Structural elucidation and complete NMR spectral assignments of Monascus monacolin analogues

Three new monacolin analogues, 3,6-dihydroxy-monacolin P (1), 6-methoxy monacolin S (2), and 6-methoxy dehydromonacolin S (3), were isolated from a fraction that strongly inhibited 3-hydroxy-3-methylglutaryl-CoA reductase from the ethyl acetate portion of red yeast rice ethanol extract. Their structures were determined through a combination of 1D and 2D NMR experiments, mass spectrometry analysis, and known literature reports.

Attention-guided variational graph autoencoders reveal heterogeneity in spatial transcriptomics

The latest breakthroughs in spatially resolved transcriptomics technology offer comprehensive opportunities to delve into gene expression patterns within the tissue microenvironment. However, the precise identification of spatial domains within tissues remains challenging. In this study, we introduce AttentionVGAE (AVGN), which integrates slice images, spatial information and raw gene expression while calibrating low-quality gene expression. By combining the variational graph autoencoder with multi-head attention blocks (MHA blocks), AVGN captures spatial relationships in tissue gene expression, adaptively focusing on key features and alleviating the need for prior knowledge of cluster numbers, thereby achieving superior clustering performance. Particularly, AVGN attempts to balance the model's attention focus on local and global structures by utilizing MHA blocks, an aspect that current graph neural networks have not extensively addressed. Benchmark testing demonstrates its significant efficacy in elucidating tissue anatomy and interpreting tumor heterogeneity, indicating its potential in advancing spatial transcriptomics research and understanding complex biological phenomena.

Role of Preoperative Albumin Quotient in Surgical Planning for Posttraumatic Syringomyelia: A Comparative Cohort Study

OBJECTIVE

Surgical procedures for patients with posttraumatic syringomyelia (PTS) remain controversial. Until now, there have been no effective quantitative evaluation methods to assist in selecting appropriate surgical plans before surgery.

METHODS

We consecutively enrolled PTS patients (arachnoid lysis group, n = 42; shunting group, n = 14) from 2003 to 2023. Additionally, 19 intrathecal anesthesia patients were included in the control group. All patients with PTS underwent physical and neurological examinations and spinal magnetic resonance imaging preoperatively, 3-12 months postoperatively and during the last follow-up. Preoperative lumbar puncture was performed and blood-spinal cord barrier disruption was detected by quotient of albumin (Qalb, cerebrospinal fluid/serum).

RESULTS

The ages (p = 0.324) and sex (p = 0.065) of the PTS and control groups did not differ significantly. There were also no significant differences in age (p = 0.216), routine blood data and prognosis (p = 0.399) between the arachnoid lysis and shunting groups. But the QAlb level of PTS patients was significantly higher than that of the control group (p < 0.001), and the shunting group had a significantly higher QAlb (p < 0.001) than the arachnoid lysis group. A high preoperative QAlb (odds ratio, 1.091; 95% confidence interval, 1.004-1.187; p = 0.041) was identified as the predictive factor for the shunting procedure, with the receiver operating characteristic curve showing 100% specificity and 80.95% sensitivity for patients with a QAlb > 12.67.

CONCLUSION

Preoperative QAlb is a significant predictive factor for the types of surgery. For PTS patients with a QAlb > 12.67, shunting represents the final recourse, necessitating the exploration and development of novel treatments for these patients.

Assessing the Efficacy of Pixel-Level Fusion Techniques for Ultra-High-Resolution Imagery: A Case Study of BJ-3A

Beijing Satellite 3 is a high-performance optical remote sensing satellite with a spatial resolution of 0.3-0.5 m. It can provide timely and independent ultra-high-resolution spatial big data and comprehensive spatial information application services. At present, there is no relevant research on the fusion method of BJ-3A satellite images. In many applications, high-resolution panchromatic images alone are insufficient. Therefore, it is necessary to fuse them with multispectral images that contain spectral color information. Currently, there is a lack of research on the fusion method of BJ-3A satellite images. This article explores six traditional pixel-level fusion methods (HPF, HCS, wavelet, modified-IHS, PC, and Brovey) for fusing the panchromatic image and multispectral image of the BJ-3A satellite. The fusion results were analyzed qualitatively from two aspects: spatial detail enhancement capability and spectral fidelity. Five indicators, namely mean, standard deviation, entropy, correlation coefficient, and average gradient, were used for quantitative analysis. Finally, the fusion results were comprehensively evaluated from three aspects: spectral curves of ground objects, absolute error figure, and object-oriented classification effects. The findings of the research suggest that the fusion method known as HPF is the optimum and appropriate technique for fusing panchromatic and multispectral images obtained from BJ-3A. These results can be utilized as a guide for the implementation of BJ-3A panchromatic and multispectral data fusion in real-world scenarios.

A Three-Dimensional Hydrophobic Surface-Enhanced Raman Scattering Sensor via a Silver-Coated Polytetrafluoroethylene Membrane for the Direct Trace Detection of Molecules in Water

We report a three-dimensional (3D) SERS substrate consisting of a silver nanoparticle (AgNP) coating on the skeleton-fiber surfaces of a polytetrafluoroethylene (PTFE) membrane. Simple thermal evaporation was employed to deposit Ag onto the PTFE membrane to produce grape-shaped AgNPs. The 3D-distributed AgNPs exhibit not only strong localized surface plasmon resonance (LSPR) but also strong hydrophobic performance. High-density hotspots via silver nano-grape structures and nanogaps, the large 3D interaction volume, and the large total surface area, in combination with the hydrophobic enrichment of the specimen, facilitate high-sensitivity sensing performance of such a SERS substrate for the direct detection of low-concentration molecules in water. An enhancement factor of up to 1.97 × 1010 was achieved in the direct detection of R6G molecules in water with a concentration of 10-13 mol/L. The lowest detection limit of 100 ppt was reached in the detection of melamine in water. Such a SERS sensor may have potential applications in food-safety control, environmental water pollution monitoring, and biomedical analysis.

Recent advances in single-atom alloys: preparation methods and applications in heterogeneous catalysis

Single-atom alloys (SAAs) are a different type of alloy where a guest metal, usually a noble metal (e.g., Pt, Pd, and Ru), is atomically dispersed on a relatively more inert (e.g., Ag and Cu) host metal. As a type of atomic-scale catalyst, single-atom alloy catalysts have broad application prospects in the field of heterogeneous catalysis for hydrogenation, dehydrogenation, oxidation, and other reactions. Numerous experimental and characterization results and theoretical calculations have confirmed that the resultant electronic structure caused by charge transfer between the host metal and guest metal and the special geometric structure of the guest metal are responsible for the high selectivity and catalytic activity of SAA catalysts. In this review, the common methods for the preparation of single-atom alloys in recent years are introduced, including initial wet impregnation, physical vapor deposition, and laser ablation in liquid technique. Afterwards, the applications of single-atom alloy catalysts in selective hydrogenation, dehydrogenation, oxidation reactions, and hydrogenolysis reactions are emphatically reviewed. Finally, several challenges for the future development of SAA catalysts are proposed.

An Automatic Needle Puncture Path-Planning Method for Thermal Ablation of Lung Tumors

Computed tomography (CT)-guided thermal ablation is an emerging treatment method for lung tumors. Ablation needle path planning in preoperative diagnosis is of critical importance. In this work, we proposed an automatic needle path-planning method for thermal lung tumor ablation. First, based on the improved cube mapping algorithm, binary classification was performed on the surface of the bounding box of the patient's CT image to obtain a feasible puncture area that satisfied all hard constraints. Then, for different clinical soft constraint conditions, corresponding grayscale constraint maps were generated, respectively, and the multi-objective optimization problem was solved by combining Pareto optimization and weighted product algorithms. Finally, several optimal puncture paths were planned within the feasible puncture area obtained for the clinicians to choose. The proposed method was evaluated with 18 tumors of varying sizes (482.79 mm3 to 9313.81 mm3) and the automatically planned paths were compared and evaluated with manually planned puncture paths by two clinicians. The results showed that over 82% of the paths (74 of 90) were considered reasonable, with clinician A finding the automated planning path superior in 7 of 18 cases, and clinician B in 9 cases. Additionally, the time efficiency of the algorithm (35 s) was much higher than that of manual planning. The proposed method is expected to aid clinicians in preoperative path planning for thermal ablation of lung tumors. By providing a valuable reference for the puncture path during preoperative diagnosis, it may reduce the clinicians' workload and enhance the objectivity and rationality of the planning process, which in turn improves the effectiveness of treatment.

Gearbox fault diagnosis method based on lightweight channel attention mechanism and transfer learning

In practical engineering, the working conditions of gearbox are complex and variable. In varying working conditions, the performance of intelligent fault diagnosis model is degraded because of limited valid samples and large data distribution differences of gearbox signals. Based on these issues, this research proposes a gearbox fault diagnosis method integrated with lightweight channel attention mechanism, and further realizes the cross-component transfer learning. First, time-frequency distribution of original signals is obtained by wavelet transform. It could intuitively reflect local characteristics of signals. Secondly, based on a local cross-channel interaction strategy, a lightweight efficient channel attention mechanism (LECA) is designed. The kernel size of 1D convolution is affected by channel number and coefficients. Multi-scale feature input is used to retain more detailed features of different dimensions. A lightweight convolutional neural network is constructed. Finally, a transfer learning method is applied to freeze lower structures of the network and fine-tune higher structures of the model using small samples. Through experimental verification, the proposed model could effectively utilize samples. The application of transfer learning could realize accurate and fast fault classification of small samples, and achieve good gearbox fault diagnosis effect under varying working conditions and cross-component conditions.

Effect of Freeze-Thaw Cycles on the Shear Strength of Root-Soil Composite

A large alpine meadow in a seasonal permafrost zone exists in the west of Sichuan, which belongs to a part of the Qinghai-Tibet Plateau, China. Due to the extreme climates and repeated freeze-thaw cycling, resulting in a diminishment in soil shear strength, disasters occur frequently. Plant roots increase the complexity of the soil freeze-thaw strength problem. This study applied the freeze-thaw cycle and direct shear tests to investigate the change in the shear strength of root-soil composite under freeze-thaw cycles. This study examined how freeze-thaw cycles and initial moisture content affect the shear strength of two sorts of soil: uncovered soil and root-soil composite. By analyzing the test information, the analysts created numerical conditions to foresee the shear quality of both sorts of soil under shifting freeze-thaw times and starting moisture levels. The results showed that: (1) Compared to the bare soil, the root-soil composite was less affected by freeze-thaw cycles in the early stage, and the shear strength of both sorts of soil was stabilized after 3-5 freeze-thaw cycles. (2) The cohesion of bare soil decreased more than that of root-soil composite with increasing moisture content. However, freeze-thaw cycles primarily influence soil cohesion more than the internal friction angle. The cohesion modification leads to changes in shear quality for both uncovered soil and root-soil composite. (3) The fitting equations obtained via experiments were used to simulate direct shear tests. The numerical results are compared with the experimental data. The difference in the soil cohesion and root-soil composite cohesion between the experiment data and the simulated result is 8.2% and 17.2%, respectively, which indicates the feasibility of the fitting equations applied to the numerical simulation of the soil and root-soil composite under the freeze-thaw process. The findings give potential applications on engineering and disaster prevention in alpine regions.

Effect of SGLT2 inhibitors on cardiovascular events in patients with atrial fibrillation: A systematic review and meta-analysis of randomized controlled trials

BACKGROUND

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) is reported to reduce incident atrial fibrillation (AF) in patients with or without diabetes; however, its cardiovascular (CV) benefit for AF patients remains unclear.

SS AIMS

To investigate the effect of SGLT2i on the incidence of CV events in patients with AF.

METHODS

Six randomized controlled trials (RCTs) assessing the effects of SGLT2i on CV outcomes in patients with or without AF were included (PROSPERO: CRD 42023431535). The primary endpoint was the composite outcome of heart failure (HF) hospitalization and CV death. Additionally, we assessed the effects of treatment in prespecified subgroups on HF hospitalization, CV death, and all-cause mortality.

RESULTS

Among 38,529 participants from all trials, 5018 patients with AF were treated with SGLT2i. The follow-up period of these trials ranged from 2.3 to 3.3 years. SGLT2i treatment was significantly associated with the risk reduction of primary endpoint in patients with AF (risk ratio [RR] 0.81, 95% confidence interval [CI] 0.74-0.88; p < 0.001), consistent with the finding in the general population (p for interaction = 0.76). SGLT2i was also associated with a consistent reduction in the risk of HF hospitalization in patients with AF (RR 0.76, 95% CI 0.69-0.84; p < 0.001) or not (RR 0.72, 95% CI 0.64-0.80; p < 0.0001), with no statistical difference between them (p for interaction = 0.41). Meta-regression further revealed no significant association between the prevalence of HF with reduced ejection fraction or diabetes and the effect size of SGLT2i.

CONCLUSIONS

The treatment effects of SGLT2i were associated with a lower incidence of CV events, especially HF hospitalization, in patients with AF.

Developing Single-Atomic Manganese Nanozymes for Synergistic Mild Photothermal/Multienzymatic Therapy

Synergistic mild photothermal/nanozyme therapy with outstanding hyperthermia performance and excellent multienzyme properties is highly needed for osteosarcoma treatment. Herein, we have developed efficient single-atom nanozymes (SANs) consisting of Mn sites atomically dispersed on nitrogen-doped carbon nanosheets (denoted as Mn-SANs) for synergistic mild photothermal/multienzymatic therapy against osteosarcoma. Benefiting from their black N-doped carbon nanosheet matrices, Mn-SANs showed an excellent NIR-II-triggered photothermal effect. On the other hand, Mn-SANs with atomically dispersed Mn sites have outstanding multienzyme activities. Mn-SANs can catalyze endogenous H2O2 in osteosarcoma into O2 by catalase (CAT)-like activity, which can effectively ease osteosarcoma hypoxia and trigger the oxidase (OXD)-like catalysis that converts O2 to the cytotoxic superoxide anion radical (•O2-). At the same time, Mn-SANs can also mimic glutathione oxidase (GSHOx) to effectively consume the antioxidant glutathione (GSH) in osteosarcoma and inhibit intracellular glutathione peroxidase 4 (GPX4) expression. Such intratumoral •O2- production, GSH depletion, and GPX4 inactivation mediated by Mn-SANs can create a large accumulation of lipid peroxides (LPO) and •O2-, leading to oxidative stress and disrupting the redox homeostasis in osteosarcoma cells, which can ultimately induce osteosarcoma cell death. More importantly, heat shock proteins (HSPs) can be significantly destroyed via Mn-SAN-mediated plentiful LPO and •O2- generation, thus effectively impairing osteosarcoma cells resistant to mild photothermal therapy. Overall, through the cooperative effect of chemical processes (boosting •O2-, consuming GSH, and enhancing LPO) and biological processes (inactivating GPX4 and hindering HSPs), collaborative mild photothermal/multienzymatic therapy mediated by Mn-SANs is a promising strategy for efficient osteosarcoma treatment.

Recent Updates on the Antimicrobial Compounds from Marine-Derived Penicillium fungi

In this review, 72 compounds isolated from marine-derived Penicillium fungi and their antimicrobial activities are reviewed from 2020 to 2023. According to their structures, these compounds can be divided into terpenoids, polyketides, alkaloids and other structural compounds, among which terpenoids and polyketides are relatively large in number. Some compounds have powerful inhibitory effects against different pathogenic bacteria and fungi. This review aims to provide more useful information and enlightenment for further efficient utilization of Penicillium spp. and their secondary metabolites.

Fast DOA Estimation Algorithms via Positive Incremental Modified Cholesky Decomposition for Augmented Coprime Array Sensors

This paper proposes a fast direction of arrival (DOA) estimation method based on positive incremental modified Cholesky decomposition atomic norm minimization (PI-CANM) for augmented coprime array sensors. The approach incorporates coprime sampling on the augmented array to generate a non-uniform, discontinuous virtual array. It then utilizes interpolation to convert this into a uniform, continuous virtual array. Based on this, the problem of DOA estimation is equivalently formulated as a gridless optimization problem, which is solved via atomic norm minimization to reconstruct a Hermitian Toeplitz covariance matrix. Furthermore, by positive incremental modified Cholesky decomposition, the covariance matrix is transformed from positive semi-definite to positive definite, which simplifies the constraint of optimization problem and reduces the complexity of the solution. Finally, the Multiple Signal Classification method is utilized to carry out statistical signal processing on the reconstructed covariance matrix, yielding initial DOA angle estimates. Experimental outcomes highlight that the PI-CANM algorithm surpasses other algorithms in estimation accuracy, demonstrating stability in difficult circumstances such as low signal-to-noise ratios and limited snapshots. Additionally, it boasts an impressive computational speed. This method enhances both the accuracy and computational efficiency of DOA estimation, showing potential for broad applicability.

Conformation Dependent Architectures of Assembled Antimicrobial Peptides with Enhanced Antimicrobial Ability

Antimicrobial peptides (AMPs) are a developing class of natural and synthetic oligopeptides with host defense mechanisms against a broad spectrum of microorganisms. With in-depth research on the structural conformations of AMPs, synthesis or modification of peptides has shown great potential in effectively obtaining new therapeutic agents with improved physicochemical and biological properties. Notably, AMPs with self-assembled properties have gradually become a hot research topic for various biomedical applications. Compared to monomeric peptides, these peptides can exist in diverse forms (e.g., nanoparticles, nanorods, and nanofibers) and possess several advantages, such as high stability, good biocompatibility, and potent biological functions, after forming aggregates under specific conditions. In particular, the stability and antibacterial property of these AMPs can be modulated by rationally regulating the peptide sequences to promote self-assembly, leading to the reconstruction of molecular structure and spatial orientation while introducing some peptide fragments into the scaffolds. In this work, four self-assembled AMPs are developed, and the relationship between their chemical structures and antibacterial activity is explored extensively through different experiments. Importantly, the evaluation of antibacterial performance in both in vitro and in vivo studies has provided a general guide for using self-assembled AMPs in subsequent treatments for combating bacterial infections.

Optimized methyl donor and reduced precursor degradation pathway for seleno-methylselenocysteine production in Bacillus subtilis

BACKGROUND

Seleno-methylselenocysteine (SeMCys) is an effective component of selenium supplementation with anti-carcinogenic potential that can ameliorate neuropathology and cognitive deficits. In a previous study, a SeMCys producing strain of Bacillus subtilis GBACB was generated by releasing feedback inhibition by overexpression of cysteine-insensitive serine O-acetyltransferase, enhancing the synthesis of S-adenosylmethionine as methyl donor by overexpression of S-adenosylmethionine synthetase, and expressing heterologous selenocysteine methyltransferase. In this study, we aimed to improve GBACB SeMCys production by synthesizing methylmethionine as a donor to methylate selenocysteine and by inhibiting the precursor degradation pathway.

RESULTS

First, the performance of three methionine S-methyltransferases that provide methylmethionine as a methyl donor for SeMCys production was determined. Integration of the NmMmt gene into GBACB improved SeMCys production from 20.7 to 687.4 μg/L. Next, the major routes for the degradation of selenocysteine, which is the precursor of SeMCys, were revealed by comparing selenocysteine hyper-accumulating and non-producing strains at the transcriptional level. The iscSB knockout strain doubled SeMCys production. Moreover, deleting sdaA, which is responsible for the degradation of serine as a precursor of selenocysteine, enhanced SeMCys production to 4120.3 μg/L. Finally, the culture conditions in the flasks were optimized. The strain was tolerant to higher selenite content in the liquid medium and the titer of SeMCys reached 7.5 mg/L.

CONCLUSIONS

The significance of methylmethionine as a methyl donor for SeMCys production in B. subtilis is reported, and enhanced precursor supply facilitates SeMCys synthesis. The results represent the highest SeMCys production to date and provide insight into Se metabolism.

Decoding the Different Aroma-Active Compounds in Soy Sauce for Cold Dishes via a Multiple Sensory Evaluation and Instrumental Analysis

Screening the suitability of soy sauce for specific cooking methods from various products is beneficial for the fine development of the soy sauce industry. Multiple sensory evaluation and gas chromatography-mass spectrometry/olfactometry (GC-MS/O) analysis were combined to decode the suitability of soy sauces for cold dishes and characterize their differential aroma-active compounds. Thirty-two kinds of soy sauce with 42 sensory descriptors were determined via a check-all-that-apply analysis, and werefurther classified into six categories via a cluster analysis. The sensory evaluation results showed that seven soy sauce samples had the highest acceptance in each category. Solid-phase microextraction and solid phase extraction results combined with the GC-MS/O analysis results showed that a total of 38 aroma-active compounds were identified in seven soy sauce samples, among which 2-methoxy-phenol (6-93), ethyl acetate (2-48), 3-methyl-1-butanol (4-30), 3-methyl-butanal (5-24), methional (0-22), dimethyl trisulfide (5-19) and dimethyl disulfide (0-8) showed a higher relative odor activity value (ROAV). A partial least squares regression prediction combined with additional tests further confirmed that 2,5-dimethyl-pyrazine; 2,6-dimethyl-pyrazine; and 2-ethyl-6-methyl-pyrazine significantly contributed to the roasted attributes, methional significantly contributed to the sauce-like notes, ethanol significantly contributed to the alcoholic notes and 2-methoxy-phenol significantly contributed to the smoky notes. 2,5-Dimethyl-pyrazine; methional; 2,6-dimethyl-pyrazine and 2-ethyl-6-methyl-pyrazine significantly contributed to the caramel-like attributes.

Identification of atrial fibrillation phenotypes at low risk of stroke in patients with CHA2DS2-VASc ≥2: Insight from the China-AF study

OBJECTIVE

Patients with atrial fibrillation (AF) are highly heterogeneous, and current risk stratification scores are only modestly good at predicting an individual's stroke risk. We aim to identify distinct AF clinical phenotypes with cluster analysis to optimize stroke prevention practices.

METHODS

From the prospective Chinese Atrial Fibrillation Registry cohort study, we included 4337 AF patients with CHA2 DS2 -VASc≥2 for males and 3 for females who were not treated with oral anticoagulation. We randomly split the patients into derivation and validation sets by a ratio of 7:3. In the derivation set, we used outcome-driven patient clustering with metric learning to group patients into clusters with different risk levels of ischemic stroke and systemic embolism, and identify clusters of patients with low risks. Then we tested the results in the validation set, using the clustering rules generated from the derivation set. Finally, the survival decision tree was applied as a sensitivity analysis to confirm the results.

RESULTS

Up to the follow-up of 1 year, 140 thromboembolic events (ischemic stroke or systemic embolism) occurred. After supervised metric learning from six variables involved in CHA2 DS2 -VASc scheme, we identified a cluster of patients (255/3035, 8.4%) at an annual thromboembolism risk of 0.8% in the derivation set. None of the patients in the low-risk cluster had prior thromboembolism, heart failure, diabetes, or age older than 70 years. After applying the regularities from metric learning on the validation set, we also identified a cluster of patients (137/1302, 10.5%) with an incident thromboembolism rate of 0.7%. Sensitivity analysis based on the survival decision tree approach selected a subgroup of patients with the same phenotypes as the metric-learning algorithm.

CONCLUSIONS

Cluster analysis identified a distinct clinical phenotype at low risk of stroke among high-risk [CHA2 DS2 -VASc≥2 (3 for females)] patients with AF. The use of the novel analytic approach has the potential to prevent a subset of AF patients from unnecessary anticoagulation and avoid the associated risk of major bleeding.

The modified vermilion border-marionette line approach: A management for buccal cancer with wider indications and higher satisfaction

OBJECTIVE

The purpose of this study is to explore the effects of modified vermilion border-marionette line (MVBML) approach on postoperative facial scar, nerves injury, and prognosis of patients with buccal squamous cell carcinoma (BSCC).

PATIENTS AND METHODS

This is a single-center, prospective cohort study that enrolled 80 patients with BSCC from June 2015 to December 2020. According to the different surgical approaches, the patients were divided into two groups: the lower lip median (LLM) approach group and the MVBML approach group.

RESULTS

The results showed that the appearance (p = 0.003), scar consciousness (p < 0.001) and satisfaction with appearance (p = 0.001) of patients in the MVBML group were significantly better than those in the LLM group, and the difference was more obvious in elderly group. Statistical analysis of postoperative nerves injury showed that the MVBML group had a lower risk of facial and mental nerves injury than the LLM group, and there was a significant statistical difference in mental nerve injury between the two groups (p < 0.001). Through Kaplan-Meier survival analysis, we found no significant difference in disease-specific survival (p = 0.47) or disease-free survival (p = 0.70) between the LLM approach group and the MVBML approach group.

CONCLUSIONS

The MVBML surgical approach is worthy of advancement for the surgical treatment of BSCC.

Thermal-Conductivity-Enhancing Copper-Plated Expanded Graphite/Paraffin Composite for Highly Stable Phase-Change Materials

Paraffin (PA)/expanded graphite (EG) is an important composite phase change material with low cost, high heat storage, good thermal conductivity and cycling stability. Its thermal conductivity needs to be further improved for application in the thermal management system of power lithium-ion batteries. In this paper, copper plated expanded graphite (CPEG) with 3D porous structure was prepared by electroless copper plating method, which was used as thermal conductivity enhancing material to replace part of EG in PA/EG composite materials. For the optimized phase change material composed of 80 %PA-14 %EG-6 %CPEG, the copper content is very low (0.768 wt %), but its thermal conductivity can be significantly improved without loss of latent heat and thermal cycling stability. Its thermal conductivity is increased from 11 times to 16.5 times that of paraffin while compared with the copper-free composite material (80 %PA-20 %EG). The PA/EG/CPEG composite material exhibits good temperature control effect on power lithium-ion batteries.

Applications of Degradable Hydrogels in Novel Approaches to Disease Treatment and New Modes of Drug Delivery

Hydrogels are particularly suitable materials for loading drug delivery agents; their high water content provides a biocompatible environment for most biomolecules, and their cross-linked nature protects the loaded agents from damage. During delivery, the delivered substance usually needs to be released gradually over time, which can be achieved by degradable cross-linked chains. In recent years, biodegradable hydrogels have become a promising technology in new methods of disease treatment and drug delivery methods due to their many advantageous properties. This review briefly discusses the degradation mechanisms of different types of biodegradable hydrogel systems and introduces the specific applications of degradable hydrogels in several new methods of disease treatment and drug delivery methods.

The Chemical Composition and Health-Promoting Benefits of Vegetable Oils-A Review

With population and economic development increasing worldwide, the public is increasingly concerned with the health benefits and nutritional properties of vegetable oils (VOs). In this review, the chemical composition and health-promoting benefits of 39 kinds of VOs were selected and summarized using Web of Science TM as the main bibliographic databases. The characteristic chemical compositions were analyzed from fatty acid composition, tocols, phytosterols, squalene, carotenoids, phenolics, and phospholipids. Health benefits including antioxidant activity, prevention of cardiovascular disease (CVD), anti-inflammatory, anti-obesity, anti-cancer, diabetes treatment, and kidney and liver protection were examined according to the key components in representative VOs. Every type of vegetable oil has shown its own unique chemical composition with significant variation in each key component and thereby illustrated their own specific advantages and health effects. Therefore, different types of VOs can be selected to meet individual needs accordingly. For example, to prevent CVD, more unsaturated fatty acids and phytosterols should be supplied by consuming pomegranate seed oil, flaxseed oil, or rice bran oil, while coconut oil or perilla seed oil have higher contents of total phenolics and might be better choices for diabetics. Several oils such as olive oil, corn oil, cress oil, and rice bran oil were recommended for their abundant nutritional ingredients, but the intake of only one type of vegetable oil might have drawbacks. This review increases the comprehensive understanding of the correlation between health effects and the characteristic composition of VOs, and provides future trends towards their utilization for the general public's nutrition, balanced diet, and as a reference for disease prevention. Nevertheless, some VOs are in the early stages of research and lack enough reliable data and long-term or large consumption information of the effect on the human body, therefore further investigations will be needed for their health benefits.

Optimization of Gearbox Fault Detection Method Based on Deep Residual Neural Network Algorithm

Because of its long running time, complex working environment, and for other reasons, a gear is prone to failure, and early failure is difficult to detect by direct observation; therefore, fault diagnosis of gears is very necessary. Neural network algorithms have been widely used to realize gear fault diagnosis, but the structure of the neural network model is complicated, the training time is long and the model is not easy to converge. To solve the above problems and combine the advantages of the ResNeXt50 model in the extraction of image features, this paper proposes a gearbox fault detection method that integrates the convolutional block attention module (CBAM). Firstly, the CBAM is embedded in the ResNeXt50 network to enhance the extraction of image channels and spatial features. Secondly, the different time-frequency analysis method was compared and analyzed, and the method with the better effect was selected to convert the one-dimensional vibration signal in the open data set of the gearbox into a two-dimensional image, eliminating the influence of the redundant background noise, and took it as the input of the model for training. Finally, the accuracy and the average training time of the model were obtained by entering the test set into the model, and the results were compared with four other classical convolutional neural network models. The results show that the proposed method performs well both in fault identification accuracy and average training time under two working conditions, and it also provides some references for existing gear failure diagnosis research.

A Janus membrane doped with carbon nanotubes for wet-thermal management

In a human skin-fibrous fabric-external environment, fibrous materials, as the "second skin" of the human body, provide comfort against the wet and heat effectively. Fibrous materials protect human health and guarantee work efficiency in various outdoor or inner scenes. Personal wet-thermal management based on fibrous materials can regulate comfort in a facile manner with low or zero energy consumption, which has become a potential development area. However, realizing synergistic management of the wet and heat effectively and conveniently is a challenge in the development and production of fibrous materials. We designed and fabricated a Janus fibrous membrane composed of 3-(trimethoxysilyl)propyl methacrylate (TMSPMA)-modified hydrophobic cotton gauze and electrospun carbon nanotubes (CNTs)-doped cellulose acetate (CA) hydrophilic fibrous membrane. Taking advantage of asymmetric wettability along its thickness direction, the Janus fibrous membrane, acting as a "liquid diode", could transport sweat/moisture from human skin to the external environment unidirectionally, which endowed a dry surface on human skin, avoiding "stickiness", and realizing wet management. Doped CNTs had good photothermal-conversion capacity, so the Janus membrane exhibited excellent heating capacity for passive radiation, so excellent synergistic wet-thermal management was obtained. The Janus membrane could be a candidate for diverse applications of fibrous membranes. Our data provide new ideas for the design and fabrication of fibrous membranes with remarkable wet-thermal management.

mRNA sequencing and CyTOF analysis revealed ASPP2 altered the response patterns of hepatocellular carcinoma HepG2 cells to usnic acid

In a previous study, our team found that ASPP2 overexpression increases the sensitivity of liver cancer cells to sorafenib. ASPP2 is an important target in the study of drug therapy for hepatocellular carcinoma. In this study, we demonstrated that ASPP2 altered the response of HepG2 cells to usnic acid (UA) by using mRNA sequencing and CyTOF. CCK8 assay was used to detect cytotoxicity of UA on HepG2 cells. Annexin V-RPE assay, TUNEL assay, and cleaved caspase 3 assay were performed to examine the apoptotic cell death induced by UA. Transcriptomic sequencing and a single-cell mass cytometry were used to analyze the dynamic response of HepG2shcon and HepG2shASPP2 cells to UA treatment. We have demonstrated that UA could inhibit proliferation in HepG2 cells in a concentration-dependent manner. Apoptotic cell death was significantly induced by UA in HepG2 cells, while knocking down ASPP2 could increase the resistance of HepG2 cells to UA. Data from mRNA-Seq indicated that knockout of ASPP2 in HepG2 cells affected cell proliferation, cycle, and metabolism. ASPP2 knockdown resulted in increased stemness and decreased apoptosis of HepG2 cells under the action of UA. CyTOF analysis confirmed the above results, ASPP2 knockdown increased oncoproteins in HepG2 cells and altered response patterns of HepG2 cells to UA. Our data suggested that the natural compound UA could inhibit liver cancer HepG2 cells; meanwhile, ASPP2 knockdown could affect response patterns of HepG2 cells to UA. The above results indicate that ASPP2 could be a research target in the chemoresistance of liver cancer.

Molecular Modeling Insights into Metal-Organic Frameworks (MOFs) as a Potential Matrix for Immobilization of Lipase: An In Silico Study

CRL is a highly versatile enzyme that finds extensive utility in numerous industries, which is attributed to its selectivity and catalytic efficiency, which have been impeded by the impracticality of its implementation, leading to a loss of native catalytic activity and non-reusability. Enzyme immobilization is a necessary step for enabling its reuse, and it provides methods for regulating the biocatalyst's functional efficacy in a synthetic setting. MOFs represent a novel category of porous materials possessing distinct superlative features that make MOFs an optimal host matrix for developing enzyme-MOF composites. In this study, we employed molecular modeling approaches, for instance, molecular docking and MD simulation, to explore the interactions between CRL and a specific MOF, ZIF-8. The present study involved conducting secondary structural analysis and homology modeling of CRL, followed by docking ZIF-8 with CRL. The results of the molecular docking analysis indicate that ZIF-8 was situated within the active site pocket of CRL, where it formed hydrogen bonds with Val-81, Phe-87, Ser-91, Asp-231, Thr-132, Lue-297, Phe-296, Phe-344, Thr-347, and Ser-450. The MD simulation analysis revealed that the CRL and ZIF-8 docked complex exhibited stability over the entire simulation period, and all interactions presented in the initial docked complex were maintained throughout the simulation. The findings derived from this investigation could promote comprehension of the molecular mechanisms underlying the interaction between CRL and ZIF-8 as well as the development of immobilized CRL for diverse industrial purposes.

Transcriptomic analysis reveals hub genes and pathways in response to acetic acid stress in Kluyveromyces marxianus during high-temperature ethanol fermentation

The thermotolerant yeast Kluyveromyces marxianus is known for its potential in high-temperature ethanol fermentation, yet it suffers from excess acetic acid production at elevated temperatures, which hinders ethanol production. To better understand how the yeast responds to acetic acid stress during high-temperature ethanol fermentation, this study investigated its transcriptomic changes under this condition. RNA sequencing (RNA-seq) was used to identify differentially expressed genes (DEGs) and enriched gene ontology (GO) terms and pathways under acetic acid stress. The results showed that 611 genes were differentially expressed, and GO and pathway enrichment analysis revealed that acetic acid stress promoted protein catabolism but repressed protein synthesis during high-temperature fermentation. Protein-protein interaction (PPI) networks were also constructed based on the interactions between proteins coded by the DEGs. Hub genes and key modules in the PPI networks were identified, providing insight into the mechanisms of this yeast's response to acetic acid stress. The findings suggest that the decrease in ethanol production is caused by the imbalance between protein catabolism and protein synthesis. Overall, this study provides valuable insights into the mechanisms of K. marxianus's response to acetic acid stress and highlights the importance of maintaining a proper balance between protein catabolism and protein synthesis for high-temperature ethanol fermentation.

The Process Analysis Method of SAR Target Recognition in Pre-Trained CNN Models

Recently, attention has been paid to the convolutional neural network (CNN) based synthetic aperture radar (SAR) target recognition method. Because of its advantages of automatic feature extraction and the preservation of translation invariance, the recognition accuracies are stronger than traditional methods. However, similar to other deep learning models, CNN is a "black-box" model, whose working process is vague. It is difficult to locate the decision reasons. Because of this, we focus on the process analysis of a pre-trained CNN model. The role of the processing to feature extraction and final recognition decision is discussed. The discussed components of CNN models are convolution, activation function, and full connection. Here, the convolution processing can be deemed as image filtering. The activation function provides a nonlinear element of processing. Moreover, the fully connected layers can also further extract features. In the experiment, four classical CNN models, i.e., AlexNet, VGG16, GoogLeNet, and ResNet-50, are trained by public MSTAR data, which can realize ten-category SAR target recognition. These pre-trained CNN models are processing objects of the proposed process analysis method. After the analysis, the content of the SAR image target features concerned by these pre-trained CNN models is further clarified. In summary, we provide a paradigm to process the analysis of pre-trained CNN models used for SAR target recognition in this paper. To some degree, the adaptability of these models to SAR images is verified.

Very-early symptomatic recurrence is associated with late recurrence after radiofrequency ablation of atrial fibrillation

AIMS

After radiofrequency catheter ablation (RFCA) of atrial fibrillation (AF), the effect of very-early (within 48 h) symptomatic recurrence (VESR) on late (after 3 months of RFCA) recurrence (LR) has been seldomly reported. We aimed to explore the relationship between VESR and LR among post-RFCA patients.

METHODS AND RESULTS

This was a single-centre prospective cohort study that enrolled 6887 AF patients who received the first RFCA procedure from June 2018 to December 2021 at Beijing Anzhen Hospital. Patients were divided into four groups based on VESR and early (from 48 h to 3 months after RFCA) recurrence (ER): Group A (no VESR, no ER); Group B (VESR but no ER); Group C (ER but no VESR); and Group D (both VESR and ER). Three hundred and thirty (4.79%) patients experienced VESR (Groups B and D). With an average follow-up of 14.7 months after grouping, the Kaplan-Meier curve showed that LR risk in VESR patients was higher than in other patients (log-rank, P < 0.001), and the difference was significant in both paroxysmal (log-rank, P < 0.001) and persistent (log-rank, P < 0.001) AF patients (P for interaction = 0.118). In multivariate analysis, Groups B, C, and D were associated with a 2.161-, 5.409-, and 7.401-fold increase in the risk of LR, respectively. What is more, compared with Group A, VESR-atrial tachycardia and VESR-AF were related to a 3.467- and 5.564-fold LR risk, respectively. In VESR patients, classification based on ER and VESR modes improved the prediction potential of LR risk.

CONCLUSION

Very-early symptomatic recurrence is associated with an increased risk of LR.

Hierarchy performance assessment of industrial solid waste utilization - tracking resource recycling and utilization centers in China

The massive production and accumulation of industrial solid waste (ISW) have led to environmental pollution and natural resource underutilization. China's efforts to build trial industrial waste resource utilization centers provide strong support for sustainable development. However, these centers and the factors driving ISW utilization have yet to be evaluated. This paper utilizes context-dependent data envelopment analysis models without explicit inputs (DEA-WEI) to evaluate the overall utilization performance of 48 industrial waste resource utilization centers in China from 2018 to 2020. It also builds a Tobit model to assess which indicators and waste types affect overall ISW utilization. The results show overall ISW utilization performance of centers in the sample has improved, with the average value falling from 1.7193 in 2018 to 1.5624 in 2020. However, there are clear regional performance gaps, with East China having the highest utilization performance (1.3113) while the Southwest had the lowest (2.2958). Finally, this paper proposes measures to improve the overall utilization of industrial waste resources based on an analysis of the factors driving solid waste utilization.

Preparation of Epoxy Resin with Disulfide-Containing Curing Agent and Its Application in Self-Healing Coating

Intrinsic self-healing polymers via dynamic covalent bonds have been attracting extensive attention because of their repeatable self-healing property. Herein, a novel self-healing epoxy resin was synthesized with disulfide-containing curing agent via the condensation of dimethyl 3,3'-dithiodipropionate (DTPA) and polyether amine (PEA). Therefore, in the structure of cured resin, flexible molecular chains and disulfide bonds were imported into the cross-linked polymer networks for triggering self-healing performance. The self-healing reaction of cracked samples was realized under a mild condition (60 °C for 6 h). The distribution of flexible polymer segments, disulfide bonds and hydrogen bonds in cross-linked networks plays a great role in the self-healing process of prepared resins. The molar ratio of PEA and DTPA strongly affects the mechanical performance and self-healing property. Especially when that molar ratio of PEA to DTPA is 2, the cured self-healing resin sample showed great ultimate elongation (795%) and excellent healing efficiency (98%). The products can be used as an organic coating, in which the crack could self-repair during a limited time. The corrosion resistance of a typical cure coating sample has been testified by an immersion experiment and electrochemistry impedance spectrum (EIS). This work provided a simple and low-cost route to prepare a self-healing coating for prolonging the service life of conventional epoxy coatings.

Human Activity Recognition Method Based on FMCW Radar Sensor with Multi-Domain Feature Attention Fusion Network

This paper proposes a human activity recognition (HAR) method for frequency-modulated continuous wave (FMCW) radar sensors. The method utilizes a multi-domain feature attention fusion network (MFAFN) model that addresses the limitation of relying on a single range or velocity feature to describe human activity. Specifically, the network fuses time-Doppler (TD) and time-range (TR) maps of human activities, resulting in a more comprehensive representation of the activities being performed. In the feature fusion phase, the multi-feature attention fusion module (MAFM) combines features of different depth levels by introducing a channel attention mechanism. Additionally, a multi-classification focus loss (MFL) function is applied to classify confusable samples. The experimental results demonstrate that the proposed method achieves 97.58% recognition accuracy on the dataset provided by the University of Glasgow, UK. Compared to existing HAR methods for the same dataset, the proposed method showed an improvement of about 0.9-5.5%, especially in the classification of confusable activities, showing an improvement of up to 18.33%.

Conformational Dynamics of the Activated GLP-1 Receptor-Gs Complex Revealed by Cross-Linking Mass Spectrometry and Integrative Structure Modeling

Despite advances in characterizing the structures and functions of G protein-coupled receptors (GPCRs), our understanding of GPCR activation and signaling is still limited by the lack of information on conformational dynamics. It is particularly challenging to study the dynamics of GPCR complexes with their signaling partners because of their transient nature and low stability. Here, by combining cross-linking mass spectrometry (CLMS) with integrative structure modeling, we map the conformational ensemble of an activated GPCR-G protein complex at near-atomic resolution. The integrative structures describe heterogeneous conformations for a high number of potential alternative active states of the GLP-1 receptor-G_s complex. These structures show marked differences from the previously determined cryo-EM structure, especially at the receptor-G_s interface and in the interior of the G_s heterotrimer. Alanine-scanning mutagenesis coupled with pharmacological assays validates the functional significance of 24 interface residue contacts only observed in the integrative structures, yet absent in the cryo-EM structure. Through the integration of spatial connectivity data from CLMS with structure modeling, our study provides a new approach that is generalizable to characterizing the conformational dynamics of GPCR signaling complexes.

Femtosecond Autocorrelation of Localized Surface Plasmons

Plasmon electronic dephasing lifetime is one of the most important characteristics of localized surface plasmons, which is crucial both for understanding the related photophysics and for their applications in photonic and optoelectronic devices. This lifetime is generally shorter than 100 fs and measured using the femtosecond pump-probe technique, which requires femtosecond laser amplifiers delivering pulses with a duration even as short as 10 fs. This implies a large-scale laser system with complicated pulse compression schemes, introducing high-cost and technological challenges. Meanwhile, the strong optical pulse from an amplifier induces more thermal-related effects, disturbing the precise resolution of the pure electronic dephasing lifetime. In this work, we use a simple autocorrelator design and integrate it with the sample of plasmonic nanostructures, where a femtosecond laser oscillator supplies the incident pulses for autocorrelation measurements. Thus, the measured autocorrelation trace carries the optical modulation on the incident pulses. The dephasing lifetime can be thus determined by a comparison between the theoretical fittings to the autocorrelation traces with and without the plasmonic modulation. The measured timescale for the autocorrelation modulation is an indirect determination of the plasmonic dephasing lifetime. This supplies a simple, rapid, and low-cost method for quantitative characterization of the ultrafast optical response of localized surface plasmons.

Function of Innate Lymphoid Cells in Periodontal Tissue Homeostasis: A Narrative Review

Periodontitis is an irreversible inflammatory response that occurs in periodontal tissues. Given the size and diversity of natural flora in the oral mucosa, host immunity must strike a balance between pathogen identification and a complicated system of tolerance. The innate immune system, which includes innate lymphoid cells (ILCs), certainly plays a crucial role in regulating this homeostasis because pathogens are quickly recognized and responded to. ILCs are a recently discovered category of tissue-resident lymphocytes that lack adaptive antigen receptors. ILCs are found in both lymphoid and non-lymphoid organs and are particularly prevalent at mucosal barrier surfaces, where they control inflammatory response and homeostasis. Recent studies have shown that ILCs are important players in periodontitis; however, the mechanisms that govern the innate immune response in periodontitis still require further investigation. This review focuses on the intricate crosstalk between ILCs and the microenvironment in periodontal tissue homeostasis, with the purpose of regulating or improving immune responses in periodontitis prevention and therapy.

Enhanced selenocysteine biosynthesis for seleno-methylselenocysteine production in Bacillus subtilis

Seleno-methylselenocysteine (SeMCys) is an effective component for selenium supplementation with anti-carcinogenic potential and can ameliorate neuropathology and cognitive deficits. In this study, we aimed to engineer Bacillus subtilis 168 for the microbial production of SeMCys. First, the accumulation of intracellular selenocysteine (SeCys) as the precursor of SeMCys was enhanced through overexpression of serine O-acetyltransferase, which was desensitized against feedback inhibition by cysteine. Next, the S-adenosylmethionine (SAM) synthetic pathway was optimized to improve methyl donor availability through expression of S-adenosylmethionine synthetase. Further, SeMCys was successfully produced through expression of the selenocysteine methyltransferase in SeCys and SAM-producing strain. The increased expression level of selenocysteine methyltransferase benefited the SeMCys production. Finally, all the heterologous genes were integrated into the genome of B. subtilis, and the strain produced SeMCys at a titer of 18.4 μg/L in fed-batch culture. This is the first report on the metabolic engineering of B. subtilis for microbial production of SeMCys and provides a good starting point for future pathway engineering to achieve the industrial-grade production of SeMCys. KEY POINTS: • Expression of the feedback-insensitive serine O-acetyltransferase provided B. subtilis the ability of accumulating SeCys. • SAM production was enhanced through expressing S-adenosylmethionine synthetase in B. subtilis. • Expression of selenocysteine methyltransferase in SeCys and SAM-accumulating strain facilitated SeMCys production.

Leader extraversion and team performance: A moderated mediation model

Extraversion is the best and most consistent predictor of important leadership outcomes. However, there has been little exploration and examination of the mechanisms underlying the effects of extraverted leadership on performance. Drawing on distal-proximal motivational theory and situational strength theory, the present study proposes and examines a moderated mediation model that explains how leader extraversion affects team performance and how situational characteristics strengthen or constrain this relationship. Respondents were recruited through management team training courses run by the eight Chinese companies. We conducted two rounds of electronic questionnaire collection. The first round of data was collected during the training session. Four weeks later, we collected the data through the training courses' WeChat groups. Data collected from 226 Chinese team leaders was analyzed using SPSS 26 and Mplus 7. We find that leader extraversion predicts team performance through a motivational mechanism operationalized as leader work engagement. We further find that goal clarity and process clarity play an important role in strengthening the positive effect of leader extraversion on leader work engagement as well as the motivational mechanism, providing an empirical explanation of how leader extraversion affects team performance through a motivational mechanism operationalized as leader work engagement. We also explore how two potential situational characteristics, operationalized as goal clarity and process clarity of leaders, affect the relationship between leader extraversion and leader work engagement as well as the motivational mechanism. Addionally, the findings suggest important practical implications for the organizations seeking to identify effective team leaders.

PAD4 and Its Inhibitors in Cancer Progression and Prognosis

The systemic spread of malignancies and the risk of cancer-associated thrombosis are major clinical challenges in cancer therapy worldwide. As an important post-translational modification enzyme, peptidyl arginine deiminase 4 (PAD4) could mediate the citrullination of protein in different components (including nucleus and cytoplasm, etc.) of a variety of cells (tumor cells, neutrophils, macrophages, etc.), thus participating in gene regulation, neutrophil extracellular trap (NET) and macrophage extracellular trap (MET). Thereby, PAD4 plays an important role in enhancing the growth of primary tumors and facilitating the distant metastasis of cancer cells. In addition, it is related to the formation of cancer-associated thrombosis. Therefore, the development of PAD4-specific inhibitors may be a promising strategy for treating cancer, and it may improve patient prognosis. In this review, we describe PAD4 involvement in gene regulation, protein citrullination, and NET formation. We also discuss its potential role in cancer and cancer-associated thrombosis, and we summarize the development and application of PAD4 inhibitors.

Role of time perspectives and self-control on well-being and ill-being during the COVID-19 pandemic: A multiple mediation model

BACKGROUND

A growing body of evidence indicates that the outbreak of COVID-19 has had a significant influence on individuals' cognition, emotion, and psychological health. This study aims to explore the effect of the association between time perspectives and self-control on the well-being and ill-being among college students in China during the COVID-19 pandemic.

METHODS

We conducted an online survey involving 1,924 participants in mainland China during the outbreak of COVID-19. A series of self-rating questionnaires measuring the perceived impact of COVID-19, time perspectives, self-control, as well as the statuses of well-being and ill-being were administered. Multiple indirect effects of time perspectives and self-control on well-being and ill-being were analysed through structural equation modelling.

RESULTS

The present-hedonistic time perspective (an orientation on immediate impulses of pleasure) meditated the effects of perceived impacts on both well-being and ill-being, and the future time perspective (considering the outcomes of actions and decisions) mediated the effects on well-being. Moreover, the mediating effects were further mediated by self-control. Specifically, the impact of the future time perspective on ill-being was fully mediated by self-control (β = 0.01, p < 0.01).

CONCLUSION

Based on the results, it is evident that the present-hedonistic time perspective, the future time perspective, and self-control are related to higher levels of well-being and lower levels of ill-being, thereby providing further insight into the theoretical framework of time perspectives during the COVID-19 pandemic. Additionally, our findings provide practical implications for psychological interventions during the on-going COVID-19 pandemic, focusing on the effects of time perspectives and self-control on the well-being and ill-being of different individuals.

Therapeutic applications and potential mechanisms of acupuncture in migraine: A literature review and perspectives

Acupuncture is commonly used as a treatment for migraines. Animal studies have suggested that acupuncture can decrease neuropeptides, immune cells, and proinflammatory and excitatory neurotransmitters, which are associated with the pathogenesis of neuroinflammation. In addition, acupuncture participates in the development of peripheral and central sensitization through modulation of the release of neuronal-sensitization-related mediators (brain-derived neurotrophic factor, glutamate), endocannabinoid system, and serotonin system activation. Clinical studies have demonstrated that acupuncture may be a beneficial migraine treatment, particularly in decreasing pain intensity, duration, emotional comorbidity, and days of acute medication intake. However, specific clinical effectiveness has not been substantiated, and the mechanisms underlying its efficacy remain obscure. With the development of biomedical and neuroimaging techniques, the neural mechanism of acupuncture in migraine has gained increasing attention. Neuroimaging studies have indicated that acupuncture may alter the abnormal functional activity and connectivity of the descending pain modulatory system, default mode network, thalamus, frontal-parietal network, occipital-temporal network, and cerebellum. Acupuncture may reduce neuroinflammation, regulate peripheral and central sensitization, and normalize abnormal brain activity, thereby preventing pain signal transmission. To summarize the effects and neural mechanisms of acupuncture in migraine, we performed a systematic review of literature about migraine and acupuncture. We summarized the characteristics of current clinical studies, including the types of participants, study designs, and clinical outcomes. The published findings from basic neuroimaging studies support the hypothesis that acupuncture alters abnormal neuroplasticity and brain activity. The benefits of acupuncture require further investigation through basic and clinical studies.

Proteomic and metabolomic profiling of acupuncture for migraine reveals a correlative link via energy metabolism

Migraine is a neurovascular disease with a high disability rate. Acupuncture treatment has emerged as a safe and viable alternative prophylactic therapy that can effectively alleviate the duration and frequency of migraine attacks. However, the therapeutic mechanisms underlying the effects of acupuncture are yet to be systematically elucidated. In this study, we enrolled female patients with migraine without aura (n = 20) and healthy controls (n = 10). Patients received acupuncture treatment on DU20, DU24, bilateral GB13, GB8, and GB20, applied three times per week over the course of 4 weeks for 12 sessions in total. Blood samples were collected from the median cubital vein before and after acupuncture treatment. Proteomic and metabolomic profiling was performed using liquid chromatography-mass spectrometry to determine the characteristics of differentially expressed molecules and expression of their corresponding biological pathways as well as to elucidate the pathogenesis of migraine and the biological effects underlying the treatment of migraine with acupuncture. Proteomic and metabolomic profiling of plasma samples from patients with migraine without aura before and after acupuncture treatment revealed enrichment of immune-related pathway functions and the arginine synthesis pathway. Joint pathway analyses revealed significant enrichment of the pentose phosphate and glycolysis/gluconeogenesis pathways in patients with migraine. The glycolysis/gluconeogenesis and riboflavin metabolism pathways were significantly enriched after acupuncture treatment. The expression levels of various key proteins and metabolites, including α-D-glucose, flavin adenine dinucleotide, biliverdin reductase B, and L-glutamate, were significantly differentially expressed before and after acupuncture treatment in patients with migraine without aura. Treatment of migraine with acupuncture was associated with significant changes in key molecules and pathways, indicative of physiological changes in the trigeminovascular system, glutamate neurotoxicity, and other migraine-related physiological changes. Overall, our comprehensive analysis using proteomic and metabolomic profiling demonstrates that energy metabolism may serve as a key correlative link in the occurrence of migraine and the therapeutic effects of acupuncture treatment. Our findings may facilitate the identification of diagnostic and therapeutic modalities in the ongoing search for effective treatments for migraine attacks.

Enhancing Organizational Citizenship Behaviors for the Environment: Integrating Social Identity and Social Exchange Perspectives

Purpose

Based on social identity theory and social exchange theory, this study tests the influence of green organizational identity, exchange ideology and perceived organizational support toward the environment on organizational citizenship behaviors for the environment.

Methods

This study conducted a three-wave survey. The data was collected from 526 employees (95% response rate) across three organizations. Structural equation modeling based on AMOS and hierarchical regression analysis based on Hayes’ PROCESS on SPSS were applied to test all hypotheses.

Results

Perceived organizational support towards the environment had a positive influence on organizational citizenship behaviors for the environment, and green organizational identity played a partial mediating role in this relationship. In addition, exchange ideology moderated the relationship between perceived organizational support towards the environment and green organizational identity, and such that this relationship was strengthened as a result of a high level of exchange ideology.

Contribution

Overall, these findings contribute to the understanding of the integration of social identity theory and social exchange theory and the ways in which both theories influence organizational citizenship behaviors for the environment.

Roles and Challenges for Village Doctors in COVID-19 Pandemic Prevention and Control in Rural Beijing, China: A Qualitative Study

Objectives

Rural areas in China are more vulnerable to COVID-19 pandemic than urban areas, due to their far fewer health care resources. Village doctors, as rural grassroots health workers in China, have been actively engaged in the pandemic prevention and control. This study aims to describe the roles of village doctors in rural China, and the challenges they have faced during the prevention and control of the COVID-19 pandemic.

Setting

This study was conducted in three towns in Huairou District, Beijing, China.

Design

We carried out semi-structured interviews with 75 key informants. All the interviews were audio-recorded and transcribed verbatim. We employed thematic analysis to define themes and sub-themes from the qualitative data.

Results

We reported four themes. First, the village doctor guided the village committee to carry out decontamination, monitored home-isolated residents, and disseminated knowledge on prevention of the COVID-19 pandemic during the rural pandemic prevention and control. Second, they took pandemic prevention measures in village clinics, distributed pandemic prevention materials, and undertook pre-screening triage. Third, village doctors provided basic medical care, including treatment of common diseases as well as the purchase and delivery of medicines to villagers. Fourth, village doctors faced difficulties and challenges, such as inadequate medical skills, aging staff structure, and lack of pandemic prevention materials.

Conclusions

Despite many difficulties and challenges, village doctors have actively participated in rural pandemic prevention and control, and made outstanding contributions to curbing spread of COVID-19 pandemic in rural areas. Village doctors provide basic health care while participating in various non-medical tasks.

The Impact of Digital Economy on the Economic Growth and the Development Strategies in the post-COVID-19 Era: Evidence From Countries Along the "Belt and Road"

The digital economy is considered as an effective measure to mitigate the negative economic impact of the Corona Virus Disease 2019 (COVID-19) epidemic. However, few studies evaluated the role of digital economy on the economic growth of countries along the "Belt and Road" and the impact of COVID-19 on their digital industries. This study constructed a comprehensive evaluation index system and applied a panel data regression model to empirically analyze the impact of digital economy on the economic growth of countries along the "Belt and Road" before COVID-19. Then, a Global Trade Analysis Project (GTAP) model was used to examine the impact of COVID-19 on their digital industries and trade pattern. Our results show that although there is an obvious regional imbalance in the digital economy development in countries along the "Belt and Road", the digital economy has a significantly positive effect on their economic growth. The main impact mechanism is through promoting industrial structure upgrading, the total employment and restructuring of employment. Furthermore, COVID-19 has generally boosted the demand for the digital industries, and the impact from the demand side is much larger than that from the supply side. Specifically, the digital industries in Armenia, Israel, Latvia and Estonia have shown great growth potential during the epidemic. On the contrast, COVID-19 has brought adverse impacts to the digital industries in Ukraine, Egypt, Turkey, and the Philippines. The development strategies are proposed to bridge the "digital divide" of countries along the "Belt and Road," and to strengthen the driving effect of the digital economy on industrial upgrading, employment and trade in the post-COVID-19 era.

An Adaptive Time-Varying Impedance Controller for Manipulators

Aiming at the situation that the structural parameters of the general manipulators are uncertain, a time-varying impedance controller based on model reference adaptive control (MRAC) is proposed in this article. The proposed controller does not need to use acceleration-based feedback or to measure external loads and can tolerate considerable structure parameter errors. The global uniform asymptotic stability of the time-varying closed-loop system is analyzed, and a selection approach for control parameters is presented. It is demonstrated that, by using the proposed control parameter selection approach, the closed-loop system under the adaptive controller is equivalent to an existing result. The feasibility of the presented controller for the general manipulators is demonstrated by some numerical simulations.

Simple and Green Synthesis of Carbonized Polymer dots from Nylon 66 Waste Fibers and its Potential Application

Carbonized polymer dots (CPDs) have attracted widespread attention owing to their unique properties and are usually prepared from monomers of polymers or polymers. To reduce the waste of high-value petropolymers and environmental pollution, a simple and green method for the preparation of CPDs using a hydrothermal technique based on the cross-linking enhanced emission effect was proposed, in which nylon 66 waste fibers were used as a precursor and glutaraldehyde as a cross-linking agent. The as-prepared CPDs possessed polymer/carbon hybrid structures with a 3.5 nm average diameter, and hydroxyl (-OH), carboxyl (-COOH), and amino (-NH₂) groups were present on the surface of CPDs. It can be found that the as-prepared CPDs display excitation-dependent photoluminescence emission, which is mainly attributed to the molecular state luminescence center. Because the molecular state fluorescence of CPDs could be affected by the presence of Fe³⁺ and the change of pH values, the as-prepared CPDs can be used as a probe for the detection of the concentration of Fe³⁺ and the pH variations of solution. The fluorescence intensity of CPDs was selectively quenched by Fe³⁺ in the range from 1 to 145 μM. In virtue of the static quenching of CPDs by Fe³⁺, a sensing system was fabricated for the quantitative detection of Fe³⁺, and its limit of detection was 0.1 μM. Based on the electrostatic doping/charging of CPDs, a pH sensor was fabricated. It showed that the fluorescence intensity of CPDs decreased along with the increase of pH from 2.60 to 12.6. What is more, the CPDs were found to be an alternative to traditional fluorescent inks for encryption and information storage.

Electrochemical Reduction of CO2 to CO over Transition Metal/N-Doped Carbon Catalysts: The Active Sites and Reaction Mechanism

Electrochemical CO2 reduction to value-added chemicals/fuels provides a promising way to mitigate CO2 emission and alleviate energy shortage. CO2 -to-CO conversion involves only two-electron/proton transfer and thus is kinetically fast. Among the various developed CO2 -to-CO reduction electrocatalysts, transition metal/N-doped carbon (M-N-C) catalysts are attractive due to their low cost and high activity. In this work, recent progress on the development of M-N-C catalysts for electrochemical CO2 -to-CO conversion is reviewed in detail. The regulation of the active sites in M-N-C catalysts and their related adjustable electrocatalytic CO2 reduction performance is discussed. A visual performance comparison of M-N-C catalysts for CO2 reduction reaction (CO2 RR) reported over the recent years is given, which suggests that Ni and Fe-N-C catalysts are the most promising candidates for large-scale reduction of CO2 to produce CO. Finally, outlooks and challenges are proposed for future research of CO2 -to-CO conversion.

Enzyme-activated near-infrared fluorogenic probe with high-efficiency intrahepatic targeting ability for visualization of drug-induced liver injury

Hepatotoxicity is a serious problem faced by thousands of clinical drugs, and drug-induced liver injury (DILI) caused by chronic administration or overdose has become a major biosafety issue. However, the near-infrared (NIR) fluorescent probes currently used for liver injury detection still suffer from poor liver targeting ability and low sensitivity. Enzyme-activated fluorogenic probes with powerful in situ targeting ability are the key to improving the imaging effect of liver injury. Herein, we rationally designed a leucine aminopeptidase (LAP) activated fluorogenic probe hCy-CA-LAP, which greatly improved the hepatocyte-targeting capability by introducing a cholic acid group. The probe hCy-CA-LAP is converted into a high-emission hCy-CA fluorophore in the presence of LAP, showing high selectivity, high sensitivity and low detection limit (0.0067 U mL-1) for LAP, and successfully realizes the sensitive detection of small fluctuations of LAP in living cells. Moreover, the probe can achieve effective in situ accumulation in the liver, thereby achieving precise imaging and evaluation of two different types of drug-induced hepatotoxicity in vivo. Therefore, the probe hCy-CA-LAP may be a potential tool for exploring the roles of LAP and evaluating the degree of DILI.

Rapid degradation behavior of encapsulated perovskite solar cells under light, bias voltage or heat fields

When the power conversion efficiency (PCE) of perovskite solar cells (PSCs) rapidly approaches that of commercial solar cells, the stability becomes the most important obstacle for the commercialization of PSCs. Aside from the widely studied slow PCE degradation, the PSCs also show a unique rapid PCE degradation. Although the degradation due to oxygen and humidity can be avoided by encapsulation, that due to bias voltage, light and heat could not be effective suppressed and will lead to considerable degradation. Usually, the rapid PCE degradation is believed to be from ion migration. However, a systematic investigation is yet to be carried out. This work quantitatively and systematically investigated the relationships between external fields (bias voltage, light or heat), ion migration and device performance. By comparing the performance of reference PSCs after 90 min degradation under these fields, we conclude that (1) the electric field affects the spatial distribution of mobile ions; (2) the light field changes the mobile ion densities and drives the ion migration; (3) the heat field results in perovskite decomposition as well as changing the mobile ion densities. In addition to the analysis of the reference device, we experimentally proved that the improved device stability upon introducing phenethylammonium iodide (PEAI) or poly-methyl methacrylate (PMMA) layers originates from the inhibition of mobile ion density and migration.

Combating the Infodemic: A Chinese Infodemic Dataset for Misinformation Identification

Misinformation posted on social media during COVID-19 is one main example of infodemic data. This phenomenon was prominent in China when COVID-19 happened at the beginning. While a lot of data can be collected from various social media platforms, publicly available infodemic detection data remains rare and is not easy to construct manually. Therefore, instead of developing techniques for infodemic detection, this paper aims at constructing a Chinese infodemic dataset, "infodemic 2019", by collecting widely spread Chinese infodemic during the COVID-19 outbreak. Each record is labeled as true, false or questionable. After a four-time adjustment, the original imbalanced dataset is converted into a balanced dataset by exploring the properties of the collected records. The final labels achieve high intercoder reliability with healthcare workers' annotations and the high-frequency words show a strong relationship between the proposed dataset and pandemic diseases. Finally, numerical experiments are carried out with RNN, CNN and fastText. All of them achieve reasonable performance and present baselines for future works.

AUXIN RESPONSE FACTOR 18-HISTONE DEACETYLASE 6 module regulates floral organ identity in rose (Rosa hybrida)

The phytohormone auxin plays a pivotal role in floral meristem initiation and gynoecium development, but whether and how auxin controls floral organ identity remain largely unknown. Here, we found that auxin levels influence organ specification, and changes in auxin levels influence homeotic transformation between petals and stamens in rose (Rosa hybrida). The PIN-FORMED-LIKES (PILS) gene RhPILS1 governs auxin levels in floral buds during floral organogenesis. RhAUXIN RESPONSE FACTOR 18 (RhARF18), whose expression decreases with increasing auxin content, encodes a transcriptional repressor of the C-class gene RhAGAMOUS (RhAG), and controls stamen-petal organ specification in an auxin-dependent manner. Moreover, RhARF18 physically interacts with the histone deacetylase (HDA) RhHDA6. Silencing of RhHDA6 increases H3K9/K14 acetylation levels at the site adjacent to the RhARF18-binding site in the RhAG promoter and reduces petal number, indicating that RhARF18 might recruit RhHDA6 to the RhAG promoter to reinforce the repression of RhAG transcription. We propose a model for how auxin homeostasis controls floral organ identity via regulating transcription of RhAG.