In order to examine whether repeated sciatic nerve blocks showed tachyphylaxis and continuity of sciatic nerve with spinal cord affected development of tachyphylaxis when assayed in vivo by duration of depression compound action potentials (CAP), rats were anesthetized with halothane, ventilated, monitored and supported with stable hemodynamics and temperature. Posterior tibial nerve distally and sciatic nerve in thigh were exposed, placed on bipolar silver electrodes for stimulation and recording respectively. Three sequential sciatic nerve blocks were performed between these electrodes using 0.15 ml of 3% chloroprocaine. Nine rats were chosen to observe the effects of repeated sciatic nerve blocks on CAP. In another 18 rats, a second investigator exposed the sciatic nerve near its origin at spinal cord and randomly performed nerve cut and sham (n=9), and closed the incision blinding the electrophysiologic investigator. The results showed that electrical stimulated tibial nerve induced sciatic nerve Aalpha/beta, Adelta, C fiber mediated CAP waves. CAP amplitudes were remained stable during whole experimental procedure. CAP amplitudes were decreased completely with 3% chloroprocaine blocked sciatic nerve and recovered fully. The duration of CAP depression were reduced with repeated blocks. There were no selective blocked effects on Aalpha/beta, Adelta, C fiber mediated CAP. With sciatic nerve cut proximally, there was no statistical significant tachyphylaxis with 3% chloroprocaine repeated blocked sciatic nerve, and the duration of first and third blocked Adelta fiber mediated CAP was 108+/-20 and 92+/-14 min respectively (P>0.05). In normal rats the duration of first and third blocked Adelta fiber mediated CAP was 110+/-20 and 75+/-16 min respectively (P<0.05). It was suggested that tachyphylaxis to local anesthetics can occur in rats repeated blocked sciatic nerve when assayed in vivo by duration of depression CAP. The continuity of sciatic nerve with spinal cord is one of the important factors affecting the development of tachyphylaxis.
Anesthetics, Local/*administration & dosage ; Nerve Block ; Procaine/administration & dosage ; Procaine/analogs & derivatives ; Sciatic Nerve ; *Tachyphylaxis/physiology

BACKGROUND: Human umbilical cord mesenchymal stem cells (hUC-MSCs) have been drawing a great attention due to their potential therapeutic effect in a variety of diseases, including immune-mediated diseases. Further characterization of the immunomodulatory properties and action pathways of hUC-MSCs is necessary to ensure their safety and effectiveness in clinical application. OBJECTIVE: To investigate the immunomodulatory properties of hUC-MSCs. METHODS: HUC-MSCs were directly co-cultured with CFSE-labeled peripheral blood mononuclear cells (PBMCs) at the ratio of 1:5, 1:10, and 1:20, or indirectly co-cultured with CFSE-labeled PBMCs at the ratio of 1:5 via the Transwell co-culture system. Phytohemagglutinin- stimulated PBMC proliferation and the percentages of Th1, Th17 and Treg subgroups in the CD4+ T cells were determined by flow cytometry. The levels of tumor necrosis factor α and interferon γ were determined by ELISA. RESULTS AND CONCLUSION: After direct co-culture, hUC-MSCs significantly inhibited the phytohemagglutinin-stimulated PBMCs proliferation in a dose-dependent manner, whereas the inhibitory effect disappeared in the Transwell co-culture system. A significant decrease of Th1, Th17 cells and an increase of Treg cells were detected in the PBMCs co-cultured with hUC-MSCs compared to the PBMCs cultured alone. Furthermore, hUC-MSCs co-culture significantly reduced tumor necrosis factor α and interferon γ levels in the PBMCs. These findings indicate that cell-to-cell contact is essential for hUC-MSCs to inhibit the proliferation, differentiation and inflammatory factor secretion of immune cells.

Objective To investigate the mastery of the management knowledge of patients with atrial fibrillation after coronary artery bypass grafting by cardiac surgeons in Beijing tertiary hospitals, and the practice status and obstacles of following the guidelines for postoperative atrial fibrillation. Methods A convenient sampling method was used to select cardiac surgeons from four tertiary hospitals in Beijing, and a self-designed questionnaire on the management of postoperative atrial fibrillation patients was used. Results A total of 227 valid questionnaires were collected. Only 47.9% of doctors and 12.8% of nurses passed in knowledge, and 31.3% of doctors and 28.5% of nurses passed in behavior. Among them, risk factor assessment, preventive medication, stroke and bleeding risk assessment were the weakest. "Lack of departmental requirements" was identified as a common barrier to healthcare workers' adherence to guidelines. Job title and participation in training were common influencing factors that affected the knowledge and behavior of healthcare workers, and knowledge level was an important factor affecting healthcare worker behavior. Conclusion In order to improve the effect of CABG surgery and improve the quality of postoperative patient management, hospitals should further strengthen the knowledge and skills training of medical staff on the management guidelines of postoperative atrial fibrillation with CABG, formulate relevant systems to ensure the clinical implementation of guidelines.

As a global disease, heart failure affects at least 26 million people, and its prevalence is still rising. Besides, the mortality rate and readmission rate remain high. Advanced heart failure is the terminal stage of various heart diseases, and often requires some treatments other than drug intervention, such as heart transplantation which is the gold standard for treatment of heart failure. However, limited by the number of donors, the number of heart transplants in the world has reached a bottleneck. There is a huge gap between the number of patients who need heart transplants and patients who get hearts for survival successfully in reality. With the exploration and development of mechanical circulation support devices for more than half a century, they have become a wonderful treatment for patients with advanced heart failure. This article will introduce the latest progress of mechanical circulatory support devices at home and abroad from the aspects of temporary and long-term devices.

Objective    To systematically evaluate the clinical value of machine learning (ML) for predicting the neurological outcome of out-of-hospital cardiac arrest (OHCA), and to develop a prediction model. Methods    We searched the PubMed, Web of Science, EMbase, CNKI, Wanfang database from January 1, 2011 to November 24, 2021. Studies on ML for predicting neurological outcomes in OHCA pateints were collected. Two researchers independently screened the literature, extracted the data and evaluated the bias of the included literature, evaluated the accuracy of different models and compared the area under the receiver operating characteristic curve (AUC). Results    A total of 20 studies were included. Eleven of the studies were from open source databases and nine were from retrospective studies. Sixteen studies directly predicted OHCA neurological outcomes, and four predicted OHCA neurological outcomes after target temperature management. A total of seven ML algorithms were used, among which neural network was the ML algorithm with the highest frequency (n=5), followed by support vector machine and random forest (n=4). Three papers used multiple algorithms. The most frequently used input characteristic was age (n=19), followed by heart rate (n=17) and gender (n=13). A total of 4 studies compared the predictive value of ML with other classical statistical models, and the AUC value of ML model was higher than that of classical statistical models. Conclusion    Existing evidence suggests that ML can more accurately predict OHCA nervous system outcomes, and the predictive performance of ML is superior to traditional statistical models in certain situations.

Objective    To explore the potential role of tumor spread through air spaces (STAS) as a prognostic indicator of non-small cell lung cancer (NSCLC) through meta-analysis. Methods    PubMed, EMbase and Web of Science, from inception to February 2022 were searched by computer about the research of the 5-year overall survival (OS) and recurrence free survival (RFS) of NSCLC patients with or without STAS. The Newcastle-Ottawa scale (NOS) was used to evaluate the quality of each study. Results    Totally 13 published articles were included with 4 647 patients, and 1 424 (30.6%) patients had STAS. The NOS score of all studies≥6 points. The meta-analysis showed that compared with the NSCLC patients without STAS, those with STAS had a worse prognosis of 5-year RFS, and the combined HR was 1.89 (95%CI 1.61-2.23); they had a shorter 5-year OS, and the combined HR was 2.25 (95%CI 1.79-2.84). There was no statistical heterogeneity among studies. Conclusion    The presence of STAS may be a poor prognostic factor for patients with NSCLC, and enough attention should be paid. The STAS should be recorded in the pathological report to guide the comprehensive treatment and evaluate the prognosis of patients.

Intelligent medical image segmentation methods have been rapidly developed and applied, while a significant challenge is domain shift. That is, the segmentation performance degrades due to distribution differences between the source domain and the target domain. This paper proposed an unsupervised end-to-end domain adaptation medical image segmentation method based on the generative adversarial network (GAN). A network training and adjustment model was designed, including segmentation and discriminant networks. In the segmentation network, the residual module was used as the basic module to increase feature reusability and reduce model optimization difficulty. Further, it learned cross-domain features at the image feature level with the help of the discriminant network and a combination of segmentation loss with adversarial loss. The discriminant network took the convolutional neural network and used the labels from the source domain, to distinguish whether the segmentation result of the generated network is from the source domain or the target domain. The whole training process was unsupervised. The proposed method was tested with experiments on a public dataset of knee magnetic resonance (MR) images and the clinical dataset from our cooperative hospital. With our method, the mean Dice similarity coefficient (DSC) of segmentation results increased by 2.52% and 6.10% to the classical feature level and image level domain adaptive method. The proposed method effectively improves the domain adaptive ability of the segmentation method, significantly improves the segmentation accuracy of the tibia and femur, and can better solve the domain transfer problem in MR image segmentation.
Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Magnetic Resonance Imaging ; Knee ; Knee Joint

OBJECTIVETo analyze the strains of bacteria in burn infection and their resistance to antibiotics in our burn unit in the recent years.

METHODSBacteria were isolated from specimens from the wounds, venous lines, blood, urine and feces of the hospitalized burn patients from January 2003 to December 2005 to analyze the vicissitude of bacteria and their drug resistance.

RESULTSThe number of Gram-negative bacteria (372 strains) was larger than Gram-positive ones (292 strains). Staphylococcus aureus (accounting for 16.7%) was predominant among Gram-positive bacteria, among which methicillin resistant staphylococcus aureus (MRSA) accounted for 82.5%. Among the Gram-negative bacteria, Pseudomonas aeruginosa accounted for 12.5%, and Escherichia coli accounted for 11.1%. The drug resistant ESPL-producing strains of Escherichia coli and Klebsiella pneumoniae accounted for 60.8% and 42.9%, respectively.

CONCLUSIONDrug resistance to antibiotics is a serious problem in a burn unit, calling for monitoring the vicissitude of bacteria strains and antibiotics sensitivity in order to control bacterial infection and dissemination.

Adolescent ; Adult ; Aged ; Anti-Bacterial Agents ; pharmacology ; Bacterial Infections ; microbiology ; Burn Units ; Burns ; microbiology ; Child ; Child, Preschool ; Drug Resistance, Bacterial ; Female ; Gram-Negative Bacteria ; drug effects ; isolation & purification ; Gram-Positive Bacteria ; drug effects ; isolation & purification ; Humans ; Male ; Middle Aged ; Young Adult

With the wide popularization of low-dose computed tomography screening for lung cancer, the proportion of early detection of lung cancer has increased significantly. Due to the favorable prognosis of ground-glass nodule-lung cancer, a prospective multicenter clinical trial in Japan has confirmed the safety and efficacy of segmentectomy. Identification of the intersegmental plane is one of the key steps in segmentectomy. Understanding its physiological mechanism can provide a theoretical basis for optimizing the identification technique, identifying intersegmental plane more accurately and quickly, improving the surgical effect and reducing complications. This article mainly introduces the identification technology of the intersegmental plane and its physiological mechanism in pulmonary segmentectomy.

Precise segmentation of lung field is a crucial step in chest radiographic computer-aided diagnosis system. With the development of deep learning, fully convolutional network based models for lung field segmentation have achieved great effect but are poor at accurate identification of the boundary and preserving lung field consistency. To solve this problem, this paper proposed a lung segmentation algorithm based on non-local attention and multi-task learning. Firstly, an encoder-decoder convolutional network based on residual connection was used to extract multi-scale context and predict the boundary of lung. Secondly, a non-local attention mechanism to capture the long-range dependencies between pixels in the boundary regions and global context was proposed to enrich feature of inconsistent region. Thirdly, a multi-task learning to predict lung field based on the enriched feature was conducted. Finally, experiments to evaluate this algorithm were performed on JSRT and Montgomery dataset. The maximum improvement of Dice coefficient and accuracy were 1.99% and 2.27%, respectively, comparing with other representative algorithms. Results show that by enhancing the attention of boundary, this algorithm can improve the accuracy and reduce false segmentation.
X-Rays ; Algorithms ; Diagnosis, Computer-Assisted ; Thorax/diagnostic imaging* ; Lung/diagnostic imaging* ; Image Processing, Computer-Assisted