Objective To investigate the expression of microRNA-1205(miR-1205)and tripartite motif containing 44(TRIM44)mRNA in colorectal cancer(CRC)tissues,and their correlation with pathological characteristics and prognosis.Methods A total of 140 CRC patients who underwent surgery in the hospital from January 2016 to June 2021 were enrolled as the CRC group,while 140 patients with colorectal adenomas who underwent pathological biopsies during the same period were included as the control group.Real-time flu-orescence quantitative polymerase chain reaction was used to detect the expression of miR-1205 and TRIM44 in CRC and colorectal adenoma tissues.The correlation between miR-1205 and TRIM44 expression and patho-logical parameters was analyzed.Binding sites between miR-1205 and TRIM44 were predicted using an online database,and Pearson correlation was used to analyze the correlation between miR-1205 and TRIM44 expres-sion.Based on miR-1205 and TRIM44 expression in CRC tissues,CRC patients were divided into high-expres-sion and low-expression groups.Kaplan-Meier method was used to plot survival curves of CRC patients in dif-ferent miR-1205 and TRIM44 expression groups.Cox regression analysis was used to investigate the influen-cing factors of mortality in CRC patients.Results The expression level of miR-1205 in the CRC group was lower,while the expression level of TRIM44 was higher compared to the control group(P＜0.05).There was a binding site at the 11583-11590 position in the 3'-untranslated region of TRIM44 and miR-1205.miR-1205 expression was negatively correlated with TRIM44 expression in CRC tissues(P＜0.05).There were statisti-cally significant differences in the expression levels of miR-1205 and TRIM44 among CRC patients with differ-ent differentiation levels,TNM stages,and lymph node metastasis(P＜0.05).The 3-year overall survival rate of the 140 CRC patients was 82.14％(115/140).The 3-year overall survival rate in the high miR-1205 ex-pression group was higher than in the low miR-1205 expression group,while the 3-year overall survival rate was lower in the high TRIM44 expression group compared to the low TRIM44 expression group(P＜0.05).After adjusting for confounding factors,miR-1205≥0.63 was an independent protective factor for mortality in CRC patients(P＜0.05),while TRIM44≥2.84 was an independent risk factor for mortality in CRC patients(P＜0.05).Conclusion miR-1205 is lowly expressed and TRIM44 is highly expressed in CRC tissues,both of which are associated with adverse pathological features and prognosis,and may become prognostic markers for CRC patients.

Objective:In order to meet the needs of building Internet of Things(IoT)of medical equipment for mobile deployment,rapid deployment,high-speed and stable data transmission,a wireless IoT acquisition terminal for medical equipment on the basis of Wi-Fi 6 was developed.Methods:Wi-Fi 6 technique was adopted to construct IoT of medical equipment,and the data acquisition terminal included Wi-Fi 6-based customer premises equipment(CPE)and intelligent wireless access point(AP).The CPE adopted a domestic main control chip and Wi-Fi chips,which included two 2.4G and 5G antennas,and was compatible with multiple interfaces such as RS232 and RJ45.The data of medical equipment were converted into wireless transmission through wired communication interfaces.The security access and data traceability of medical equipment were supported through secure secondary authentication with security control enhanced by"white list plus certificate".The intelligent wireless AP was compatible with various RF devices such as Wi-Fi,bluetooth,radio frequency identification,etc.(included 2.4G and 5G antennas).CPE and AP jointly apply dual-transmitter selection technique to ensure stable data transmission.Results:The key performance of wireless IoT acquisition terminals has been tested,and the results indicated that the integrity of acquisition data of intelligent acquisition terminal was consistent with that of output data,with a maximum latency of 9 ms and an average latency of 2 ms.The tested results can meet the expected requirements.Conclusion:The wireless IoT data of medical equipment that based on the acquisition terminal can stably and quickly collect data of equipment to IoT platform,providing paradigm for the construction of wireless IoT of medical equipment.

Objective:To explore the clinical characteristics of adult mediastinal bronchial cysts complicated with aspergillus infection, aiming to improve clinicians′ understanding of this rare lesion.Methods:A case of adult mediastinal bronchial cyst with aspergillus infection admitted to the Foshan Second People′s Hospital in February 2024, mainly presenting with fever and chest pain, was reported. Chest CT showed a mediastinal mass, and postoperative pathology confirmed bronchial cyst with aspergillus infection. Combined with relevant literature review, the clinical features, diagnosis and treatment points of the disease were summarized.Results:The patient successfully underwent surgical resection of the lesion, and pathological examination confirmed the diagnosis of bronchial cyst complicated with aspergillus infection. Literature review indicated that mediastinal bronchial cysts are relatively rare in adults, and cases complicated with aspergillus infection are even rarer.Conclusions:Adult mediastinal bronchial cyst complicated with aspergillus infection is a rare lesion with non-specific clinical manifestations. Imaging examination is an important diagnostic method, and the final diagnosis depends on pathological examination. Enhancing clinicians′ awareness of this disease is helpful for timely and accurate diagnosis and reasonable treatment.

Objective To construct a risk prediction model for post-stroke dysphagia(PSD)based on clinical and laboratory indicators of elderly stroke patients with explainable machine learning.Methods A retrospective analysis was conducted on 3994 stroke patients hospitalized in Depart-ment of Neurology of First Medical Center of Chinese PLA General Hospital from October 2010 to December 2021.Among them,the 1390 cases admitted during January 2019 and December 2021 were assigned into an external validation set,and the 2604 cases admitted during October 2010 to January 2019 were into a training group.Those from the training group were further divided into a training set(1823 cases)and an internal validation set(781 cases)in a 7∶3 ratio,and also grouped into a PSD subgroup(773 cases)and a non-PSD group(1831 cases).With occurrence of swallowing difficulties as an endpoint,risk prediction models were constructed using random for-est(RF),eXtreme Gradient Boosting(XGBoost),Support Vector Machine(SVM),and logistic regression.ROC curve analysis was employed to evaluate the performance of our models.After the optimal model was selected,SHAP was employed to interpret feature contributions.Results There were significant differences in muscle strength,right/left-sided stroke,and area of brain in-jury between the PSD and the non-PSD groups(P＜0.01).The PSD group had obviously larger proportions of hypertension,diabetes,and drinking history,increased neutrophil counts,and de-creased levels of potassium and albumin when compared with the non-PSD group(P＜0.05,P＜0.01).Multivariate logistic regression analysis showed that age,drinking history,diabetes,hyper-tension,muscle strength grade,area of brain injury,hemispheric stroke,neutrophil count,and al-bumin and potassium levels were risk factors for PSD(P＜0.05,P＜0.01).The external validation results showed that the area under curve value of the RF model,XGBoost model,SVM model,and our logistic model was 0.883,0.902,0.877,and 0.868,respectively.The distribution of SHAP value showed that drinking history,hypertension and diabetes were positively correlated with PSD risk;Muscle strength was negatively correlated with the risk;Age growth was positively correlated with the risk;Subtentorial lesions showed stronger predictive efficacy than supratentorial lesions and entire lesions;The bilateral and right-sided stroke had higher risk for PSD than the left-sided stroke.Conclusion The model based on the XGBoost model shows best performance in predicting the risk for swallowing disorders in elderly patients after stroke.

Objective To construct a risk prediction model for post-stroke dysphagia(PSD)based on clinical and laboratory indicators of elderly stroke patients with explainable machine learning.Methods A retrospective analysis was conducted on 3994 stroke patients hospitalized in Depart-ment of Neurology of First Medical Center of Chinese PLA General Hospital from October 2010 to December 2021.Among them,the 1390 cases admitted during January 2019 and December 2021 were assigned into an external validation set,and the 2604 cases admitted during October 2010 to January 2019 were into a training group.Those from the training group were further divided into a training set(1823 cases)and an internal validation set(781 cases)in a 7∶3 ratio,and also grouped into a PSD subgroup(773 cases)and a non-PSD group(1831 cases).With occurrence of swallowing difficulties as an endpoint,risk prediction models were constructed using random for-est(RF),eXtreme Gradient Boosting(XGBoost),Support Vector Machine(SVM),and logistic regression.ROC curve analysis was employed to evaluate the performance of our models.After the optimal model was selected,SHAP was employed to interpret feature contributions.Results There were significant differences in muscle strength,right/left-sided stroke,and area of brain in-jury between the PSD and the non-PSD groups(P＜0.01).The PSD group had obviously larger proportions of hypertension,diabetes,and drinking history,increased neutrophil counts,and de-creased levels of potassium and albumin when compared with the non-PSD group(P＜0.05,P＜0.01).Multivariate logistic regression analysis showed that age,drinking history,diabetes,hyper-tension,muscle strength grade,area of brain injury,hemispheric stroke,neutrophil count,and al-bumin and potassium levels were risk factors for PSD(P＜0.05,P＜0.01).The external validation results showed that the area under curve value of the RF model,XGBoost model,SVM model,and our logistic model was 0.883,0.902,0.877,and 0.868,respectively.The distribution of SHAP value showed that drinking history,hypertension and diabetes were positively correlated with PSD risk;Muscle strength was negatively correlated with the risk;Age growth was positively correlated with the risk;Subtentorial lesions showed stronger predictive efficacy than supratentorial lesions and entire lesions;The bilateral and right-sided stroke had higher risk for PSD than the left-sided stroke.Conclusion The model based on the XGBoost model shows best performance in predicting the risk for swallowing disorders in elderly patients after stroke.

Objective:In order to meet the needs of building Internet of Things(IoT)of medical equipment for mobile deployment,rapid deployment,high-speed and stable data transmission,a wireless IoT acquisition terminal for medical equipment on the basis of Wi-Fi 6 was developed.Methods:Wi-Fi 6 technique was adopted to construct IoT of medical equipment,and the data acquisition terminal included Wi-Fi 6-based customer premises equipment(CPE)and intelligent wireless access point(AP).The CPE adopted a domestic main control chip and Wi-Fi chips,which included two 2.4G and 5G antennas,and was compatible with multiple interfaces such as RS232 and RJ45.The data of medical equipment were converted into wireless transmission through wired communication interfaces.The security access and data traceability of medical equipment were supported through secure secondary authentication with security control enhanced by"white list plus certificate".The intelligent wireless AP was compatible with various RF devices such as Wi-Fi,bluetooth,radio frequency identification,etc.(included 2.4G and 5G antennas).CPE and AP jointly apply dual-transmitter selection technique to ensure stable data transmission.Results:The key performance of wireless IoT acquisition terminals has been tested,and the results indicated that the integrity of acquisition data of intelligent acquisition terminal was consistent with that of output data,with a maximum latency of 9 ms and an average latency of 2 ms.The tested results can meet the expected requirements.Conclusion:The wireless IoT data of medical equipment that based on the acquisition terminal can stably and quickly collect data of equipment to IoT platform,providing paradigm for the construction of wireless IoT of medical equipment.

Objective:To explore the clinical characteristics of adult mediastinal bronchial cysts complicated with aspergillus infection, aiming to improve clinicians′ understanding of this rare lesion.Methods:A case of adult mediastinal bronchial cyst with aspergillus infection admitted to the Foshan Second People′s Hospital in February 2024, mainly presenting with fever and chest pain, was reported. Chest CT showed a mediastinal mass, and postoperative pathology confirmed bronchial cyst with aspergillus infection. Combined with relevant literature review, the clinical features, diagnosis and treatment points of the disease were summarized.Results:The patient successfully underwent surgical resection of the lesion, and pathological examination confirmed the diagnosis of bronchial cyst complicated with aspergillus infection. Literature review indicated that mediastinal bronchial cysts are relatively rare in adults, and cases complicated with aspergillus infection are even rarer.Conclusions:Adult mediastinal bronchial cyst complicated with aspergillus infection is a rare lesion with non-specific clinical manifestations. Imaging examination is an important diagnostic method, and the final diagnosis depends on pathological examination. Enhancing clinicians′ awareness of this disease is helpful for timely and accurate diagnosis and reasonable treatment.

Intelligent medical devices are flourishing with the deep integration of modern information and artificial intelligence technologies into healthcare.Testing is an important means of performance evaluation and quality control for intelligent medical devices.Compared with traditional medical devices,the testing methods and technologies of intelligent medical devices are still immature,and need active research to promote the progress in this area.Intelligent medical devices are classified according to their characteristics as artificial intelligence medical devices in the form of software and medical robots based on a general discussion of their development.The medical-device Internet of Things(IoT)system has also been included due to its close relation to the construction of smart hospitals.For each type of intelligent medical device,testing indexes and testing plans are discussed.It is suggested that specific test rules should be further developed for various specific devices.Besides,the evaluation method of complex intelligent systems should be introduced and real-world data should be used for evaluation.This paper aims to accelerate the development of intelligent medical device testing,laying the foundation for quality control and performance evaluation of intelligent medical devices.

With the progress of science and technology and the increase of clinical demand, medical robots have developed rapidly and played a important role in promoting the medical cause. Service robot is a branch of medical robot, which is mainly oriented to medical service and assistance needs, and has been applied in many medical scenarios and achieved demonstration effects. This research first describes the development of medical service robots, and then summarizes the key technologies and clinical applications of robots. Finally, it points out the challenges and directions that medical service robots face at present, and puts forward prospects for their further development in the medical field.
Robotics ; Technology

【Objective】 To determine the reference range of thromboelastogram(TEG) and establish a TEG feature for local population by measuring TEG parameters in healthy adults in Shenzhen comparing the difference between gender and age, and analyzing the reference data provided by reagent manufacturer. 【Methods】 A total of 916 healthy adults, aged between 19 to 59, who did their regular health checks in our hospital from September 2020 to August 2021 were selected. The TEG(from Lepu Medical Technology Co., Ltd.) was performed, and the clot reaction time(R), clot formation time(K), coagulation angle(α-Angle), maximum amplitude(MA), coagulation index(CI), fibrinolysis index LY30 and the estimated percent lysis (EPL) were analyzed. 【Results】 The reference ranges of TEG parameters, including R, K, α-Angle, MA, CI, LY30 and EPL, of 916 healthy adults from Shenzhen were 3.25~8.19 min, 0.66~3.18min, 47.70~76.56deg, 50.05~72.91mm, -4.3~3.4, 0~2.2% and 0~3%, respectively. The value of α-Angle, CI, K, LY30, MA and R didn’t all meet the given range provided by the manufacturer; some were exceeding and some inferior to. A total of 227 out of 916 individuals presented abnormal results, relative to the references, in at least one parameter, and 78 were diagnosed of abnormal coagulation based on the given reference range, with a specificity of 75.2%. 【Conclusion】 The reference range of TEG parameters of Shenzhen locals is significantly different from that provided by manufacturers. And it is imperative for local TEG laboratories to establish their own reference ranges according to age and gender groups based on local population characteristics.