Sweat permeable and ultrahigh strength 3D PVDF piezoelectric nanoyarn fabric strain sensor

Commercial wearable piezoelectric sensors possess excellent anti-interference stability due to their electronic packaging. However, this packaging renders them barely breathable and compromises human comfort. To address this issue, we develop a PVDF piezoelectric nanoyarns with an ultrahigh strength of 313.3 MPa, weaving them with different yarns to form three-dimensional piezoelectric fabric (3DPF) sensor using the advanced 3D textile technology. The tensile strength (46.0 MPa) of 3DPF exhibits the highest among the reported flexible piezoelectric sensors. The 3DPF features anti-gravity unidirectional liquid transport that allows sweat to move from the inner layer near to the skin to the outer layer in 4 s, resulting in a comfortable and dry environment for the user. It should be noted that sweating does not weaken the piezoelectric properties of 3DPF, but rather enhances. Additionally, the durability and comfortability of 3DPF are similar to those of the commercial cotton T-shirts. This work provides a strategy for developing comfortable flexible wearable electronic devices

Specific biomarker mining and rapid detection of Burkholderia cepacia complex by recombinase polymerase amplification

ObjectiveTo mine specific proteins and their protein-coding genes as suitable molecular biomarkers for the Burkholderia cepacia Complex (BCC) bacteria detection based on mega analysis of microbial proteomic and genomic data comparisons and to develop a real-time recombinase polymerase amplification (rt-RPA) assay for rapid isothermal screening for pharmaceutical and personal care products.MethodsWe constructed an automatic screening framework based on Python to compare the microbial proteomes of 78 BCC strains and 263 non-BCC strains to identify BCC-specific protein sequences. In addition, the specific protein-coding gene and its core DNA sequence were validated in silico with a self-built genome database containing 158 thousand bacteria. The appropriate methodology for BCC detection using rt-RPA was evaluated by 58 strains in pure culture and 33 batches of artificially contaminated pharmaceutical and personal care products.ResultsWe identified the protein SecY and its protein-coding gene secY through the automatic comparison framework. The virtual evaluation of the conserved region of the secY gene showed more than 99.8% specificity from the genome database, and it can distinguish all known BCC species from other bacteria by phylogenetic analysis. Furthermore, the detection limit of the rt-RPA assay targeting the secY gene was 5.6 × 102 CFU of BCC bacteria in pure culture or 1.2 pg of BCC bacteria genomic DNA within 30 min. It was validated to detect <1 CFU/portion of BCC bacteria from artificially contaminated samples after a pre-enrichment process. The relative trueness and sensitivity of the rt-RPA assay were 100% in practice compared to the reference methods.ConclusionThe automatic comparison framework for molecular biomarker mining is straightforward, universal, applicable, and efficient. Based on recognizing the BCC-specific protein SecY and its gene, we successfully established the rt-RPA assay for rapid detection in pharmaceutical and personal care products

Association of GSDMD with microvascular-ischemia reperfusion injury after ST-elevation myocardial infarction

ObjectivesLittle is known about the clinical prognosis of gasdermin D (GSDMD) in patients with ST-elevation myocardial infarction (STEMI). The purpose of this study was to investigate the association of GSDMD with microvascular injury, infarction size (IS), left ventricular ejection fraction (LVEF), and major adverse cardiac events (MACEs), in STEMI patients with primary percutaneous coronary intervention (pPCI).MethodsWe retrospectively analyzed 120 prospectively enrolled STEMI patients (median age 53 years, 80% men) treated with pPCI between 2020 and 2021 who underwent serum GSDMD assessment and cardiac magnetic resonance (CMR) within 48 h post-reperfusion; CMR was also performed at one year follow-up.ResultsMicrovascular obstruction was observed in 37 patients (31%). GSDMD concentrations ≧ median (13 ng/L) in patients were associated with a higher risk of microvascular obstruction and IMH (46% vs. 19%, P = 0.003; 31% vs. 13%, P = 0.02, respectively), as well as with a lower LVEF both in the acute phase after infarction (35% vs. 54%, P < 0.001) and in the chronic phase (42% vs. 56%, P < 0.001), larger IS in the acute (32% vs. 15%, P < 0.001) and in the chronic phases (26% vs. 11%, P < 0.001), and larger left ventricular volumes (119 ± 20 vs. 98 ± 14, P = 0.003) by CMR. Univariable and multivariable Cox regression analysis results showed that patients with GSDMD concentrations ≧ median (13 ng/L) had a higher incidence of MACE (P < 0.05).ConclusionsHigh GSDMD concentrations in STEMI patients are associated with microvascular injury (including MVO and IMH), which is a powerful MACE predictor. Nevertheless, the therapeutic implications of this relation need further research

Prediction of recurrence of ischemic stroke within 1 year of discharge based on machine learning MRI radiomics

PurposeThis study aimed to investigate the value of a machine learning-based magnetic resonance imaging (MRI) radiomics model in predicting the risk of recurrence within 1 year following an acute ischemic stroke (AIS).MethodsThe MRI and clinical data of 612 patients diagnosed with AIS at the Second Affiliated Hospital of Nanchang University from March 1, 2019, to March 5, 2021, were obtained. The patients were divided into recurrence and non-recurrence groups according to whether they had a recurrent stroke within 1 year after discharge. Randomized splitting was used to divide the data into training and validation sets using a ratio of 7:3. Two radiologists used the 3D-slicer software to label the lesions on brain diffusion-weighted (DWI) MRI sequences. Radiomics features were extracted from the annotated images using the pyradiomics software package, and the features were filtered using the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. Four machine learning algorithms, logistic regression (LR), Support Vector Classification (SVC), LightGBM, and Random forest (RF), were used to construct a recurrence prediction model. For each algorithm, three models were constructed based on the MRI radiomics features, clinical features, and combined MRI radiomics and clinical features. The sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve (AUC) were used to compare the predictive efficacy of the models.ResultsTwenty features were selected from 1,037 radiomics features extracted from DWI images. The LightGBM model based on data with three different features achieved the best prediction accuracy from all 4 models in the validation set. The LightGBM model based solely on radiomics features achieved a sensitivity, specificity, and AUC of 0.65, 0.671, and 0.647, respectively, and the model based on clinical data achieved a sensitivity, specificity, and AUC of 0.7, 0.799, 0.735, respectively. The sensitivity, specificity, and AUC of the LightGBM model base on both radiomics and clinical features achieved the best performance with a sensitivity, specificity, and AUC of 0.85, 0.805, 0.789, respectively.ConclusionThe ischemic stroke recurrence prediction model based on LightGBM achieved the best prediction of recurrence within 1 year following an AIS. The combination of MRI radiomics features and clinical data improved the prediction performance of the model

Investigation of Variation in Gene Expression Profiling of Human Blood by Extended Principle Component Analysis

BACKGROUND: Human peripheral blood is a promising material for biomedical research. However, various kinds of biological and technological factors result in a large degree of variation in blood gene expression profiles. METHODOLOGY/PRINCIPAL FINDINGS: Human peripheral blood samples were drawn from healthy volunteers and analysed using the Human Genome U133Plus2 Microarray. We applied a novel approach using the Principle Component Analysis and Eigen-R(2) methods to dissect the overall variation of blood gene expression profiles with respect to the interested biological and technological factors. The results indicated that the predominating sources of the variation could be traced to the individual heterogeneity of the relative proportions of different blood cell types (leukocyte subsets and erythrocytes). The physiological factors like age, gender and BMI were demonstrated to be associated with 5.3% to 9.2% of the total variation in the blood gene expression profiles. We investigated the gene expression profiles of samples from the same donors but with different levels of RNA quality. Although the proportion of variation associated to the RNA Integrity Number was mild (2.1%), the significant impact of RNA quality on the expression of individual genes was observed. CONCLUSIONS: By characterizing the major sources of variation in blood gene expression profiles, such variability can be minimized by modifications to study designs. Increasing sample size, balancing confounding factors between study groups, using rigorous selection criteria for sample quality, and well controlled experimental processes will significantly improve the accuracy and reproducibility of blood transcriptome study

In vivo cellular and molecular magnetic resonance imaging of brain functions and injuries

As compared with other imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI) provides distinctive advantages with better contrast and resolution in imaging brain anatomy and function in vivo. As compared with electrophysiological and histological tracing techniques, MRI enables longitudinal investigation with higher efficiency, lower labor cost and less possibility of sampling error. The major objective of this doctoral work is to utilize cellular and molecular MRI to investigate normal brain functions and injuries in vivo. The results successfully demonstrated MRI as an efficient and sensitive tool for providing comprehensive assessment of brain injuries for promoting accurate prognosis and timely intervention, and for studying fundamental questions with regard to cortical adaptations to challenges in the young adulthood. Firstly, diffusion tensor imaging (DTI) and T2-weighted imaging were employed to characterize longitudinal neuronal and axonal changes of pyramidal tract (PY), a critical part of corticospinal tract, following experimental intracerebral hemorrhage (ICH). Combining DTI with T2-weighted imaging results, ipsilateral PY injuries following ICH were diagnosed as four stages. Quantitative analysis revealed transient diffusivity decreases in PY both contralateral and ipsilateral to the primary hemorrhagic site. Evolution of the ipsilateral DTI parameters correlated with histological findings and indicated evolving and complex pathological processes underlying monotonic FA decrease. These results demonstrated multi-parametric DTI as a valuable imaging tool for non-invasive and longitudinal monitoring of secondary PY injuries. Secondly, DTI and manganese-enhanced MRI (MEMRI) were utilized to detect neuronal changes of substantia nigra (SN) following experimental ICH in rodents. DTI revealed early changes in SN both contralateral and ipsilateral to the primary hemorrhagic site. Evolution of the ipsilateral parameters correlated with the histological results. MEMRI provided insights into the cellular phenotype changes at the late stage. DTI can serve as a valuable imaging tool for non-invasive early detection and longitudinal monitoring of secondary SN injuries, while MEMRI could complementally provide information regarding the late stage inflammation process. Multi-parametric MRI could facilitate clinical and preclinical investigations of SN injuries for exploring disease mechanisms and developing new therapeutic strategies. Thirdly, MEMRI was performed to characterize the interhemispheric interactions in normal and monocularly deprived rodent visual brain. Characteristic transcallosal manganese labeling was observed in the normal group in a manner consistent with previous histological findings. Significant decrease of such labeling was observed in rats with left or right eyelid suturing, or with left eye enucleation, but not in rats with right eye enucleation. These results demonstrated MEMRI as an efficient tool for investigating interhemispheric interactions both anatomically and functionally. These results also indicated that the adult brain recruits different mechanisms for its adaptations to eyelid suturing and enucleation, thus shedding light on our understanding of the transcallosal interhemispheric excitation and inhibition. Lastly, new paradigms other than pressure injection for intracortical manganese administration in MEMRI were introduced to minimize the neuro-toxicity of manganese and maximize the sensitivity of MEMRI for studying cortical functional changes. Transmeningeal diffusion, osmotic pump-based infusion, and intranasal instillation were demonstrated to be successful in tracing interhemispheric connections and detecting stress-related cortical and subcortical changes.published_or_final_versionElectrical and Electronic EngineeringDoctoralDoctor of Philosoph

In vivo cellular and molecular magnetic resonance imaging of brain functions and injuries

abstractElectrical and Electronic EngineeringDoctoralDoctor of Philosoph