The lungs are the most common sites of metastases from non-pulmonarymalignancies. Endobronchial metastases are rare and have no specificity in clinical manifestations,thus being prone to misdiagnosis and delayed treatment.The common tumors associated with endobronchial metastasis are renal,breast,and colorectal cancers.This article reported one case of postoperative rectal cancer with endobronchial and lung metastases,which was relieved by high-frequency electrocautery ablation via bronchoscope,chemotherapy,and targeted drugs,aiming to provide a reference for clinical diagnosis and treatment.
Humans ; Rectal Neoplasms/pathology* ; Electrocoagulation/methods* ; Bronchial Neoplasms/drug therapy* ; Bronchoscopy ; Lung Neoplasms/secondary* ; Bronchoscopes

OBJECTIVE: To explore the safety and efficacy of high-dose etoposide (VP-16) combined with recombinant human granulocyte colony-stimulating factor (rhG-CSF) as salvage mobilization for peripheral blood stem cells (PBSC) in newly diagnosed multiple myeloma (NDMM) patients. METHODS: From April 2021 to May 2023, eight NDMM patients who had failed to yield sufficient PBSC during initial mobilization with high-dose cyclophosphamide (CTX) combined with rhG-CSF underwent salvage mobilization with 1.2 g/m2 etoposide combined with rhG-CSF 10 μg/(kg·d). The effects and adverse reactions of initial mobilization and salvage mobilization were analyzed. RESULTS: For salvage mobilization and initial mobilization, the numbers of PBSC collections were 16 and 18, respectively. The mean value of total collected CD34⁺ cells were (11.90±5.75)×10⁶/kg and (1.67±0.75)×10⁶/kg (P =0.0010) in salvage mobilization group and initial mobilization group, respectively. The proportion of patients with a total collection of CD34⁺ cell count≥2×10⁶/kg were 100% and 37.5% (P =0.0625), and the proportion of patients with a total collection of CD34⁺ cell count≥5×10⁶/kg were 87.5% and 0% (P =0.0156) in salvage mobilization group and initial mobilization group, respectively. For five patients who underwent high-dose CTX initial mobilization but had a total CD34⁺ cell count < 2×10⁶/kg, successful collection was achieved through salvage mobilization with high-dose VP-16. Salvage mobilization with high-dose VP-16 was scheduled 2-3 weeks after failure of CTX mobilization. Adverse reactions of high-dose VP-16 mobilization did not increase compared to the initial mobilization with high-dose CTX. CONCLUSION As a salvage mobilization regimen, VP-16 1.2 g/m² combined with rhG-CSF is safe and highly effective in NDMM patients who failed to initial mobilization with high-dose CTX combined with rhG-CSF.
Humans ; Multiple Myeloma/therapy* ; Etoposide/therapeutic use* ; Hematopoietic Stem Cell Mobilization/methods* ; Cyclophosphamide/therapeutic use* ; Granulocyte Colony-Stimulating Factor ; Salvage Therapy ; Peripheral Blood Stem Cells ; Male ; Middle Aged ; Female ; Peripheral Blood Stem Cell Transplantation

Objective:To design an assisted management system for medical consumables that integrated management logic of diagnosis related groups(DRG)for disease,so as to standardize the use for medical consumables and to strengthen regulatory efficiency.Methods:The system was designed by a microservices architecture,and the data fusion of business data,data of diagnosis and treatment,and DRG data was realized through constructed data lake.A knowledge graph of associated rule for medical consumables was established,and the intelligent analysis function included prediction for demand,usage optimization,and anomaly detection was provided to assist management decision-making on the basis of inference for historical data and knowledge,and multi-dimensional data queries.A rule engine was deployed at key clinical nodes for real-time compliance review and intelligent alerts.A DRG-based business management process was constructed to cover full lifecycle of consumables,including admission,procurement,warehousing,storage,requisition,usage billing,and traceability,so as to realize real-time monitoring and early warning for consumable costs at the DRG level.Six clinical doctors with 2-3 years of experience in using medical consumable were selected as test users from Tangdu Hospital of the Air Force Medical University,and they were randomly assigned into a system group and a control group,with 3 subjects in each group.The system group utilized the auxiliary management system for medical consumable to perform prediction for the demand of monthly procurement,and rationality verification of consumable.The control group relied on individual experience of doctors.The predicted monthly procurement demand for medical consumables,the accuracy of verifying rationality of using medical consumables between two groups were compared,and the efficiencies of two kinds of management modes also were compared.Results:The accuracy rate of system group was 89.17%in predicting the monthly procurement demand for medical consumables,and the rate of checking accuracy and the rate of checking comprehensiveness of system group were respectively 87.50%and 91.67%in verifying rationality of using medical consumables,which were significantly higher than those of control group,and the differences were significant(x2=6.62,1.96,16.73,P<0.05).The durations of predicting the demand for procurement,and verifying and testing the rationality of consumables in system group were significantly shorter than these in control group[(3.54±0.45)s,(2.23±0.15)s],and the differences were statistically significant(t=1.97,1.65,P<0.05).Conclusion:The medical consumables auxiliary management system integrated with DRG management logic can significantly enhance the accuracy of monthly demand prediction for consumables and the recall rate and precision rate of rationality verification for consumables usage,while greatly improving work efficiency.It is conducive to enhancing the standardized and refined supervision level of consumables usage.

Objective:To design an assisted management system for medical consumables that integrated management logic of diagnosis related groups(DRG)for disease,so as to standardize the use for medical consumables and to strengthen regulatory efficiency.Methods:The system was designed by a microservices architecture,and the data fusion of business data,data of diagnosis and treatment,and DRG data was realized through constructed data lake.A knowledge graph of associated rule for medical consumables was established,and the intelligent analysis function included prediction for demand,usage optimization,and anomaly detection was provided to assist management decision-making on the basis of inference for historical data and knowledge,and multi-dimensional data queries.A rule engine was deployed at key clinical nodes for real-time compliance review and intelligent alerts.A DRG-based business management process was constructed to cover full lifecycle of consumables,including admission,procurement,warehousing,storage,requisition,usage billing,and traceability,so as to realize real-time monitoring and early warning for consumable costs at the DRG level.Six clinical doctors with 2-3 years of experience in using medical consumable were selected as test users from Tangdu Hospital of the Air Force Medical University,and they were randomly assigned into a system group and a control group,with 3 subjects in each group.The system group utilized the auxiliary management system for medical consumable to perform prediction for the demand of monthly procurement,and rationality verification of consumable.The control group relied on individual experience of doctors.The predicted monthly procurement demand for medical consumables,the accuracy of verifying rationality of using medical consumables between two groups were compared,and the efficiencies of two kinds of management modes also were compared.Results:The accuracy rate of system group was 89.17%in predicting the monthly procurement demand for medical consumables,and the rate of checking accuracy and the rate of checking comprehensiveness of system group were respectively 87.50%and 91.67%in verifying rationality of using medical consumables,which were significantly higher than those of control group,and the differences were significant(x2=6.62,1.96,16.73,P<0.05).The durations of predicting the demand for procurement,and verifying and testing the rationality of consumables in system group were significantly shorter than these in control group[(3.54±0.45)s,(2.23±0.15)s],and the differences were statistically significant(t=1.97,1.65,P<0.05).Conclusion:The medical consumables auxiliary management system integrated with DRG management logic can significantly enhance the accuracy of monthly demand prediction for consumables and the recall rate and precision rate of rationality verification for consumables usage,while greatly improving work efficiency.It is conducive to enhancing the standardized and refined supervision level of consumables usage.

Objective:To investigate the effect of iron overload on the expression of programmed death-1(PD-1)on the surface of T lymphocyte in mice,in order to analyze the mechanism of iron overload inhibiting T cell function.Methods:Flow cytometry was used to detect the labile iron pool(LIP),reactive oxygen species(ROS),and the expression of PD-1 in peripheral blood T cells in mice with iron overload.Results:The mean fluorescence intensity of calcein in T cells of mice in iron overload group was 2 492±311.1,which was significantly lower than 3 136±537.3 in the control group(P＜0.01),suggesting that increased LIP in iron overload group.Compared with the control group,the ratio of CD4/CD8 of peripheral blood T cells was normal or increased in iron overload group.The level of ROS in T cells was 2 452±393.3 in iron overload group,which was significantly increased compared to 1 874±121.8 in the control group(P＜0.001).The expression of PD-1 on the surface of T cells was significantly increased.The percentage of PD-1+cells in CD8+T cells was(12.97±6.92)％and(6.18±2.95)％in iron overload group and control group,respectively(P＜0.05),and that in CD8-T cells was(33.55±15.69)％and(12.51±4.11)％(P＜0.001).Conclusion:The expression of PD-1 on peripheral blood T cells in mice with iron overload is significantly increased,which may be involved in inhibiting T cell effector function.

Aim To investigate the role of metabolites of eicosapentaenoic acid (EPA) in promoting the transdifferentiation of pancreatic α cells to β cells. Methods Male C57BL/6J mice were injected intraperitoneally with 60 mg/kg streptozocin (STZ) for five consecutive days to establish a type 1 diabetes (T1DM) mouse model. After two weeks, they were randomly divided into model groups and 97% EPA diet intervention group, 75% fish oil (50% EPA +25% DHA) diet intervention group, and random blood glucose was detected every week; after the model expired, the regeneration of pancreatic β cells in mouse pancreas was observed by immunofluorescence staining. The islets of mice (obtained by crossing GCG

People frequently struggle to juggle their work, family, and social life in today’s fast-paced environment, which can leave them exhausted and worn out. The development of technologies for detecting fatigue while driving is an important field of research since driving when fatigued poses concerns to road safety. In order to throw light on the most recent advancements in this field of research, this paper provides an extensive review of fatigue driving detection approaches based on electroencephalography (EEG) data. The process of fatigue driving detection based on EEG signals encompasses signal acquisition, preprocessing, feature extraction, and classification. Each step plays a crucial role in accurately identifying driver fatigue. In this review, we delve into the signal acquisition techniques, including the use of portable EEG devices worn on the scalp that capture brain signals in real-time. Preprocessing techniques, such as artifact removal, filtering, and segmentation, are explored to ensure that the extracted EEG signals are of high quality and suitable for subsequent analysis. A crucial stage in the fatigue driving detection process is feature extraction, which entails taking pertinent data out of the EEG signals and using it to distinguish between tired and non-fatigued states. We give a thorough rundown of several feature extraction techniques, such as topology features, frequency-domain analysis, and time-domain analysis. Techniques for frequency-domain analysis, such wavelet transform and power spectral density, allow the identification of particular frequency bands linked to weariness. Temporal patterns in the EEG signals are captured by time-domain features such autoregressive modeling and statistical moments. Furthermore, topological characteristics like brain area connection and synchronization provide light on how the brain’s functional network alters with weariness. Furthermore, the review includes an analysis of different classifiers used in fatigue driving detection, such as support vector machine (SVM), artificial neural network (ANN), and Bayesian classifier. We discuss the advantages and limitations of each classifier, along with their applications in EEG-based fatigue driving detection. Evaluation metrics and performance assessment are crucial aspects of any detection system. We discuss the commonly used evaluation criteria, including accuracy, sensitivity, specificity, and receiver operating characteristic (ROC) curves. Comparative analyses of existing models are conducted, highlighting their strengths and weaknesses. Additionally, we emphasize the need for a standardized data marking protocol and an increased number of test subjects to enhance the robustness and generalizability of fatigue driving detection models. The review also discusses the challenges and potential solutions in EEG-based fatigue driving detection. These challenges include variability in EEG signals across individuals, environmental factors, and the influence of different driving scenarios. To address these challenges, we propose solutions such as personalized models, multi-modal data fusion, and real-time implementation strategies. In conclusion, this comprehensive review provides an extensive overview of the current state of fatigue driving detection based on EEG signals. It covers various aspects, including signal acquisition, preprocessing, feature extraction, classification, performance evaluation, and challenges. The review aims to serve as a valuable resource for researchers, engineers, and practitioners in the field of driving safety, facilitating further advancements in fatigue detection technologies and ultimately enhancing road safety.

Objective:To explore the influence of age on the passive stiffness of women′s quadriceps muscles and the relationship between stiffness and muscle functioning.Methods:Twenty healthy elderly women formed the senior-aged group, while 20 young, healthy women were selected as the young group. The passive stiffness of the subjects′ vastus medialis, rectus femoris and vastus lateralis muscles was measured using ultrasound shear wave imaging with the knee flexed to 30°, 60°, 90° and 105°. Both groups completed the 6-minute walk test (6MWT) and the five times sit-to-stand test (FTSST). Maximum voluntary isometric contraction (MIVC) strength during knee extension was also measured.Results:The passive muscle stiffness of the rectus femoris and vastus lateralis muscles was significantly greater in the senior-aged group when the knee was flexed at 60°, 90° or 105°. The 6MWT and FTSST times of the young group were of course significantly better, and their MIVC at 60° and 90° of knee flexion was also significantly stronger. Rectus femoris stiffness among the senior-aged group was negatively correlated with MIVC when the knee was flexed at 60°.Conclusions:The passive stiffness of the muscles studied increases with age, especially in stretching. When the knee joint is flexed at 60° there tends to be a negative correlation between the MIVC of the quadriceps femoris and the stiffness of the rectus femoris among elderly females.

The main components and working principle of the negative pressure isolation treatment equipment were described,and the classification and application scopes of the negative pressure isolation treatment equipment from foreign countries and China were reviewed.The structure,key technical parameters and characteristics of different types of negative pressure isolation treatment equipment were analyzed under different conditions.The problems of the negative pressure isolation treatment equipment were analyzed,and it's pointed out it would be enhanced in component simplification,comfort,intelligence and multifunctionality.[Chinese Medical Equipment Journal,2024,45(2):97-104]