Objective:To investigate the application of time series models in forecasting pre-hospital emergency ambulance trips in Handan City and develop the LPro ensemble model for improved prediction accuracy to support emergency resource allocation.Methods:Pre-hospital emergency data from Handan Emergency Medical Command Center (2019-2023) were retrospectively analyzed. From 324 799 original records, 289 949 valid records were included after cleaning. The training set (2019-2022: 215 918 records) included 35 527 records in 2019, 52 015 in 2020, 61 836 in 2021, and 66 540 in 2022. The validation set (2023) contained 74 031 records. ARIMA, linear trend seasonal, exponential smoothing, and Prophet models were fitted to the training set. The LPro ensemble model was constructed using MAPE-based weighting (linear trend seasonal model: 0.38, Prophet: 0.62). Performance metrics included MAPE, RMSE, MAE, and R 2. Results:Data showed annual growth (compound annual growth rate 23.27%) and seasonal patterns (October peaks, February troughs). Ambulance dispatches increased annually with monthly cyclical patterns. For 2023 validation predictions: ARIMA (MAPE 8.76%, RMSE 619, MAE 491, R 2 0.4563), linear trend seasonal (MAPE 9.83%, RMSE 671, MAE 545, R 2 0.3608), Prophet (MAPE 8.43%, RMSE 562, MAE 503, R 2 0.5513), exponential smoothing (MAPE 8.08%, RMSE 643, MAE 410, R 2 0.4124). LPro model showed superior performance (MAPE 7.05%, RMSE 491, MAE 393, R 2 0.6570), with 16.37% lower MAPE, 12.63% lower RMSE, 21.87% lower MAE, and 19.17% higher R 2 versus Prophet. Conclusion:The LPro ensemble model substantially enhances prediction accuracy and reliability, offering scientific support for emergency resource optimization and dispatch scheduling in Handan City.

Background: Metabolic dysregulation is a hallmark of type 2 diabetes mellitus (T2DM), in which the abnormalities in brown adipose tissue (BAT) play important roles. However, the cellular composition and function of BAT as well as its pathological significance in diabetes remain incompletely understood. Our objective is to delineate the single-cell landscape of BAT-derived stromal vascular fraction (SVF) and their characteristic alterations in T2DM rats. Methods: T2DM was induced in rats by intraperitoneal injection of low-dose streptozotocin and high-fat diet feeding. Single-cell mRNA sequencing was then performed on BAT samples and compared to normal rats to characterize changes in T2DM rats. Subsequently, the importance of key cell subsets in T2DM was elucidated using various functional studies. Results: Almost all cell types in the BAT-derived SVF of T2DM rats exhibited enhanced inflammatory responses, increased angiogenesis, and disordered glucose and lipid metabolism. The multidirectional differentiation potential of adipose tissue-derived stem cells was also reduced. Moreover, macrophages played a pivotal role in intercellular crosstalk of BAT-derived SVF. A novel Rarres2+macrophage subset promoted the differentiation and metabolic function of brown adipocytes via adipose-immune crosstalk. Conclusion BAT SVF exhibited strong heterogeneity in cellular composition and function and contributed to T2DM as a significant inflammation source, in which a novel macrophage subset was identified that can promote brown adipocyte function.