Application of iterative feedback tuning

Master'sMASTER OF ENGINEERIN

Increased transgene expression mediated by recombinant adeno-associated virus in human neuroglia cells under microgravity conditions

The space environment has the special characteristics of radiation, noise particularity and weightlessness, all of which have adverse effects on astronauts’ muscles, bones, neurons and immune system. Some reports have shown that chemotherapy and radiotherapy can increase the activity of the recombinant adeno-associated virus (AAV) which is widely used in gene therapy. In this paper, recombinant AAV2 (rAAV2) was first packaged with the enhanced green fluorescence protein (eGFP) gene and used to infect neuroglia cells including the U87 and U251 cell lines, under microgravity conditions; it was then detected by fluorescence microscopy and flow cytometry. The results show that microgravity affects the adhesion ability of cells, promotes transgene expression induced by rAAV2 and causes changes of viral infection receptors at different time points. These findings broaden the current understanding of the microgravity effects on rAAV, with significant implications in gene therapy and the mechanisms of increased virus pathogenicity under space microgravity.

Noninvasive suspicious liquid detection using wireless signals

Conventional liquid detection instruments are very expensive and not conducive to large-scale deployment. In this work, we propose a method for detecting and identifying suspicious liquids based on the dielectric constant by utilizing the radio signals at a 5G frequency band. There are three major experiments: first, we use wireless channel information (WCI) to distinguish between suspicious and nonsuspicious liquids; then we identify the type of suspicious liquids; and finally, we distinguish the different concentrations of alcohol. The K-Nearest Neighbor (KNN) algorithm is used to classify the amplitude information extracted from the WCI matrix to detect and identify liquids, which is suitable for multimodal problems and easy to implement without training. The experimental result analysis showed that our method could detect more than 98% of the suspicious liquids, identify more than 97% of the suspicious liquid types, and distinguish up to 94% of the different concentrations of alcohol

Protein-energy malnutrition and worse outcomes after major cancer surgery: A nationwide analysis

BackgroundProtein-energy malnutrition (PEM) has been recognized as a poor prognostic factor in many clinical issues. However, nationwide population studies concerning the impact of PEM on outcomes after major cancer surgery (MCS) are lacking. We aimed to evaluate the postoperative outcomes associated with PEM following MCS.MethodsBy using the Nationwide Inpatient Sample database, data of patients undergoing MCS including colectomy, cystectomy, esophagectomy, gastrectomy, hysterectomy, lung resection, pancreatectomy, or prostatectomy were analyzed retrospectively from 2009 to 2015, resulting in a weighted estimate of 1,335,681 patients. The prevalence trend of PEM, as well as mortality and major complications after MCS were calculated. Multivariable regression analysis was applied to estimate the impact of PEM on postoperative outcomes after MCS.ResultsPEM showed an estimated annual percentage increase of 7.17% (95% confidence interval (CI): 4-10.44%) from 2009 to 2015, which contrasts with a 4.52% (95% CI: -6.58–2.41%) and 1.21% (95% CI: -1.85–0.56%) annual decrease in mortality and major complications in patients with PEM after MCS. PEM was associated with increased risk of mortality (odds ratio (OR)=2.26; 95% CI: 2.08-2.44; P < 0.0001), major complications (OR=2.46; 95% CI: 2.36-2.56; P < 0.0001), higher total cost ($35814 [$22292, $59579] vs.$16825 [$11393,$24164], P < 0.0001), and longer length of stay (14 [9-21] days vs. 4 [2-7] days, P < 0.0001), especially in patients underwent prostatectomy, hysterectomy and lung resection.ConclusionsPEM was associated with increased worse outcomes after major cancer surgery. Early identification and timely medical treatment of PEM for patients with cancer are crucial for improving postoperative outcomes

Acid-Base Clusters during Atmospheric New Particle Formation in Urban Beijing

Molecular clustering is the initial step of atmospheric new particle formation (NPF) that generates numerous secondary particles. Using two online mass spectrometers with and without a chemical ionization inlet, we characterized the neutral clusters and the naturally charged ion clusters during NPF periods in urban Beijing. In ion clusters, we observed pure sulfuric acid (SA) clusters, SA-amine clusters, SA-ammonia (NH3) clusters, and SA-amine-NH3 clusters. However, only SA clusters and SA-amine clusters were observed in the neutral form. Meanwhile, oxygenated organic molecule (OOM) clusters charged by a nitrate ion and a bisulfate ion were observed in ion clusters. Acid-base clusters correlate well with the occurrence of sub-3 nm particles, whereas OOM clusters do not. Moreover, with the increasing cluster size, amine fractions in ion acid-base clusters decrease, while NH3 fractions increase. This variation results from the reduced stability differences between SA-amine clusters and SA-NH3 clusters, which is supported by both quantum chemistry calculations and chamber experiments. The lower average number of dimethylamine (DMA) molecules in atmospheric ion clusters than the saturated value from controlled SA-DMA nucleation experiments suggests that there is insufficient DMA in urban Beijing to fully stabilize large SA clusters, and therefore, other basic molecules such as NH3 play an important role.Peer reviewe

Associations between maternal complications during pregnancy and childhood asthma: a retrospective cohort study

© 2023 The Authors. Published by the European Respiratory Society. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://openres.ersjournals.com/content/9/2/00548-2022Background Studies on the associations between maternal complications during pregnancy and childhood asthma are exclusively conducted in Western countries. The findings are mixed and may not be translated to other populations. We aimed to investigate the associations among the Chinese population and to determine whether the associations were mediated through pre-term birth, caesarean delivery, low birthweight and not breastfeeding in the first 6 months. Methods We conducted a retrospective cohort study of 166 772 children in Guangzhou, China. Information on maternal gestational hypertension, gestational diabetes and gestational anaemia during pregnancy was extracted from medical records. Ever-diagnosis of asthma in children aged 6–12 years was obtained by questionnaire. Logistic regression models and mediation analyses were used to estimate the adjusted odds ratios (aORs) and 95% confidence intervals for childhood asthma. Results Gestational hypertension, gestational diabetes and gestational anaemia during pregnancy were associated with an increased risk of ever-diagnosed childhood asthma: aOR 1.48 (95% CI 1.37–1.60), 1.71 (95% CI 1.65–1.78) and 1.34 (95% CI 1.26–1.45), respectively. A stronger association was observed for two or three gestational complications (aOR 2.02 (95% CI 1.93–2.16)) than one gestational complication (aOR 1.64 (95% CI 1.52–1.77)). The aOR for the three gestational complications was 1.35 (95% CI 1.26–1.45), 1.63 (95% CI 1.58–1.70) and 1.32 (95% CI 1.24–1.43), respectively, after controlling for the mediators, including pre-term birth, caesarean delivery, low birthweight and not breastfeeding in the first 6 months. Conclusions Gestational hypertension, gestational diabetes and gestational anaemia were associated with childhood asthma, and the associations were partially explained by the mediation effects.This study was supported by National Natural Science Foundation of China (82073571 and 81773457 to J. Tang).Published versio

Evaluation of a computer-aided diagnostic model for corneal diseases by analyzing in vivo confocal microscopy images

ObjectiveIn order to automatically and rapidly recognize the layers of corneal images using in vivo confocal microscopy (IVCM) and classify them into normal and abnormal images, a computer-aided diagnostic model was developed and tested based on deep learning to reduce physicians’ workload.MethodsA total of 19,612 corneal images were retrospectively collected from 423 patients who underwent IVCM between January 2021 and August 2022 from Renmin Hospital of Wuhan University (Wuhan, China) and Zhongnan Hospital of Wuhan University (Wuhan, China). Images were then reviewed and categorized by three corneal specialists before training and testing the models, including the layer recognition model (epithelium, bowman’s membrane, stroma, and endothelium) and diagnostic model, to identify the layers of corneal images and distinguish normal images from abnormal images. Totally, 580 database-independent IVCM images were used in a human-machine competition to assess the speed and accuracy of image recognition by 4 ophthalmologists and artificial intelligence (AI). To evaluate the efficacy of the model, 8 trainees were employed to recognize these 580 images both with and without model assistance, and the results of the two evaluations were analyzed to explore the effects of model assistance.ResultsThe accuracy of the model reached 0.914, 0.957, 0.967, and 0.950 for the recognition of 4 layers of epithelium, bowman’s membrane, stroma, and endothelium in the internal test dataset, respectively, and it was 0.961, 0.932, 0.945, and 0.959 for the recognition of normal/abnormal images at each layer, respectively. In the external test dataset, the accuracy of the recognition of corneal layers was 0.960, 0.965, 0.966, and 0.964, respectively, and the accuracy of normal/abnormal image recognition was 0.983, 0.972, 0.940, and 0.982, respectively. In the human-machine competition, the model achieved an accuracy of 0.929, which was similar to that of specialists and higher than that of senior physicians, and the recognition speed was 237 times faster than that of specialists. With model assistance, the accuracy of trainees increased from 0.712 to 0.886.ConclusionA computer-aided diagnostic model was developed for IVCM images based on deep learning, which rapidly recognized the layers of corneal images and classified them as normal and abnormal. This model can increase the efficacy of clinical diagnosis and assist physicians in training and learning for clinical purposes

A type of novel energy harvesting device

Pervasive networks of wi reless sensors and communication nodes have been developed during past decades and most of them are powered by fixed-energy sources, e.g., wiring power and batteries. However, these traditional energy sources are impractical for powering wireless devices due to their inherent limitations, e.g., the high setup cost of wiring power and the finite life span of batteries. In view of these facts, more attentions have been drawn on vibration energy sources existing in ambient environment where sensors operate. Dozens of different types of vibrat ion energy scavenging devices have been developed, which are mainly consisted of mechanical systems coupled with transduction mechanisms. The linear mechanical system has been used in most of existing vibration generators. The main drawback of such system is that it has a rather narrow bandwidth, meaning that the device can only effectively harvest vibration energy when the resonance frequency of the system coincides with the excitation frequency. Various methods have been proposed recently 10 overcome the drawback including utili sing mechan ical systems with non-linear mechanisms in order to increase the bandwidth of vibration energy scavenging devices. The dissertation is intended 10 fi nd a practically effective non-linear mechanical system with desirab le dynamic behaviours for vibration energy scavenging devices. To do so, we first examined three non-linear mechanisms numerically to find the most desirable one based on the corresponding typical mechanical systems. The Numerical Simulation (NS) method built in Matlab has been used to explore the static and dynamic characteristics of these systems with hardening and softening mechanismsEThOS - Electronic Theses Online ServiceGBUnited Kingdo