Objective: To explore the characteristics and policy tools of cell and gene therapy industry policies in China's three major urban agglomerations and to comprehensively improve the development of China's cell and gene therapy industry policies. Methods: Based on the content analysis method, a quantitative text analysis of 88 cell and gene therapy industry-related policies issued by the relevant departments of the three major urban agglomerations was conducted from the dimensions of policy tools and policy themes by constructing a policy tool framework. Results: In terms of the use of policy tools, supply-type>environment-type>demand-type. In terms of policy themes, “industry” and “development” appear most frequently in the word clouds of the policy texts of the three major city clusters, indicating that the three major urban agglomerations have  clear objectives and plans to promote the development of the cell and gene therapy industry. Conclusion: It is recommended that China balance the use of cell and gene therpy industrial policy tools, increase the proportion of demand-type and environment-type policy tools, emphasize the concept of risk supervision, accelerate the application transformation and industrialization of cell and gene therapy, improve the construction and top-level design of cell and gene therapy industry policies, and promote multi-faceted coordinated development.

Objective: Given that traditional patent value evaluation methods are easily influenced by subjective factors and struggle to comprehensively and objectively reflect the value of patents, this study proposed a patent value evaluation method to identify high-value patents. Methods: This study employs information gain and variance analysis methods to perform feature selection on patent data from medical universities, optimizing input features and reducing redundant information. In terms of model construction, a three-layer BP neural network structure was designed, incorporating ReLU activation functions and Dropout techniques to mitigate overfitting issues and enhance the model's ability to handle nonlinear relationships, thereby improving the model's stability and generalization. Results: The experimental results showed that the model achieved a prediction accuracy of 96%. Feature selection effectively improved the model's performance to a certain extent, demonstrating good results across multiple evaluation metrics and verifying the feasibility of the proposed method. Conclusion: This study provides a feasible and effective practical method for patent value evaluation in medical universities, offering valuable reference and application significance, particularly in the identification and prediction of high-value patents.

Drug development is a complex and time-consuming process, and traditional drug research models have obvious limitations, and there is an urgent need to establish a new model system. Organoids are three-dimensional tissue analogues derived from stem cells that have attracted attention for their excellent physiological relevance. Organoid technology has shown great application potential in the fields of disease modeling, drug screening, toxicity testing, and personalized medicine, and can also be combined with organ-on-a-chip technologies to provide a new platform for the construction of complex physiological correlation models and the study of multi-organ interactions. This article reviews the development history of organoid technology and the progress in its research and application in drug development, discusses the challenges and development directions, to provide references for the key process of drug development and help promote the application and development of organoid technology in drug research and development.

Polycystic kidney disease (PKD) is a common hereditary renal disorder characterized by abnormal proliferation and dilation of renal tubular cysts, which can eventually lead to renal failure. Currently, drug screening plays a pivotal role in PKD therapeutic research, but traditional cell and animal models exhibit significant limitations in mimicking disease complexity and screening efficiency, failing to meet clinical needs. In recent years, organoid models, as innovative in vitro research tools, have demonstrated unique advantages and enormous application potential by precisely simulating the three-dimensional structure, pathological features, and patient-specific characteristics of PKD. This article systematically reviewed the research status of PKD drug screening models, covering the construction and application of cell models, animal models, organoid models, and cutting-edge technologies such as organ-on-a-chip. Through typical case analyses and multi-model comparisons, the characteristics of different models were analyzed in-depth, and the core value of organoid models in high-throughput drug screening, precision medicine practice, and personalized therapy exploration was explicitly highlighted. Studies have confirmed that organoid models can effectively compensate for the shortcomings of traditional models, holding promise as key tools to drive breakthroughs in PKD therapeutic research and opening new pathways for clinical translation. Meanwhile, this article scientifically prospects the future development directions of organoid models in the field of PKD research, aiming to provide references and inspiration for follow-up studies.

Antibody-dependent enhancement (ADE) refers to the phenomenon where certain non-neutralizing antibodies or sub-neutralizing concentrations of antibodies do not eliminate viruses during viral infection but instead promote viral invasion and replication. In human immunodeficiency virus (HIV) infection, it has been found that some antibodies can form immune complexes with the virus and mediate viral entry into target cells through Fc receptors (FcR) or the complement system, thereby exacerbating disease progression. In recent years, with the in-depth study of HIV infection, the ADE phenomenon has received extensive attention in the development and clinical application of HIV vaccines. This article reviewed the mechanism of ADE in HIV infection, the influencing factors of ADE occurrence, and the implications of ADE for drug development, and explored the impact and potential risks of ADE in HIV infection in depth, providing theoretical support for the development of safe and effective HIV vaccines and antibody drugs.

Objective: To systematically elucidate the pivotal role of computational pharmaceutics in unveiling the structure-function relationships of nanodiamond (ND), addressing the challenges posed by their microscopic complexity in experimental research. Methods: This review focused on multi-scale computational approaches, including molecular dynamics (MD) simulation, density functional theory (DFT), and machine learning, summarizing their application strategies and progress in ND research. Results: Computational simulations successfully revealed the pH-responsive drug release mechanisms governed by ND surface modifications, the influence of shape and charge on transmembrane behavior, and the optical stability of vacancy centers (e.g., NV/SiV). The simulation results showed strong agreement with experimental observations and provided atomic-scale insights into ND dispersion properties and interfacial interactions. Conclusion: Computational pharmaceutics serves as a core driver for the rational design and application development of ND. Advancing high-precision machine learning potentials and deep multi-scale coupling will accelerate innovative applications of ND in cutting-edge fields such as precision medicine and biosensing.

The incidence and mortality rate of non-small cell lung cancer (NSCLC) rank among the highest among malignant tumors globally. Currently, the management of NSCLC patients poses significant challenges in clinical practice, characterized by high postoperative complication mortality rates and substantial side effects from drug therapy. In recent years, nanomedicine approaches have emerged by providing efficient nano-drug delivery systems that precisely deliver anticancer drugs to cancer cells, overcoming the limitations of traditional chemotherapy to enhance NSCLC treatment efficacy. Furthermore, traditional Chinese medicine (TCM) demonstrates remarkable advantages in the prevention and treatment of NSCLC. Various TCM monomers, active components, and compound formulations enhance immunity, improve quality of life, and reduce NSCLC metastasis risk through multi-component, multi-target, and multi-pathway mechanisms. However, they face challenges such as poor water solubility, low bioavailability, and insufficient targeting specificity. Nano-delivery systems address these issues by enhancing the bioavailability and solubility of active TCM components while enabling precise targeting of cancer cells for efficient and accurate NSCLC treatment. Therefore, this article reviews the research progress in the synergistic treatment of NSCLC using TCM-nano strategies based on nano-delivery systems, while exploring their application prospects, aiming to develop new methods and approaches for NSCLC therapy.

Objective: To provide a reference for the compliance management of sample testing cooperation between pharmaceutical companies and third-party testing institutions in drug clinical trials. Methods: Based on the actual practice of sample testing cooperation in drug clinical trials, this paper analyzes the core points and potential risks in the cooperation from the perspectives of cooperation key points and risk prevention and control, and proposes targeted prevention and control strategies. Results: Overall, non-compliant behaviors in the cooperation may expose both parties to civil liability, administrative liability, or even criminal liability. From the perspective of cooperation practice, pharmaceutical companies and third-party testing institutions generally face problems such as vague definitions of service content, unclear division of rights and obligations, and insufficient quality control. From the perspective of the industry environment, drug clinical trials regulation is becoming increasingly stringent, with continuously rising requirements for the standardization of sample testing and data authenticity. Conclusion: In sample testing cooperation between pharmaceutical companies and third-party testing institutions, both parties should clarify the key points of cooperation, including refining the scope of services, standardizing expense settlement, defining the ownership of technological achievements, fulfilling confidentiality obligations, establishing a communication mechanism and adopting standardized entrustment agreements. They should also strengthen their awareness of risk prevention and control and improve their compliance management systems. At the same time, targeted prevention and control measures should be constructed against risks such as approval deficiencies, subcontracting, quality control failures, expense disputes, and intellectual property infringement, so as to ensure the quality of clinical trial data and the safety of subjects, safeguard the legitimate rights and interests of both parties, and promote the stable and orderly development of cooperation.

Objective: To prepare a borneol-low molecular organic gelator xerogel and evaluate its effect on borneol volatility. Methods: 4-Hydroxybenzaldehyde was used as the starting material, and the target low molecular organic gelator was synthesized through Williamson etherification reaction and condensation reaction. The gel was prepared by dissolving borneol and low molecular organic gelator in anhydrous ethanol and subsequently undergoing vacuum freeze-drying to remove the solvent, resulting in the borneol-low molecular organic gelator xerogel. The microscopic morphology of the xerogel was observed by scanning electron microscope (SEM). The phase transition temperature was determined by differential scanning calorimeter (DSC). The driving force for the gel formation was analyzed by Fourier transform infrared spectroscopy (FT-IR). The loss of borneol from borneol sample, borneol-low molecular organic gelator xerogel, and the borneol-low molecular organic gelator-glycerol xerogel were compared by accelerated evaporation experiment over 10 h. Results: Mixtures of borneol and low molecular organic gelator with mass ratios of 2∶1, 3∶1 and 4∶1 formed a gel in anhydrous ethanol. SEM imaging revealed that the low molecular organic gelator showed a multilayered sheet-like structure. In contrast, the microstructures of the borneol-low molecular organic gelator xerogel with mass ratios of 2∶1, 3∶1 and 4∶1 showed a bulk, sheet-like and reticulate structure, respectively, which proved that the assemblies were formed. Furthermore, the addition of glycerol to the borneol-low molecular organic gelator system did not significantly alter the microstructure of the resulting xerogel. DSC analysis showed that the heat absorption peaks of the borneol-low molecular organic gelator xerogel varied with the mass ratios. FT-IR analysis revealed a shift in the hydroxyl group stretching vibration to lower wavenumbers for both borneol-low molecular organic gelator xerogel and borneol-low molecular organic gelator-glycerol xerogel, confirming that hydrogen bonding was involved in the formation of gel. After the 5 h accelerated volatilization test at 50 ℃, the borneol loss rate was 39.34% from borneol sample, while it was 17.40% from the 4∶1 borneol-low molecular organic gelator xerogel, and 9.98% after glycerol was added. Conclusion: The borneol-low molecular organic gelator xerogel reduces the volatility of borneol, with a further reduction observed upon the addition of glycerol.

Objective: To establish the HPLC fingerprinting and quantitative method of eight characteristic components in water-decocted extract of Angelicae Dahuricae Radix, and investigate the similarities of 14 batches of Angelicae Dahuricae Radix samples. Methods: SinoChrom ODS-BP column（250 mm×4.6 mm，5 μm）was used for the fingerprinting and quantitative assay. The mobile phase was 0.025% phosphoric acid-acetonitrile under gradient elution mode. The column temperature was 35 ℃, the detection wavelength was 220 nm, the flow rates were 1.0 mL·min^－1 for fingerprinting and 1.2 mL·min^－1 for quantitative assay, respectively. Results: In the HPLC fingerprinting, there were 29 common peaks in 14 batches of Angelicae Dahuricae Radix, and eight characteristic components were identified (xanthotol, 5-hydroxy-8-methoxypsoralen, oxypeucedanin hydrate, byakangelicin, xanthotoxin, bergapten, isoimpinellin, imperatorin, and phellopterin). The fingerprints of the 14 batches of Angelicae Dahuricae Radix were similar and the similarities were greater than 0.980. The linear ranges of xanthotoxol, 5-hydroxy-8-methoxypsoralen, oxypeucedanin hydrate, byakangelicin, xanthotoxin, bergapten, imperatorin, and phellopterin were 3.24~162.00, 2.86~143.00, 3.10~155.00, 2.98~149.00, 3.12~156.00, 3.02~151.0, 3.16~158.00, and 2.30~115.00 μg·mg^－1, respectively. The content ranges of xanthotoxol, 5-hydroxy-8-methoxypsoralen, oxypeucedanin hydrate, byakangelicin, xanthotoxin, bergapten, imperatorin, and phellopterin were 0.14~0.37, 0.26~0.39, 2.31~3.48, 1.09~2.22, 0.04~0.26, 0.19~0.34, 0.03~0.14, and 0.11~0.23 μg·mg^－1, respectively for the 14 batches of Angelicae Dahuricae Radix. Conclusion: The established methods of HPLC fingerprinting and quantitative analysis are reproducible, reliable, and stabile. In the future, these methods can be used for the quality control of original, processed materials and products of Angelicae Dahuricae Radix.

Objective: To investigate the pharmacological basis and potential mechanism of Chuanbei Qingfei Syrup in the treatment of viral pneumonia based on UPLC-Q-Exactive Orbitrap-HRMS and network pharmacology. Methods: UPLC-Q-Exactive Orbitrap-HRMS was employed for qualitative characterization of the chemical constituents of Chuanbei Qingfei Syrup. Active compounds and their corresponding targets were identified using the TCMSP and BATMAN-TCM databases, while viral-pneumonia-related targets were retrieved from GeneCards and OMIM. The intersection of the two target sets was obtained with Venny 2.1.0. Protein-protein interaction networks were constructed via the STRING 11.0 database and visualized in Cytoscape. Finally, GO functional annotation and KEGG pathway enrichment analysis of the common targets were performed using the DAVID database. Results: A total of 256 constituents were identified in Chuanbei Qingfei Syrup. Network pharmacology revealed 113 targets overlapping with viral pneumonia, including 35 hub genes such as TNF, IL-6, IL-1β, and STAT3. GO enrichment indicated that the syrup modulates viral pneumonia mainly through biological processes related to gene expression, apoptosis, and inflammatory response. KEGG analysis further showed that the principal signaling pathways involved include AGE-RAGE, TNF, and IL-17 signaling. Conclusion: Chuanbei Qingfei Syrup exerts therapeutic effects against viral pneumonia via multi-component, multi-target, and multi-pathway mechanisms. The putative active compounds are flavonoids, saccharides and glycosides, terpenoids, and phenylpropanoids, which act on targets such as TNF, AKT1, and IL-6 and regulate the TNF and IL-17 signaling pathways.

Objective: To systematically evaluate the efficacy and safety of injectable non-steroidal anti-inflammatory drugs (NSAIDs) for postoperative analgesia. Methods: A comprehensive literature search was conducted across databases including CNKI, WanFang, VIP, SinoMed, PubMed, Embase, Web of Science, and the Cochrane Library, supplemented by clinical trial registries, from inception to September 2025. The Cochrane Risk of Bias tool was utilized to assess the methodological quality of the included studies. Data synthesis and Meta-analysis were performed using RevMan 5.4 and Stata software. Results: A total of 58 studies involving nine injectable NSAIDs were included. Compared with placebo, all evaluated NSAIDs significantly reduced cumulative opioid consumption at 24 hours postoperatively (all P＜0.05). Notably, binaprofen exhibited the most substantial opioid-sparing effect (pooled reduction rate: 36.8%, 95% CI: 32.0% to 40.0%). Furthermore, binaprofen significantly decreased the requirement for patient-controlled analgesia (PCA) rescue [RR=0.42, 95%CI(0.30, 0.58), P＜0.001] and the number of effective PCA demands at 24 h. Regarding analgesic efficacy, both parecoxib and ibuprofen significantly lowered pain scores at 24 h postoperatively (both P＜0.001). In terms of safety, parecoxib significantly reduced the risk of overall adverse events [RR=0.61, 95%CI (0.51, 0.73)] and gastrointestinal events [RR=0.67, 95%CI (0.54, 0.85)]. Binaprofen also demonstrated a favorable safety profile. Conclusion: Injectable NSAIDs effectively alleviate postoperative pain and exert a significant opioid-sparing effect, with parecoxib and binaprofen demonstrating favorable safety profiles. Future well-designed studies should focus on the dose-response relationship and long-term safety in specific patient populations.

Objective: To systematically evaluate the efficacy and safety of different combination regimens based on immune checkpoint inhibitors (ICI) as first-line treatment for advanced or metastatic renal cell carcinoma (RCC), and provide evidence for clinical treatment selection. Methods: A comprehensive search of electronic databases was conducted, including PubMed, The Cochrane Library, Embase, Web of Science, CNKI, and Wanfang Data from inception until January 30, 2025, for relevant randomized controlled trial (RCT). After literature screening, data extraction, and risk of bias assessment for the included studies were performed independently by two investigators, a network Meta-analysis was performed using R software version 4.5.0. Results: A total of seven RCT involving eight treatment interventions were included. Network Meta-analysis results showed that for overall survival (OS), a statistically significant difference was observed only between atezolizumab plus bevacizumab and nivolumab plus ipilimumab, with no significant differences detected among other regimen comparisons. Cumulative ranking probabilities indicated that toripalimab plus axitinib had the highest probability of being the most effective regimen for OS. Regarding progression-free survival (PFS), lenvatinib plus pembrolizumab was identified as the most effective intervention. It demonstrated a statistically significant reduction in the risk of disease progression compared to several other regimens, including atezolizumab plus bevacizumab, avelumab plus axitinib, nivolumab plus ipilimumab, and pembrolizumab plus axitinib. For objective response rate (ORR), nivolumab plus cabozantinib and lenvatinib plus pembrolizumab were associated with higher ORR, with both showing significant superiority to regimens such as pembrolizumab plus axitinib. In terms of safety, the incidence of grade ≥3 treatment-related adverse events (TRAE) was significantly lower with nivolumab plus ipilimumab and atezolizumab plus bevacizumab compared to the other combination regimens. However, no statistically significant difference in TRAE was found between them. Conclusion: In the first-line treatment of advanced or metastatic RCC, ICI combination regimens generally demonstrated superior efficacy compared to sunitinib. No statistically significant differences in OS were observed for most comparisons between the combination regimens. However, statistically significant differences were detected among specific regimens in terms of PFS, ORR, and TRAE. Their relative rankings need further confirmation through more head-to-head studies in the future.