Chronic obstructive pulmonary disease （COPD） is a chronic respiratory disease that poses a significant threat to global health， exhibiting high morbidity， disability and mortality rate， with its prevention and treatment situation becoming increasingly critical. The pathogenesis of COPD is complex， and the underlying cellular and molecular biological mechanisms remain incompletely elucidated. Programmed cell death （PCD） is the process wherein cells actively undergo demise to maintain internal environmental stability in response to certain signals or specific stimuli. Contemporary medical research indicates that the dysregulation of PCD patterns such as apoptosis， necroptosis， pyroptosis， autophagy， and ferroptosis is closely related to the onset and progression of COPD. Clarifying the molecular mechanisms of PCD in COPD may provide novel perspectives for in-depth understanding and prevention of the disease. Traditional Chinese medicine （TCM） is characterized by holistic regulation. In recent years， extensive research has been conducted in the TCM field focusing on modulating apoptosis， necroptosis， pyroptosis， autophagy， and ferroptosis for the treatment of COPD， yielding remarkable achievements. Therefore， this study systematically explored the molecular mechanism of PCD in COPD and reviewed the potential mechanisms and intervention status of TCM targeting PCD in COPD， aiming to provide insights and references for the clinical prevention， treatment and in-depth research of COPD.

Chronic obstructive pulmonary disease （COPD） is a chronic respiratory disease that poses a significant threat to global health， exhibiting high morbidity， disability and mortality rate， with its prevention and treatment situation becoming increasingly critical. The pathogenesis of COPD is complex， and the underlying cellular and molecular biological mechanisms remain incompletely elucidated. Programmed cell death （PCD） is the process wherein cells actively undergo demise to maintain internal environmental stability in response to certain signals or specific stimuli. Contemporary medical research indicates that the dysregulation of PCD patterns such as apoptosis， necroptosis， pyroptosis， autophagy， and ferroptosis is closely related to the onset and progression of COPD. Clarifying the molecular mechanisms of PCD in COPD may provide novel perspectives for in-depth understanding and prevention of the disease. Traditional Chinese medicine （TCM） is characterized by holistic regulation. In recent years， extensive research has been conducted in the TCM field focusing on modulating apoptosis， necroptosis， pyroptosis， autophagy， and ferroptosis for the treatment of COPD， yielding remarkable achievements. Therefore， this study systematically explored the molecular mechanism of PCD in COPD and reviewed the potential mechanisms and intervention status of TCM targeting PCD in COPD， aiming to provide insights and references for the clinical prevention， treatment and in-depth research of COPD.

Viral pneumonia is an infectious disease caused by virus invading the lung parenchyma and interstitial tissue and causing lung inflammation， with the incidence rising year by year. Traditional Chinese medicine （TCM） can treat viral pneumonia in a multi-component， multi-target， and holistic manner by targeting the core pathogenesis of pneumonia caused by different respiratory viruses， demonstrating minimal side effects and significant advantages. According to the theory of healthy Qi and pathogenic Qi in TCM， the struggle between healthy Qi and pathogenic Qi and the imbalance between immunity and inflammation run through the entire process of viral pneumonia， and the immunity-inflammation status at different stages of the disease reflects different relationships between healthy Qi and pathogenic Qi. Immune dysfunction leads to the deficiency of healthy Qi， causing viral infections. The struggle between healthy Qi and pathogenic Qi causes immunity-inflammation imbalance， leading to the onset of viral pneumonia. Inflammatory damage causes persistent accumulation of phlegm and stasis， leading to the progression of viral pneumonia. The cytokine storm causes immunodepletion， leading to the excess of pathogenic Qi and diminution of healthy Qi and the deterioration of viral pneumonia. After the recovery from viral pneumonia， there is a long-term imbalance between immunity and micro-inflammation， which results in healthy Qi deficiency and pathogenic Qi lingering. Healthy Qi deficiency and pathogenic Qi excess act as common core causes of pneumonia caused by different respiratory viruses. Clinical treatment should emphasize both replenishing healthy Qi and eliminating pathogenic Qi， helping to restore the balance between healthy Qi and pathogenic Qi as well as between immunity and inflammation， thus promoting the recovery of patients from viral pneumonia. According to the TCM theory of healthy Qi and pathogenic Qi， this article summarizes the immunity-inflammation mechanisms at different stages of viral pneumonia， and explores the application of the method of replenishing healthy Qi and eliminating pathogenic Qi in viral pneumonia. The aim is to probe into the scientific connotation of the TCM theory of healthy Qi and pathogenic Qi in viral pneumonia and provide ideas for the clinical application of the method of replenishing healthy Qi and eliminating pathogenic Qi to assist in the treatment of viral pneumonia.

Platelets are well-known for their functions in blood clotting and vascular repair. However, in recent years, the regulatory role of platelets in the occurrence and development of malignant tumors has received significant attention. While extensive research has been conducted on the regulation of tumors by circulating platelets in peripheral blood, there is a lack of coherence and continuity among these studies. The tumor microenvironment encompasses the intricate network of cellular and acellular elements that surround and interact with tumor cells, creating a supportive ecosystem for their survival and growth. It plays a crucial role in the initiation and progression of tumors. Similar to dark matter in the universe, platelets, as tiny and enigmatic entities, play an essential role in tumor development and treatment within the tumor microenvironment. Although our current understanding of platelet regulation in the tumor microenvironment is limited, they hold immense untapped potential. In-depth studies on the tumor microenvironment have revealed platelets as a meaningful component, influencing various aspects of tumor development, metastasis, and immune evasion. Platelets, through the release of various bioactive substances or direct interaction with tumor cells, impact tumor progression while being influenced by the tumor in return. Therefore, understanding the role and mechanisms of platelets in the tumor microenvironment is of great importance for tumor prevention and treatment. This review provides a summary of the research progress on the interplay between platelets and tumors in the tumor microenvironment, and presents a promising outlook on the potential of platelets in tumor therapy.

Objective To investigate the effect of compound betamethasone adjuvant on break-through pain after unicompartmental knee arthroplasty under sciatic nerve combined with femoral nerve block.Methods A total of 100 patients underwent unicondylar knee arthroplasty,32 males and 68 females,aged 55-75 years,BMI 18.5-35.0 kg/m2,ASA physical status Ⅰ-Ⅲ,were divided into three groups according to random number table method:no adjuvant group(group C,n=34),dexamethasone adjuvant group(group D,n=33)and compound betamethasone adjuvant group(group B,n=33).The patients in the three groups received sciatic nerve block and 0.4％ropivacaine 15 ml before anesthesia in-duction,then femoral nerve block,0.4％ropivacaine 15 ml in group C,0.4％ropivacaine 15 ml in group D(containing dexamethasone 5 mg),and 0.4％ropivacaine 15 ml in group B(containing compound beca-methasone 4 mg).The occurrence of breakthrough pain,the number of effective analgesic pump compres-sions,opioid dosage,and the number of remedial analgesia cases were recorded.The ground movement dis-tance was recorded 0-24 hours,24-48 hours,and 48-72 hours after operation.The sleep quality scores and adverse events were also recorded.Results Compared with group C,the incidence rate of breakthrough pain was lower(P＜0.05),the number of effective analgesia pump compressions,the dosage of opioid,and the sleep quality score on the first night after operation were significantly decreased in group B(P＜0.05).Compared with group D,the incidence rate of breakthrough pain and breakthrough pain score were lower(P＜0.05),the number of effective analgesia pump compressions,the dosage of opioid,and the sleep quality score on the 1 st night after operation were significantly decreased in group B(P＜0.05).There was no significant difference in the ground movement distance of in different time periods and inci-dence of adverse events among the three groups.Conclusion Compound betamethasone adjuvant can reduce the incidence of breakthrough pain after unicompartmental knee arthroplasty under sciatic nerve com-bined with femoral nerve block,provide perfect analgesic effect,reduce postoperative opioid consumption,and improve the sleep quality of patients on the first night after surgery.

Objective:To evaluate the detection performance of left ventricular ejection fraction (LVEF) in patients with chronic renal failure (CRF) by an artificial intelligence (AI) model based on yolox framework integrating left ventricular segmentation and critical point detection.Methods:From January 2019 to June 2023, a total of 4 284 echocardiographic images of 2 000 adults aged 18-80 years without segmental wall motion abnormalities, structural heart disease, cardiac surgery or cardiomyopathy were collected in Henan Provincial People′s Hospital to delineate the endocardial membrane, as a training set, an AI model based on yolox framework integrating left ventricular segmentation and critical point detection was established. The images were divided into the training set( n=1 675) and the test set( n=325) in a ratio of about 5∶1. All 228 echocardiographic images of 100 normal adult volunteers who were treated in Henan Provincial Chest Hospital from May 2020 to May 2021 were collected as external test set validation. All 792 echocardiographic images of 204 patients treated in Henan Provincial People′s Hospital from April 2019 to June 2023 were continuously enrolled to evaluate the measurement efficiency of AI model. Spearman correlation statistical method was used to analyze the consistency of AI model measurement with manual measurement and TomTec software measurement methods of 3 senior echocardiographic professionals. Subjects were divided into clear image group, unclear image group, normal LVEF group and reduced LVEF group, the differences of general data between the two groups were compared. The correlation coefficient(ICC) within the group was calculated to analyze the consistency, so as to evaluate the model performance. Results:LVEF measured by AI model was significantly correlated with both manual measurement and TomTec model measurement ( rs=0.834, 0.826; all P<0.01). ICC values of the clear image group and the unclear image group were 0.96 and 0.97, respectively. ICC values for all subjects, normal LVEF group and reduced LVEF group were 0.96, 0.90 and 0.96, respectively. Conclusions:The AI model based on yolox framework integrating left ventricular segmentation and critical point detection has good diagnostic performance in the automatic measurement of LVEF in patients with CRF.

A fixation device for experimental rat in moxibustion was developed. Using this device, the points for moxibustion can be fully exposed, and the temperature of moxibustion be relatively constant. This fixation device consists of three parts: fixation seat, fixation clip and moxa-stick holder; characterized as the flexible fixation and easy operation. The device is advantaged at simultaneous operation of moxibustion at many points and supports the point combinations. It makes up for the shortcomings of the existing fixation devices, reduces the workload of moxibustion in experimental rat and improves the work efficiency and experimental safety of experimenters.
Animals ; Rats ; Moxibustion/methods* ; Equipment Design ; Acupuncture Points ; Humans ; Male ; Rats, Sprague-Dawley

Objective: To investigate the expression and molecular mechanism of dickkopf 1 ( DKK1 ) in tongue squamous cell carcinoma (TSCC) by bioinformatics method and molecular biology experiments． Methods: The patients information wasdownload from TCGA-TSCC database，the differentially expressed genes between the cancer and normal tissues were screened by NetworkAnalysed site，the key genes and clinical prognosis were identified through Kaplan-Meier analysis and Lasson regression，the functions and pathways of differentially expressed genes were gained by GO and KEGG database，the expression of DKK1 mRNA and protein in TSCC as well as its relationship with clinicopathological features were analyzed by UALCAN database and immunohistochemistry．Western blot assay was conducted to detect the protein expression of DKK1 in TSCC cells，and siRNA was used to konck down the expression of DKK1 protein in Cal27 cells. Results : The three key genes DKK1，CYP19A1 and IRX4， which were highly expressed in tongue squamous cell carcinoma and the survival rate of TSCC patients with high expression group was poor，were screened through NetworkAnalysed ，Kaplan-Meier analysis and Lasson regression method．UALCAN database showed that the mRNA level of DKK1 in TSCC tissues was higher than that in normal tissues，and its high expression was significantly correlated with clinical stage，histological grade and lymph node metastasis of TSCC patients．The immunohistochemistry assay suggested that the positive rate of DKK1 protein in clinical stage Ⅲ + Ⅳ TSCC tissues was significantly higher than that in stage Ⅰ + Ⅱ TSCC tissues．In addition， the expression level of DKK1 protein in TSCC tissues was significantly higher than that in adjacent tissues．Western blot assay also showed that the protein expression of DKK1 in TSCC cell Cal27 was much higher than normal oral epithelial cell HOEC．When knock down the protein expression of DKK1 in Cal27，the expression of β-catenin、p- p65 和 p65 werealso reduced． Conclusion DKK1 is highly expressed in tongue squamous cell carcinoma tissues and cells and plays an important role．It may be a new target for early diagnosis and drug treatment of TSCC.

3D bioprinting technology is a rapidly developing technique that employs bioinks containing biological materials and living cells to construct biomedical products. However, 3D-printed tissues are static, while human tissues are in real-time dynamic states that can change in morphology and performance. To improve the compatibility between in vitro and in vivo environments, an in vitro tissue engineering technique that simulates this dynamic process is required. The concept of 4D printing, which combines "3D printing + time" provides a new approach to achieving this complex technique. 4D printing involves applying one or more smart materials that respond to stimuli, enabling them to change their shape, performance, and function under the corresponding stimulus to meet various needs. This article focuses on the latest research progress and potential application areas of 4D printing technology in the cardiovascular system, providing a theoretical and practical reference for the development of this technology.
Humans ; Tissue Engineering/methods* ; Bioprinting/methods* ; Printing, Three-Dimensional ; Cardiovascular System ; Tissue Scaffolds

Objective:To assess the effectiveness of a model created using clinical features and preoperative chest CT imaging features in predicting the chronic obstructive pulmonary disease (COPD) among patients diagnosed with lung cancer.Methods:A retrospective analysis was conducted on clinical (age, gender, smoking history, smoking index, etc.) and imaging (lesion size, location, density, lobulation sign, etc.) data from 444 lung cancer patients confirmed by pathology at the Second Affiliated Hospital of Naval Medical University between June 2014 and March 2021. These patients were randomly divided into a training set (310 patients) and an internal test set (134 patients) using a 7∶3 ratio through the random function in Python. Based on the results of pulmonary function tests, the patients were further categorized into two groups: lung cancer combined with COPD and lung cancer non-COPD. Initially, univariate analysis was performed to identify statistically significant differences in clinical characteristics between the two groups. The variables showing significance were then included in the logistic regression analysis to determine the independent factors predicting lung cancer combined with COPD, thereby constructing the clinical model. The image features underwent a filtering process using the minimum absolute value convergence and selection operator. The reliability of these features was assessed through leave-P groups-out cross-validation repeated five times. Subsequently, a radiological model was developed. Finally, a combined model was established by combining the radiological signature with the clinical features. Receiver operating characteristic (ROC) curves and decision curve analysis (DCA) curves were plotted to evaluate the predictive capability and clinical applicability of the model. The area under the curve (AUC) for each model in predicting lung cancer combined with COPD was compared using the DeLong test.Results:In the training set, there were 182 cases in the lung cancer combined with COPD group and 128 cases in the lung cancer non-COPD group. The combined model demonstrated an AUC of 0.89 for predicting lung cancer combined with COPD, while the clinical model achieved an AUC of 0.82 and the radiological model had an AUC of 0.85. In the test set, there were 78 cases in the lung cancer combined with COPD group and 56 cases in the lung cancer non-COPD group. The combined model yielded an AUC of 0.85 for predicting lung cancer combined with COPD, compared to 0.77 for the clinical model and 0.83 for the radiological model. The difference in AUC between the radiological model and the clinical model was not statistically significant ( Z=1.40, P=0.163). However, there were statistically significant differences in the AUC values between the combined model and the clinical model ( Z=-4.01, P=0.010), as well as between the combined model and the radiological model ( Z=-2.57, P<0.001). DCA showed the maximum net benifit of the combined model. Conclusion:The developed synthetic diagnostic combined model, incorporating both radiological signature and clinical features, demonstrates the ability to predict COPD in patients with lung cancer.