Background Fine particulate matter (PM_2.5) monitoring stations may generate missing data for a certain period of time due to various factors. This data loss will adversely affect air quality assessment and pollution control decision-making. Objective To propose an inverse distance weighted (IDW) spatiotemporal interpolation method based on particle swarm optimization (PSO) to interpolate and fill missing PM_2.5 spatiotemporal sequence data and increase interpolation accuracy. Methods An interpolation experiment was designed into two parts. The first part used hourly PM_2.5 observational data from four moments on January 1, 2017 in the Yangtze River Delta region. The second part employed daily PM_2.5 observational data from the first 10 d of January 2017 in the Beijing-Tianjin-Hebei region. Interpolation accuracy was evaluated using four metrics: root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and mean relative error (MRE). Results IDW spatiotemporal interpolation method optimized with PSO significantly improved the accuracy of filling missing PM_2.5 spatiotemporal sequence data. In the hourly-scale experiment conducted in the Yangtze River Delta region, compared to a distance index of 2, the accuracy metrics RMSE, MAE, MAPE, and MRE generated by the proposed method improved on average by 0.17 μg·m⁻³, 0.27 μg·m⁻³, 0.17%, and 0.01%, respectively. The PM_2.5 spatial field maps generated for four moments based on this method clearly illustrated the spatiotemporal distribution characteristics of hourly PM_2.5 concentrations in the Yangtze River Delta region. In the daily-scale experiment conducted in the Beijing-Tianjin-Hebei region, the PSO-optimized distance index outperformed the traditional method, with interpolation accuracy improvements of approximately 0.215 μg·m⁻³, 0.283 μg·m⁻³, 0.174%, and 0.014%, respectively. Furthermore, the seasonal PM_2.5 spatial field maps generated by this method revealed the spatiotemporal distribution characteristics of PM_2.5 concentrations in the Beijing-Tianjin-Hebei region across different seasons, further validating the effectiveness and applicability of this method. Conclusion The IDW spatiotemporal interpolation method optimized with PSO is highly accurate and reliable for interpolating the missing data in the Yangtze River Delta region and the Beijing-Tianjin-Hebei region, providing valuable insights for air pollution control and public health protection.

Adipose tissue is a critical energy reservoir in animals and humans, with multifaceted roles in endocrine regulation, immune response, and providing mechanical protection. Based on anatomical location and functional characteristics, adipose tissue can be categorized into distinct types, including white adipose tissue (WAT), brown adipose tissue (BAT), beige adipose tissue, and pink adipose tissue. Traditionally, adipose tissue research has centered on its morphological and functional properties as a whole. However, with the advent of single-cell transcriptomics, a new level of complexity in adipose tissue has been unveiled, showing that even under identical conditions, cells of the same type may exhibit significant variation in morphology, structure, function, and gene expression——phenomena collectively referred to as cellular heterogeneity. Single-cell transcriptomics, including techniques like single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), enables in-depth analysis of the diversity and heterogeneity of adipocytes at the single-cell level. This high-resolution approach has not only deepened our understanding of adipocyte functionality but also facilitated the discovery of previously unidentified cell types and gene expression patterns that may play key roles in adipose tissue function. This review delves into the latest advances in the application of single-cell transcriptomics in elucidating the heterogeneity and diversity within adipose tissue, highlighting how these findings have redefined the understanding of cell subpopulations within different adipose depots. Moreover, the review explores how single-cell transcriptomic technologies have enabled the study of cellular communication pathways and differentiation trajectories among adipose cell subgroups. By mapping these interactions and differentiation processes, researchers gain insights into how distinct cellular subpopulations coordinate within adipose tissues, which is crucial for maintaining tissue homeostasis and function. Understanding these mechanisms is essential, as dysregulation in adipose cell interactions and differentiation underlies a range of metabolic disorders, including obesity and diabetes mellitus type 2. Furthermore, single-cell transcriptomics holds promising implications for identifying therapeutic targets; by pinpointing specific cell types and gene pathways involved in adipose tissue dysfunction, these technologies pave the way for developing targeted interventions aimed at modulating specific adipose subpopulations. In summary, this review provides a comprehensive analysis of the role of single-cell transcriptomic technologies in uncovering the heterogeneity and functional diversity of adipose tissues.

OBJECTIVE To assess the cost-effectiveness of durvalumab combined with chemotherapy as a first-line treatment for advanced biliary tract cancer from the perspective of the Chinese healthcare system. METHODS Using data from the TOPAZ-1 clinical trial， a three-state Markov model comprising progression-free survival （PFS）， progressive disease （PD） and death was developed， with a cycle length of 21 days and a 10-year time horizon. Patients in the observation group received durvalumab in combination with gemcitabine and cisplatin， whereas those in the control group received placebo plus the same chemotherapy regimen. The evaluation indexes were quality-adjusted life year （QALY） and the incremental cost-effectiveness ratio （ICER）. The willingness-to-pay （WTP） threshold was set at three times the 2024 Chinese per capita gross domestic product （GDP） （287 247 yuan/QALY）. The sensitivity analyses， along with scenario analyses， were performed. RESULTS In the base-case analysis， the ICER of observation group compared to control group was 1 166 344.46 yuan/QALY， far exceeding the WTP threshold， indicating that the regimen was not cost-effective. One-way sensitivity analysis identified the PD state utility， discount rate， cost of durvalumab， and PFS state utility as the main drivers of ICER variation. Probabilistic sensitivity analysis showed that， at the above WTP threshold， the probability of the acceeptance of this regimen was 0， further supporting the robustness of the base-case findings. In the scenario analysis， inclusion of a patient assistance program reduced the ICER to 235 885.16 yuan/ QALY， below the above WTP threshold， suggesting cost-effectiveness under this assistance program. However， when applying a regional WTP threshold set at three times the per capita GDP （158 475 yuan/QALY） of Gansu Province （the province with the lowest GDP in China in 2024）， the ICER remained above the threshold， indicating that the regimen was not cost-effective at the regional level. CONCLUSIONS At current pricing， durvalumab plus chemotherapy as a first-line treatment for advanced biliary tract cancer is not cost-effective in China. Although the introduction of a patient assistance program can substantially reduce the ICER and achieve cost-effectiveness at a WTP threshold set at three times the 2024 per capita GDP of China， due to limited affordability in low-income areas， the program remains not cost-effective.

Objective To investigate the bioequivalence of gliclazide sustained-release tablets in Chinese healthy subjects.Methods The study was designed using a single-center,open,randomized,single-dose,two-cycle,two-sequence administration method;subjects were orally administered the test/reference preparation 30 mg on an fasting or fed conditions,with self-cross-dosing.The concentration of gliclazide in human plasma was determined by liquid chromatography tandem mass spectrometry(LC-MS/MS)method.The main pharmacokinetic parameters of gliclazide(Cmax,AUC0-t and AUC0-∞)were analyzed by non-atrioventricular model of WinNonlin.Result In the fasting study,24 subjects were recruited and 22 completed the study.The main pharmacokinetic parameters of gliclazide sustained-release tablets test preparation and reference preparation in the fasting group were as follows:Cmax were(862.48±294.48)and(902.96±259.09)ng·mL-1;AUC0-t were(2.60 × 104±8 930.46)and(2.50 ×104±7 573.42)h·ng-1·mL-1;AUC0-∞ were(3.00 × 104±1.43 × 104)and(2.68 × 104±7 085.99)h·ng·mL-1.In the fed study,twenty-four subjects were enrolled and 23 completed the study.The main pharmacokinetic parameters of gliclazide sustained-release tablets test preparation and reference preparation in fed group:Cmax were(1 531.74±273.49)and(1 510.87±241.08)ng·mL-1;AUC0-t were(2.78 ×104±9 565.89)and(2.76 ×104±9 821.43)h·ng·mL-1;AUC0-∞ were(3.02 ×104±1.24 ×104)and(3.02 × 104±1.30 × 104)h·ng·mL-1 h·ng·mL-1.The 90％confidence intervals of the geometric mean ratios of Cmax,AUC0-t,AUC0-∞ for the test preparation and reference preparation gliclazide sustained-release tablets were all between 80％and 125％.Conclusion The test and the reference preparation of gliclazide sustained-release tablets are bioequivalent in Chinese healthy subjects.

OBJECTIVE: To investigate a new noninvasive diagnostic model for nonalcoholic fatty liver disease (NAFLD) based on features of tongue images. METHODS: Healthy controls and volunteers confirmed to have NAFLD by liver ultrasound were recruited from China-Japan Friendship Hospital between September 2018 and May 2019, then the anthropometric indexes and sampled tongue images were measured. The tongue images were labeled by features, based on a brief protocol, without knowing any other clinical data, after a series of corrections and data cleaning. The algorithm was trained on images using labels and several anthropometric indexes for inputs, utilizing machine learning technology. Finally, a logistic regression algorithm and a decision tree model were constructed as 2 diagnostic models for NAFLD. RESULTS: A total of 720 subjects were enrolled in this study, including 432 patients with NAFLD and 288 healthy volunteers. Of them, 482 were randomly allocated into the training set and 238 into the validation set. The diagnostic model based on logistic regression exhibited excellent performance: in validation set, it achieved an accuracy of 86.98%, sensitivity of 91.43%, and specificity of 80.61%; with an area under the curve (AUC) of 0.93 [95% confidence interval (CI) 0.68-0.98]. The decision tree model achieved an accuracy of 81.09%, sensitivity of 91.43%, and specificity of 66.33%; with an AUC of 0.89 (95% CI 0.66-0.92) in validation set. CONCLUSIONS The features of tongue images were associated with NAFLD. Both the 2 diagnostic models, which would be convenient, noninvasive, lightweight, rapid, and inexpensive technical references for early screening, can accurately distinguish NAFLD and are worth further study.
Humans ; Non-alcoholic Fatty Liver Disease/diagnostic imaging* ; Ultrasonography ; Anthropometry ; Algorithms ; China

Astrocytes are the largest glial population in the mammalian brain. However, we have a minimal understanding of astrocyte development, especially fate specification in different regions of the brain. Through lineage tracing of the progenitors of the third ventricle (3V) wall via in-utero electroporation in the embryonic mouse brain, we show the fate specification and migration pattern of astrocytes derived from radial glia along the 3V wall. Unexpectedly, radial glia located in different regions along the 3V wall of the diencephalon produce distinct cell types: radial glia in the upper region produce astrocytes and those in the lower region produce neurons in the diencephalon. With genetic fate mapping analysis, we reveal that the first population of astrocytes appears along the zona incerta in the diencephalon. Astrogenesis occurs at an early time point in the dorsal region relative to that in the ventral region of the developing diencephalon. With transcriptomic analysis of the region-specific 3V wall and lateral ventricle (LV) wall, we identified cohorts of differentially-expressed genes in the dorsal 3V wall compared to the ventral 3V wall and LV wall that may regulate astrogenesis in the dorsal diencephalon. Together, these results demonstrate that the generation of astrocytes shows a spatiotemporal pattern in the developing mouse diencephalon.
Mice ; Animals ; Astrocytes ; Neuroglia/physiology* ; Diencephalon ; Brain ; Neurons ; Mammals

Evaluate the interventional effect of Lycium barbarum leaves extract on cataract rats and its effects on plasma and liver tissue metabolites. The ultimate goal is to explore the scientific connotation of Lycium barbarum leaves extract on vision improvement. All experiments were approved by the experimental animal ethics committee from Nanjing University of Chinese Medicine (202306A067). D-Galactose (D-gal) induced cataract model in rats was established. The lens opacity, lens and liver tissue pathology, level of oxidative stress and polyol metabolism regulation in the lens, level of oxidative stress in serum and liver tissue, and the content of inflammatory cytokines such as tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in serum and liver tissue were analysed to evaluate the effect of Lycium barbarum leaves extract on cataract. The metabolite profiles of plasma and liver tissue of rats were analyzed by UPLC-QTOF-MS/MS. Principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were used to compare and analyze the metabolic data in control group and cataract group, and screen potential biomarkers. The related metabolic pathways were further constructed by KEGG database analysis. The results showed that lens and liver pathology of cataract rats were improved after being intervened by the leaves extract of Lycium barbarum. The contents of AR and Ca²⁺ were significantly decreased in lens, and the contents of SDH and GSH and the ability of CAT were significantly increased; the content of GSH and the ability of SOD were significantly improved in serum and liver tissue, the content of MDA, the abilities of ALT and AST and the level of inflammatory factors were significantly reduced. The metabolomics results showed that there were 15 different metabolites in plasma and liver tissue of cataract rats, and 9 different biomarkers including retinyl ester, stearic acid, and palmitic acid, were returned by Lycium barbarum leaves extract. As revealed by pathway enrichment in plasma and liver tissue, it was found that the retinol metabolic pathway was mainly regulated by Lycium barbarum leaves extract. In summary, Lycium barbarum leaves can effectively alleviate the pathological changes of cataract, inhibit inflammation and improve antioxidant capacity, which may relate to the retinol metabolic pathway. It provides scientific basis and support for revealing the scientific connotation of the effect of Lycium barbarum leaves on vision improvement.

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.