ObjectiveTo investigate the status of overlapping hepatitis B virus （HBV） infection in patients with chronic hepatitis C virus （HCV） infection and the serological characteristics of such patients. MethodsA total of 8 637 patients with HCV infection who were hospitalized from January 1， 2010 to December 31， 2020 and had complete data of HBV serological markers were enrolled， and the composition ratio of patients with overlapping HBV serological markers was analyzed among the patients with HCV infection. The patients were divided into groups based on age and year of birth， and serological characteristics were analyzed， and the distribution of HBV-related serological characteristics were analyzed across different HCV genotypes. ResultsThe patients with HCV/HBV overlapping infection accounted for 5.85%， and the patients with previous HBV infection accounted for 48.10%； the patients with protective immunity against HBV accounted for 14.67%， while the patients with a lack of protective immunity against HBV accounted for 31.39%. The patients were divided into groups based on age： in the 0 — 17 years group， the patients with protective immunity against HBV accounted for 61.41% （304 patients）； the 18 — 44 years group was mainly composed of patients with previous HBV infection （698 patients， 37.31%）， the 45 — 59 years group was predominantly composed of patients with previous HBV infection （1 945 patients， 50.38%）， and the ≥60 years group was also predominantly composed of patients with previous HBV infection （1 486 patients， 61.66%）. The patients were divided into groups based on the year of birth： in the pre-1992 group， the patients with previous HBV infection accounted for 51.63% （4 112 patients）； in the 1992 — 2005 group， the patients with protective immunity against HBV accounted for 54.72% （168 patients）； in the post-2005 group， the patients with protective immunity against HBV accounted for 64.38% （235 patients）. In this study， 6 301 patients underwent HCV genotype testing： the patients with genotype 1b accounted for the highest proportion of 51.71% （3 258 patients）， followed by those with genotype 2a （1 769 patients， 28.07%）， genotype 3b （63 patients， 1.00%）， genotype 3a （10 patients， 0.16%）， genotype 4 （21 patients， 0.33%）， and genotype 6a （5 patients， 0.08%）. ConclusionWith the implementation of hepatitis B planned vaccination program in China， there has been a significant reduction in the proportion of patients with previous HBV infection among the patients with HCV/HBV overlapping infection， but there is still a relatively high proportion of patients with a lack of protective immunity against HBV.

Diabetic kidney disease（DKD） is a chronic kidney structural and functional disorder caused by diabetes. With the global prevalence of diabetes continuing to rise， DKD has gradually become a major cause of chronic kidney disease and end-stage renal disease（ESRD）， posing a serious threat to patients' quality of life and long-term health outcomes. Studies have shown that apoptosis plays a pivotal role in the development and progression of DKD， with its mechanisms involving abnormal activation of multiple signaling pathways such as Toll-like receptor 4（TLR4）/nuclear transcription factor-κB（NF-κB）/B-cell lymphoma-2（Bcl-2）/cysteinyl aspartate-specific proteinase（Caspase）-3， protein kinase R-like endoplasmic reticulum kinase（PERK）/eukaryotic initiation factor 2α（eIF2α）/activating transcript factor 4（ATF4）/CCAAT enhancer-binding protein homologous protein（CHOP）， phosphatidylinositol 3-kinase（PI3K）/protein kinase B（Akt）/glycogen synthase kinase-3β（GSK-3β）， Janus kinase 2（JAK2）/signal transducer and activator of transcription 3（STAT3）， adenosine monophosphate-activated protein kinase（AMPK）/mammalian target of rapamycin（mTOR） and silent information regulator 1（SIRT1）/tumor suppressor protein 53（p53）， thereby accelerating renal pathological damage in DKD. Extensive evidence-based medical studies have confirmed that traditional Chinese medicine（TCM）， leveraging its unique therapeutic advantages of multi-target， multi-component and multi-pathway approaches， has demonstrated remarkable efficacy and favorable safety profiles in treating DKD. Recent studies have demonstrated that active components of TCM can specifically target and modulate key effectors in apoptotic signaling pathways. Meanwhile， traditional compound formulations exert synergistic effects through multiple approaches such as replenishing deficiency and activating blood circulation， detoxifying and dredging collaterals， tonifying kidney essence， and removing stasis and purging turbidity， thereby comprehensively regulating critical pathological processes including endoplasmic reticulum stress and mitochondrial apoptosis pathways. This combined therapeutic approach of molecular targeting and holistic regulation provides novel strategies for delaying the progression of DKD. Based on this， this paper provides an in-depth analysis of key apoptotic signaling pathways and their regulatory mechanisms， while systematically summarizing recent research advances regarding the therapeutic effects of TCM active components， compound formulations， and proprietary Chinese medicines on DKD through modulation of these pathways， with particular emphasis on their underlying molecular mechanisms. These findings not only elucidate the modern scientific connotation and theoretical basis of TCM in treating DKD but also establish a solid theoretical and practical foundation for promoting the wider clinical application and further research of TCM in the field of DKD treatment.

Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

ObjectiveThe accuracy of Y-chromosome haplogroup assignment is crucial for tracing paternal lineage in male samples. With the advancement of high-throughput sequencing technologies, high-density Y-SNP genotyping from whole-genome or array-based data has become a standard method for determiningY-chromosome haplogroups. This study systematically evaluated the performance of 4 commonly used high-density SNP genotyping systems—namely, the Global Screening Array (GSA), Chinese Genotyping Array (CGA), Affymetrix array, and the 1240K capture panel—for haplogroup assignment. This work provides a reference for data comparison across different systems. MethodsWe extracted genotype data for the 4 Y-SNP panels from 30× whole-genome sequencing (WGS) data of 1 590 male samples from the 1000 Genomes Project. Additionally, GSA array genotype data from 384 relative pairs (spanning 1st- to 12th-degree relationships) from 109 Chinese Han families were collected. Haplogroup assignment was performed using Y-LineageTracker v1.3.0 software. We assessed the concordance and resolution of haplogroup assignments between the four Y-SNP panels and the WGS data. The consistency and resolution of haplogroup assignments were also evaluated for both the 1000 Genomes Project samples and the 109 family samples collected in this study. Furthermore, the impact of varying numbers of Y-SNPs on haplogroup assignment was examined. ResultsThe GSA and CGA panels demonstrated superior resolution and discrimination of haplogroup subclades compared with the other two panels. The haplogroup assignments from the GSA, CGA, and 1240K panels showed high concordance with WGS data, with consistency rates exceeding 88.70%, whereas the Affymetrix platform exhibited a significantly lower consistency rate of 61.89%. Specifically, the GSA and CGA panels consistently demonstrated superior performance compared with the other two panels in the assignment of haplogroups O-M175 and H-L901, achieving complete concordance (100%) for both haplogroups. In contrast, the Affymetrix panel erroneously assigned all individuals belonging to haplogroup O-M175 to haplogroup K2-M526. Furthermore, its accuracy for haplogroup H-L901 was exceedingly low, at merely 1.41%. This poor performance was characterized by the misassignment of 98.59% of H-L901 samples—specifically, 1.41% to J-M304 and a predominant 97.18% to F-M89. For haplogroup R-M207, all four panels exhibited uniformly high levels of consistency, with concordance values exceeding 94.00%. Notably, for haplogroup E-M96, the 1240K and Affymetrix panels outperformed the GSA and CGA panels in terms of concordance, representing the first instance in which these two panels surpassed the latter. Conversely, for haplogroups J-M304, Q-M242, and I-M170, all 4 panels showed relatively elevated misclassification rates, with the Affymetrix array demonstrating the poorest overall performance. None of the four panels showed any discordant haplogroup assignments among the familial relative pairs analyzed. A positive correlation was observed between the number of Y-SNPs (ranging from 1 000 to 10 000) and classification consistency; however, classification consistency plateaued when the number of Y-SNPs exceeded 10 000. Furthermore, a random sampling analysis conducted on the GSA and CGA panels demonstrated that the haplogroup misclassification rate exhibited negligible fluctuation across the Y-SNP range of 500 to 1 000. Conversely, a marked enhancement in classification consistency was observed as the number of markers increased from 1 000 to 5 000, ultimately reaching a plateau within the interval of 5 000 to 8 000 markers. ConclusionThese findings indicate that the GSA and CGA panels provide high resolution and concordance, delivering reliable Y-haplogroup assignment for forensic investigations.

Organoid-on-a-chip technology represents a promising interdisciplinary advancement that merges two cutting-edge biomedical platforms: stem cell-derived organoids and microfluidics-based organ-on-a-chip systems. Organoids are self-organizing three-dimensional (3D) cell cultures that mimic the key structural and functional features of in vivo organs. However, traditional organoid culture systems are often static, lacking dynamic environmental cues and suffering from limitations such as batch-to-batch variability, low stability, and low throughput. Organ-on-a-chip platforms, by contrast, utilize microfluidic technologies to simulate the dynamic physiological microenvironment of human tissues and organs, enabling more controlled cell growth and differentiation. By integrating the advantages of organoids and organ-on-a-chip technologies, organoid-on-a-chip systems transcend the limitations of conventional 3D culture models, offering a more physiologically relevant and controllable in vitro platform. In organoid-on-a-chip systems, stem cells or pre-formed organoids are cultured in micro-engineered environments that mimic in vivo conditions, enabling precise control over fluid flow, mechanical forces, and biochemical cues. Specifically, these platforms employ advanced strategies including bio-inspired 3D scaffolds for structural support, precise spatial cell patterning via 3D bioprinting, and integrated biosensors for real-time monitoring of metabolic activities. These synergistic elements recreate complex extracellular matrix signals and ensure high structural fidelity. Based on structural complexity, organoid-on-a-chip systems are classified into single-organoid and multi-organoid types, forming a trajectory from unit biomimicry to systemic simulation. Single-organoid chips focus on highly biomimetic units by integrating vascular, immune, or neural functions. Multi-organoid chips simulate inter-organ crosstalk and systemic homeostasis, advancing complex disease modeling and PK/PD evaluation. This emerging technology has demonstrated broad application potential in multiple fields of biomedicine. Organoid-on-a-chip systems can recapitulate organ developmentin vitro, facilitating research in developmental biology. They mimic organ-specific physiological activities and mechanisms, showing promising applications in regenerative medicine for tissue repair or replacement. In disease modeling, they support the reconstruction of models for neurodegenerative, inflammatory, infectious, metabolic diseases, and cancers. These platforms also enable in vitro drug testing and pharmacokinetic studies (ADME). Patient-derived chips preserve genetic and pathological features, offering potential for precision medicine. Additionally, they reduce species differences in toxicology, providing human-relevant data for environmental, food, cosmetic, and drug safety assessments. Despite progress, organoid-on-a-chip systems face challenges in dynamic simulation, extracellular matrix (ECM) variability, and limited real-time 3D imaging, requiring improved materials and the integration of developmental signals. Current bottlenecks also include the high technical threshold for automation and the lack of standardized validation frameworks for regulatory adoption. Meanwhile, the concept of a “human-on-a-chip” has been proposed to mimic whole-body physiology by integrating multiple organoid modules. This approach enables systemic modeling of drug responses and toxicity, with the potential to reduce animal testing and revolutionize drug development. Future advancements in bio-responsive hydrogels and flexible biosensors will further empower these platforms to bridge the gap between bench-side research and personalized clinical interventions. In conclusion, organoid-on-a-chip technology offers a transformative in vitro model that closely recapitulates the complexity of human tissues and organ systems. It provides an unprecedented platform for advancing biomedical research, clinical translation, and pharmaceutical innovation. Continued development in biomaterials, microengineering, and analytical technologies will be essential to unlocking the full potential of this powerful tool.

ObjectiveThe accuracy of Y-chromosome haplogroup assignment is crucial for tracing paternal lineage in male samples. With the advancement of high-throughput sequencing technologies, high-density Y-SNP genotyping from whole-genome or array-based data has become a standard method for determiningY-chromosome haplogroups. This study systematically evaluated the performance of 4 commonly used high-density SNP genotyping systems—namely, the Global Screening Array (GSA), Chinese Genotyping Array (CGA), Affymetrix array, and the 1240K capture panel—for haplogroup assignment. This work provides a reference for data comparison across different systems. MethodsWe extracted genotype data for the 4 Y-SNP panels from 30× whole-genome sequencing (WGS) data of 1 590 male samples from the 1000 Genomes Project. Additionally, GSA array genotype data from 384 relative pairs (spanning 1st- to 12th-degree relationships) from 109 Chinese Han families were collected. Haplogroup assignment was performed using Y-LineageTracker v1.3.0 software. We assessed the concordance and resolution of haplogroup assignments between the four Y-SNP panels and the WGS data. The consistency and resolution of haplogroup assignments were also evaluated for both the 1000 Genomes Project samples and the 109 family samples collected in this study. Furthermore, the impact of varying numbers of Y-SNPs on haplogroup assignment was examined. ResultsThe GSA and CGA panels demonstrated superior resolution and discrimination of haplogroup subclades compared with the other two panels. The haplogroup assignments from the GSA, CGA, and 1240K panels showed high concordance with WGS data, with consistency rates exceeding 88.70%, whereas the Affymetrix platform exhibited a significantly lower consistency rate of 61.89%. Specifically, the GSA and CGA panels consistently demonstrated superior performance compared with the other two panels in the assignment of haplogroups O-M175 and H-L901, achieving complete concordance (100%) for both haplogroups. In contrast, the Affymetrix panel erroneously assigned all individuals belonging to haplogroup O-M175 to haplogroup K2-M526. Furthermore, its accuracy for haplogroup H-L901 was exceedingly low, at merely 1.41%. This poor performance was characterized by the misassignment of 98.59% of H-L901 samples—specifically, 1.41% to J-M304 and a predominant 97.18% to F-M89. For haplogroup R-M207, all four panels exhibited uniformly high levels of consistency, with concordance values exceeding 94.00%. Notably, for haplogroup E-M96, the 1240K and Affymetrix panels outperformed the GSA and CGA panels in terms of concordance, representing the first instance in which these two panels surpassed the latter. Conversely, for haplogroups J-M304, Q-M242, and I-M170, all 4 panels showed relatively elevated misclassification rates, with the Affymetrix array demonstrating the poorest overall performance. None of the four panels showed any discordant haplogroup assignments among the familial relative pairs analyzed. A positive correlation was observed between the number of Y-SNPs (ranging from 1 000 to 10 000) and classification consistency; however, classification consistency plateaued when the number of Y-SNPs exceeded 10 000. Furthermore, a random sampling analysis conducted on the GSA and CGA panels demonstrated that the haplogroup misclassification rate exhibited negligible fluctuation across the Y-SNP range of 500 to 1 000. Conversely, a marked enhancement in classification consistency was observed as the number of markers increased from 1 000 to 5 000, ultimately reaching a plateau within the interval of 5 000 to 8 000 markers. ConclusionThese findings indicate that the GSA and CGA panels provide high resolution and concordance, delivering reliable Y-haplogroup assignment for forensic investigations.

ObjectiveGastric hemorrhage is one of the most common and life-threatening emergencies of the upper digestive tract. Early identification and continuous monitoring are essential for reducing rebleeding rates and mortality, particularly within the critical early hours after onset. Although endoscopy and radiological imaging can accurately localize bleeding sites, these approaches are invasive, resource-intensive, and unsuitable for continuous bedside monitoring. Electrical impedance tomography (EIT), as a noninvasive and radiation-free functional imaging technique, offers real-time visualization of conductivity distribution and has the potential for detecting intragastric bleeding based on the electrical contrast between blood and surrounding gastric tissues. In this study, a three-dimensional gastric EIT (3D-gEIT) framework is proposed to achieve noninvasive, real-time, and dynamic monitoring of gastric hemorrhage, with emphasis on spatial localization and quantitative volume assessment. MethodsA three-dimensional upper-abdominal simulation model incorporating the stomach, gastric wall, gastric contents, and surrounding tissues was established. Three electrode configurations, namely the dual layer ring, the four layer staggered ring, and the opposed dual plane array, were designed and systematically compared to evaluate their influence on depth sensitivity and spatial resolution. Based on the Tikhonov-Noser hybrid regularization scheme, a region-clustering constraint was introduced to develop the TK-Noser-RCC algorithm. This approach aggregates spatially adjacent elements with similar conductivity variations, thereby enhancing structural continuity and suppressing isolated noise artifacts. To validate the proposed framework, an upper-abdominal physical phantom was constructed using agar to simulate background tissue conductivity. Hemispherical high-conductivity inclusions with volumes ranging from 10 ml to 50 ml were attached to the inner gastric wall to mimic localized bleeding under different gastric filling states. Boundary voltages were acquired under a 120 kHz excitation current and reconstructed using the TK-Noser-RCC algorithm. Furthermore, an in vivo animal experiment was performed using a porcine model with adult-scale abdominal dimensions. A total of 100 ml of autologous blood was injected incrementally into the stomach to simulate progressive gastric hemorrhage, and time-difference EIT reconstruction was conducted at each injection stage to assess the dynamic system response under physiological conditions. ResultsSimulation results demonstrated that the opposed dual-plane electrode array achieved superior depth sensitivity distribution and spatial resolution. For a 40 ml hemorrhage model, the average ICC and SSIM improved by 55.9% and 38.8% compared with the dual-layer ring configuration, and by 64.0% and 39.5% compared with the four-layer staggered configuration. The proposed region-clustering constraint significantly enhanced reconstruction stability. Under added Gaussian noise of 40 dB and 30 dB, ICC values remained approximately 0.85, indicating effective artifact suppression and preservation of boundary integrity. In physical phantom experiments, reconstructed hemorrhage volumes increased approximately linearly with the preset hemispherical volumes, and the reconstructed high-conductivity regions closely matched the actual bleeding locations. Both empty-stomach and full-stomach conditions were evaluated, demonstrating that the opposed dual-plane configuration maintained stable imaging performance across varying gastric contents. In the animal experiment, reconstructed low-impedance regions expanded progressively with increasing injected blood volume. The spatial localization of the hemorrhage remained stable throughout the procedure, and no significant artifacts were observed. Quantitative analysis showed that reconstructed volume and average conductivity variation exhibited an approximately linear growth trend with injected blood volume, confirming the sensitivity of the system to dynamic intragastric conductivity changes. ConclusionThe proposed 3D-gEIT framework enables quantitative reconstruction of gastric hemorrhage volume and spatial distribution with improved depth sensitivity, structural continuity, and noise robustness compared with conventional EIT approaches. By integrating optimized electrode configuration and a region-clustering-constrained reconstruction algorithm, the system provides stable dynamic monitoring under both controlled phantom conditions and in vivo physiological environments. This method offers a noninvasive, real-time, and low-cost imaging strategy for early diagnosis, postoperative monitoring, and bedside surveillance of gastric bleeding.

Objective: To define the mechanism by which swine TRIM25 restricts vesicular stomatitis virus replication. Methods: Porcine 3D4/21 cells with TRIM25 overexpression or knockdown were infected with vesicular stomatitis virus. Viral replication was quantified by immunoblotting, quantitative reverse transcription polymerase chain reaction, and 50% tissue culture infectious dose assays. Type I interferon signaling was assessed by transcript quantification, interferon-beta and interferon-stimulated response element reporter assays, and co-immunoprecipitation.Viral RNA binding was tested by RNA immunoprecipitation. Results: TRIM25 overexpression reduced viral RNA and infectious titers, whereas TRIM25 knockdown increased replication (p < 0.01). TRIM25 increased interferon-beta and interferon-stimulated gene expression and enhanced interferon-beta and interferonstimulated response element promoter activity (p < 0.01). Mechanistically, TRIM25 promoted Lys63-linked ubiquitination of RIG-I and increased phosphorylation of TANK-binding kinase 1 and interferon regulatory factor 3. TRIM25 also bound vesicular stomatitis virus genomic RNA, and binding required the C-terminal region. Conclusions and Relevance: Porcine TRIM25 restricts vesicular stomatitis virus replication by amplifying type I interferon signaling and directly binding viral RNA.

Background: and Purpose Live cell-based assays (LCBA) are increasingly used for serological antibody detection due to their ability to preserve antigen conformation, offering moderately higher sensitivity than fixed cell-based assays. However, the clinical necessity of prioritizing LCBA for the detection of aquaporin-4 immunoglobulin G (AQP4-IgG) in neuromyelitis optica spectrum disorder (NMOSD) remains unclear, especially when compared to its established role in diagnosing myelin oligodendrocyte glycoprotein antibody-associated disease. Methods: We compared the performance of live cell-based assays using immunofluorescence (LCBA-IF) and fixed cell-based assays using immunofluorescence (FCBA-IF) in detecting AQP4-IgG in 90 cases of NMOSD meeting 2015 International Panel for Neuromyelitis Optica Diagnosis criteria, alongside 40 controls. Additionally, we further investigated the relationship between AQP4-IgG titers as measured by LCBA-IF and FCBA-IF and clinical parameters in NMOSD patients. Results: Results showed 96.9% agreement between LCBA-IF and FCBA-IF (Cohen’s κ=0.935), with a strong Spearman correlation (0.977, p<0.001). Both methods demonstrated 100% specificity, with LCBA-IF showing slightly higher sensitivity compared to FCBA-IF. Within LCBAIF-tested groups, statistically significant differences in annualized relapse rates were observed across all pairwise comparisons (low-titer vs. moderate-titer, low-titer vs. high-titer, and moderate-titer vs. high-titer; all p<0.050). However, this association reached statistical significance in some FCBA-IF-tested groups. Conclusions Overall, there is a strong concordance between LCBA-IF and FCBA-IF in detecting AQP4-IgG, where LCBA-IF shows slightly higher sensitivity. Furthermore, there is a potential link between elevated AQP4-IgG titers and an increased risk of relapse, and this correlation may appear more pronounced when using LCBA-IF.

OBJECTIVE To clarify the current development status of clinical pharmacist training bases and the pharmacist workforce in China， and to provide evidence for standardizing base construction and promoting the high-quality development of hospital pharmacy. METHODS Questionnaires were distributed to all clinical pharmacist training bases for urgently-needed health professionals and clinical pharmacist training bases under the Chinese Hospital Association that had been approved by the end of 2023 to collect data including base profiles and pharmacist staffing conditions. Expert teams carried out field investigations to verify the collected data. Descriptive statistical analyses were conducted on the quantity， type and regional distribution of training bases， and the influencing factors of pharmacist staffing in the bases were analyzed. RESULTS Field surveys were completed covering 297 training bases across 31 provincial-level administrative regions. Among the base hospitals， 87.88% were Grade A tertiary general hospitals， and 65.32% were located in provincial capitals. The eastern region had the largest number of bases （136， accounting for 45.79%）， followed by the western region （79， 26.60%）. Great disparities existed among provinces in terms of base quantity and hospital scale. The median proportion of pharmaceutical technical personnel in base hospitals was 4.05%， and the median number of clinical pharmacists per 100 hospital beds was 0.53. Both indicators reached the highest in the eastern region （0.57， 4.43%） and the lowest in the northeastern region （0.45， 3.01%）. A total of 3 627 full-time clinical pharmacists were employed in all surveyed bases， among whom 83.68% held clinical pharmacist training certificates， 35.43% possessed senior professional titles， and 78.19% had postgraduate or higher educational background. The total annual training capacity of the surveyed bases was 4 291 trainees， with obvious differences in annual training capacity across regions and provinces. Training specialties covered 19 specialized disciplines plus one general discipline， and no province could deliver training for all 20 specialties simultaneously. Multivariate Logistic regression analysis showed that geographic region exerte d a significant impact on the proportion of pharmaceutical technical personnel （≥4%） （ P ＜0.05）， while the approval time of training bases and hospital scale had significant effects on the number of clinical pharmacists per 100 beds （≥0.6） （ P ＜0.05）. CONCLUSIONS China’s clinical pharmacist training system has basically matured and taken initial shape. The distribution of clinical pharmacist training resources is generally consistent with regional population and economic development levels. However， the allocation of pharmaceutical staff and clinical pharmacists has not yet met national standards and clinical service demands.