Novel Polyurethane Based, Fully Flexible, High-Performance Piezoresistive Sensor for Real-Time Pressure Monitoring.

Flexible piezoresistive pressure sensors are garnering substantial attention, in line with advancements in biointegrated and wearable electronics. However, a significant portion of piezoresistive pressure sensors suffer from the trade-off between sensitivity and pressure range. Moreover, the current piezoresistive sensors generally rely on a rigid metallic electrode, severely deteriorating their long-term durability. Herein, a fully flexible piezoresistive sensor coupling polyurethane (PU) based electrode and active sensing element is proposed to circumvent the aforementioned problems. By rationally regulating the double-permeable conductive networks within the PU matrix, an elastomeric electrode and sensing element are implemented, respectively. The assembled heterostructured configurations enable impressive sensitivity up to 7.023 kPa-1, broad pressure detection (up to 420 kPa), an ultralow pressure sensing limit (0.1 Pa), and extraordinary operation stability over 80000 cyclic pressings along with fast response/relaxation times (60 ms/80 ms). Additionally, the fully flexible sensor is capable of both real-time detection of physiological signals and mimicking keyboards, implying its viability as a high-performance pressure sensor.

Safe Food Supply Chain as Health Network: An Evolutionary Game Analysis of Behavior Strategy for Quality Investment.

There is a natural relation between human health and the quality of their food and drinks, and elevating the quality input level of food production for all enterprises within the food supply chain system forms the foundation for preventing various potential food safety risks that may be encountered. Unlike the previous research on quality investment of food production by enterprises, this paper probes into the evolutionary routes of the behavior strategy selection of subjects in the food supply chain and the preconditions for the equilibrium points of the social co-governance system. It takes the approach of establishing a tripartite evolutionary game model of food suppliers, food manufacturers and consumers on the basis of the social co-governance framework, in view of the above, this paper focuses on the influence of the reputation mechanism and the market contracts among supply chain subjects on the selection of a behavior strategy for quality investment by enterprises under the condition of lawful regulation by government. The results show that every subject selects their own behavior strategy on the basis of the balance of their respective interests. The net disbursement incurred by enterprises for quality investment and the costs of participation in governance by consumers constitute the dominant factors that influence both enterprises' selection of a behavior strategy and the level of social co-governance. Compared with the increase in economic punishment imposed on suppliers for production of risky food raw materials, it is more efficient to control food safety risks by lowering the costs of quality investment by suppliers. Accordingly, this paper proposes advice on policy in an attempt to provide inspiration for preventing and controlling food safety risks.

An improved Bi-LSTM method based on heterogeneous features fusion and attention mechanism for ECG recognition.

Electrocardiogram (ECG) plays a critical role in early prevention and diagnosis of cardiovascular diseases. However, extracting powerful deep features from ECG signal for recognition is still a challenging problem today due to the variable abnormal rhythms and noise distribution. This work proposes a Bi-LSTM algorithm based on heterogeneous features fusion and attention mechanism (HFFAM + Bi-LSTM). Combining the empirical features and the features learned by the deep learning network, HFFAM + Bi-LSTM can comprehensively extract the temporal frequency information and spatial structure information of the ECG signal. Meanwhile, a novel attention mechanism based on improved DTW (AM-DTW) is designed to analyze and control the fusion process of features. The role of AM-DTW in HFFAM + Bi-LSTM is twofold, one is to measure the feature similarity between ECG signal sets with different labels using the improved DTW, and the other is to distinguish the features into isomorphic and heterogeneous features as well as adaptive weighting of the features. It is worth mentioning that overly similar isomorphic features are filtered out to further optimize the algorithm. Thus, HFFAM + Bi-LSTM has the advantage of strengthening the heterogeneous information in the feature subspace while accounting for the isomorphic features. The accuracy of HFFAM + Bi-LSTM reaches up to 98.1 % and 97.1 % on the simulated and real datasets, respectively. Compared to the all benchmark models, the classification accuracy of HFFAM + Bi-LSTM is 1.3 % higher than the best. The experiments also demonstrate that HFFAM + Bi-LSTM has better performance compared with existing methods, which provides a new scheme for automatic detection of ECG signal.

Food manufacturer willingness to employ blockchain technology system under the social Co-governance framework: China's situation.

The blockchain technology system has gradually come to be employed in the food supply chain system, and it has emerged that the system offers the unique function of effectively curbing counterfeiting by food manufacturers. Unlike previous research on adoption by enterprises of new technology, this paper probes into the specific evolutionary routes of game subjects from the perspective of the precondition for enterprises' willingness to employ blockchain technology on the basis of China's social co-governance framework and by establishing a tripartite evolutionary game model of food manufacturer, government and consumer. The study then tests and verifies the stability conditions of equilibrium points and the relationship between these equilibrium points and the social co-governance level through numerical simulation analysis. On the above basis, the expected market proceeds of food producers employing blockchain technology and the influence of government and consumer behavior on enterprises' selection of a behavior strategy and the level of social co-governance are analyzed. The results show that every subject selects their own behavior strategy on the basis of the balance of their respective interests, and the final stability condition of the system is independent of their initial intentions. Rather, the expected sales volume of foods employing blockchain technology, governmental behavior (e.g., supervision, casual inspection, economic punishment, and fiscal subsidies), and complaints made by consumers constitute the main factors that influence food enterprises' selection of a behavior strategy. The level of social co-governance and the behavior of both government and consumers will ultimately be accomplished by influencing enterprises' expected economic returns, and the selection of an enterprise behavior strategy internally depends on the expected economic returns from producing foods employing blockchain technology. Therefore, this paper makes relevant proposals in an attempt to assist the Chinese government to better promote and popularize the blockchain technology system among food manufacturing enterprises.

Bacterial quorum sensing orchestrates longitudinal interactions to shape microbiota assembly.

BACKGROUND: The mechanism of microbiota assembly is one of the main problems in microbiome research, which is also the primary theoretical basis for precise manipulation of microbial communities. Bacterial quorum sensing (QS), as the most common means for bacteria to exchange information and interactions, is characterized by universality, specificity, and regulatory power, which therefore may influence the assembly processes of human microbiota. However, the regulating role of QS in microbiota assembly is rarely reported. In this study, we developed an optimized in vitro oral biofilm microbiota assembling (OBMA) model to simulate the time-series assembly of oral biofilm microbiota (OBM), by which to excavate the QS network and its regulating power in the process. RESULTS: By using the optimized OBMA model, we were able to restore the assembly process of OBM and generate time-series OBM metagenomes of each day. We discovered a total of 2291 QS protein homologues related to 21 QS pathways. Most of these pathways were newly reported and sequentially enriched during OBM assembling. These QS pathways formed a comprehensive longitudinal QS network that included successively enriched QS hubs, such as Streptococcus, Veillonella-Megasphaera group, and Prevotella-Fusobacteria group, for information delivery. Bidirectional cross-talk among the QS hubs was found to play critical role in the directional turnover of microbiota structure, which in turn, influenced the assembly process. Subsequent QS-interfering experiments accurately predicted and experimentally verified the directional shaping power of the longitudinal QS network in the assembly process. As a result, the QS-interfered OBM exhibited delayed and fragile maturity with prolonged membership of Streptococcus and impeded membership of Prevotella and Fusobacterium. CONCLUSION: Our results revealed an unprecedented longitudinal QS network during OBM assembly and experimentally verified its power in predicting and manipulating the assembling process. Our work provides a new perspective to uncover underlying mechanism in natural complex microbiota assembling and a theoretical basis for ultimately precisely manipulating human microbiota through intervention in the QS network. Video Abstract.

Unique microbial landscape in the human oropharynx during different types of acute respiratory tract infections.

BACKGROUND: Secondary bacterial infections and pneumonia are major mortality causes of respiratory viruses, and the disruption of the upper respiratory tract (URT) microbiota is a crucial component of this process. However, whether this URT dysbiosis associates with the viral species (in other words, is viral type-specific) is unclear. RESULTS: Here, we recruited 735 outpatients with upper respiratory symptoms, identified the infectious virus types in 349 participants using multiplex RT-PCR, and profiled their upper respiratory microbiome using the 16S ribosomal RNA gene and metagenomic gene sequencing. Microbial and viral data were subsequently used as inputs for multivariate analysis aimed at revealing viral type-specific disruption of the upper respiratory microbiota. We found that the oropharyngeal microbiota shaped by influenza A virus (FluA), influenza B virus (FluB), respiratory syncytial virus (RSV), and human rhinovirus (HRV) infections exhibited three distinct patterns of dysbiosis, and Veillonella was identified as a prominent biomarker for any type of respiratory viral infections. Influenza virus infections are significantly correlated with increased oropharynx microbiota diversity and enrichment of functional metabolic pathways such as L-arginine biosynthesis and tetracycline resistance gene tetW. We used the GRiD algorithm and found the predicted growth rate of common respiratory pathogens was increased upon influenza virus infection, while commensal bacteria, such as Streptococcus infantis and Streptococcus mitis, may act as a colonization resistance to the overgrowth of these pathogens. CONCLUSIONS: We found that respiratory viral infections are linked with viral type-specific disruption of the upper respiratory microbiota, particularly, influenza infections uniquely associated with increased microbial diversity and growth rates of specific pathogens in URT. These findings are essential for clarifying the differences and dynamics of respiratory microbiota in healthy participants and acute respiratory viral infections, which contribute to elucidating the pathogenesis of viral-host-bacterial interactions to provide insights into future studies on effective prevention and treatment of respiratory tract infections. Video Abstract.

Preparation of Nanocomposites for Antibacterial Orthodontic Invisible Appliance Based on Piezoelectric Catalysis.

Compared to fixed orthodontic appliances with brackets, thermoplastic invisible orthodontic aligners offer several advantages, such as high aesthetic performance, good comfort, and convenient oral health maintenance, and are widely used in orthodontic fields. However, prolonged use of thermoplastic invisible aligners may lead to demineralization and even caries in most patients' teeth, as they enclose the tooth surface for an extended period. To address this issue, we have created PETG composites that contain piezoelectric barium titanate nanoparticles (BaTiO3NPs) to obtain antibacterial properties. First, we prepared piezoelectric composites by incorporating varying amounts of BaTiO3NPs into PETG matrix material. The composites were then characterized using techniques such as SEM, XRD, and Raman spectroscopy, which confirmed the successful synthesis of the composites. We cultivated biofilms of Streptococcus mutans (S. mutans) on the surface of the nanocomposites under both polarized and unpolarized conditions. We then activated piezoelectric charges by subjecting the nanocomposites to 10 Hz cyclic mechanical vibration. The interactions between the biofilms and materials were evaluated by measuring the biofilm biomass. The addition of piezoelectric nanoparticles had a noticeable antibacterial effect on both the unpolarized and polarized conditions. Under polarized conditions, nanocomposites demonstrated a greater antibacterial effect than under unpolarized conditions. Additionally, as the concentration of BaTiO3NPs increased, the antibacterial rate also increased, with the surface antibacterial rate reaching 67.39% (30 wt% BaTiO3NPs). These findings have the potential for application in wearable, invisible appliances to improve clinical services and reduce the need for cleaning methods.

Rapid, artifact-reduced, image reconstruction for super-resolution structured illumination microscopy.

Super-resolution structured illumination microscopy (SR-SIM) is finding increasing application in biomedical research due to its superior ability to visualize subcellular dynamics in living cells. However, during image reconstruction artifacts can be introduced and when coupled with time-consuming postprocessing procedures, limits this technique from becoming a routine imaging tool for biologists. To address these issues, an accelerated, artifact-reduced reconstruction algorithm termed joint space frequency reconstruction-based artifact reduction algorithm (JSFR-AR-SIM) was developed by integrating a high-speed reconstruction framework with a high-fidelity optimization approach designed to suppress the sidelobe artifact. Consequently, JSFR-AR-SIM produces high-quality, super-resolution images with minimal artifacts, and the reconstruction speed is increased. We anticipate this algorithm to facilitate SR-SIM becoming a routine tool in biomedical laboratories.

Baicalin inhibits influenza A (H1N1)-induced pyroptosis of lung alveolar epithelial cells via caspase-3/GSDME pathway.

Baicalin (7-d-glucuronic acid-5, 6-dihydroxyflavone) derived from the root of Scutellaria baicalensis used as Traditional Chinese Medicine (TCM) has been revealed to exert potential antiviral activity via various pathways, while the molecular mechanisms have not been fully understood. Pyroptosis, an inflammatory form of programmed cell death (PCD), is reported to play a crucial role in host cell fate during viral infection. In this study, transcriptome analysis of mice lung tissue reveals that baicalin reverses the alterations of the mRNA levels of PCD-associated genes upon H1N1 challenge, with a concomitant decrease in the population of H1N1-induced propidium iodide (PI)+ and Annexin Ⅴ+ cells. Intriguingly, we find that baicalin contributes to the survival of infected lung alveolar epithelial cells partly through its inhibition of H1N1-induced cell pyroptosis, which is manifested by reduced bubble-like protrusion cells and lactate dehydrogenase (LDH) release. Moreover, the antipyroptosis effect of baicalin in response to H1N1 infection is found to be mediated by its repression on caspase-3/Gasdermin E (GSDME) pathway. Cleaved caspase-3 and N-terminal fragment of GSDME (GSDME-N) are detected in H1N1-infected cell lines and mice lung tissues, which are markedly reversed by baicalin treatment. Furthermore, inhibition of caspase-3/GSDME pathway by caspase-3 inhibitor or siRNA exerts an antipyroptosis effect equal to that of baicalin treatment in infected A549 and BEAS-2B cells, indicating a pivotal role of caspase-3 in the antiviral activities of baicalin. Conclusively, for the first time, we demonstrate that baicalin could effectively suppress H1N1-induced pyroptosis of lung alveolar epithelial cells via caspase-3/GSDME pathway both in vitro and in vivo.

Revised Tunable Q-Factor Wavelet Transform for EEG-Based Epileptic Seizure Detection.

Electroencephalogram (EEG) signals are an essential tool for the detection of epilepsy. Because of the complex time series and frequency features of EEG signals, traditional feature extraction methods have difficulty meeting the requirements of recognition performance. The tunable Q-factor wavelet transform (TQWT), which is a constant-Q transform that is easily invertible and modestly oversampled, has been successfully used for feature extraction of EEG signals. Because the constant-Q is set in advance and cannot be optimized, further applications of the TQWT are restricted. To solve this problem, the revised tunable Q-factor wavelet transform (RTQWT) is proposed in this paper. RTQWT is based on the weighted normalized entropy and overcomes the problems of a nontunable Q-factor and the lack of an optimized tunable criterion. In contrast to the continuous wavelet transform and the raw tunable Q-factor wavelet transform, the wavelet transform corresponding to the revised Q-factor, i.e., RTQWT, is sufficiently better adapted to the nonstationary nature of EEG signals. Therefore, the precise and specific characteristic subspaces obtained can improve the classification accuracy of EEG signals. The classification of the extracted features was performed using the decision tree, linear discriminant, naive Bayes, SVM and KNN classifiers. The performance of the new approach was tested by evaluating the accuracies of five time-frequency distributions: FT, EMD, DWT, CWT and TQWT. The experiments showed that the RTQWT proposed in this paper can be used to extract detailed features more effectively and improve the classification accuracy of EEG signals.

Direct Construction of Corrole-Peptide Conjugates by Controllable Bilane Formation on Resin.

Corroles have attracted increasing research interests in recent decades owing to their unique properties over porphyrins. However, the relatively inefficient and tedious synthetic procedures of corrole building blocks with functional groups for bioconjugation hindered their bioapplications. Herein, we report a highly efficient protocol to synthesize corrole-peptide conjugates with good yields (up to 63 %) without using prepared corrole building blocks. By condensing two -COOH-bearing-dipyrromethane molecules onto an aldehyde group on resin-bound peptide chains in a controllable manner, a series of desired products with long (up to 25 residues) and bioactive peptide chains were obtained with at most one chromatographic purification. The synthesized compounds exhibited potential applications as chelators for metal ions for biomedical applications, as building blocks for supramolecular materials, as well as targeted fluorescent probes.

Engineering the Thermostability of Sucrose Synthase by Reshaping the Subunit Interaction Contributes to Efficient UDP-Glucose Production.

The restricted availability of UDP-glucose, an essential precursor that targets oligo/polysaccharide and glycoside synthesis, makes its practical application difficult. Sucrose synthase (Susy), which catalyzes one-step UDP-glucose synthesis, is a promising candidate. However, due to poor thermostability of Susy, mesophilic conditions are required for synthesis, which slow down the process, limit productivity, and prevent scaled and efficient UDP-glucose preparation. Here, we obtained an engineered thermostable Susy (mutant M4) from Nitrosospira multiformis through automated prediction and greedy accumulation of beneficial mutations. The mutant improved the T1/2 value at 55 °C by 27-fold, resulting in UDP-glucose synthesis at 37 g/L/h of space-time yield that met industrial biotransformation standards. Furthermore, global interaction between mutant M4 subunits was reconstructed by newly formed interfaces according to molecular dynamics simulations, with residue Trp162 playing an important role in strengthening the interface interaction. This work enabled effective, time-saving UDP-glucose production and paved the way for rational thermostability engineering of oligomeric enzymes.

Diabetic Macular Edema: Current Understanding, Molecular Mechanisms and Therapeutic Implications.

Diabetic retinopathy (DR), with increasing incidence, is the major cause of vision loss and blindness worldwide in working-age adults. Diabetic macular edema (DME) remains the main cause of vision impairment in diabetic patients, with its pathogenesis still not completely elucidated. Vascular endothelial growth factor (VEGF) plays a pivotal role in the pathogenesis of DR and DME. Currently, intravitreal injection of anti-VEGF agents remains as the first-line therapy in DME treatment due to the superior anatomic and functional outcomes. However, some patients do not respond satisfactorily to anti-VEGF injections. More than 30% patients still exist with persistent DME even after regular intravitreal injection for at least 4 injections within 24 weeks, suggesting other pathogenic factors, beyond VEGF, might contribute to the pathogenesis of DME. Recent advances showed nearly all the retinal cells are involved in DR and DME, including breakdown of blood-retinal barrier (BRB), drainage dysfunction of Müller glia and retinal pigment epithelium (RPE), involvement of inflammation, oxidative stress, and neurodegeneration, all complicating the pathogenesis of DME. The profound understanding of the changes in proteomics and metabolomics helps improve the elucidation of the pathogenesis of DR and DME and leads to the identification of novel targets, biomarkers and potential therapeutic strategies for DME treatment. The present review aimed to summarize the current understanding of DME, the involved molecular mechanisms, and the changes in proteomics and metabolomics, thus to propose the potential therapeutic recommendations for personalized treatment of DME.

Three-Dimensional Reduced Graphene Oxide Hybrid Nano-Silver Scaffolds with High Antibacterial Properties.

In recent years, hazardous wastewater treatment has been a complex and global problem. In this work, by considering the antimicrobial activity of Ag nanoparticles (AgNPs) and reduced graphene oxide (rGO), we constructed an antibacterial device (G-AgNP) with AgNPs conformably deposited onto a 3D scaffold of reduced graphene oxide in situ. The major limitation, which is difficult to recycle, of two-dimensional graphene-silver composite materials in previous studies is improved. Characterization techniques, SEM, TEM, XRD, and XPS, confirmed the synthesis of nanocomposites. Attributed to its larger specific area, more active sites, and synergistic enhancement, the G-AgNP device demonstrated the best bacterial removal capacity, with an antibacterial rate for both E. coli and S. aureus as high as 100% at quite low AgNP contents. The reported G-AgNP has potential application as a wearable sewage treatment device and for the protection of wearable sensors as a promising sterilizing candidate based on its high and stable antibacterial efficiency.

Case report: Bilateral central serous chorioretinopathy-like abnormalities in a man with pulmonary arterial hypertension.

Background: Pulmonary arterial hypertension (PAH) leads to progressive increases in pulmonary vascular resistance, right heart failure, and death if left untreated. Ocular complications secondary to PAH were less reported. In this study, we reported a case of bilateral visual loss and metamorphopsia in a patient with PAH, who developed central serous chorioretinopathy (CSCR)-like abnormalities and optic disc atrophy. Case summary: A 45-year-old man presented with decreasing central vision and metamorphopsia in both eyes. He had a history of PAH and 6-year history of low-dose oral sildenafil treatment. Slit-lamp examination revealed prominent dilated and tortuous episcleral and conjunctival vessels. Ultrawide-field color picture showed retinal pigment epithelial mottling and atrophy in ring-like configurations. Ultrawide-field autofluorescence showed multiple irregular hyper-autofluorescence with a constellation-like pattern surrounding the optic nerve head and macular region. Optical coherence tomography angiography (OCTA) b-scan demonstrated CSCR-like changes. Swept-source optical coherence tomography (SS-OCT) analysis showed optic nerve atrophy with enlarged cup/disc ratio in right eye, which was confirmed with perimetry. Fluorescein angiography (FA) showed marked leakage of macula and optic nerve head with time, cystoid macular edema, early blocking with late staining of the flecks as shown in the backgrounds of infrared and autofluorescence, and mild leakage in peripheral retina. Indocyanine green angiography (ICGA) showed dilation, tortuosity and congestion of all vortex veins without obvious leakage. Conclusion: Undertreated PAH may cause the congestion of the choroid and induce CSCR-like abnormalities.

Differential Oral Microbial Input Determines Two Microbiota Pneumo-Types Associated with Health Status.

The oral and upper respiratory tracts are closely linked anatomically and physiologically with the lower respiratory tract and lungs, and the influence of oral and upper respiratory microbes on the lung microbiota is increasingly being recognized. However, the ecological process and individual heterogeneity of the oral and upper respiratory tract microbes shaping the lung microbiota remain unclear owing to the lack of controlled analyses with sufficient sample sizes. Here, the microbiomes of saliva, nasal cavity, oropharyngeal area, and bronchoalveolar lavage samples are profiled and the shaping process of multisource microbes on the lung microbiota is measured. It is found that oral and nasal microbial inputs jointly shape the lung microbiota by occupying different ecological niches. It is also observed that the spread of oral microbes to the lungs is heterogeneous, with more oral microbes entering the lungs being associated with decreased lung function and increased lung proinflammatory cytokines. These results depict the external shaping process of lung microbiota and indicate the great value of oral samples, such as saliva, in monitoring and assessing lung microbiota status in clinical settings.

Assessing the Impact of Continuous Vaccination and Voluntary Isolation on the Dynamics of COVID-19: A Mathematical Optimal Control of SEIR Epidemic Model.

In order to study the impact of continuous vaccination and voluntary isolation for the COVID-19, a susceptible-exposed-infected-recovered-quarantine-vaccines (SEIR-QV) model is proposed. A basic regeneration number R 0 is defined to determine the extinction or persistence of the disease. We numerically analyze the impact of key parameters based on actual parameters of COVID-19, such as the vaccination rate, population importation rate, and natural (or causal) mortality transmission rate on the dynamics of disease transmission. Then we obtain sensitivity indices of some parameters on R 0 by sensitivity analysis. Finally, the stability of the system and the effectiveness of the optimal control strategy are verified by numerical simulation.

Design, Synthesis, and In Vitro and In Vivo Antifungal Activity of Novel Triazoles Containing Phenylethynyl Pyrazole Side Chains.

A series of triazole derivatives containing phenylethynyl pyrazole moiety as side chain were designed, synthesized, and most of them exhibited good in vitro antifungal activities. Especially, compounds 5k and 6c showed excellent in vitro activities against C. albicans (MIC = 0.125, 0.0625 µg/mL), C. neoformans (MIC = 0.125, 0.0625 µg/mL), and A. fumigatus (MIC = 8.0, 4.0 µg/mL). Compound 6c also exerted superior activity to compound 5k and fluconazole in inhibiting hyphae growth of C. albicans and inhibiting drug-resistant strains of C. albicans, and it could reduce fungal burdens in mice kidney at a dosage of 1.0 mg/kg. An in vivo efficacy evaluation indicated that 6c could effectively protect mice models from C. albicans infection at doses of 0.5, 1.0, and 2.0 mg/kg. These results suggested that compound 6c deserves further investigation.

Predicting Readmission Following Hospital Treatment for Patients with Alcohol Related Diagnoses in an Australian Regional Health District.

This study aims to investigate the prediction of hospital readmission of alcohol use disorder patients within 28 days of discharge and compare the performance of six machine learning methods i.e., random forest (RF), logistics regression, linear support vector machine (SVM), polynomial SVM, radial SVM, and sigmoid SVM.