality of floating and sinking fresh Rehmanniae Radix samples. An evaporative light-scattering detector was used to compare the content of five sugars. The extract yield and drying rate were determined, and the quality connotation of sinking Rehmanniae Radix has the best quality was explained by multiple indicators. A total of 41 components were preliminarily identified from fresh Rehmanniae Radix by UHPLC-Q-Orbitrap HRMS, including 7 iridoid glycosides, 9 phenylethanol glycosides, 6 amino acids, 4 sugars, 3 phenolic acids, 5 nucleosides, 3 organic acids, 1 ionone, 1 furan, 1 coumarin, and 1 phenylpropanoid. The results showed that the main chemical components were consistent between floating and sinking fresh Rehmanniae Radix. Nine common peaks were identified in the fingerprints of 15 batches of floating and sinking fresh Rehmanniae Radix samples, and the similarity of fingerprints was greater than 0.9. The cluster analysis, PCA, and OPLS-DA classified floating and sinking fresh Rehmanniae Radix sasmples into two categories, indicating differences in the quality between them. The total content of catalpol, rehmannioside D, ajugol, and verbascoside in sinking fresh Rehmanniae Radix samples was higher than that in floating samples of the same batch and specification, and the main differential component was catalpol. The total content of fructose, glucose, sucrose, raffinose, and stachyose in sinking fresh Rehmanniae Radix samples was higher than that in floating samples of the same batch and specification, and the main differential component was stachyose. The extract yield and drying rate of the sinking samples were higher than those of floating samples. This study preliminarily showed that floating and sinking fresh Rehmanniae Radix samples had the same components but great differences in the content of medicinal substance basis. The total content of four glycosides and five sugars, extract yield, and drying rate of sinking fresh Rehmanniae Radix samples is higher than that of floating samples of the same batch and specification. These findings, to a certain extent, explains the scientificity of sinking Rehmanniae Radix has the best quality recorded in ancient books and provide a reference for the quality control and clinical application of fresh Rehmanniae Radix.
Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Rehmannia/chemistry* ; Chemometrics ; Mass Spectrometry/methods* ; Quality Control ; Principal Component Analysis ; Plant Extracts

This study aims to explore the effects and action mechanisms of the active ingredients in Buyang Huanwu Decoction(BYHWD), namely tetramethylpyrazine(TMP) and hydroxy-safflor yellow A(HSYA), on oxygen-glucose deprivation/reglucose-reoxygenation(OGD/R)-induced inflammation and oxidative stress of microglia(MG). Network pharmacology was used to screen the effective monomer ingredients of BYHWD and determine the safe concentration range for each component. Inflammation and oxidative stress models were established to further screen the best ingredient combination and optimal concentration ratio with the most effective anti-inflammatory and antioxidant effects. OGD/R BV2 cell models were constructed, and BV2 cells in the logarithmic growth phase were divided into a normal group, a model group, an HSYA group, a TMP group, and an HSYA + TMP group. Enzyme-linked immunosorbent assay(ELISA) was used to detect the levels of inflammatory cytokines such as interleukin-1β(IL-1β), tumor necrosis factor-α(TNF-α), and interleukin-6(IL-6). Oxidative stress markers, including superoxide dismutase(SOD), nitric oxide(NO), and malondialdehyde(MDA), were also measured. Western blot was used to analyze the protein expression of both inflammation-related pathway [Toll-like receptor 4(TLR4)/nuclear factor-kappa B(NF-κB)] and oxidative stress-related pathway [nuclear factor erythroid 2-related factor 2(Nrf2)/heme oxygenase-1(HO-1)]. Immunofluorescence was used to assess the expression of proteins such as inducible nitric oxide synthase(iNOS) and arginase-1(Arg-1). The most effective ingredients for anti-inflammatory and antioxidant effects in BYHWD were TMP and HSYA. Compared to the normal group, the model group showed significantly increased levels of IL-1β, TNF-α, IL-6, NO, and MDA, along with significantly higher protein expression of NF-κB, TLR4, Nrf2, and HO-1 and significantly lower SOD levels. The differences between the two groups were statistically significant. Compared to the model group, both the HSYA group and the TMP group showed significantly reduced levels of IL-1β, TNF-α, IL-6, NO, and MDA, lower expression of NF-κB and TLR4 proteins, higher levels of SOD, and significantly increased protein expression of Nrf2 and HO-1. Additionally, the expression of the M1-type MG marker iNOS was significantly reduced, while the expression of the M2-type MG marker Arg-1 was significantly increased. The results of the HSYA group and the TMP group had statistically significant differences from those of the model group. Compared to the HSYA group and the TMP group, the HSYA + TMP group showed further significant reductions in IL-1β, TNF-α, IL-6, NO, and MDA levels, along with significant reductions in NF-κB and TLR4 protein expression, an increase in SOD levels, and elevated Nrf2 and HO-1 protein expression. Additionally, the expression of the M1-type MG marker iNOS was reduced, while the M2-type MG marker Arg-1 expression increased significantly in the HSYA + TMP group compared to the TMP or HSYA group. The differences in the results were statistically significant between the HSYA + TMP group and the TMP or HSYA group. The findings indicated that the combined use of HSYA and TMP, the active ingredients of BYHWD, can effectively inhibit OGD/R-induced inflammation and oxidative stress of MG, showing superior effects compared to the individual use of either component.
Oxidative Stress/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Animals ; Mice ; Glucose/metabolism* ; Cell Line ; Inflammation/genetics* ; Oxygen/metabolism* ; Pyrazines/pharmacology* ; Microglia/metabolism* ; NF-E2-Related Factor 2/immunology* ; NF-kappa B/immunology* ; Toll-Like Receptor 4/immunology* ; Anti-Inflammatory Agents/pharmacology* ; Humans

The quality of drugs is a crucial premise for ensuring the safety and effectiveness of clinical medication, while quality control during the pharmaceutical process directly affects the quality and consistency of the final product formulation. However, there is a lack of a comprehensive and scientific system for assessing and optimizing the quality control level during the manufacturing process in the field of drug quality control. Therefore, this study proposed the concept of "pharmaceutical process omics", clarified its advantages in guiding drug production, and explored in depth the research approaches, diverse analytical techniques, and broad range of applications in drug quality control. In addition, this study anticipated the broad application prospects of pharmaceutical process omics in the field of drug quality control, aiming to provide a scientific basis for the development of pharmaceutical process quality control standards.
Quality Control ; Humans ; Drugs, Chinese Herbal/chemistry*