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Geological complexities along mountain highways frequently trigger landslides, posing significant threats to transportation safety and infrastructure. This study evaluates landslide susceptibility along the Lizha-Jiezi section of China’s G345 national highway using Random Forest (RF) and Support Vector Machine (SVM) models. Eleven conditioning factors including altitude, slope, aspect, plan curvature, profile curvature, lithology, distance to fault, rainfall, distance to river, normalized difference vegetation index (NDVI), and distance to road were analyzed using remote sensing and field surveys. A landslide inventory of 67 events was divided into training (70%) and validation (30%) datasets, with non-landslide samples selected at least 100 m away from landslide locations to minimize spatial overlap. Factor contribution analysis identified distance to road as the most significant predictor, highlighting anthropogenic impacts on slope destabilization. Model validation via receiver operating characteristic (ROC) curves demonstrated RF’s superior performance (AUC = 0.887) over SVM (AUC = 0.735). The RF-derived susceptibility map classified five risk levels, revealing high-risk zones concentrated within 200 m of roads, consistent with field observations. Results emphasize the necessity of integrating anthropogenic factors into landslide risk management for mountainous infrastructure. This study provides actionable insights for mitigation strategies and land-use planning, offering a scalable framework adaptable to similar regions.

Objective: We aimed to evaluate alirocumab- and evolocumab-related adverse events (AEs) in real-world compared with all other drugs, overall and by gender and age subgroups; we also aimed to compare their risks of cognitive impairment, musculoskeletal disorders and diabetes with various statins and ezetimibe. Methods: We retrospectively extracted AE reports from the FDA Adverse Event Reporting System (FAERS) database during July 2015-June 2021. Disproportionality analyses were performed using reporting odds ratios (RORs) to detect AE signals of alirocumab and evolocumab in the overall population and in different age and gender subgroups, respectively. Results: Compared with all other drugs, both alirocumab and evolocumab had a significant signal in “musculoskeletal and connective tissue disorders” (ROR 1 = 2.626, 95% CI 2.552–2.702; ROR2 = 2.575, 95% CI 2.538–2.613). The highest ROR value of 2.311 (95% CI 2.272–2.351) was for “injury, poisoning and procedural complications” and was found in patients aged ≥65 years on evolocumab. The most frequent AEs were “general disorders and administration site conditions” and “musculoskeletal and connective tissue disorders” for all subpopulations. At the preferred term level, the most frequent AE signal was myalgia for alirocumab and injection site pain for evolocumab, overall and by subgroups. Compared with statins/ezetimibe, PCSK9 inhibitors exhibited lower ROR values for adverse events associated with SOC “nervous system disorders”, “psychiatric disorders” and “metabolism and nutrition disorders” (all RORs < 1), but mixed results for musculoskeletal disorders. Compared with all other drugs, undocumented AEs, such as acute cardiac event (ROR = 30.0, 95% CI 9.4–95.3) and xanthoma (ROR = 9.3, 95% CI 3.4–25.5), were also reported. Conclusion: Real-world evidence showed that PCSK9 inhibitors were associated with an increased risk of musculoskeletal and connective tissue disorders and general disorders and administration site conditions, overall and by subgroups. Muscle toxicity, injection site reactions, and influenza-like illness were significant AE signals. Compared with various statins and ezetimibe, PCSK9 inhibitors have shown a favorable safety profile in muscle-related events, cognitive impairment and diabetes. Some undocumented AE signals were also reported. Due to the limitations of spontaneous reporting databases, further studies are still needed to establish causality and validate our results.

Landslides are a major geological hazard worldwide. Landslide susceptibility assessments are useful to mitigate human casualties, loss of property, and damage to natural resources, ecosystems, and infrastructures. This study aims to evaluate landslide susceptibility using a novel hybrid intelligence approach with the rotation forest-based credal decision tree (RF-CDT) classifier. First, 152 landslide locations and 15 landslide conditioning factors were collected from the study area. Then, these conditioning factors were assigned values using an entropy method and subsequently optimized using correlation attribute evaluation (CAE). Finally, the performance of the proposed hybrid model was validated using the receiver operating characteristic (ROC) curve and compared with two well-known ensemble models, bagging (bag-CDT) and MultiBoostAB (MB-CDT). Results show that the proposed RF-CDT model had better performance than the single CDT model and hybrid bag-CDT and MB-CDT models. The findings in the present study overall confirm that a combination of the meta model with a decision tree classifier could enhance the prediction power of the single landslide model. The resulting susceptibility maps could be effective for enforcement of land management regulations to reduce landslide hazards in the study area and other similar areas in the world.

Natural medicine has been widely used for clinical treatment and health care in many countries and regions. Additionally, extracting active ingredients from traditional Chinese medicine and other natural plants, defining their chemical structure and pharmacological effects, and screening potential druggable candidates are also uprising directions in new drug research and development. Physiologically based pharmacokinetic (PBPK) modeling is a mathematical modeling technique that simulates the absorption, distribution, metabolism, and elimination of drugs in various tissues and organs in vivo based on physiological and anatomical characteristics and physicochemical properties. PBPK modeling in drug research and development has gradually been recognized by regulatory authorities in recent years, including the U.S. Food and Drug Administration. This review summarizes the general situation and shortcomings of the current research on the pharmacokinetics of natural medicine and introduces the concept and the advantages of the PBPK model in the study of pharmacokinetics of natural medicine. Finally, the pharmacokinetic studies of natural medicine using the PBPK models are summed up, followed by discussions on the applications of PBPK modeling to the enzyme-mediated pharmacokinetic changes, special populations, new drug research and development, and new indication adding for natural medicine. This paper aims to provide a novel strategy for the preclinical research and clinical use of natural medicine.

To evaluate the cost-utility of different dosing regimens of PCSK9 inhibitors, added to statin therapy, in patients with hypercholesterolemia or at high cardiovascular risk in China. A Markov cohort multistate-transition model was developed from the perspective of the Chinese healthcare system, with a 1-year cycle and lifetime horizon. Treatment effects were derived from a network meta-analysis. Costs, utilities, and mortality data were obtained from published literature and national databases. Both costs and outcomes were discounted at a rate of 5% annually. The primary outcome was the incremental cost-utility ratio (ICUR). The willingness-to-pay (WTP) threshold was set at 1-3 times China's 2024 gross domestic product. One-way, probabilistic, and scenario sensitivity analyses were performed to test model robustness. In the base-case analysis, evolocumab 140 mg every 2 weeks (Q2W) was the most cost-effective option, dominating all other active regimens. Compared with statin therapy alone, it generated incremental costs of $11,109.27 and a quality-adjusted life year (QALY) gain of 0.42. The resulting ICUR was $26,217.47 per QALY, which is below the WTP threshold of $39,875.0 per QALY. Although less favorable than evolocumab, alirocumab 75 mg Q2W and tafolecimab 150 mg Q2W were also cost-effective versus statins alone, with ICURs of $34,279.73 and $34,002.10 per QALY, respectively. All other regimens were dominated, and inclisiran showed the least favorable cost-utility profile (ICUR $113,800.14 per QALY). Sensitivity analyses identified the discount rate as the key driver of uncertainty, with ICURs for evolocumab 140 mg Q2W versus statins alone ranging from $15,903.46 to $34,573.62 per QALY. Probabilistic sensitivity analysis showed a 98.9% probability of evolocumab 140 mg Q2W being cost-effective versus statins alone. At the current negotiated price, evolocumab 140 mg Q2W is the most cost-effective PCSK9 inhibitor regimen for Chinese patients with hypercholesterolemia or at high cardiovascular risk when added to statin therapy. Alirocumab 75 mg Q2W and tafolecimab 150 mg Q2W also represent cost-effective alternatives. These findings provide important evidence to support clinical decision-making and optimize resource allocation in China.

Pharmacokinetic characterization plays a vital role in drug discovery and development. Although involving numerous laboratory animals with error-prone, labor-intensive, and time-consuming procedures, pharmacokinetic profiling is still irreplaceable in preclinical studies. With physiologically based pharmacokinetic (PBPK) modeling, the in vivo profiles of drug absorption, distribution, metabolism, and excretion can be predicted. To evaluate the application of such an approach in preclinical investigations, the plasma pharmacokinetic profiles of seven commonly used probe substrates of microsomal enzymes, including phenacetin, tolbutamide, omeprazole, metoprolol, chlorzoxazone, nifedipine, and baicalein, were predicted in rats using bottom-up PBPK models built with in vitro data alone. The prediction’s reliability was assessed by comparison with in vivo pharmacokinetic data reported in the literature. The overall predicted accuracy of PBPK models was good with most fold errors within 2, and the coefficient of determination (R 2 ) between the predicted concentration data and the observed ones was more than 0.8. Moreover, most of the observation dots were within the prediction span of the sensitivity analysis. We conclude that PBPK modeling with acceptable accuracy may be incorporated into preclinical studies to refine in vivo investigations, and PBPK modeling is a feasible strategy to practice the principles of 3Rs.

BackgroundIrinotecan (CPT-11) is a prodrug that is bioactivated to SN-38, which is primarily cleared via UGT1A1-mediated glucuronidation. Its complex metabolism, which also involves CYP3A-mediated oxidation, makes irinotecan highly susceptible to enzyme-mediated drug-drug interactions (DDIs). This study aimed to develop and qualify an adult whole-body physiologically based pharmacokinetic (PBPK) model of irinotecan and its metabolites (SN-38, SN-38G, and APC) to predict systemic pharmacokinetics and UGT1A1/CYP3A-mediated DDIs.MethodsAn adult middle-out PBPK model was implemented in Simcyp®, integrating key pathways for carboxylesterase (CES) -mediated activation, UGT1A1/UGT1A9-driven glucuronidation, and CYP3A4/5-mediated oxidation. The model was calibrated using 175–300 mg/m2 monotherapy data and was validated across a 33–750 mg/m2 dose range, including drug-drug interactions with ketoconazole, sorafenib, and lopinavir/ritonavir.ResultsMost observed irinotecan and SN-38 concentrations fell within the fifth–95th percentile prediction intervals, and dose–exposure slopes were close to unity. Across monotherapy evaluations, 54/56 (96.4%) comparisons of maximum concentration (Cmax) and area under the concentration–time curve (AUC) met the 2-fold acceptance criterion. The model further captured the direction and magnitude of exposure changes across all inhibitor scenarios, with CPT-11 and SN-38 exposure ratios remaining within acceptable limits, although APC exposure was overpredicted in the ketoconazole scenario.ConclusionThe mechanistically informed and validated whole-body PBPK model reliably describes dose-dependent irinotecan and SN-38 pharmacokinetics and UGT1A1/CYP3A-mediated drug-drug interactions. This framework provides a clinically relevant tool for enzyme-mediated DDI risk assessment and for exploratory simulation of dose–exposure relationships under standard irinotecan regimens.

(1) Objective: To assess the reliability and validity of the simplified Chinese version of the brief Diabetes Quality of Life (DQoL) questionnaire in measuring health-related quality of life (HRQoL) in Chinese type 2 diabetes (T2D) patients. (2) Methods: A cross-sectional validation study including 277 patients was conducted at a tertiary hospital in Shanghai, China during April–May, 2018. The English brief DQoL was forward and back-translated into simplified Chinese. The expert interview, exploratory factor analysis (EFA), and Spearman correlation with the 5-level version of EuroQoL-5 (EQ-5D-5L) were employed to establish its validity. The internal reliability was assessed by Cronbach’s alpha. Participants were also stratified into subgroups to evaluate if the Chinese brief DQoL had more test effectiveness in a specific subpopulation. (3) Results: No items were removed from the original English brief DQoL based on the results of factor analysis and expert interview. The Spearman coefficient revealed a low-moderate inverse correlation between DQoL and EQ-5D-5L index and visual analogue scale (VAS), respectively (ρ1 = −0.364, p < 0.0001; ρ2 = −0.514, p < 0.0001). The Cronbach’s alpha coefficient of the final scale was 0.731. (4) Conclusions: The simplified Chinese version of the brief DQoL questionnaire showed reasonable reliability and validity, suggesting its potential appropriateness for evaluating quality of life in Chinese T2D patients. More future efforts should be made to generalize the application of the findings.

Physiologically based pharmacokinetic (PBPK) modeling, a cornerstone of model‐informed drug development and model‐informed precision dosing, simulates drug disposition in the human body by integrating physiological, biochemical, and physicochemical parameters. While PBPK modeling has advanced globally since the 1970s, China's adoption of this technology has followed a distinctive path, characterized by accelerated growth over the past 2 decades. This review provides a comprehensive analysis of China's contributions to PBPK modeling, addressing knowledge gaps in publication trends, application domains, and platform preferences. A systematic literature search yielded 266 original PBPK research articles from PubMed up to August 08, 2024. The analysis revealed that drug disposition and drug–drug interaction studies constitute the largest proportion of PBPK analyses in China. Chinese universities and hospitals emerge as the leading contributors to PBPK research among institutions in China. Although established commercial PBPK platform such as GastroPlus and Simcyp remain popular within the Chinese pharmaceutical industry, open‐source platforms like PK‐Sim are gaining significant traction in PBPK applications across China. This review underscores the transformative potential of PBPK modeling in drug development within China, offering valuable insights into future directions and challenges in the field.

Background: Ganciclovir and valganciclovir are used for prophylaxis and treatment of cytomegalovirus infection. However, there is great interindividual variability in ganciclovir’s pharmacokinetics (PK), highlighting the importance of individualized dosing. To facilitate model-informed precision dosing (MIPD), this study aimed to establish a parametric model repository of ganciclovir and valganciclovir by summarizing existing population pharmacokinetic information and analyzing the sources of variability. (2) Methods: A total of four databases were searched for published population PK models. We replicated these models, evaluated the impact of covariates on clearance, calculated the probability of target attainment for each model based on a predetermined dosing regimen, and developed an area under the concentration–time curve (AUC) calculator using maximum a posteriori Bayesian estimation. (3) Results: A total of 16 models, one- or two-compartment models, were included. The most significant covariates were body size (weight and body surface area) and renal function. The results show that 5 mg/kg/12 h of ganciclovir could make the AUC0–24h within 40–80 mg·h/L for 50.03% pediatrics but cause AUC0–24h exceeding the exposure thresholds for toxicity (120 mg·h/L) in 51.24% adults. (4) Conclusions: Dosing regimens of ganciclovir and valganciclovir should be adjusted according to body size and renal function. This model repository has a broad range of potential applications in MIPD.