Objective To propose a lightweight end-to-end neural network model for automated Korotkoff sound phase recognition and subsequent blood pressure (BP) measurement, aiming to improve measurement accuracy and population adaptability. Methods We developed a streamlined architecture integrating depthwise separable convolution (DSConv), multi-head attention (MHA), and bidirectional gated recurrent unit (BiGRU). The model directly processes Korotkoff sound time-series signals to identify auscultatory phases. Systolic BP (SBP) and diastolic BP (DBP) were determined using Phase Ⅰ and PhaseⅤdetections, respectively. Given the clinical relevance of phase Ⅳ for specific populations (e.g., children and pregnant women, denoted as DBPIV), BP values from this phase were also recorded. Results The study enrolled 106 volunteers with 70 males, 36 females at mean age of (40.0±12.0) years. The model achieved 94.25% phase recognition accuracy. Measurement errors were (0.1±2.5) mm Hg (SBP), (0.9±3.4) mm Hg (DBPIV), and (0.8±2.6) mm Hg (DBP). Conclusion Our method enables precise phase recognition and BP measurement, demonstrating potential for developing population-adaptive blood pressure monitoring systems.
ObjectiveTo summarize the latest progress of parathyroid gland identification in thyroid surgery, and to provide some reference for improving the clinical efficacy.MethodThe literatures about the identification of parathyroid gland in thyroid surgery in recent years were collected to make an review.ResultsThere were many methods for identifying parathyroid gland in thyroid surgery, such as naked eye identification method, intraoperative frozen section, intraoperative staining identification method, intraoperative optical identification method, intraoperative parathyroid hormone assay, γ-detector, and histological identification, each method had its own advantages and disadvantages.ConclusionThe identification of parathyroid gland does not only depend on a certain method, but also require surgeons to enhance their ability to distinguish parathyroid gland.
ObjectiveTo introduce a new method for identifying intersegmental planes during thoracoscopic segmentectomy using pulmonary circulation single-blocking in the target segment. MethodsTo retrospectively analyze the clinical data of 83 patients who underwent thoracoscopic pulmonary segmentectomy from January 2019 to March 2020 using the pulmonary circulation single-blocking method. There were 33 males and 50 females, with a median age of 54 (46-65) years, and they were divided into a single vein group (SVG, n=31) and a single artery group (SAG, n=52), and the clinical data of two groups were compared. ResultsThe intersegmental planes were identified successfully in both groups and there were no statistically significant differences between the two groups in terms of intersegmental plane management (P=0.823), operating time (P=0.786), intraoperative blood loss (P=0.775), chest drainage time (P=0.659), postoperative hospital stay (P=0.824) or the incidence of postoperative complications (P=1.000). ConclusionThe use of pulmonary circulation single-blocking for intersegmental plane identification during thoracoscopic segmentectomy is safe and feasible, and the intersegmental plane can be satisfactorily identified by the single-blocking of arteries or veins.
The existing one-time identity authentication technology cannot continuously guarantee the legitimacy of user identity during the whole human-computer interaction session, and often requires active cooperation of users, which seriously limits the availability. This study proposes a new non-contact identity recognition technology based on cardiac micro-motion detection using ultra wideband (UWB) bio-radar. After the multi-point micro-motion echoes in the range dimension of the human heart surface area were continuously detected by ultra wideband bio-radar, the two-dimensional principal component analysis (2D-PCA) was exploited to extract the compressed features of the two-dimensional image matrix, namely the distance channel-heart beat sampling point (DC-HBP) matrix, in each accurate segmented heart beat cycle for identity recognition. In the practical measurement experiment, based on the proposed multi-range-bin & 2D-PCA feature scheme along with two conventional reference feature schemes, three typical classifiers were selected as representatives to conduct the heart beat identification under two states of normal breathing and breath holding. The results showed that the multi-range-bin & 2D-PCA feature scheme proposed in this paper showed the best recognition effect. Compared with the optimal range-bin & overall heart beat feature scheme, our proposed scheme held an overall average recognition accuracy of 6.16% higher (normal respiration: 6.84%; breath holding: 5.48%). Compared with the multi-distance unit & whole heart beat feature scheme, the overall average accuracy increase was 27.42% (normal respiration: 28.63%; breath holding: 26.21%) for our proposed scheme. This study is expected to provide a new method of undisturbed, all-weather, non-contact and continuous identification for authentication.
ObjectiveTo investigate the status of knowledge, attitude, and practice of patient identification in nurses, and provide a basis for clinical managers to carry out targeted training.MethodsA total of 3 696 nurses of tertiary, secondary, and primary hospitals in Guizhou Province were recruited and investigated for the status of knowledge, attitude, and practice of patient identification with a questionnaire by using convenient sampling in May 2019.ResultsThe scores of identification knowledge, attitude, and practice of the 3 696 nurses were 47.87±6.10, 27.39±3.15, and 57.19±4.86, respectively. Logistic regression analysis showed that the higher the educational level was, the higher the score of nurses’ knowledge of patient identification was [odds ratio (OR)=1.592, 95% confidence interval (CI) (1.084, 2.338), P=0.018]; the higher the personal monthly income was, the more positive the nurses’ attitude towards patient identification was [OR=1.570, 95%CI (1.005, 2.453), P=0.048].ConclusionsThe general situation of patient identification in nurses is good, but there are still differences among nurses with different characteristics. It is suggested that managers should pay special attention to the training of nurses with low educational level and low income, make them master the knowledge of patient identification, at the same time, improve their enthusiasm and standardize their behavior, so as to ensure the safety of patients.
Objective To evaluate the effectiveness and safety of pure carbon dioxide (CO2) combined with a modified inflation-deflation technique for identifying the intersegmental plane during thoracoscopic segmentectomy. Methods A prospective study was conducted, enrolling 30 patients diagnosed with pulmonary nodules who underwent thoracoscopic anatomical segmentectomy at the Department of Thoracic Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, from March 2024 to March 2025. Patients were randomly assigned to one of two groups using a random number table: A pure oxygen group (O2 group, n=15, 8 females, 7 males, age 28-75 years) and a pure carbon dioxide group (CO2 group, n=15, 8 females, 7 males, age 37-69 years). All patients underwent preoperative three-dimensional computed tomography bronchovascular angiography to reconstruct pulmonary vessels, bronchi, and the virtual intersegmental plane. The time to identification of the ideal intersegmental plane was recorded intraoperatively, along with arterial blood gas measurements before lung inflation and at 5 and 15 minutes after lung inflation on the surgical side. Results The time to identify the intersegmental plane was significantly shorter in the CO2 group compared to the O2 group [(151.1±39.5) s vs. (998.7±78.9) s, P<0.001], and there were no significant fluctuations in intraoperative oxygen saturation in patients in the CO2 group. Furthermore, there were no statistically significant differences between the two groups in terms of operation duration, intraoperative blood loss, postoperative extubation time, total postoperative chest tube drainage, postoperative length of hospital stay, or postoperative complication rate (all P>0.05). Conclusion Pure CO2 combined with a modified inflation-deflation technique can rapidly, accurately, and clearly identify the intersegmental plane, and its safety is non-inferior to that of the pure O2 method, making it worthy of clinical promotion and application.
Real-time free breathing cardiac cine imaging is a reproducible method with shorter acquisition time and without breath-hold for cardiac magnetic resonance imaging. However, the detection of end-diastole and end-systole frames of real-time free breathing cardiac cine imaging for left ventricle function analysis is commonly completed by visual identification, which is time-consuming and laborious. In order to save processing time, we propose a method for semi-automatic identification of end-diastole and end-systole frames. The method fits respiratory motion signal and acquires the expiration phase, end-diastole and end-systole frames by cross correlation coefficient. The procedure successfully worked on ten healthy volunteers and validated by the analysis of left ventricle function compared to the standard breath-hold steady-state free precession cardiac cine imaging without any significant statistical differences. The results demonstrated that the present method could correctly detect end-diastole and end-systole frames. In the future, this technique may be used for rapid left ventricle function analysis in clinic.
Intravascular ultrasound (IVUS) is widely used in coronary artery examination. Ultrasonic elastography combined with IVUS is very conspicuous in identifying plaque component and in detecting plaque vulnerability degree. In this study, a simulation model of the blood vessel based on finite element analysis (FEA) was established. The vessel walls generally have radial changes caused by different intravascular pressure. The signals at lower pressures were used as the pre-deformation data and the signals at higher pressure were used as the post-deformation data. Displacement distribution was constructed using the time-domain cross-correlation method, and then strain images. By comparison of elastograms under different pressures, we obtained the optimal pressure step. Furthermore, on the basis of the obtained optimize pressure step, the simulation results showed that this method could effectively distinguish characteristics between different component plaques, and could guide the later experiments and clinical applications.
Objective To investigate the effect of monocyte chemoattractant protein 1 (MCP-1) on the migration of the induced and differentiated mouse bone marrow mesenchymal stem cells (BMSCs) for raising the efficacy of intravenous transplantation of BMSCs. Methods The BMSCs were cultured with the method of differential adhesion and density gradient centrifugation of C57/BL10 mice, and were identified by alkal ine phosphatase Gomori modified staining after osteogenic inducing. At the 3rd passage, the BMSCs were induced to the myoblasts with 5-azacytidine (5-Aza). The chemotaxis of MCP-1 in the induced and differentiated BMSCs in vitro at concentrations of 25, 50, 100, 200, and 400 ng/mL was observed through the migration test, by counting the number of the migrated cells. The expression of the chemokine receptor 2 (CKR-2) in the induced and differentiated BMSCs was detected with the flow cytometry. Results The cells could be cultured with the methods of differential adhesion and density gradient centrifugation and still had higher prol iferative and differentiative potency; the induced cells at the 3rd passage could differenciate to the osteoblasts, confirming that the cells were BMSCs; the myogenic induced BMSCs possesed the sarcotubule structure. The number of the migrating BMSCs at MCP-1 concentrations of 25-400 ng/ mL were respectively 35.066 7 ± 6.584 2, 43.200 0 ± 6.460 8, 44.466 7 ± 4.823 5, 45.600 0 ± 8.650 3, and 50.733 3 ± 7.582 5; showing significant difference when compared with control group (28.333 3 ± 8.917 6, P lt; 0.05), and presenting significant difference among 25, 50, 400 ng/mL groups compared with each other (P lt; 0.05). The expression of CKR-2 in the mouse BMSCs (48.0%) was significantly higher (P lt; 0.001) than those of blank control (0.6%) and negative control (17.0%). Conclusion The results indicate that the MCP-1 can induce the migration of mouse BMSCs by MCP-1/CKR-2 pathway.
Using modular identification methods in gene-drug multiplex networks to infer new gene-drug associations can identify new therapeutic target genes for known drugs. In this paper, based on the gene expression data and drug response data of lung cancer in the genomics of drug sensitivity in cancer (GDSC) database, a multiple network algorithm is proposed. First, a heterogeneous network of genes of lung cancer and drugs in different cell lines is constructed, and then a network module identification method based on graph entropy is used. In this heterogeneous network, network modules are identified, and five lung cancer gene-drug association modules are identified through iterative convergence. Compared with other methods, the algorithm has better results in terms of running time, accuracy and robustness, and the identified modules have obvious biological significance. The research results in this article have guiding significance for the medication and treatment of lung cancer, and can provide references for the treatment of other diseases with the same targeted genes.