Human Respiratory Stem Cells (RSCs) play a crucial role in the maintenance, repair and regeneration of the respiratory system. As a novel therapeutic method, stem cell therapy is a popular research direction in the medical field. And with the in-depth research on the mechanism of pneumonia caused by respiratory infections in recent years, the use of RSCs to explore pneumonia caused by respiratory infections and its therapeutic strategies has become a hot topic. In this paper, we firstly outlined the types of RSCs, summarized the mechanism of pneumonia caused by respiratory tract infections, discussed the advantages of RSCs application and the progress of culture differentiation, and elaborated the therapeutic exploration of RSCs in pneumonia caused by respiratory tract infections.

The construction of an information system for equipment budget management in public hospitals is an important measure to strengthen comprehensive budget management, serving as an important foundation for promoting the development of clinical disciplines and enhancing operational management. Since September 2023, a tertiary public hospital had explored the construction of equipment budget management informatization. This practice had established a supporting budget management information system, which included an equipment demand reserve library and a general use product library, linked performance evaluation indicators, implemented visualizing real-time project progress, and strengthened data governance. A series of measures had been taken to move management to equipment demand research, expand the time window for departments to fill in budget requirements, simplify the department application process, and achieve a closed-loop management of the entire chain of department equipment demand research, budget approval, and execution, ensuring the rationality and accuracy of the budget. By the end of 2024, the budget management information system had covered 87 departments and included 30 000 sets of equipment applications, providing detailed data support and critical management references for demand departments, equipment management departments, and hospital decision-makers, while improving the quality and efficiency of in-hospital equipment management. This practice could provide references for other public hospitals in China to optimize their equipment budget management.

Periodontal bone defects, primarily caused by periodontitis, are highly prevalent in clinical settings and manifest as bone fenestration, dehiscence, or attachment loss, presenting a significant challenge to oral health. In regenerative medicine, harnessing developmental principles for tissue repair offers promising therapeutic potential. Of particular interest is the condensation of progenitor cells, an essential event in organogenesis that has inspired clinically effective cell aggregation approaches in dental regeneration. However, the precise cellular coordination mechanisms during condensation and regeneration remain elusive. Here, taking the tooth as a model organ, we employed single-cell RNA sequencing to dissect the cellular composition and heterogeneity of human dental follicle and dental papilla, revealing a distinct Platelet-derived growth factor receptor alpha (PDGFRA) mesenchymal stem/stromal cell (MSC) population with remarkable odontogenic potential. Interestingly, a reciprocal paracrine interaction between PDGFRA⁺ dental follicle stem cells (DFSCs) and CD31⁺ Endomucin⁺ endothelial cells (ECs) was mediated by Vascular endothelial growth factor A (VEGFA) and Platelet-derived growth factor subunit BB (PDGFBB). This crosstalk not only maintains the functionality of PDGFRA⁺ DFSCs but also drives specialized angiogenesis. In vivo periodontal bone regeneration experiments further reveal that communication between PDGFRA⁺ DFSC aggregates and recipient ECs is essential for effective angiogenic-osteogenic coupling and rapid tissue repair. Collectively, our results unravel the importance of MSC-EC crosstalk mediated by the VEGFA and PDGFBB-PDGFRA reciprocal signaling in orchestrating angiogenesis and osteogenesis. These findings not only establish a framework for deciphering and promoting periodontal bone regeneration in potential clinical applications but also offer insights for future therapeutic strategies in dental or broader regenerative medicine.
Receptor, Platelet-Derived Growth Factor alpha/metabolism* ; Humans ; Neovascularization, Physiologic/physiology* ; Dental Sac/cytology* ; Single-Cell Analysis ; Transcriptome ; Mesenchymal Stem Cells/metabolism* ; Bone Regeneration ; Animals ; Dental Papilla/cytology* ; Periodontium/physiology* ; Stem Cells/metabolism* ; Regeneration ; Angiogenesis

Objective:To explore the learning curve of primary urologists mastering Holmium laser enucleation of the prostate for the treatment of large volume benign prostatic hyperplasia (BPH).Methods:The clinical data of 92 patients with larger volume BPH who received HoLEP performed by a urologist in Beijing Friendship Hospital Pinggu Campus, Capital Medical University were retrospectively reviewed. 92 patients were divided into group A (1-23 cases, n=23), group B (24-46 cases, n=23), group C (47-69 cases, n=23), and group D (70-92 cases, n=23) based on the sequence of surgery. The clinical characteristics, including prostate volume, operation time, enucleation efficiency, indwelling catheter time, decrease value of hemoglobin, intraoperative blood transfusion, perioperative complications, and international prostate symptom score (IPSS), quality of life (QOL) score, Qmax, and postvoid residual urine (PVR) at 3 months postoperatively were compared between the four groups. Measurement data were expressed as mean ± standard deviation ( ± s), one-way analysis of variance was used for comparisons among multiple groups, and t-test was used for comparisons between two groups. Count data were expressed as the cases and percentage, and the Chi-square test was used for comparison between groups. Results:There were significant differences among the four groups in terms of operation time [(94.43±8.26) min, (86.39±5.89) min, (70.70±5.64) min, (64.70±4.23) min, P=0.001], enucleation efficiency [(0.90±0.08) mL/min, (1.01±0.07) mL/min, (1.23±0.12) mL/min, (1.34±0.12) mL/min, P=0.001], decrease value of hemoglobin [(25.98±1.39) g/L, (23.27±1.49) g/L, (20.03±1.07) g/L, (18.49±0.96) g/L, P=0.001] and indwelling catheter time [(5.91±1.54) d, (5.35±1.27) d, (3.39±0.72) d, (3.04±0.64) d, P=0.001]. Compared with group C and group D, the operation time was longer, the enucleation efficiency was lower, the decrease value of hemoglobin before and after the operation was higher, and the indwelling catheter time was longer, the above differences were all statistically significant ( P<0.05). However, there was no statistically significant difference between group A and group B, or group C and group D ( P>0.05). Among the 92 patients, only 3 patients received blood transfusion during operation, including 2 patients in group A and 1 patient in group B. 2 patients underwent surgical complications during the perioperative period. Among them, 1 patient suffered bladder wall injury due to improper operation of the tissue pulverizer in group A, and 1 patient developed prostatic capsule perforation in group B. Furthermore, after 56 cases of operation, a primary urologist can perform HoLEP surgery quickly and safely. Conclusion:The learning curve of a primary urologist mastering HoLEP for larger volume (≥ 80 mL) BPH was 56 procedures, and the operation efficiency and safety were significantly improved.

Objective Based on the assumption of spatial heterogeneity,the distribution pattern and risk characteristics of health poverty in middle-aged and elderly people with chronic diseases are described from the perspective of spatial differentiation.In order to providing a theoretical basis for the optimization of subsequent poverty reduction policies and a model policy for other countries.Methods It used factor detector and interaction detector to capture the role of single-factor and multi-factor interactions on the spatial differentiation of health poverty,and risk detectors were utilized to explore the high-risk factors in risky areas Results The single factor explanation of medical assistance and health education activities is prominent,and the factors such as PM2.5,old-age dependency ratio and urban unemployment rate have strong interaction.Furthermore,it identified high-risk factor characteristics in areas at high risk of health poverty.Conclusion The spatial differentiation pattern of health poverty among the middle-aged and elderly chronic disease population in China is the result of the synergistic driving effect of multidimensional factors,and there is variability in the risk characteristics among regions.The government should establish a contextual optimization strategy and pay attention to the joint effect of multiple factors to establish a synergistic management system.

Objective Based on the assumption of spatial heterogeneity,the distribution pattern and risk characteristics of health poverty in middle-aged and elderly people with chronic diseases are described from the perspective of spatial differentiation.In order to providing a theoretical basis for the optimization of subsequent poverty reduction policies and a model policy for other countries.Methods It used factor detector and interaction detector to capture the role of single-factor and multi-factor interactions on the spatial differentiation of health poverty,and risk detectors were utilized to explore the high-risk factors in risky areas Results The single factor explanation of medical assistance and health education activities is prominent,and the factors such as PM2.5,old-age dependency ratio and urban unemployment rate have strong interaction.Furthermore,it identified high-risk factor characteristics in areas at high risk of health poverty.Conclusion The spatial differentiation pattern of health poverty among the middle-aged and elderly chronic disease population in China is the result of the synergistic driving effect of multidimensional factors,and there is variability in the risk characteristics among regions.The government should establish a contextual optimization strategy and pay attention to the joint effect of multiple factors to establish a synergistic management system.

Human Respiratory Stem Cells (RSCs) play a crucial role in the maintenance, repair and regeneration of the respiratory system. As a novel therapeutic method, stem cell therapy is a popular research direction in the medical field. And with the in-depth research on the mechanism of pneumonia caused by respiratory infections in recent years, the use of RSCs to explore pneumonia caused by respiratory infections and its therapeutic strategies has become a hot topic. In this paper, we firstly outlined the types of RSCs, summarized the mechanism of pneumonia caused by respiratory tract infections, discussed the advantages of RSCs application and the progress of culture differentiation, and elaborated the therapeutic exploration of RSCs in pneumonia caused by respiratory tract infections.

The construction of an information system for equipment budget management in public hospitals is an important measure to strengthen comprehensive budget management, serving as an important foundation for promoting the development of clinical disciplines and enhancing operational management. Since September 2023, a tertiary public hospital had explored the construction of equipment budget management informatization. This practice had established a supporting budget management information system, which included an equipment demand reserve library and a general use product library, linked performance evaluation indicators, implemented visualizing real-time project progress, and strengthened data governance. A series of measures had been taken to move management to equipment demand research, expand the time window for departments to fill in budget requirements, simplify the department application process, and achieve a closed-loop management of the entire chain of department equipment demand research, budget approval, and execution, ensuring the rationality and accuracy of the budget. By the end of 2024, the budget management information system had covered 87 departments and included 30 000 sets of equipment applications, providing detailed data support and critical management references for demand departments, equipment management departments, and hospital decision-makers, while improving the quality and efficiency of in-hospital equipment management. This practice could provide references for other public hospitals in China to optimize their equipment budget management.

Objective To develop and evaluate a fine-tuned large language model(LLM)for traditional Chinese medicine(TCM)prescription recommendation named TCMLLM-PR.Methods First,we constructed an instruction-tuning dataset containing 68 654 samples(ap-proximately 10 million tokens)by integrating data from eight sources,including four TCM textbooks,Pharmacopoeia of the People's Republic of China 2020(CHP),Chinese Medicine Clinical Cases(CMCC),and hospital clinical records covering lung disease,liver disease,stroke,diabetes,and splenic-stomach disease.Then,we trained TCMLLM-PR using Chat-GLM-6B with P-Tuning v2 technology.The evaluation consisted of three aspects:(i)compari-son with traditional prescription recommendation models(PTM,TCMPR,and PresRecST);(ii)comparison with TCM-specific LLMs(ShenNong,Huatuo,and HuatuoGPT)and general-domain ChatGPT;(iii)assessment of model migration capability across different disease datasets.We employed precision,recall,and F1 score as evaluation metrics.Results The experiments showed that TCMLLM-PR significantly outperformed baseline models on TCM textbooks and CHP datasets,with F1@10 improvements of 31.80%and 59.48%,respectively.In cross-dataset validation,the model performed best when migrating from TCM textbooks to liver disease dataset,achieving an F1@10 of 0.155 1.Analysis of real-world cases demonstrated that TCMLLM-PR's prescription recommendations most closely matched actual doctors'prescriptions.Conclusion This study integrated LLMs into TCM prescription recommendations,leverag-ing a tailored instruction-tuning dataset and developing TCMLLM-PR.This study will pub-licly release the best model parameters of TCMLLM-PR to promote the development of the decision-making process in TCM practices(https://github.com/2020MEAI/TCMLLM).

Objective To develop and evaluate a fine-tuned large language model(LLM)for traditional Chinese medicine(TCM)prescription recommendation named TCMLLM-PR.Methods First,we constructed an instruction-tuning dataset containing 68 654 samples(ap-proximately 10 million tokens)by integrating data from eight sources,including four TCM textbooks,Pharmacopoeia of the People's Republic of China 2020(CHP),Chinese Medicine Clinical Cases(CMCC),and hospital clinical records covering lung disease,liver disease,stroke,diabetes,and splenic-stomach disease.Then,we trained TCMLLM-PR using Chat-GLM-6B with P-Tuning v2 technology.The evaluation consisted of three aspects:(i)compari-son with traditional prescription recommendation models(PTM,TCMPR,and PresRecST);(ii)comparison with TCM-specific LLMs(ShenNong,Huatuo,and HuatuoGPT)and general-domain ChatGPT;(iii)assessment of model migration capability across different disease datasets.We employed precision,recall,and F1 score as evaluation metrics.Results The experiments showed that TCMLLM-PR significantly outperformed baseline models on TCM textbooks and CHP datasets,with F1@10 improvements of 31.80%and 59.48%,respectively.In cross-dataset validation,the model performed best when migrating from TCM textbooks to liver disease dataset,achieving an F1@10 of 0.155 1.Analysis of real-world cases demonstrated that TCMLLM-PR's prescription recommendations most closely matched actual doctors'prescriptions.Conclusion This study integrated LLMs into TCM prescription recommendations,leverag-ing a tailored instruction-tuning dataset and developing TCMLLM-PR.This study will pub-licly release the best model parameters of TCMLLM-PR to promote the development of the decision-making process in TCM practices(https://github.com/2020MEAI/TCMLLM).