Kaempferol attenuates particle-induced osteogenic impairment by regulating ER stress via the IRE1α-XBP1s pathway.

Periprosthetic osteolysis and subsequent aseptic loosening are the primary causes of failure following total joint arthroplasty. Wear particle-induced osteogenic impairment is recognized as an important contributing factor in the development of osteolysis, with endoplasmic reticulum (ER) stress emerging as a pivotal underlying mechanism. Hence, searching for potential therapeutic targets and agents capable of modulating ER stress in osteoblasts is crucial for preventing aseptic loosening. Kaempferol (KAE), a natural flavonol compound, has shown promising osteoprotective effects and anti-ER stress properties in diverse diseases. However, the influence of KAE on ER stress-mediated osteogenic impairment induced by wear particles remains unclear. In this study, we observed that KAE effectively relieved TiAl6V4 particles-induced osteolysis by improving osteogenesis in a mouse calvarial model. Furthermore, we demonstrated that KAE could attenuate ER stress-mediated apoptosis in osteoblasts exposed to TiAl6V4 particles, both in vitro and in vivo. Mechanistically, our results revealed that KAE mitigated ER stress-mediated apoptosis by upregulating the IRE1α-XBP1s pathway while concurrently partially inhibiting the IRE1α-regulated RIDD and JNK activation. Collectively, our findings suggest that KAE is a prospective therapeutic agent for treating wear particle-induced osteolysis and highlight the IRE1α-XBP1s pathway as a potential therapeutic target for preventing aseptic loosening.

Bi-enzyme competition based on ZIF-67 co-immobilization for real-time monitoring of exocellular ATP.

Monitoring exocellular adenosine-5'-triphosphate (ATP) is a demanding task but the biosensor development is limited by the low concentration and rapid degradation of ATP. Herein, we developed a simple yet effective biosensor based on ZIF-67 loaded with bi-enzymes of glucose (GOx) and hexokinase (HEX) for effective detection of ATP. In the confined space of the porous matrix, the bi-enzymes competed for the glucose substrate in the presence of ATP, facilitating the biosensor to detect low ATP concentrations down to the micromole level (3.75 µM) at working potential of 0.55 V (vs. Ag/AgCl). Furthermore, ZIF-67 with cobalt served as a porous matrix to specifically adsorb ATP molecules, allowing it to differentiate isomers with sensitivity of 0.53 nA/µM, RSD of 5.4%, and recovery rate of 93.3%. We successfully applied the fabricated biosensor to measure ATP secreted from rat PC12 cells in the pericellular space thus realizing time-resolving measurement. This work paved the path for real-time monitoring of ATP released by cells, which will aid in understanding tumor cell glycolysis and immune responses.

The Clinical Risk Factors of Adenovirus Pneumonia in Children Based on the Logistic Regression Model: Correlation with Lactate Dehydrogenase.

Methods: Children with bacterial pneumonia (41 cases) and adenovirus pneumonia (179 cases) hospitalized in Tianjin Children's Hospital from January to October 2020 were selected. The differences in baseline and clinical characteristics between children with two pneumonias, respectively, were compared via the chi-square test and Wilcox test. The Least Absolute Shrinkage and Selection Operator (LASSO) model was applied to screen the pneumonia type-related characteristics. Patients were randomly divided into the training set (n = 154) and test set (n = 66). The logistic model was constructed using the screened characteristics in the training set to predict whether the cases are bacterial pneumonia or adenovirus pneumonia. Finally, the model was validated by receiver operating characteristic (ROC) curve and area under curve (AUC) in the test set. Results: The age (p < 0.001), hospital stay (p < 0.001), tonsil condition (p < 0.001), interleukin-6 (IL-6; p=0.033), and lactate dehydrogenase (LDH; p < 0.001) between children with bacterial pneumonia and adenovirus pneumonia were significantly different. Sex, tonsil condition, age, hospital stay, r-glutamyltransferase (r-GT), and LDH levels were the factors associated with the types of pneumonia. Compared with bacterial pneumonia, children with adenovirus pneumonia were younger (OR = 0.207, 95% CI: 0.041-0.475), with longer hospital stay (OR = 7.974, 95% CI: 2.626-74.354) and higher LDH expression level (OR = 1.025, 95% CI: 1.006-1.060). 92.4% types of pneumonia were correctly predicted, and the AUC value of the model was 0.981. Conclusion: The LDH level was the associated factor to predict the types of pneumonia. Adenovirus pneumonia was associated with earlier age and longer hospital stay than bacterial pneumonia. The established model can well predict the types of pneumonia in children and provide clinical basis for guiding the individualized treatment of children.

On the Effect of Sweat on Sheet Resistance of Knitted Conductive Yarns in Wearable Antenna Design.

Researchers are looking for new methods to integrate sensing capabilities into textiles while maintaining the durability, flexibility, and comfort of the garment. One method for imparting sensing capabilities into garments is through coupling conductive yarns with the radio frequency identification (RFID) technology. These smart devices have exhibited promising results for short-term use. However, long-term studies of their performance are still needed to evaluate their performance over a longer period. Like all garments, wearable sensors are susceptible to environmental factors during use. These factors can lead to dielectric coupling and corrosion of conductive yarns, which has the potential to degrade the performance of the device. This letter analyzes the effect of sweat and moisture on silver-coated nylon yarn by extracting the sheet resistance at 913 MHz from transmission line measurements. HFSS simulation shows the level of perturbation in antenna performance as sheet resistance increased with each cycle of sweat-immersion, washing, and drying.

Architecture Augmentation for Performance Predictor via Graph Isomorphism.

Neural architecture search (NAS) can automatically design architectures for deep neural networks (DNNs) and has become one of the hottest research topics in the current machine learning community. However, NAS is often computationally expensive because a large number of DNNs require to be trained for obtaining performance during the search process. Performance predictors can greatly alleviate the prohibitive cost of NAS by directly predicting the performance of DNNs. However, building satisfactory performance predictors highly depends on enough trained DNN architectures, which are difficult to obtain due to the high computational cost. To solve this critical issue, we propose an effective DNN architecture augmentation method named graph isomorphism-based architecture augmentation method (GIAug) in this article. Specifically, we first propose a mechanism based on graph isomorphism, which has the merit of efficiently generating a factorial of n (i.e., n ) diverse annotated architectures upon a single architecture having n nodes. In addition, we also design a generic method to encode the architectures into the form suitable to most prediction models. As a result, GIAug can be flexibly utilized by various existing performance predictors-based NAS algorithms. We perform extensive experiments on CIFAR-10 and ImageNet benchmark datasets on small-, medium- and large-scale search space. The experiments show that GIAug can significantly enhance the performance of the state-of-the-art peer predictors. In addition, GIAug can save three magnitude order of computation cost at most on ImageNet yet with similar performance when compared with state-of-the-art NAS algorithms.

Defective state regulation of Ru-doped Nb2O5 boosts fast lithium storage.

Breaking through the limitations of lithium-ion transmission is imperative for high-power rechargeable batteries. As a promising anode material for fast-charging lithium-ion batteries (LIBs), niobium pentoxide (Nb2O5) has garnered considerable research attention due to its exceptional rate performance, stable lithium storage performance and high safety attributes. Nevertheless, the limited intrinsic conductivity of Nb2O5, coupled with its structural degradation during the cycling process, imposes constraints on its viability as a commercially viable electrode material. Herein, a ruthenium (Ru) doping method is employed to regulate the oxygen defects and the interlayer spacing of the tetragonal Nb2O5 (M-Nb2O5), offering superior reaction kinetics, higher stability for lithium storage sites and more unobstructed lithium-ion transport channels. Ru-doped Nb2O5 (RNO) manifests excellent electrochemical properties, including remarkable rate capacity (166 mAh/g at 80C), reversible capacity (246.98 mAh/g at 0.5C), improved initial Coulombic efficiency (95.77 % compared to 81.44 % of the pure sample) and cycling stability (maintaining a capacity of 113.5 mAh/g at 10C for 2,000 cycles). The enhancement mechanism of Ru doping on the structural stability and ion transport kinetics in tetragonal Nb2O5 is comprehensively elucidated through diverse electrochemical analyses and in-situ techniques.

Correlation of DNA load, genotyping, and clinical phenotype of Mycoplasma pneumoniae infection in children.

Introduction: This study aimed to investigate the correlation between Mycoplasma pneumoniae (MP)-DNA load in the bronchoalveolar lavage fluid (BALF) of children with MP pneumonia (MPP) and its subtypes, relevant laboratory data, imaging, extrapulmonary complications in infected children, and its clinical significance in evaluating the disease. Methods: Children hospitalized with MPP at Tianjin Children's Hospital between December 2017 and December 2020 were selected for the study, excluding those with mixed viral, bacterial, and fungal infections. Children were divided into low- and high-load groups according to the MP DNA load in BALF using real-time quantitative fluorescence polymerase chain reaction (PCR). After a successful MP culture, positive specimens were subjected to PCR-Restriction fragment length polymorphism and Multiple-locus variable number tandem repeat analysis typing. Basic data, clinical information, laboratory data, and radiological results were collected from all children included in the study. Results: The PI-I type dominated the different load groups. Children in the low-load group had more wheezing and shortness of breath; however, children in the high-load group had a higher length of hospitalization, maximum fever temperature, higher chills/chilliness, incidence of abdominal pain, and higher C-reactive protein (CRP), procalcitonin (PCT) and aspartate aminotransferase (AST) levels. Children in the high-load group were more likely to have imaging changes such as pleural effusion, and the incidence of respiratory infections and extrapulmonary complications was higher than that of those in the low-load group. We applied Spearman's correlation analysis to clarify the relationship between MP DNA load and the clinical severity of MPP. We found that MP DNA load was positively correlated with length of hospitalization, maximum fever temperature, CRP, PCT, Interleukin-6 (IL-6), and AST levels, and negatively correlated with fever and cough durations, white blood cell count (WBC), and proportion of monocytes (MONO). The degree of correlation was as follows: length of hospitalization > IL-6 > cough duration > AST > fever duration > PCT > WBC > proportion of MONO > maximum fever temperature > CRP levels. Conclusions: MP DNA load was not correlated with MP typing but was significantly correlated with the children's clinical phenotype. Therefore, the MP DNA load helps in the early diagnosis of infection and can better predict disease regression.

A Survey on Evolutionary Neural Architecture Search.

Deep neural networks (DNNs) have achieved great success in many applications. The architectures of DNNs play a crucial role in their performance, which is usually manually designed with rich expertise. However, such a design process is labor-intensive because of the trial-and-error process and also not easy to realize due to the rare expertise in practice. Neural architecture search (NAS) is a type of technology that can design the architectures automatically. Among different methods to realize NAS, the evolutionary computation (EC) methods have recently gained much attention and success. Unfortunately, there has not yet been a comprehensive summary of the EC-based NAS algorithms. This article reviews over 200 articles of most recent EC-based NAS methods in light of the core components, to systematically discuss their design principles and justifications on the design. Furthermore, current challenges and issues are also discussed to identify future research in this emerging field.

Facile fabrication of laser induced versatile graphene-metal nanoparticles electrodes for the detection of hazardous molecules.

In this work, we developed a facile method to fabricate laser induced versatile graphene-metal nanoparticles (LIG-MNPs) electrodes with redox molecules sensing capabilities. Unlike conventional post-electrodes deposition, versatile graphene-based composites were engraved by a facile synthesis process. As a general protocol, we successfully prepared modular electrodes including LIG-PtNPs and LIG-AuNPs and applied them to electrochemical sensing. This facile laser engraving process enables rapid preparation and modification of electrodes, as well as simple replacement of metal particles modification towards varied sensing targets. The LIG-MNPs showed high sensitivity towards H2O2 and H2S due to their excellent electron transmission efficiency and electrocatalytic activity. By simply changing the types of coated precursors, the LIG-MNPs electrodes have successfully achieved real-time monitoring of H2O2 released from tumor cells and H2S contained in wastewater. This work contributed a universal and versatile protocol for quantitatively detecting a wide range of hazardous redox molecules.

Revolutionizing Precision Medicine: Exploring Wearable Sensors for Therapeutic Drug Monitoring and Personalized Therapy.

Precision medicine, particularly therapeutic drug monitoring (TDM), is essential for optimizing drug dosage and minimizing toxicity. However, current TDM methods have limitations, including the need for skilled operators, patient discomfort, and the inability to monitor dynamic drug level changes. In recent years, wearable sensors have emerged as a promising solution for drug monitoring. These sensors offer real-time and continuous measurement of drug concentrations in biofluids, enabling personalized medicine and reducing the risk of toxicity. This review provides an overview of drugs detectable by wearable sensors and explores biosensing technologies that can enable drug monitoring in the future. It presents a comparative analysis of multiple biosensing technologies and evaluates their strengths and limitations for integration into wearable detection systems. The promising capabilities of wearable sensors for real-time and continuous drug monitoring offer revolutionary advancements in diagnostic tools, supporting personalized medicine and optimal therapeutic effects. Wearable sensors are poised to become essential components of healthcare systems, catering to the diverse needs of patients and reducing healthcare costs.

Multi-Channel MEMS-FAIMS Gas Sensor for VOCs Detection.

Aimed at the problems of a large equipment size, long time and high price of environmental VOC gas detection, the FAIMS-VOC gas sensor was designed and prepared according to the principle that the ionization energy of the common VOC gas is less than 10.6 eV. The sensor is small in size, fast in detection, low in power consumption, and can work continuously. The sensor was fabricated through the MEMS process, a specific process which included photolithography, etching, anodic bonding, etc. The sensor is 5160 µm long, 5300 µm wide and 800 µm high. We built a test system to detect two typical VOC gases: isobutylene and acetone. The results show that in the detection of isobutylene gas and acetone gas, the sensor voltage value changes with the change of gas concentration. The linearity of testing isobutylene is 0.961, and the linearity of testing acetone is 0.987. When the isobutylene gas concentration is 50 ppm, the response time is 8 s and the recovery time is 6 s; when the acetone gas concentration is 50 ppm, the response time is 9 s and the recovery time is 10 s. In addition, the sensor demonstrates good repeatability and stability, which are conducive to the detection of VOCs in the environment.

Tumor cell membrane-coated continuous electrochemical sensor for GLUT1 inhibitor screening.

Glucose transporter 1 (GLUT1) overexpression in tumor cells is a potential target for drug therapy, but few studies have reported screening GLUT1 inhibitors from natural or synthetic compounds. With current analysis techniques, it is difficult to accurately monitor the GLUT1 inhibitory effect of drug molecules in real-time. We developed a cell membrane-based glucose sensor (CMGS) that integrated a hydrogel electrode with tumor cell membranes to monitor GLUT1 transmembrane transport and screen for GLUT1 inhibitors in traditional Chinese medicines (TCMs). CMGS is compatible with cell membranes of various origins, including different types of tumors and cell lines with GLUT1 expression knocked down by small interfering RNA or small molecules. Based on CMGS continuous monitoring technique, we investigated the glucose transport kinetics of cell membranes with varying levels of GLUT1 expression. We used CMGS to determine the GLUT1-inhibitory effects of drug monomers with similar structures from Scutellaria baicalensis and catechins families. Results were consistent with those of the cellular glucose uptake test and molecular-docking simulation. CMGS could accurately screen drug molecules in TCMs that inhibit GLUT1, providing a new strategy for studying transmembrane protein-receptor interactions.

Significantly Enhancing Mechanical and Thermal Properties of Cellulose-Based Composites by Adding Small Amounts of Lysozyme-Modified Graphene Nanoplatelets via Forming Strong Double-Cross-Linked Interface Interactions.

Thermally conductive cellulose-based composites have great application potential in the thermal management of portable and wearable electronic devices. In this work, cellulose-based composites with excellent mechanical and thermal properties were developed by using lysozyme-modified graphene nanoplatelets (LmGNP), epichlorohydrin (ECH), and hydrolyzed cellulose via forming strong double-cross-linked interface interactions, including the hydrogen bond network generated between LmGNP and cellulose and the chemical cross-link of ECH. As for the composites containing 8 wt % LmGNP, the in-plane thermal conductivity was 3.341 W·m-1K-1, while the tensile stress was 114.60 MPa, which increased by 297.3 and 146.2%, respectively, compared to pure cellulose. Along with the good stability, insulation, and lightweight properties, the fabricated composites have the potential to become a promising heat dissipation material for wearable electronic devices.

Measurement of sucrose in beverages using a blood glucose meter with cascade-catalysis enzyme particle.

In this paper, we developed a sensor for on-site measuring beverage sucrose level based on cascade enzyme particles and a blood glucose meter. The cascade enzyme particles with sucrose hydrolyzing capability were prepared by co-precipitation of manganese carbonate, in which the stability of the enzymes was substantially enhanced by the particle encapsulation effect. The quantitative measurement of glucose produced by the hydrolysis of sucrose was performed using a commercial glucose meter, a commonly owned electrochemical device in homes, greatly improving detection accuracy and expanding applications. Actual sample testing demonstrated the high sensitivity and selectivity of the sensor, allowing for accurate detection of sucrose in beverages. This sensing strategy can also be further expanded to a variety of analytical assays, using blood glucose meters for portable quantitative testing.

Genetic predisposition to subjective well-being, depression, and suicide in relation to COVID-19 susceptibility and severity.

BACKGROUND: Epidemiological studies have reported associations between subjective well-being (SWB), depression, and suicide with COVID-19 illness, but the causality has not been established. We performed a two-sample Mendelian randomization (MR) analysis to investigate the causal link between SWB, depression, suicide and COVID-19 susceptibility and severity. METHODS: Summary statistics for SWB (298,420 cases), depression (113,769 cases) and suicide (52,208 cases) were obtained from three large-scale GWAS. Data on the associations between the Single Nucleotide Polymorphisms (SNPs) and COVID-19 (159,840 cases), hospitalized COVID-19 (44,986 cases), and severe COVID-19 (18,152 cases) were collected from the COVID-19 host genetics initiative. The causal estimate was calculated by the Inverse Variance Weighted, MR Egger and Weighted Median methods. Sensitivity tests were used to evaluate the validity of the causal relationship. RESULTS: Our results showed that genetically predicted SWB (OR = 0.98, 95 % CI: 0.86-1.10, P = 0.69), depression (OR = 0.76, 95 % CI: 0.54-1.06, P = 0.11), and suicide (OR = 0.99, 95 % CI: 0.96-1.02, P = 0.56) were not causally related to COVID-19 susceptibility. Similarly, we did not find a potential causal relationship between SWB, depression, suicide and COVID-19 severity. CONCLUSIONS: This indicated that positive or negative emotions would not make COVID-19 better or worse, and strategies that attempted to use positive emotions to improve COVID-19 symptoms may be useless. Improving knowledge about the SARS-CoV-2 and timely medical intervention to reduce panic during a pandemic is one of the effective measures to deal with the current decrease in well-being and increase in depression and suicide rates.

An enzyme-particle hybrid ink for one step screen-printing and long-term metabolism monitoring.

Targeting the long-term monitoring of biological carbohydrate metabolism, we developed a one-step screen-printing method to fabricate electrochemical sensors using an enzyme microparticle hybrid ink. Most enzymes have low stability in high temperatures and organic solvents, making conventional enzyme modification a bottom-up procedure to be performed after electrode fabrication, resulting in inactivation and detachment in long-term work. Enzyme-loaded microparticles prepared by manganese carbonate co-precipitation had higher stability than free enzymes, which could to be mixed directly with carbon paste for direct screen-printing. Due to the co-printing immobilization and the local hydration environment in enzyme particles, the prepared electrodes exhibited higher long-term operational stability than the conventional multi-step cross-linking method. In the sensing applications, we prepared microparticles loaded with single enzyme (glucose oxidase) and dual enzymes (ß-galactosidase and glucose oxidase) for glucose and lactose monitoring, respectively. Both electrodes can accurately measure the consumption of the corresponding carbohydrates throughout the cell or bacterial culture period thus providing a sensing platform for bio-metabolic monitoring and drug screening.

Cell membrane coated electrochemical sensor for kinetic measurements of GLUT transport.

The upregulation of glucose transporter (GLUT) is a typical pathological marker in numerous cancer types and a potential target for anti-cancer drug therapy. We developed a cell membrane-based glucose sensor for real-time monitoring of GLUT transport kinetics. By combining hydrogel layers and liposomes, a planar cell membrane was constructed over the electrode, preventing pore leakage and allowing for highly sensitive and selective measurements. Based on this continuous monitoring technique, we investigated the effect of GLUT1-specific inhibitors such as Cytorelaxation B and BAY-876. We also measured the affinity of different hexoses to GLUT1 using a normalized response time comparison based on the cell membrane sensor. Experimental results were consistent with the molecular docking simulation, indicating that the sensor can be adapted to measure the glucose transport kinetics in different pharmacological conditions. This work demonstrated that cell membrane transport channels could maintain their transmembrane function in-vitro, and it has potential application in evaluating drug-receptor interaction.

Micro-Volume Blood Separation Membrane for In-Situ Biosensing.

In this paper, we report a point-of-care (POCT) testing strip based on a porous membrane structure for whole blood separation and colorimetric analysis without external supporting equipment. Conventional blood tests rely on large instruments for blood pretreatment and separation to improve measurement accuracy. Cellulose acetate (CA) membranes with different pore diameters and structures were prepared via a non-solvent method for the separation of whole blood. Among them, CA@PEG-2000 membranes with nano-pores on the surface and micro-pores in the interior facilitated the capture of blood cells on the surface, as well as the free diffusion of plasma through the porous interior structure. The fluid flow of blood in the asymmetric porous structure can be theoretically estimated using the Lucas-Washburn equation. Compared with the conventional paper strips and other porous membranes, the CA@PEG-2000 membrane with an immobilized sensing layer exhibited efficient blood separation, a short response time (less than 2 min), an ultralow dosage volume (5 µL), and high sensitivity. The fabricated blood separation membranes can be further used for the detection of various biomarkers in whole blood, providing additional options for rapid quantitative POCT tests.

Establishment of a predictive nomogram and its validation for severe adenovirus pneumonia in children.

BACKGROUND: Severe adenovirus pneumonia (SAP) of children is prone to multi-system complications, has the high mortality rate and high incidence of sequelae. Severity prediction can facilitate an adequate individualized treatment plan. Our study try to develop and evaluate a predictive nomogram for children with SAP. METHODS: An observational study was designed and performed retrospectively. The data were categorized as training and validation datasets using the method of credible random split-sample (split ratio =0.7:0.3). The predictors were selected using Lasso (least absolute shrinkage and selection operator) logistic regression and the nomogram was developed. Nomogram discrimination was assessed using the receiver operating characteristic (ROC) curve, and the prediction accuracy was evaluated using a calibration curve. The nomogram was also evaluated for clinical effectiveness by the decision curve analysis (DCA). A P value of <0.05 was deemed statistically significant. RESULTS: The identified predictors were fever duration, and interleukin-6 and CD4+ T cells and were assembled into the nomogram. The nomogram exhibited good discrimination with area under ROC curve in training dataset (0.79, 95% CI: 0.60-0.92) and test dataset (0.76, 95% CI: 0.63-0.87). The nomogram seems to be useful clinically as per DCA. CONCLUSIONS: A nomogram with a potentially effective application was developed to facilitate individualized prediction for SAP in children.

Solution-Processed Ti3 C2 Tx MXene Antennas for Radio-Frequency Communication.

Highly integrated, flexible, and ultrathin wireless communication components are in significant demand due to the explosive growth of portable and wearable electronic devices in the fifth-generation (5G) network era, but only conventional metals meet the requirements for emerging radio-frequency (RF) devices so far. Here, it is reported on Ti3 C2 Tx MXene microstrip transmission lines with low-energy attenuation and patch antennas with high-power radiation at frequencies from 5.6 to 16.4 GHz. The radiation efficiency of a 5.5 µm thick MXene patch antenna manufactured by spray-coating from aqueous solution reaches 99% at 16.4 GHz, which is about the same as that of a standard 35 µm thick copper patch antenna at about 15% of its thickness and 7% of the copper weight. MXene outperforms all other materials evaluated for patch antennas to date. Moreover, it is demonstrated that an MXene patch antenna array with integrated feeding circuits on a conformal surface has comparable performance with that of a copper antenna array at 28 GHz, which is a target frequency in practical 5G applications. The versatility of MXene antennas in wide frequency ranges coupled with the flexibility, scalability, and ease of solution processing makes MXene promising for integrated RF components in various flexible electronic devices.