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Objective: The aim of this study is to elucidate the underlying mechanism through which glial cell line-derived neurotrophic factor (GDNF) improves cognitive deficits in adults resulting from neonatal surgical interventions. Methods: Newborn Sprague–Dawley rats, regardless of gender, were randomly allocated into seven groups on postnatal day 7 as follows (n=15): (1) Control group (not subjected to anesthesia, surgery, or any pharmaceutical interventions); (2) GDNF group (received intracerebroventricular injection of GDNF); (3) Surgery group (underwent right carotid artery exposure under anesthesia with 3 % sevoflurane); (4) Surgery plus GDNF group; (5) Surgery plus GDNF and type II JAK inhibitor NVP-BBT594 (BBT594) group (administered intraperitoneal injection of BBT594); (6) BBT group; and (7) Surgery plus BBT group. Starting from postnatal day 33, all rats underwent Barnes maze and fear conditioning tests, followed by decapitation under sevoflurane anesthesia for subsequent analyses. The left hemibrains underwent Golgi staining, while the right hemibrains were used for hippocampal protein extraction to assess Protein kinase Mζ (PKMζ) and Kalirin expression through western blotting. Results: GDNF demonstrated a mitigating effect on spatial learning and memory impairment, as well as context-related fear memory impairment, reductions in dendritic total lengths, and spinal density within the hippocampus induced by surgical intervention. Notably, all of these ameliorative effects of GDNF were reversed upon administration of the RET inhibitor BBT594. Additionally, GDNF alleviated the downregulation of protein expression of PKMζ and Kalirin in the hippocampus of rats subjected to surgery, subsequently reversed by BBT594. Conclusion: The effective impact of GDNF on learning and memory impairment caused by surgical intervention appears to be mediated through the RET pathway. Moreover, GDNF may exert its influence by upregulating the expression of PKMζ and Kalirin, consequently enhancing the development of dendrites and dendritic spines.

Monitoring the building blast vibration signal is an efficient way to determine the power of blast vibration hazards. Due to the harsh measurement environment, noise is inevitably introduced into the recorded signals. This research presents a denoising approach based on Improved complete ensemble empirical mode decomposition with adaptive noise(ICEEMDAN) and Composite Multiscale Permutation Entropy (CMPE). First, the noisy blast vibration signal is decomposed into different intrinsic mode functions using ICEEMDAN; then multiple intrinsic mode functions (IMFs) are separated into pure and noisy using CMPE, the noisy IMFs are denoised using wavelet thresholding; finally the blast wave is reconstructed using the pure and denoised mixed IMFs. The proposed approach was compared with four other approaches (CEEMDAN-CMPE, VMD-CMPE, SVMD-CMPE, and WST). The results indicate that the proposed approach has better performance and can be considered as an effective denoising method for building blast vibration signals.

Introduction The lumbar puncture (LP) technique is widely used for diagnostic and therapeutic purposes. In recent years, the paramedian approach technique (PAT) has gained increasing interest due to its advantages over the conventional midline approach technique (MAT) that has been traditionally employed in clinical practice for LP. However, there have been inconsistent discussions regarding the efficacy of different LP techniques. Based on digital virtual human and computer simulation techniques, a new approach called computerised modified PAT (CMPAT) was proposed. Therefore, the aim of this study is to discuss a randomised controlled trial (RCT) protocol to investigate and compare the effects of CMPAT and MAT in patients undergoing LP.Methods and analysis We will conduct a prospective, multicentre RCT. The study will recruit 84 patients aged 18–99 years who require LP. Participants will be randomly assigned to either the CMPAT treatment group (group A) or the MAT treatment group (group B). The primary outcome measure will be the number of needle insertion attempts required for a successful LP. Secondary outcomes will include the puncture success rate, pain assessment in the back, head, and legs, and the occurrence of complications. The measurement of these secondary outcomes will be taken during the procedure, as well as at specific time points: 30 min, 6 hours, 1 day, 3 days, 7 days, 2 weeks and 4 weeks after the procedure. Pain levels will be assessed using a Numerical Rating Scale.Ethics and dissemination Ethical approval (2022YF052-01) has been obtained from the Ethics Committee of Fujian Medical University Union Hospital, Fuzhou, China. The research findings will be published in an international peer-reviewed scientific journal and presented at scientific conferences.Trial registration number ChiCTR2300067937.

ObjectiveTo evaluate the safety and clinical effect of tubular esophagogastric anastomosis in laparoscopic radical proximal gastrectomy.MethodsA retrospective analysis was conducted involving 191 patients who underwent laparoscopic radical proximal gastrectomy in the Department of Gastrointestinal Surgery, Qilu Hospital of Shandong University from January 2017 to October 2020. Patients were divided into tubular esophagogastric anastomosis group (TG group) and traditional esophagogastric anastomosis group (EG group) according to the digestive tract reconstruction. Their intraoperative conditions, perioperative recovery and postoperative follow-up were compared. Patients were also divided into indocyanine green group and non-indocyanine green group according to whether or not indocyanine green tracer technology was used during the operation. Their intraoperative condition and perioperative recovery were compared and analyzed after propensity score matching.ResultsThe operation was successfully completed in all patients. Compared with the EG group, the TG group had less volume of gastric tube drainage, shorter gastric tube drainage time and proton pump inhibitors application time, and lower reuse rate of proton pump inhibitors. However, the TG group had a higher anastomotic stenosis at three months after surgery, as measured using anastomotic width and dysphagia score. Nevertheless, the incidence of reflux esophagitis and postoperative quality of life score in the TG group were lower compared with the EG group at 1st and 2nd year after surgery. In the indocyanine green analysis, the indocyanine green group had significantly shorter total operation time and lymph node dissection time and less intraoperative blood loss compared with the non-indocyanine green group. However, compared with the non-indocyanine green group, more postoperative lymph nodes were obtained in the indocyanine green group.ConclusionLaparoscopic radical proximal gastrectomy is safe and effective treatment option for upper gastric cancer. Tubular esophagogastric anastomosis has more advantages in restoring postoperative gastrointestinal function and reducing reflux, but it has a higher incidence of postoperative anastomotic stenosis compared with traditional esophagogastrostomy. The application of indocyanine green tracer technique in laparoscopic radical proximal gastrectomy has positive significance.

A predictive model utilizing near-infrared spectroscopy was developed to estimate the loss on drying, total contents of crocin I and crocin II, and picrocrocin content of saffron. Initially, the LD values were determined using a moisture-ash analyzer, while HPLC was employed for measuring the total contents of crocin I, crocin II, and picrocrocin. The near-infrared spectra of 928 saffron samples were collected and preprocessed using first derivative, standard normal variable transformation, detrended correction, multivariate scattering correction, Savitzky–Golay smoothing, and mean centering methods. Leveraging the partial least squares method, regression models were constructed, with parameters optimized through a selective combination of the above six preprocessing methods. Subsequently, prediction models for loss on drying, total contents of crocin I and crocin II, and picrocrocin content were established, and the prediction accuracy of the models was verified. The correlation coefficients and root mean square error of loss on drying, total contents of crocin I and crocin II, and picrocrocin content demonstrated high accuracy, with R2 values of 0.8627, 0.8851, and 0.8592 and root mean square error values of 0.0260, 0.0682, and 0.0465. This near-infrared prediction model established in the present study offers a precise and efficient means of assessing loss on drying, total contents of crocin I and crocin II, and picrocrocin content in saffron and is useful for the development of a rapid quality evaluation system. [ABSTRACT FROM AUTHOR]

Taking the test signals of magneto-rheological vibration system under different states as research objects, four Generalized Regression Neural Network (GRNN) prediction algorithms, based on time series, time series Auto-Regressive (AR) model coefficients, time series box dimensions, and Variational Modal Decomposition (VMD) box dimensions, are designed. Moreover, four Back Propagation Neural Network (BPNN)comparative prediction algorithms, based on the four previous parameters, are also designed. These eight algorithms are applied to predict vibration damping efficiency of the system. The prediction results show that, compared to the BPNN prediction algorithm, the corresponding four GRNN prediction algorithms have the advantages of strong self-learning ability, fast convergence speed, high prediction accuracy, and stable prediction results. Among the eight prediction algorithms, the GRNN prediction algorithm, based on VMD box dimension, forecasts the results with good stability, better self-learning ability, and higher computing speed, which can maximize the prediction accuracy of the system, the minimum prediction error can reach 1.9049% when the parameters K = 4, N = 33 , and Spread = 0.601. To sum up, through parameter optimization, the optimal parameter combination scheme of GRNN prediction algorithm, based on VMD box dimension, is obtained, and the best prediction effect is achieved.