Based on his extensive clinical experience and the team's mechanistic research, Professor XU Nenggui has proposed the academic concept that "the governor vessel governs the brain and treats cerebral viscus diseases", and established a novel acupuncture approach for encephalopathy treatment centered on the integrated theory of "governor vessel-brain-mind", and developed a staged acupuncture protocol of "governor vessel regulating spirit" for ischemic stroke. This article introduces the academic features of this method in treating post-stroke dysphagia from four aspects: theoretical framework, treatment principles and point selection, mechanistic research, and clinical case studies. In clinical application, the method emphasizes syndrome differentiation based on meridians, harmonization between the conception and governor vessels; precise acupoint selection to treat both form and spirit; stage-specific differentiation with targeted needling. Furthermore, Professor XU integrates basic research with clinical practice, focusing on the neurobiological mechanisms underlying the efficacy of acupuncture in treating post-stroke dysphagia.
Acupuncture Therapy/methods* ; Humans ; Deglutition Disorders/psychology* ; Stroke/complications* ; Meridians ; Acupuncture Points

BACKGROUND: Several studies have demonstrated the occurrence of secondary tumors as a rare but significant complication of chimeric antigen receptor T (CAR-T) cell therapy, underscoring the need for a detailed investigation. Given the limited variety of secondary tumor types reported to date, a comprehensive characterization of the various secondary tumors arising after CAR-T therapy is essential to understand the associated risks and to define the role of the immune microenvironment in malignant transformation. This study aims to characterize the immune microenvironment of a newly identified secondary tumor post-CAR-T therapy, to clarify its pathogenesis and potential therapeutic targets. METHODS: In this study, the bone marrow (BM) samples were collected by aspiration from the primary and secondary tumors before and after CD19 CAR-T treatment. The CD45 + BM cells were enriched with human CD45 microbeads. The CD45 + cells were then sent for 10× genomics single-cell RNA sequencing (scRNA-seq) to identify cell populations. The Cell Ranger pipeline and CellChat were used for detailed analysis. RESULTS: In this study, a rare type of secondary chronic myelomonocytic leukemia (CMML) were reported in a patient with diffuse large B-cell lymphoma (DLBCL) who had previously received CD19 CAR-T therapy. The scRNA-seq analysis revealed increased inflammatory cytokines, chemokines, and an immunosuppressive state of monocytes/macrophages, which may impair cytotoxic activity in both T and natural killer (NK) cells in secondary CMML before treatment. In contrast, their cytotoxicity was restored in secondary CMML after treatment. CONCLUSIONS This finding delineates a previously unrecognized type of secondary tumor, CMML, after CAR-T therapy and provide a framework for defining the immune microenvironment of secondary tumor occurrence after CAR-T therapy. In addition, the results provide a rationale for targeting macrophages to improve treatment strategies for CMML treatment.
Humans ; Lymphoma, Large B-Cell, Diffuse/therapy* ; Tumor Microenvironment/genetics* ; Antigens, CD19/metabolism* ; Leukemia, Myelomonocytic, Chronic/genetics* ; Immunotherapy, Adoptive/adverse effects* ; Male ; Single-Cell Analysis/methods* ; Female ; Sequence Analysis, RNA/methods* ; Receptors, Chimeric Antigen ; Middle Aged

Objective:To compare the etiological characteristics between influenza-like illness (ILI) cases in outpatient and emergency departments and those with severe acute respiratory infection (SARI) in Guangdong Province, hoping to provide scientific evidence for the treatment, prevention, and control of respiratory infectious diseases.Methods:Laboratory testing for multiple respiratory pathogens was conducted on 6 090 specimens collected from ILI and SARI cases in Guangdong Province from August to December 2023. Chi-square test was used to analyze the differences in positive rates. Results:The overall positive rate of respiratory pathogens was 49.5% (3 016/6 090). The positive rate was 54.5% (2 260/4 145) in ILI cases and 38.9% (756/1 945) in SARI cases. The overall positive rate was higher in ILI cases than in SARI cases across all genders and age groups, and in most cities of the province, with statistically significant differences ( P<0.05). No significant difference was found in the overall positive rate between different genders. However, the difference between different age groups was statistically significant( P<0.001), with the highest rate identified in children aged 5-14 years (57.2%, 957/1 673). The main pathogens detected in ILI cases were influenza virus, human rhinovirus/enterovirus, and Streptococcus pneumoniae, while in SARI cases they were Mycoplasma pneumoniae, human rhinovirus/enterovirus, and influenza virus. The positive rates of adenovirus, human parainfluenza virus, SARS-CoV-2, human coronavirus, influenza virus, and Streptococcus pneumoniae were significantly higher in ILI cases than in SARI cases, while the positive rate of Mycoplasma pneumoniae was significantly higher in SARI cases ( P<0.05). Moreover, ILI cases were characterized by a higher risk of coinfection compared with SARI cases, especially in males or those aged 25-59 years. Conclusions:There are differences in the detection rates and spectrum of respiratory pathogens between ILI and SARI cases in Guangdong Province. Case features should be considered when developing strategies for preventing and treating respiratory infections.

Objective Using Meta-analysis to systematically evaluate the incidence and risk factors of pulmonary infection occurring in patients with acute ischemic stroke(AIS)after receiving mechanical thrombectomy.Methods A computerized retrieval of academic papers concerning the case-control study and cohort study of lung infection in patients with AIS after mechanical thrombectomy from the databases of PubMed,Web of Science,Embase,Cochrane Library,China Knowledge Network,Wanfang Data Knowledge Service Platform,and Wipro.com databases was conducted by two independent investigators.The retrieval time period was from the establishment of the database to December 2023.STAT A 16.0 software was used to make the Meta-analysis of the extracted literature.Results A total of 10 literature were included,with a combined sample size of 6 149 cases and 2 076 cases occurring lung infections.Meta-analysis revealed that the pulmonary infection in patients after mechanical thrombectomy for AIS showed a high degree of heterogeneity in the included studies(I2=97.87％,P＜0.001),and a random-effects model yielded an incidence of 31.8％for pulmonary infection.Risk factors for the occurrence of postoperative lung infection included atrial fibrillation(OR=1.33,95％CI:1.10-1.6,P=0.004),dysphagia(OR=3.83,95％CI:2.43-6.05,P＜0.001),high NIHSS score(OR=1.43,95％CI:1.05-1.94,P=0.023),impaired consciousness(OR=2.29,95％CI:1.38-3.81,P＜0.001),and intraoperative use of sedative drugs(OR=3.21,95％CI:2.91-3.54,P＜0.001).Conclusion The existing evidences indicate that patient's age ≥60 years,atrial fibrillation,dysphagia,impaired consciousness,high NIHSS score,and intraoperative use of sedative drugs are risk factors for the occurrence of pulmonary infection in AIS patients after receiving mechanical thrombectomy.In clinical practice,these risk factors should be highly valued,and these risk factors should be included in the postoperative comprehensive assessment and intervention strategies for patients so as to reduce the incidence of pulmonary infection.

Objective To evaluate the risk factors for pulmonary infection in patients with acute ischemic stroke after receiving mechanical thrombectomy and to construct a risk prediction model based on machine-learning algorithm technology.Methods A total of 315 patients with acute ischemic stroke,who received mechanical thrombectomy at the Kunming Yan'an Hospital and Kunming Municipal First People's Hospital,were enrolled in this study.The 315 patients who were admitted to the hospital between January 2019 and December 2023 were collected as the modeling group,and other 73 patients who were admitted to the hospital between January 2024 and September 2024 were collected as the validation group.The demographic materials and the clinical diagnosis and treatment data were collected within 24 h after admission,and the risk factors for pulmonary infection after mechanical thrombectomy were analyzed.A total of seven machine learning algorithms were employed to establish a predictive model for pulmonary infection in patients with large-vessel occlusive stroke after receiving mechanical thrombectomy.Based on the accuracy,recall,precision,F1 index,and area under the receiver operating characteristic curve(AUC),the performance of model was evaluated.Results The comprehensive performance in accuracy,recall,precision,F1 index and AUC of the gradient boosting classifier in both the modeling group and the validation group are all excellent.Conclusion The risk prediction model constructed on the basis of machine-learning algorithm technology can early identify lung infection and discover the risk factors in patients with acute ischemic stroke after receiving mechanical thrombectomy,therefore,the prevention and control measures can be promptly taken,the incidence of lung infection can be effectively decreased.

Osteoporosis is a systemic disease characterized by imbalanced bone metabolism and destruction of bone microstructure, with reduced bone density, decreased bone quality, and significantly increased risk of fracture as its hallmarks. At present, osteoporosis is primarily diagnosed through bone density measurement. However, this method has low sensitivity and is challenging for the early diagnosis of osteoporosis. We analyzed osteoporosis-related metabolomics studies based on blood, urine, and fecal samples, as well as the application of multi-omics approaches in elucidating its pathogenesis. Evidence suggests that metabolomics can detect metabolic alterations prior to measurable changes in bone mineral density, offering promising avenues for early osteoporosis detection. Blood-based metabolomics studies indicate that amino acid metabolism dysregulation is a key feature of osteoporosis. Specifically, glycine, glutamine, lysine, and hydroxyproline exhibit negative correlations with bone mineral density, whereas tryptophan, branched-chain amino acids, and arginine show positive associations. Lipid metabolism disturbances are characterized by increased levels of phosphatidylcholine, phosphatidylethanolamine, and triglycerides, alongside decreased levels of sphingomyelin and carnitine. Fecal metabolomics studies highlight the significance of the "gut-bone axis" in osteoporosis, where gut microbiota dysbiosis influences bone metabolism through modulation of arginine and proline metabolism and aminoacyl-tRNA biosynthesis pathways. Multi-omics approaches integrate metabolomics, genomics, proteomics, and other omics data to provide a more comprehensive understanding of osteoporosis' molecular mechanisms, enabling the identification of key biomarkers and therapeutic targets. Metabolomics holds considerable potential for early diagnosis, while multi-omics integration offers novel insights into the complex pathophysiological mechanisms underlying osteoporosis. As detection technologies and analytical methods continue to advance, omics-based strategies are expected to play a pivotal role in the development of precision medicine for osteoporosis.

Osteoporosis is a systemic disease characterized by imbalanced bone metabolism and destruction of bone microstructure, with reduced bone density, decreased bone quality, and significantly increased risk of fracture as its hallmarks. At present, osteoporosis is primarily diagnosed through bone density measurement. However, this method has low sensitivity and is challenging for the early diagnosis of osteoporosis. We analyzed osteoporosis-related metabolomics studies based on blood, urine, and fecal samples, as well as the application of multi-omics approaches in elucidating its pathogenesis. Evidence suggests that metabolomics can detect metabolic alterations prior to measurable changes in bone mineral density, offering promising avenues for early osteoporosis detection. Blood-based metabolomics studies indicate that amino acid metabolism dysregulation is a key feature of osteoporosis. Specifically, glycine, glutamine, lysine, and hydroxyproline exhibit negative correlations with bone mineral density, whereas tryptophan, branched-chain amino acids, and arginine show positive associations. Lipid metabolism disturbances are characterized by increased levels of phosphatidylcholine, phosphatidylethanolamine, and triglycerides, alongside decreased levels of sphingomyelin and carnitine. Fecal metabolomics studies highlight the significance of the "gut-bone axis" in osteoporosis, where gut microbiota dysbiosis influences bone metabolism through modulation of arginine and proline metabolism and aminoacyl-tRNA biosynthesis pathways. Multi-omics approaches integrate metabolomics, genomics, proteomics, and other omics data to provide a more comprehensive understanding of osteoporosis' molecular mechanisms, enabling the identification of key biomarkers and therapeutic targets. Metabolomics holds considerable potential for early diagnosis, while multi-omics integration offers novel insights into the complex pathophysiological mechanisms underlying osteoporosis. As detection technologies and analytical methods continue to advance, omics-based strategies are expected to play a pivotal role in the development of precision medicine for osteoporosis.

BACKGROUND:Growth factor is the key effect molecule that plays a role in platelet-rich plasma in clinical treatment.There are differences in the concentration of growth factor after different activators activate platelet-rich plasma,which is an important factor affecting clinical efficacy. OBJECTIVE:To analyze the influence of different activators on the mass concentration of growth factors in platelet-rich plasma. METHODS:Totally 12 healthy volunteers were recruited to collect EDTA-K2 anticoagulant venous blood.Secondary centrifugation was used to prepare platelet-rich plasma.The difference in mass concentrations of growth factors was compared between venous blood and platelet-rich plasma.The platelet-rich plasma was mixed with four activators(normal saline,thrombin,calcium gluconate,calcium gluconate+thrombin)according to the volume ratio of 10:1,and incubated in a constant temperature water bath at 37 °C for 30 minutes.After centrifugation,the supernatant was extracted and the mass concentration of growth factor was detected.The bacterial growth in supernatant was measured by blood agar plate.Pearson correlation was used to analyze the correlation between different activators and the mass concentration of growth factor in platelet-rich plasma,and the correlation between the value of thrombocytometer and the mass concentration of growth factors in platelet-rich plasma. RESULTS AND CONCLUSION:(1)The mass concentrations of platelet-derived growth factor-BB,platelet-derived growth factor-AB,vascular endothelial growth factor,and epidermal growth factor in platelet-rich plasma were 8.7,22.2,2.3,and 2.8 times of those in venous blood,respectively(P<0.05).(2)Compared with normal saline group,the mass concentrations of platelet-derived growth factor BB,platelet-derived growth factor AB,vascular endothelial growth factor,and epidermal growth factor were increased in the thrombin group,calcium gluconate group,and calcium gluconate+thrombin group(P<0.05).The mass concentration of platelet-derived growth factor BB in the thrombin group and calcium gluconate group was higher than that in the calcium gluconate+thrombin group(P<0.05),and the mass concentration of platelet-derived growth factor AB in the thrombin group was higher than that in the calcium gluconate group and calcium gluconate+thrombin group(P<0.05).Epidermal growth factor mass concentration in the thrombin group was lower than that in the calcium gluconate group and calcium gluconate+thrombin group(P<0.05).(3)The results of blood agar plate test showed no bacterial growth in the supernatant of the four groups.(4)Pearson correlation analysis showed that the mass concentration of platelet-derived growth factor BB in platelet-rich plasma was strongly positively correlated with thrombin(r=0.683,P<0.05),and the mass concentration of vascular endothelial growth factor was strongly positively correlated with thrombin,calcium gluconate,calcium gluconate+thrombin stimulant(r=0.730,0.789,0.686,P<0.05).There was no correlation between the value of thrombocytometer and the mass concentration of four kinds of growth factors(P>0.05).(5)The results suggest that different activators have an impact on the concentration of growth factors in platelet-rich plasma.It is suggested to choose different activators to improve clinical efficacy according to different growth factor mass concentrations and treatment needs.

Objective To observe the value of transvaginal two-dimensional ultrasonography(2D-TVS)combined with three-dimensional ultrasonography OmniView for diagnosing intrauterine adhesion(IUA).Methods Totally 200 women with suspected IUA were retrospectively enrolled,including 172 cases who were ultimately diagnosed IUA and the rest 28 without IUA.The efficacy of 2D-TVS combined with OmniView for diagnosing IUA was analyzed.Results Among 200 cases,150 cases were diagnosed IUA with 2D-TVS(135 cases were diagnosed correctly),167 cases were diagnosed IUA with OmniView(159 cases were diagnosed correctly),and 170 cases were diagnosed with combination of the above two(165 cases were diagnosed correctly).The area under the curve(AUC)of 2D-TVS,OmniView and 2D-TVS combined with OmniView for diagnosing IUA was 0.625,0.819 and 0.890,respectively,and 2D-TVS combined with OmniView had the highest AUC(both P＜0.05),with sensitivity of 95.93％,specificity of 82.14％,positive predictive value of 97.06％and negative predictive value of 76.67％.Conclusion 2D-TVS combined with OmniView could be helpful for diagnosing IUA.