Enzymatic Reaction Enhanced Diffusion Accelerates Cargo Transport through Micro/Nano-Channels.

Energy conversion and transfer of enzyme-catalyzed reactions at molecular level are an interesting and challenging scientific topic that helps understanding biological processes in nature. In this study, it is demonstrated that enzyme-catalyzed reactions can enhance diffusion of surrounding molecules and thus accelerate cargo transport within 1D micro/nanochannels. Specifically, urease is immobilized on the inner walls of silica micro/nano-tubes to construct bio-catalytically active micro/nanochannels. The catalytic reaction inside the channels drives a variety of cargoes, including small dye molecules, polymers, and rigid nanoparticles (e.g., quantum dots, QDs), to pass through these micro/nanochannels much faster than they will by free diffusion. The enhanced diffusion of molecular species inside the channels is validated by direct observation of the Brownian motion of tracer particles, and further confirmed by significantly enhanced Raman intensity of reporter molecules. Finite element and Brownian dynamics simulations provide a theoretical understanding of these experimental observations. Furthermore, the effect of the channels' size on the diffusion enhancement is examined. The acceleration effect of the cargo transport through these enzymatically active micro/nanochannels can be turned on or off via chemical activators or inhibitors. This study provides valuable insights on the design of biomimetic channels capable of controlled and efficient transmembrane transport.

Association between obstructive sleep apnea severity and depression risk: a systematic review and dose-response meta-analysis.

Obstructive sleep apnea (OSA) has received considerable attention as a potential risk factor for depressive symptoms. The systematic review was conducted to confirm the dose‒response connection between OSA severity and depression risk. A systematic literature search of English and Chinese articles published in PubMed, EMBASE, Scopus, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), and SinoMed databases from their inception to 28 August 2023 was conducted. An evaluation using the Newcastle‒Ottawa Scale was performed. A meta-analysis was used to evaluate the impact of OSA severity. A random-effects dose‒response model was conducted to evaluate the linear and nonlinear dose‒response connections. We evaluated publication bias by funnel plots, and symmetry by Egger's test. We identified 18 cross-sectional researches. 3143 participants which were involved in the dose‒response meta-analysis. Contrasted with mild OSA, individuals with severe OSA had a higher adjusted risk of depression (rate ratio: 1.34, 95% confidence interval = 1.05-1.70), with substantial heterogeneity (I2 = 70.9%, Pheterogeneity<0.001). There is a significant linear connection between OSA severity and depression risk. The depression risk increased by 0.4% for every 1 event per hour increase in the apnea-hypopnea index (AHI). The protocol for this unfunded research was drafted and registered at PROSPERO (ID CRD42023474097).

An Adaptive Multi-Population Approach for Sphericity Error Evaluation in the Manufacture of Hemispherical Shell Resonators.

The performance of a hemispherical resonant gyroscope (HRG) is directly affected by the sphericity error of the thin-walled spherical shell of the hemispherical shell resonator (HSR). In the production process of the HSRs, high-speed, high-accuracy, and high-robustness requirements are necessary for evaluating sphericity errors. We designed a sphericity error evaluation method based on the minimum zone criterion with an adaptive number of subpopulations. The method utilizes the global optimal solution and the subpopulations' optimal solution to guide the search, initializes the subpopulations through clustering, and dynamically eliminates inferior subpopulations. Simulation experiments demonstrate that the algorithm exhibits excellent evaluation accuracy when processing simulation datasets with different sphericity errors, radii, and numbers of sampling points. The uncertainty of the results reached the order of 10-9 mm. When processing up to 6000 simulation datasets, the algorithm's solution deviation from the ideal sphericity error remained around -3 × 10-9 mm. And the sphericity error evaluation was completed within 1 s on average. Additionally, comparison experiments further confirmed the evaluation accuracy of the algorithm. In the HSR sample measurement experiments, our algorithm improved the sphericity error assessment accuracy of the HSR's inner and outer contour sampling datasets by 17% and 4%, compared with the results given by the coordinate measuring machine. The experiment results demonstrated that the algorithm meets the requirements of sphericity error assessment in the manufacturing process of the HSRs and has the potential to be widely used in the future.

Effectiveness of Maze IV procedure versus thoracoscopic ablation for atrial fibrillation: a propensity score-matched analysis.

Background: Thoracoscopic ablation (TA) has emerged as a promising treatment for atrial fibrillation (AF), with the Cox-Maze IV Procedure (CMP-IV) as the current gold-standard intervention. This study aims to evaluate and compare the outcomes of TA and CMP-IV in treating AF. Methods: Patients with AF underwent either CMP-IV or TA through a left-side chest approach. The CMP-IV entailed bi-atrium ablation, whereas the TA involved creating three circular plus three linear ablations in the left atrium. We analyzed baseline characteristics, perioperative outcomes and recurrence rates using propensity score matching (PSM) at a 1:1 ratio, to ensure comparability between the two treatment groups. Results: A total of 459 patients underwent either CMP-IV (n=93) or TA via left chest (n=366) and 174 patients were deemed eligible for 1:1 PSM. The TA group experienced significantly shorter intensive care unit (ICU) and hospital stays. The mean follow-up period was 31.5±22.1 months. Pre- and post-matching analysis showed that CMP-IV had a higher rate of freedom from recurrence compared to TA, particularly in non-paroxysmal AF patients. Multivariable Cox regression analysis revealed that CMP-IV was associated with a reduced risk of recurrence, while an increased left atrial size emerged as an independent predictor of postoperative recurrence, regardless of the use of CMP-IV or TA. Conclusions: Our study suggests that while the therapeutic efficacy of TA for "lone" AF may fall short of the classic CMP-IV, its less invasive nature results in significantly shorter ICU and hospital stays. To enhance patient outcomes following TA, it is essential to improve the quality of ablation, refine the ablation route, and focus on careful patient selection.

SIRT6-mediated vascular smooth muscle cells senescence participates in the pathogenesis of abdominal aortic aneurysm.

BACKGROUND AND AIMS: In this study, we carried out a clinical sample study, and in vivo and in vitro studies to evaluate the effect of SIRT6 and SIRT6-mediated vascular smooth muscle senescence on the development of abdominal aortic aneurysm (AAA). METHOD AND RESULTS: AAA specimen showed an increased P16, P21 level and a decreased SIRT6 level compared with control aorta. Time curve study of Ang II infusion AAA model showed similar P16, P21 and SIRT6 changes at the early phase of AAA induction. The in vivo overexpression of SIRT6 significantly prevented AAA formation in Ang II infusion model. The expression of P16 and P21 was significantly reduced after SIRT6 overexpression. SIRT6 overexpression also attenuated chronic inflammation and neo-angiogenesis in Ang II infusion model. The overexpression of SIRT6 could attenuate premature senescence, inflammatory response and neo-angiogenesis in human aortic smooth muscle cells (HASMC) under Ang II stimulation. CONCLUSIONS: SIRT6 overexpression could limit AAA formation via attenuation of vascular smooth muscle senescence, chronic inflammation and neovascularity.

Differences in attentional function between experienced mindfulness meditators and non-meditators.

Introduction: Attentional enhancement has often been identified as the central cognitive mechanism underlying the benefits of mindfulness meditation. However, the extent to which this enhancement is observable in the neural processes underlying long-term meditation is unclear. This current study aimed to examine differences in attentional performance between meditators and controls (non-meditators) using a visual oddball task with concurrent electroencephalography (EEG) recordings. Methods: Thirty-four participants were recruited, including 16 meditators and 18 healthy controls, who were non-meditators. The participants completed a visual oddball task, using visual stimuli, and EEG recording. Results: Self-reports revealed that meditators had higher mindful attention scores than did the control group. The behavioral results showed that the meditators demonstrated faster reaction times than the non-meditators did. Neural findings indicated a higher P2 amplitude in the meditators than in the controls. The meditators demonstrated a significantly higher P3 in the target trials than in the distractor trials, which was not observed in the controls. Additionally, the time-frequency analysis demonstrated that the delta and theta powers in the meditators were significantly higher than those in the controls. Conclusions: The study suggests the meditators exhibited greater attentional performance than the controls did, as revealed by EEG and behavioral measures. This study extends previous research on the effects of mindfulness meditation on attention and adds to our understanding of the effects of long-term mindfulness meditation.

A systematic evaluation of computation methods for cell segmentation.

Cell segmentation is a fundamental task in analyzing biomedical images. Many computational methods have been developed for cell segmentation, but their performances are not well understood in various scenarios. We systematically evaluated the performance of 18 segmentation methods to perform cell nuclei and whole cell segmentation using light microscopy and fluorescence staining images. We found that general-purpose methods incorporating the attention mechanism exhibit the best overall performance. We identified various factors influencing segmentation performances, including training data and cell morphology, and evaluated the generalizability of methods across image modalities. We also provide guidelines for choosing the optimal segmentation methods in various real application scenarios. We developed Seggal, an online resource for downloading segmentation models already pre-trained with various tissue and cell types, which substantially reduces the time and effort for training cell segmentation models.

The application of impulse oscillometry system based on machine learning algorithm in the diagnosis of chronic obstructive pulmonary disease.

Objective. Diagnosing chronic obstructive pulmonary disease (COPD) using impulse oscillometry (IOS) is challenging due to the high level of clinical expertise it demands from doctors, which limits the clinical application of IOS in screening. The primary aim of this study is to develop a COPD diagnostic model based on machine learning algorithms using IOS test results.Approach. Feature selection was conducted to identify the optimal subset of features from the original feature set, which significantly enhanced the classifier's performance. Additionally, secondary features area of reactance (AX) were derived from the original features based on clinical theory, further enhancing the performance of the classifier. The performance of the model was analyzed and validated using various classifiers and hyperparameter settings to identify the optimal classifier. We collected 528 clinical data examples from the China-Japan Friendship Hospital for training and validating the model.Main results. The proposed model achieved reasonably accurate diagnostic results in the clinical data (accuracy = 0.920, specificity = 0.941, precision = 0.875, recall = 0.875).Significance. The results of this study demonstrate that the proposed classifier model, feature selection method, and derived secondary feature AX provide significant auxiliary support in reducing the requirement for clinical experience in COPD diagnosis using IOS.

The Impact of Spatial Frequency on the Perception of Crowd Emotion: An fMRI Study.

Recognizing the emotions of faces in a crowd is crucial for understanding overall behavior and intention as well as for smooth and friendly social interactions. However, it is unclear whether the spatial frequency of faces affects the discrimination of crowd emotion. Although high- and low-spatial-frequency information for individual faces is processed by distinct neural channels, there is a lack of evidence on how this applies to crowd faces. Here, we used functional magnetic resonance imaging (fMRI) to investigate neural representations of crowd faces at different spatial frequencies. Thirty-three participants were asked to compare whether a test face was happy or more fearful than a crowd face that varied in high, low, and broad spatial frequencies. Our findings revealed that fearful faces with low spatial frequencies were easier to recognize in terms of accuracy (78.9%) and response time (927 ms). Brain regions, such as the fusiform gyrus, located in the ventral visual stream, were preferentially activated in high spatial frequency crowds, which, however, were the most difficult to recognize behaviorally (68.9%). Finally, the right inferior frontal gyrus was found to be better activated in the broad spatial frequency crowds. Our study suggests that people are more sensitive to fearful crowd faces with low spatial frequency and that high spatial frequency does not promote crowd face recognition.

Importance of timing and training to implement awake prone positioning in patients with COVID-19: a single-center prospective observational study.

Background: Awake prone positioning (APP) is broadly implemented in patients with severe acute respiratory syndrome coronavirus 2 related disease [coronavirus disease 2019 (COVID-19)] admitted to hospital with severe respiratory distress syndrome. This prospective observational study aimed to explore the factors influencing the implementation of APP in patients with acute respiratory failure due to COVID-19. Methods: Patients with COVID-19, all hospitalized with positive X-ray findings and oxygen supplementation requirement, in the Respiratory Step-Down Unit of the Peking University Third Hospital between January 6th, 2023, and January 20th, 2023, were included in this study. Data regarding basic information, activities of daily living (ADLs) scores, oxygen therapy, vital signs, and duration of APP were collected to investigate the factors influencing prone positioning. Results: Among the 134 patients included, 55.2% showed an improvement in oxygen saturation 1 hour after APP. Logistic regression revealed that the pre-APP heart rate (HR) [odds ratio (OR) =1.032; P=0.046] and peripheral oxygen saturation (SpO2) (OR =0.720; P<0.001) were the associated factors of the improvement in SpO2 after treatment. Multiple linear regression revealed that the ADL scores and pre-APP respiratory rate (RR) were the associated factors of the duration of prone positioning (P<0.01). The APP technical steering group effectively improved duration of APP. Conclusions: Patients with low SpO2 and increased HR before treatment showed greater improvement in oxygen saturation. Patients with lower tolerance to ADL but lower RRs were those to demonstrate a longer duration of prone positioning. This is pointing towards establishing the most favorable time window for APP during the course of COVID-19: after the ADLs have already decreased, but before significant tachypnea has appeared.