Neurocritical care involves complex pathophysiological mechanisms, and its incidence is higher, injuries are more severe, and treatment is more challenging in high-altitude environments. This consensus, based on the latest domestic and international evidence-based medical data, establishes a standardized, goal-oriented framework for neurocritical care management applicable in high-altitude regions and nationwide. The consensus was developed following international standards for evidence quality assessment and underwent two rounds of Delphi expert consultation, resulting in 32 recommendation statements covering three parts: management systems, monitoring and assessment, and core strategies. Key updates include: advocating for the establishment of independent neurocritical care units and implementing precise tiered diagnosis and treatment based on the "Five Differences in Critical Care" concept; constructing a "trinity" multimodal brain monitoring system centered on cerebral blood flow, cerebral oxygenation, and brain function, emphasizing routine bedside transcranial Doppler ultrasound, cerebral oximetry, and continuous electroencephalography monitoring; shifting management strategies from mild hypothermia therapy to targeted temperature management, and defining the "446" target management pathway for the supercritical stage; emphasizing the assessment of static and dynamic cerebrovascular autoregulation functions through multimodal methods to achieve individualized optimal mean arterial pressure management; elevating cerebrospinal fluid management goals to the level of "glymphatic system" function maintenance; implementing a multidisciplinary collaborative, whole-process management model focusing on patients' long-term neurological functional outcomes; de-escalation criteria include multidimensional indicators such as recovery of brain structure, restoration of cerebrovascular autoregulation, improvement in cerebrospinal fluid dynamics, and reduction in biomarker levels; and integrating cutting-edge technologies like artificial intelligence into post-critical care management and rehabilitation planning. This consensus systematically integrates the entire process of neurocritical care management, reflecting the modern connotation of goal-oriented, dynamic, and multimodal integration in neurocritical care medicine. It aims to adapt to new trends such as deepening understanding of pathophysiological mechanisms, the integration of medicine and engineering, and the empowerment of artificial intelligence, thereby further advancing the discipline of critical care medicine.

Collagen is a major structural protein in the matrix of animal cells and the most widely distributed and abundant functional protein in mammals. Collagen’s good biocompatibility, biodegradability and biological activity make it a very valuable biomaterial. According to the source of collagen, it can be broadly categorized into two types: one is animal collagen; the other is recombinant collagen. Animal collagen is mainly extracted and purified from animal connective tissues by chemical methods, such as acid, alkali and enzyme methods, etc. Recombinant collagen refers to collagen produced by gene splicing technology, where the amino acid sequence is first designed and improved according to one’s own needs, and the gene sequence of improved recombinant collagen is highly consistent with that of human beings, and then the designed gene sequence is cloned into the appropriate vector, and then transferred to the appropriate expression vector. The designed gene sequence is cloned into a suitable vector, and then transferred to a suitable expression system for full expression, and finally the target protein is obtained by extraction and purification technology. Recombinant collagen has excellent histocompatibility and water solubility, can be directly absorbed by the human body and participate in the construction of collagen, remodeling of the extracellular matrix, cell growth, wound healing and site filling, etc., which has demonstrated significant effects, and has become the focus of the development of modern biomedical materials. This paper firstly elaborates the structure, type, and tissue distribution of human collagen, as well as the associated genetic diseases of different types of collagen, then introduces the specific process of producing animal source collagen and recombinant collagen, explains the advantages of recombinant collagen production method, and then introduces the various systems of expressing recombinant collagen, as well as their advantages and disadvantages, and finally briefly introduces the application of animal collagen, focusing on the use of animal collagen in the development of biopharmaceutical materials. In terms of application, it focuses on the use of animal disease models exploring the application effects of recombinant collagen in wound hemostasis, wound repair, corneal therapy, female pelvic floor dysfunction (FPFD), vaginal atrophy (VA) and vaginal dryness, thin endometritis (TE), chronic endometritis (CE), bone tissue regeneration in vivo, cardiovascular diseases, breast cancer (BC) and anti-aging. The mechanism of action of recombinant collagen in the treatment of FPFD and CE was introduced, and the clinical application and curative effect of recombinant collagen in skin burn, skin wound, dermatitis, acne and menopausal urogenital syndrome (GSM) were summarized. From the exploratory studies and clinical applications, it is evident that recombinant collagen has demonstrated surprising effects in the treatment of all types of diseases, such as reducing inflammation, promoting cell proliferation, migration and adhesion, increasing collagen deposition, and remodeling the extracellular matrix. At the end of the review, the challenges faced by recombinant collagen are summarized: to develop new recombinant collagen types and dosage forms, to explore the mechanism of action of recombinant collagen, and to provide an outlook for the future development and application of recombinant collagen.

Electromagnetic fields can regulate the fundamental biological processes involved in bone remodeling. As a non-invasive physical therapy, electromagnetic fields with specific parameters have demonstrated therapeutic effects on bone remodeling diseases, such as fractures and osteoporosis. Electromagnetic fields can be generated by the movement of charged particles or induced by varying currents. Based on whether the strength and direction of the electric field change over time, electromagnetic fields can be classified into static and time-varying fields. The treatment of bone remodeling diseases with static magnetic fields primarily focuses on fractures, often using magnetic splints to immobilize the fracture site while studying the effects of static magnetic fields on bone healing. However, there has been relatively little research on the prevention and treatment of osteoporosis using static magnetic fields. Pulsed electromagnetic fields, a type of time-varying field, have been widely used in clinical studies for treating fractures, osteoporosis, and non-union. However, current clinical applications are limited to low-frequency, and research on the relationship between frequency and biological effects remains insufficient. We believe that different types of electromagnetic fields acting on bone can induce various “secondary physical quantities”, such as magnetism, force, electricity, acoustics, and thermal energy, which can stimulate bone cells either individually or simultaneously. Bone cells possess specific electromagnetic properties, and in a static magnetic field, the presence of a magnetic field gradient can exert a certain magnetism on the bone tissue, leading to observable effects. In a time-varying magnetic field, the charged particles within the bone experience varying Lorentz forces, causing vibrations and generating acoustic effects. Additionally, as the frequency of the time-varying field increases, induced currents or potentials can be generated within the bone, leading to electrical effects. When the frequency and power exceed a certain threshold, electromagnetic energy can be converted into thermal energy, producing thermal effects. In summary, external electromagnetic fields with different characteristics can generate multiple physical quantities within biological tissues, such as magnetic, electric, mechanical, acoustic, and thermal effects. These physical quantities may also interact and couple with each other, stimulating the biological tissues in a combined or composite manner, thereby producing biological effects. This understanding is key to elucidating the electromagnetic mechanisms of how electromagnetic fields influence biological tissues. In the study of electromagnetic fields for bone remodeling diseases, attention should be paid to the biological effects of bone remodeling under different electromagnetic wave characteristics. This includes exploring innovative electromagnetic source technologies applicable to bone remodeling, identifying safe and effective electromagnetic field parameters, and combining basic research with technological invention to develop scientifically grounded, advanced key technologies for innovative electromagnetic treatment devices targeting bone remodeling diseases. In conclusion, electromagnetic fields and multiple physical factors have the potential to prevent and treat bone remodeling diseases, and have significant application prospects.

Traditional Chinese medicine （TCM） thinking serves as a comprehensive cognitive approach of TCM in recognizing and solving problem. It encompasses specific techniques （methods）and particular structures （patterns） in application. Its essential characteristics include the holistic view of "harmony between humanity and nature"， the dialectical perspective of "differences and similarities in disease treatment"， and the practical outlook of "unity of knowledge and action". The methods of TCM thinking emphasizes the integration of multiple cognitive approaches， forming various modes of thinking such as TCM holistic thinking， TCM four-dimensional thinking， TCM Xiang （象） and numerical thinking， and TCM clinical thinking. Currently， TCM faces both opportunities and challenges. TCM thinking plays a crucial role in the inheritance and innovation pathways of TCM， such as "cultivating medicine through culture"， "leading medicine through pharmaceutical practices"， "boosting industries with pharmaceuticals"， and "benefiting the people through industry". At the same time， integrating TCM and modern technology not only enriches the connotation of TCM thinking， but also advances the innovation of TCM theories， addressing challenges in complex disease treatment， health management， and preventive healthcare. This integration promotes the continued prosperity of the TCM and accelerates its internationalization.

Objective By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.

ObjectiveTo analyze the characteristic expression patterns of six neurotransmitters including 5-hydroxytryptamine （5-HT）， dopamine （DA）， acetylcholine （ACh）， norepinephrine （NE）， inhibitory neurotransmitter （INH）， and excitatory neurotransmitter （EXC） in the whole brain and different brain regions of depression patients by Search of Encephalo Telex （SET）， providing new ideas for the study of heterogeneous etiology of depression. Methods（1） A retrospective study was conducted on supra-slow signals of EEG fluctuations in 1 028 patients with depression. The SET system was used to obtain the expression information of six neurotransmitters in the whole brain and 12 brain regions： left frontal region （F3）， right frontal region （F4）， left central region （C3）， right central region （C4）， left parietal region （P3）， right parietal region （P4）， left occipital region （O1）， right occipital region （O2）， left anterior temporal region （F7）， right anterior temporal region （F8）， left posterior temporal region （T5）， and right posterior temporal region （T6）. The expression information of each neurotransmitter was compared with the normal model， and it was found that single neurotransmitter was in one of three states： increased， decreased， or normal expression. The simultaneous expression states of six neurotransmitters in the brain space were referred to as the expression pattern of multiple neurotransmitters. （2） A MySQL database was established to analyze the actual expression patterns of different neurotransmitters in the whole brain of patients with depression. （3） Factor analysis was conducted to further analyze the characteristic rules of 78 variables of neurotransmitters in the whole brain and 12 brain regions in depression patients. Results（1） The expression of single neurotransmitters in the whole brain and different brain regions of the total depression population showed one of three expression states （increased/decreased/normal）， being normal in the majority. The decreased and increased expression of 5-HT， ACh， DA， INH， EXC， and NE in the whole brain occurred in 6% and 25%， 31% and 17%， 36% and 9%， 15% and 31%， 32% and 14%， and 22% and 22%， respectively. （2） The antagonizing pairs of neurotransmitters （EXC/INH， DA/5-HT， and ACh/NE） showed significant antagonistic relationships in the whole brain and different brain regions， with a strong negative correlation between EXC and INH （P<0.01， |r| values ranging from 0.69 to 0.76）， a strong negative correlation between DA and 5-HT （P<0.01， |r| values ranging from 0.83 to 0.90）， and a moderate negative correlation between ACh and NE （P<0.01， with |r| values ranging from 0.56 to 0.66）. Meanwhile， non-antagonizing pairs of neurotransmitters in the whole brain and different brain regions also showed correlations， with DA/NE （P<0.01， |r| values ranging from 0.38 to 0.46） and NE/EXC （P<0.01， |r| values ranging from 0.56 to 0.61） showing weak and moderate negative correlations， respectively， and DA/EXC showing a weak positive correlation （P<0.01， |r| values ranging from 0.38 to 0.47）. （3） The six neurotransmitters in the 1 028 patients with depression presented a total of 170 expression patterns in the whole brain. The top 30 expression patterns were reported in this paper， with a cumulative rate of 60.60%， including patterns ① INH+/5-HT-/ACh+/DA+/NE-/EXC- （9.05%）， ② INH+/5-HT-/ACh↓/DA+/NE-/EXC- （4.57%）， and ③ INH+/5-HT-/ACh+/DA+/NE↓/EXC- （3.31%）. That is， the proportion of depression patients with normal levels of all the six neurotransmitters was 9.05%， and the patients with at least one neurotransmitter abnormality accounted for 91.95%. （4） The factor analysis extracted 22 common factors from 78 variables in the whole brain and different brain regions. These common factors showed the absolute values of loadings ranging from 0.32 to 0.86 and the eigenvalues （F） ranging from 1.03 to 13.43， with a cumulative contribution rate of 76.82%. The characteristic expression patterns included ① ACh_P3↓/ACh_W↓/ACh_C3↓/ACh_F3↓/ACh_O1↓/ACh_T5↓/ACh_F7↓/NE_P3↑/NE_W↑/NE_C3↑/NE_F3↑/NE_O1↑/NE_T5↑/NE_F7↑ （F=13.43， whole brain）， ② 5-HT_O2↑/DA_O2↓/5-HT_P4↑/DA_P4↓/5-HT_W↑/DA_W↓/5-HT_C4↑/DA_C4↓ （F=5.94）， and ③ EXC_F4↓/DA_F4↓/NE_F4↑/INH_F4↑/5-HT_F4↑/ACh_F4↓ （F=5.33）. ConclusionThe actual 170 expression patterns of 6 neurotransmitters in the whole brain of 1 028 depression patients indicate that depression is a heterogeneous disease with individualized characteristics. The 22 characteristic expression patterns in the whole brain and 12 brain regions verify the pathogenesis hypothesis of multi-neurotransmitters oscillation imbalance in brains of depression patients. In summary， this study provides new guidance for the etiology， diagnosis， and treatment of depression and establishes a methodological foundation for the effectiveness evaluation of individualized treatment of depression by traditional Chinese medicine based on the objective biological markers.

ObjectiveTo analyze the characteristic expression patterns of six neurotransmitters including 5-hydroxytryptamine （5-HT）， dopamine （DA）， acetylcholine （ACh）， norepinephrine （NE）， inhibitory neurotransmitter （INH）， and excitatory neurotransmitter （EXC） in the whole brain and different brain regions of depression patients by Search of Encephalo Telex （SET）， providing new ideas for the study of heterogeneous etiology of depression. Methods（1） A retrospective study was conducted on supra-slow signals of EEG fluctuations in 1 028 patients with depression. The SET system was used to obtain the expression information of six neurotransmitters in the whole brain and 12 brain regions： left frontal region （F3）， right frontal region （F4）， left central region （C3）， right central region （C4）， left parietal region （P3）， right parietal region （P4）， left occipital region （O1）， right occipital region （O2）， left anterior temporal region （F7）， right anterior temporal region （F8）， left posterior temporal region （T5）， and right posterior temporal region （T6）. The expression information of each neurotransmitter was compared with the normal model， and it was found that single neurotransmitter was in one of three states： increased， decreased， or normal expression. The simultaneous expression states of six neurotransmitters in the brain space were referred to as the expression pattern of multiple neurotransmitters. （2） A MySQL database was established to analyze the actual expression patterns of different neurotransmitters in the whole brain of patients with depression. （3） Factor analysis was conducted to further analyze the characteristic rules of 78 variables of neurotransmitters in the whole brain and 12 brain regions in depression patients. Results（1） The expression of single neurotransmitters in the whole brain and different brain regions of the total depression population showed one of three expression states （increased/decreased/normal）， being normal in the majority. The decreased and increased expression of 5-HT， ACh， DA， INH， EXC， and NE in the whole brain occurred in 6% and 25%， 31% and 17%， 36% and 9%， 15% and 31%， 32% and 14%， and 22% and 22%， respectively. （2） The antagonizing pairs of neurotransmitters （EXC/INH， DA/5-HT， and ACh/NE） showed significant antagonistic relationships in the whole brain and different brain regions， with a strong negative correlation between EXC and INH （P<0.01， |r| values ranging from 0.69 to 0.76）， a strong negative correlation between DA and 5-HT （P<0.01， |r| values ranging from 0.83 to 0.90）， and a moderate negative correlation between ACh and NE （P<0.01， with |r| values ranging from 0.56 to 0.66）. Meanwhile， non-antagonizing pairs of neurotransmitters in the whole brain and different brain regions also showed correlations， with DA/NE （P<0.01， |r| values ranging from 0.38 to 0.46） and NE/EXC （P<0.01， |r| values ranging from 0.56 to 0.61） showing weak and moderate negative correlations， respectively， and DA/EXC showing a weak positive correlation （P<0.01， |r| values ranging from 0.38 to 0.47）. （3） The six neurotransmitters in the 1 028 patients with depression presented a total of 170 expression patterns in the whole brain. The top 30 expression patterns were reported in this paper， with a cumulative rate of 60.60%， including patterns ① INH+/5-HT-/ACh+/DA+/NE-/EXC- （9.05%）， ② INH+/5-HT-/ACh↓/DA+/NE-/EXC- （4.57%）， and ③ INH+/5-HT-/ACh+/DA+/NE↓/EXC- （3.31%）. That is， the proportion of depression patients with normal levels of all the six neurotransmitters was 9.05%， and the patients with at least one neurotransmitter abnormality accounted for 91.95%. （4） The factor analysis extracted 22 common factors from 78 variables in the whole brain and different brain regions. These common factors showed the absolute values of loadings ranging from 0.32 to 0.86 and the eigenvalues （F） ranging from 1.03 to 13.43， with a cumulative contribution rate of 76.82%. The characteristic expression patterns included ① ACh_P3↓/ACh_W↓/ACh_C3↓/ACh_F3↓/ACh_O1↓/ACh_T5↓/ACh_F7↓/NE_P3↑/NE_W↑/NE_C3↑/NE_F3↑/NE_O1↑/NE_T5↑/NE_F7↑ （F=13.43， whole brain）， ② 5-HT_O2↑/DA_O2↓/5-HT_P4↑/DA_P4↓/5-HT_W↑/DA_W↓/5-HT_C4↑/DA_C4↓ （F=5.94）， and ③ EXC_F4↓/DA_F4↓/NE_F4↑/INH_F4↑/5-HT_F4↑/ACh_F4↓ （F=5.33）. ConclusionThe actual 170 expression patterns of 6 neurotransmitters in the whole brain of 1 028 depression patients indicate that depression is a heterogeneous disease with individualized characteristics. The 22 characteristic expression patterns in the whole brain and 12 brain regions verify the pathogenesis hypothesis of multi-neurotransmitters oscillation imbalance in brains of depression patients. In summary， this study provides new guidance for the etiology， diagnosis， and treatment of depression and establishes a methodological foundation for the effectiveness evaluation of individualized treatment of depression by traditional Chinese medicine based on the objective biological markers.

Objective: To investigate the current status of knowledge, attitudes and practices regarding drinking water among primary school students in rural areas of China, so as to provide scientific basis for implementing health interventions related to drinking water. Methods: From November to December 2023, a stratified cluster random sampling method was employed to select 6 354 fourth to sixth grade primary school students in Shanxi, Zhejiang, Jiangxi, Guangxi and Gansu for a questionnaire survey. A uniformly designed questionnaire (including basic information, drinking water-related knowledge, attitudes and practices indicators) was distributed and completed by the students themselves. The χ 2 test was used to analyze the differences in drinking water-related indicators among students of different gender and boarder, and Logistic regression was used to analyze the influencing factors of drinking water practices among students. Results: Among the indicators of drinking water knowledge, the awareness rate of appropriate daily water intake for respective student age groups was the lowest (27.90%). The awareness rate among nonresident students was significantly higher than that among boarding students (31.29%, 15.49%, χ 2=132.75, P <0.01). Regarding attitudes toward drinking water, 13.33% of the students believed that well water or tap water could be drunk directly, and 9.58% believed that going to the toilet at school was troublesome. Regarding practices, the self-reported water intake among students was 1 000 (600, 1 200) mL. The results of multifactorial Logistic regression showed that higher grades ( OR=1.60, 95%CI =1.34-1.92), nonresident students ( OR=1.32, 95%CI = 1.15 -1.52), northern region ( OR=1.43, 95%CI =1.27-1.61), knowledge of appropriate daily water intake ( OR=1.41, 95%CI =1.24-1.60), drinking temperature ( OR=1.43, 95%CI =1.28-1.60), scientific hydration methods ( OR=1.25, 95%CI =1.08- 1.44 ), and adopting scientific hydration methods regularly ( OR=1.75, 95%CI =1.50-2.04) were the independent influences on daily water intake attainment ( P <0.05). Conclusions Rural primary school students lack knowledge about healthy drinking water, have cognitive biases about safe drinking water and exhibit unhealthy drinking behavior. It is suggested that health education be carried out in combination with the characteristics of students to enhance their drinking water literacy.

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

OBJECTIVE: To investigate the common mechanisms among collagen-induced arthritis (CIA), bleomycin (BLM)-induced pulmonary fibrosis, and CIA+BLM to evaluate the therapeutic effect of triptolide (TP) on CIA+BLM. METHODS: Thirty-six male Sprague-Dawley rats were randomly assigned to 6 groups according to a random number table (n=6 per group): normal control (NC), CIA, BLM, combined CIA+BLM model, TP low-dose (TP-L, 0.0931 mg/kg), and TP high-dose (TP-H, 0.1862 mg/kg) groups. The CIA model was induced by intradermal injection at the base of the tail with emulsion of bovine type II collagen and incomplete Freund's adjuvant (1:1), with 200 µL administered on day 0 and a booster of 100 µL on day 7. Pulmonary fibrosis was induced via a single intratracheal injection of BLM (5 mg/kg). The CIA+BLM model combined both protocols, and TP was administered orally from day 14 to 35. After successful modeling, arthritis scores were recorded every 3 days, and pulmonary function was assessed once at the end of the treatment period. Lung tissues were collected for histological analysis (hematoxylin eosin and Masson staining), immunohistochemistry, measurement of hydroxyproline (HYP) content, and calculation of lung coefficient. In addition, HE staining was performed on the ankle joint. Total RNA was extracted from lung tissues for transcriptomic analysis. Differentially expressed genes (DEGs) were compared with those from the RA-associated interstitial lung diseases patient dataset GSE199152 to identify overlapping genes, which were then used to construct a protein-protein interaction network. Hub genes were identified using multiple topological algorithms. RESULTS: The successfully established CIA+BLM rat model exhibited significantly increased arthritis scores and severe pulmonary fibrosis (P<0.01). By intersecting the DEGs obtained from transcriptomic analysis of lung tissues in CIA, BLM, and CIA+BLM rats with DEGs from rheumatoid arthritis-interstitial lung disease patients (GSE199152 dataset), 50 upregulated and 44 downregulated genes were identified. Through integrated PPI network analysis using multiple topological algorithms, IGF1 was identified as a central hub gene. TP intervention significantly improved pulmonary function by increasing peak inspiratory flow (P<0.01), and reduced lung index and HYP content (P<0.01). Histopathological analysis showed that TP alleviated alveolar collapse, interstitial thickening, and collagen deposition in the lung tissues (P<0.01). Moreover, TP treatment reduced the expression of collagen type I and α-SMA and increased E-cadherin levels (P<0.01). TP also significantly reduced arthritis scores and ameliorated synovial inflammation (P<0.05). Both transcriptomic and immunohistochemical analyses confirmed that IGF1 expression was elevated in the CIA+BLM group and downregulated following TP treatment (P<0.05). CONCLUSION TP exerts protective effects in the CIA+BLM model by alleviating arthritis and pulmonary fibrosis through the inhibition of IGF1-mediated EMT.
Animals ; Pulmonary Fibrosis/complications* ; Bleomycin/adverse effects* ; Phenanthrenes/pharmacology* ; Male ; Rats, Sprague-Dawley ; Diterpenes/pharmacology* ; Epoxy Compounds/therapeutic use* ; Arthritis, Experimental/complications* ; Insulin-Like Growth Factor I/metabolism* ; Rats ; Lung/physiopathology*