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By systematically analyzing the natural gas composition, carbon isotopes, and source rock characteristics in the Yongfeng sub-sag of the Bogda Mountain front belt, natural gas characteristics were determined, and the genetic types and sources of natural gas were investigated. The research results indicate that methane is the main component of natural gas in the Yongfeng sub-sag, with low levels of heavy hydrocarbons and a high drying coefficient. These characteristics make it dry gas, which refers to natural gas with a methane content of over 95%. The ethane carbon isotope δ13C2 of natural gas is −28.5‰ and belongs to oil type gas. The methane carbon isotope δ13C1 of natural gas is −58.6‰~−59.4‰, has a relatively depleted methane carbon isotope value, shows significant differences from the surrounding natural gas methane carbon isotope, and belongs to the category of biogenic gas. The Permian Lucaogou Formation is the main source rock in the study area, with good organic matter abundance. The microscopic components of kerogen are mainly composed of sapropelic formations and the organic matter type is I–II1. The source rock has a high maturity and has reached the mature stage, mainly consisting of oil and wet gas. The ethane carbon isotope of natural gas in the Yongfeng sub-sag shows as oil type gas, which is consistent with the kerogen type of the Lucaogou Formation source rocks, indicating that the natural gas mainly comes from the Lucaogou Formation source rocks. Based on comprehensive data and information on natural gas composition, carbon isotopes, and burial history of the source rocks, it is believed that some of the crude oil generated from the Lucaogou Formation in the early stage underwent biodegradation due to tectonic uplift, resulting in biogenic methane and the formation of crude oil biodegraded gas.

To further enhance the application of nobiletin (an important active ingredient in Citrus fruits), we used ultrasonic homogenization-assisted antisolvent precipitation to create ultrafine particles of nobiletin (UPN). DMSO was used as the solvent, and deionized water was used as the antisolvent. When ultrasonication (670 W) and homogenization (16000 r/min) were synergistic, the solution concentration was 57 mg/mL, and the minimum particle size of UPN was 521.02 nm. The UPN samples outperformed the RN samples in terms of the inhibition of porcine pancreatic lipase, which was inhibited (by 500 mg/mL) by 68.41 % in the raw sample, 90.34 % in the ultrafine sample, and 83.59 % in the positive control, according to the data. Fourier transform infrared spectroscopy analysis revealed no chemical changes in the samples before or after preparation. However, the crystallinity of the processed ultrafine nobiletin particles decreased. Thus, this work offers significant relevance for applications in the realm of food chemistry and indirectly illustrates the expanded application potential of nobiletin.

Psoriasis is a common chronic inflammatory skin disease, which has seriously affected human health. Berberine is a plant alkaloid with significant anti-inflammatory effect. In this study, we aimed to determine whether topical application of berberine could ameliorate skin inflammation in psoriasis and explore the potential molecular mechanism. Imiquimod (IMQ)-induced psoriasis-like dermatitis in mice was firstly used to reveal the potential pathogenic mechanism. The transcriptome analysis showed that Janus kinase (JAK)-Signal transducer and activator of transcription (STAT) signaling pathway was significantly enriched in IMQ-induced dermatitis, which included the key genes such as Janus kinase 1 (JAK1), Interleukin-2 (IL2), Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA), Phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit beta isoform (PIK3CB) and Signal transducer and activator of transcription 1 (STAT1). Network pharmacology and molecular docking then predicted that topical berberine may treat psoriasis by JAK-STAT signaling pathway, especially act on JAK1, IL2, PIK3CA and PIK3CB. Experimental studies in vivo further demonstrated that topical application of berberine could ameliorate IMQ-induced psoriasis-like skin inflammation by suppressing JAK-STAT signaling pathway. In addition, experimental studies in vitro showed that berberine could directly act on and enter into human immortalized keratinocytes (HaCaT cells). Meanwhile, berberine may inhibit the hyperproliferation and proinflammatory functions of HaCaT cells induced by Interferon-gamma (IFN-γ) via suppressing JAK1/STAT1 signaling pathway. In conclusion, this study suggested that berberine may be a promising topical agent to ameliorate skin inflammation in psoriasis.

Tea plants are a perennial crop with significant economic value. Chlorophyll, a key factor in tea leaf color and photosynthetic efficiency, is affected by the photoperiod and usually exhibits diurnal and seasonal variations. In this study, high-throughput transcriptomic analysis was used to study the chlorophyll metabolism, under different photoperiods, of tea plants. We conducted a time-series sampling under a skeleton photoperiod (6L6D) and continuous light conditions (24 L), measuring the chlorophyll and carotenoid content at a photoperiod interval of 3 h (24 h). Transcriptome sequencing was performed at six time points across two light cycles, followed by bioinformatics analysis to identify and annotate the differentially expressed genes (DEGs) involved in chlorophyll metabolism. The results revealed distinct expression patterns of key genes in the chlorophyll biosynthetic pathway. The expression levels of CHLE (magnesium-protoporphyrin IX monomethyl ester cyclase gene), CHLP (geranylgeranyl reductase gene), CLH (chlorophyllase gene), and POR (cytochrome P450 oxidoreductase gene), encoding enzymes in chlorophyll synthesis, were increased under continuous light conditions (24 L). At 6L6D, the expression levels of CHLP1.1, POR1.1, and POR1.2 showed an oscillating trend. The expression levels of CHLP1.2 and CLH1.1 showed the same trend, they both decreased under light treatment and increased under dark treatment. Our findings provide potential insights into the molecular basis of how photoperiods regulate chlorophyll metabolism in tea plants.

The booming growth of the internet of things has brought about widespread deployment of devices and massive amounts of sensing data to be processed. Federated learning (FL)-empowered mobile edge computing, known for pushing artificial intelligence to the network edge while preserving data privacy in learning cooperation, is a promising way to unleash the potential information of the data. However, FL’s multi-server collaborative operating architecture inevitably results in communication energy consumption between edge servers, which poses great challenges to servers with constrained energy budgets, especially wireless communication servers that rely on battery power. The device-to-device (D2D) communication mode developed for FL turns high-cost and long-distance server interactions into energy-efficient proximity delivery and multi-level aggregations, effectively alleviating the server energy constraints. A few studies have been devoted to D2D-enabled FL management, but most of them have neglected to investigate server computing power for FL operation, and they have all ignored the impact of dataset characteristics on model training, thus failing to fully exploit the data processing capabilities of energy-constrained edge servers. To fill this gap, in this paper we propose a D2D-assisted FL mechanism for energy-constrained edge computing, which jointly incorporates computing power allocation and dataset correlation into FL scheduling. In view of the variable impacts of computational power on model accuracy at different training stages, we design a partite graph-based FL scheme with adaptive D2D pairing and aperiodic variable local iterations of heterogeneous edge servers. Moreover, we leverage graph learning to exploit the performance gain of the dataset correlation between the edge servers in the model aggregation process, and we propose a graph-and-deep reinforcement learning-based D2D server pairing algorithm, which effectively reduces FL model error. The numerical results demonstrate that our designed FL schemes have great advantages in improving FL training accuracy under edge servers’ energy constraints.

Photoacoustic imaging integrates the strengths of optics and ultrasound, offering high resolution, depth penetration, and multimodal imaging capabilities. Practical considerations with instrumentation and geometry limit the number of available acoustic sensors and their “view” of the imaging target, which result in image reconstruction artifacts degrading image quality. To address this problem, YOLOv8-Pix2Pix is proposed as a hybrid artifact-removal algorithm, which is advantageous in comprehensively eliminating various types of artifacts and effectively restoring image details compared to existing algorithms. The proposed algorithm demonstrates superior performance in artifact removal and segmentation of photoacoustic images of brain tumors. For the purpose of further expanding its application fields and aligning with actual clinical needs, an experimental system for photoacoustic detection is designed in this paper to be verified. The experimental results show that the processed images are better than the pre-processed images in terms of reconstruction metrics PSNR and SSIM, and also the segmentation performance is significantly improved, which provides an effective solution for the further development of photoacoustic imaging technology.

A new imaging technique called photoacoustic imaging (PAI) combines the advantages of ultrasound imaging and optical absorption to provide structural and functional details of tissues. It has broad application prospects in the accurate diagnosis and treatment monitoring of brain tumours. However, the existing photoacoustic image classification algorithms cannot effectively distinguish benign tumours from malignant tumours. To address this problem, the YoLov8-MedSAM model is proposed in this research to provide precise and adaptable brain tumour identification and detection segmentation. Additionally, it employs convolutional neural networks (CNNs) to classify and identify tumours in order to distinguish between benign and malignant variations in PAI. The experimental results show that the method proposed in this study not only effectively detects and segments brain tumours of various shapes and sizes but also increases the accuracy of brain tumour classification to 97.02%. The method provides richer and more valuable diagnostic information to the clinic and effectively optimizes the diagnosis and treatment strategy of brain tumours.

Photoacoustic imaging (PAI) is an emerging imaging technique that offers real-time, non-invasive, and radiation-free measurements of optical tissue properties. However, image quality degradation due to factors such as non-ideal signal detection hampers its clinical applicability. To address this challenge, this paper proposes an algorithm for super-resolution reconstruction and segmentation based on deep learning. The proposed enhanced deep super-resolution minimalistic network (EDSR-M) not only mitigates the shortcomings of the original algorithm regarding computational complexity and parameter count but also employs residual learning and attention mechanisms to extract image features and enhance image details, thereby achieving high-quality reconstruction of PAI. DeepLabV3+ is used to segment the images before and after reconstruction to verify the network reconstruction performance. The experimental results demonstrate average improvements of 19.76% in peak-signal-to-noise ratio (PSNR) and 4.80% in structural similarity index (SSIM) for the reconstructed images compared to those of their pre-reconstructed counterparts. Additionally, mean accuracy, mean intersection and union ratio (IoU), and mean boundary F1 score (BFScore) for segmentation showed enhancements of 8.27%, 6.20%, and 6.28%, respectively. The proposed algorithm enhances the effect and texture features of PAI and makes the overall structure of the image restoration more complete.

Abstract The collision cross section (CCS) values derived from ion mobility spectrometry can be used to improve the accuracy of compound identification. Here, we have developed the Structure included graph merging with adduct method for CCS prediction (SigmaCCS) based on graph neural networks using 3D conformers as inputs. A model was trained, evaluated, and tested with >5,000 experimental CCS values. It achieved a coefficient of determination of 0.9945 and a median relative error of 1.1751% on the test set. The model-agnostic interpretation method and the visualization of the learned representations were used to investigate the chemical rationality of SigmaCCS. An in-silico database with 282 million CCS values was generated for three different adduct types of 94 million compounds. Its source code is publicly available at https://github.com/zmzhang/SigmaCCS . Altogether, SigmaCCS is an accurate, rational, and off-the-shelf method to directly predict CCS values from molecular structures.

Flexible thermoelectric generators (FTEGs), which can overcome the energy supply limitations of wearable devices, have received considerable attention. However, the use of toxic Te-based materials and fracture-prone electrodes constrains the application of FTEGs. In this study, a novel Ag2Se and Poly (3,4-ethylene dioxythiophene): poly (styrene sulfonate) (PEDOT:PSS)/multi-walled carbon nanotube (MWCNT) FTEG with a high output performance and good flexibility is developed. The thermoelectric columns formulated in the work are environmentally friendly and reliable. The key enabler of this work is the use of embedded EGaIn electrodes, which increase the temperature difference collected by the thermoelectric column, thereby improving the FTEG output performance. Additionally, the embedded EGaIn electrodes could be directly printed on polydimethylsiloxane (PDMS) molds without wax paper, which simplifies the preparation process of FTEGs and enhances the fabrication efficiency. The FTEG with embedded electrodes exhibits the highest output power density of 25.83 μW/cm2 and the highest output power of 10.95 μW at ΔT = 15 K. The latter is 31.6% higher than that of silver-based FTEGs and 2.5% higher than that of covered EGaIn-based FTEGs. Moreover, the prepared FTEG has an excellent flexibility (>1500 bends) and output power stability (>30 days). At high humidity and high temperature, the prepared FTEG maintains good performance. These results demonstrate that the prepared FTEGs can be used as a stable and environmentally friendly energy supply for wearable devices.

The circadian clock refers to the formation of a certain rule in the long-term evolution of an organism, which is an invisible ‘clock’ in the body of an organism. As one of the largest TF families in higher plants, the MYB transcription factor is involved in plant growth and development. MYB is also inextricably correlated with the circadian rhythm. In this study, the transcriptome data of the tea plant ‘Baiyeyihao’ were measured at a photoperiod interval of 4 h (24 h). A total of 25,306 unigenes were obtained, including 14,615 unigenes that were annotated across 20 functional categories within the GO classification. Additionally, 10,443 single-gene clusters were annotated to 11 sublevels of metabolic pathways using KEGG. Based on the results of gene annotation and differential gene transcript analysis, 22 genes encoding MYB transcription factors were identified. The G10 group in the phylogenetic tree had 13 members, of which 5 were related to the circadian rhythm, accounting for 39%. The G1, G2, G8, G9, G15, G16, G18, G19, G20, G21 and G23 groups had no members associated with the circadian rhythm. Among the 22 differentially expressed MYB transcription factors, 3 members of LHY, RVE1 and RVE8 were core circadian rhythm genes belonging to the G10, G12 and G10 groups, respectively. Real-time fluorescence quantitative PCR was used to detect and validate the expression of the gene transcripts encoding MYB transcription factors associated with the circadian rhythm.

Li-ion batteries play a key role in energy storage and conversion in engineering systems such as electric vehicles and grid energy storage, with critical impact on electrification and storage of renewable energy. A key unresolved technological challenge in Li-ion batteries pertains to thermal runaway initiation and propagation in a battery pack, which can lead to subsequent fire and explosion. Despite significant past work, there remains a critical need to understand how thermal runaway propagates in a pack. This work presents a comprehensive investigation of the effect of radiative heat transfer on thermal runaway propagation. Radiation can be important when a battery is exposed to adjacent heat and fire sources, as well as in thermal runaway propagation from one hot cell to another. A theoretical radiative heat transfer model based on view factor theory is developed. Calculations based on this model for a simple 2D cylinder-to-cylinder geometry are found to be in very good agreement with analytical expressions. Radiation-induced thermal runaway propagation between two cylindrical 18650 batteries is evaluated. It is shown that radiation may play a key role in thermal runaway propagation, depending strongly on the triggering temperature. It is found that radiative effects in thermal runaway propagation exhibit both nonlinear and non-monotonic characteristics. At high temperatures, thermal runaway is triggered rapidly in the region close to the battery surface, where the chemical reactions are strongly coupled, and radiation plays a dominant role. In contrast, at lower temperatures, thermal runaway is triggered much more slowly and towards the core of the cell, where some chemical reactions may be decoupled, and pre-runaway chemical heat release plays an increasingly important role. The results presented here suggest that radiation can either facilitate or mitigate thermal runaway. The net radiation heat flux has a cross-over instant, beyond which radiation starts to retard thermal runaway. Additionally, the blocking effect in radiative heat transfer between cells arranged in equal-spacing homogenous or orthogonal arrangements in a battery pack is investigated, along with the effect of the hot spot size. Results from this work help understand the role of radiation in thermal runaway propagation and provide useful insights into the thermal runaway control and design of safe Li-ion battery packs.

Fine-grained recognition has many applications in many fields and aims to identify targets from subcategories. This is a highly challenging task due to the minor differences between subcategories. Both modal missing and adversarial sample attacks are easily encountered in fine-grained recognition tasks based on multimodal data. These situations can easily lead to the model needing to be fixed. An Enhanced Framework for the Complementarity of Multimodal Features (EFCMF) is proposed in this study to solve this problem. The model’s learning of multimodal data complementarity is enhanced by randomly deactivating modal features in the constructed multimodal fine-grained recognition model. The results show that the model gains the ability to handle modal missing without additional training of the model and can achieve 91.14% and 99.31% accuracy on Birds and Flowers datasets. The average accuracy of EFCMF on the two datasets is 52.85%, which is 27.13% higher than that of Bi-modal PMA when facing four adversarial example attacks, namely FGSM, BIM, PGD and C&W. In the face of missing modal cases, the average accuracy of EFCMF is 76.33% on both datasets respectively, which is 32.63% higher than that of Bi-modal PMA. Compared with existing methods, EFCMF is robust in the face of modal missing and adversarial example attacks in multimodal fine-grained recognition tasks. The source code is available at https://github.com/RPZ97/EFCMF (accessed on 8 January 2023).

Porous organometallic nanomaterials are a new class of materials based on a three-dimensional structure. They have excellent applications in different fields, but their applications in gas storage and separation have not been fully developed. CO2 adsorption storage and hydrocarbon separation has been a challenging industrial problem. Several typical molecular adsorbents have been used to study the separation, but the problems of long-term stability, high selectivity and synthetic complexity of these adsorbents remain to be solved. Here, we have designed and synthesized tetrahedral metal supramolecular nanocage with custom cavities based on the unique rigid structure of triptycene derivatives. Using the unique discrete porous structure of tetrahedral metal nanocages, the gas adsorption and separation performance of the metal supramolecular nanocage was investigated. By analyzing the adsorption and desorption isotherms and the multi-component competitive adsorption curves, we noticed that the tetrahedral supramolecular nanocages had good CO2 storage capacity and good separation capacity for C2H2/CO2 and C2H2/N2. All these indicate that porous organic metal nanomaterials are expected to be a new energy saving separation material.

Traumatic spinal cord injury (SCI) initiates a series of cellular and molecular events that include both primary and secondary injury cascades. This secondary cascade provides opportunities for the delivery of therapeutic intervention. Growth differentiation factor 11 (GDF11), a member of the transforming growth factor-β (TGF-β) superfamily, regulates various biological processes in mammals. The effects of GDF11 in the nervous system were not fully elucidated. Here, we perform extensive in vitro and in vivo studies to unravel the effects of GDF11 on spinal cord after injury. In vitro culture studies showed that GDF11 increased the survival of both neuronal and oligodendroglial cells but decreased microglial cells. In stressed cultures, GDF11 effectively inhibited LPS stimulation and also protected neurons from ischemic damage. Intravenous GDF11 administration to rat after eliciting SCI significantly improved hindlimb functional restoration of SCI rats. Reduced neuronal connectivity was evident at 6 weeks post-injury and these deficits were markedly attenuated by GDF11 treatment. Furthermore, SCI-associated oligodendroglial alteration were more preserved by GDF11 treatment. Taken together, GDF11 infusion via intravenous route to SCI rats is beneficial, facilitating its therapeutic application in the future.

Nitrate nitrogen is an important nitrogen source for tea plants’ growth and development. LBD transcription factors play important roles in response to the presence of nitrate in plants. The functional study of LBD transcription factors in tea plants remains limited. In this study, the LBD family gene CsLBD39 was isolated and characterized from tea plants. Sequence analysis indicated that CsLBD39 contained a highly conserved CX2CX6CX3CX domain. The phylogenetic tree assay showed that CsLBD39 belonged to class II subfamily of the LBD family. CsLBD39 was highly expressed in flowers and root; we determined that its expression could be induced by nitrate treatment. The CsLBD39 protein was located in the nucleus and has transcriptional activation activity in yeast. Compared with the wild type, overexpression of CsLBD39 gene in Arabidopsis resulted in smaller rosettes, shorter main roots, reduced lateral roots and lower plant weights. The nitrate content and the expression levels of genes related to nitrate transport and regulation were decreased in transgenic Arabidopsis hosting CsLBD39 gene. Compared with the wild type, CsLBD39 overexpression in transgenic Arabidopsis had smaller cell structure of leaves, shorter diameter of stem cross section, and slender and compact cell of stem longitudinal section. Under KNO3 treatment, the contents of nitrate, anthocyanins, and chlorophyll in leaves, and the content of nitrate in roots of Arabidopsis overexpressing CsLBD39 were reduced, the expression levels of nitrate transport and regulation related genes were decreased. The results revealed that CsLBD39 may be involved in nitrate signal transduction in tea plants as a negative regulator and laid the groundwork for future studies into the mechanism of nitrate response.

The gel plugging and flooding system has a long history of being researched and applied, but the Changqing reservoir geological characteristics are complex, and the synergistic performance of the composite gel foam plugging system is not fully understood, resulting in poor field application. Additionally, the technique boundary chart of the heterogeneous reservoir plugging system has hardly appeared. In this work, reservoir models of porous, fracture, and pore-fracture were constructed, a composite gel foam plugging system was developed, and its static injection and dynamic profile control and oil displacement performance were evaluated. Finally, combined with the experimental studies, a technical boundary chart of plugging systems for heterogeneous reservoirs is proposed. The research results show that the adsorption effect of microspheres (WQ-100) on the surface of elastic gel particles-1 (PEG-1) is more potent than that of pre-crosslinked particle gel (PPG) and the deposition is mainly on the surface of PPG. The adsorption effect of PEG-1 on the surface of PPG is not apparent, primarily manifested as deposition stacking. The gel was synthesized with 0.2% hydrolyzed polyacrylamide (HPAM) + 0.2% organic chromium cross-linking agent, and the strength of enhanced gel with WQ-100 was higher than that of PEG-1 and PPG. The comprehensive value of WQ-100 reinforced foam is greater than that of PEG-1, and PPG reinforced foam, and the enhanced foam with gel has a thick liquid film and poor foaming effect. For the heterogeneous porous reservoir with the permeability of 5/100 mD, the enhanced foam with WQ-100 shows better performance in plugging control and flooding, and the recovery factor increases by 28.05%. The improved foam with gel enhances the fluid flow diversion ability and the recovery factor of fractured reservoirs with fracture widths of 50 μm and 180 μm increases by 29.41% and 24.39%, respectively. For pore-fractured reservoirs with a permeability of 52/167 mD, the PEG + WQ-100 microsphere and enhanced foam with WQ-100 systems show better plugging and recovering performance, and the recovery factor increases are 20.52% and 17.08%, 24.44%, and 21.43%, respectively. The smaller the particle size of the prefabricated gel, the more uniform the adsorption on the foam liquid film and the stronger the stability of the foam system. The plugging performance of the composite gel system is stronger than that of the enhanced gel with foam, but the oil displacement performance of the gel-enhanced foam is better than that of the composite gel system due to the “plug-flooding-integrated” feature of the foam. Combined with the plugging and flooding performance of each plugging system, a technique boundary chart for the plugging system was established for the coexisting porous, fracture, and pore-fracture heterogeneous reservoirs in Changqing Oilfield.

Drug resistance and relapse lead to high mortality in acute myeloid leukemia, and studies have shown that CXCR4 overexpression is highly correlated with poor prognosis and drug resistance in leukemia cells. Isolation and detection of AML cells with CXCR4 overexpression will be crucial to the treatment of AML. In this paper, magnetic nanoparticles were firstly prepared successfully by high-temperature thermal decomposition method, and then characterized by TEM, VSM and DLS. Subsequently CXCR4-targeted magnetic fluorescent nanoprobes conjugated with antibody 12G5 were constructed by stepwise coupling. In cell experiments, the obtained probes demonstrated excellent targeting efficacy to CXCR4 overexpressed AML cells HL-60. In addition, HL-60 cells labelled with the magnetic probes can be magnetic isolated successfully in one microfluidics chip, with efficiency of 82.92 ± 7.03%. Overall, this method utilizes the superiority of superparamagnetic nanomaterials and microfluidic technology to achieve the enrichment and capture of drug-resistant cells in a microfluidic chip, providing a new idea for the isolation and detective of drug-resistant acute myeloid leukemia cells.

Graphene is often used to improve interlaminar fracture toughness of carbon fiber/epoxy resin (CF/EP) composites. It is still a challenge to improve the toughness while maintaining the in-layer properties. In this study, 2D graphene oxide carbon fiber reinforced epoxy resin matrix (2D CF-GO/EP) composites were prepared by a vacuum infiltration hot-press forming experimental system (VIHPS), and three-point flexural and end notch flexural (ENF) tests were carried out. With the increase of the fiber mass fraction in the composites, the mode II interlaminar fracture toughness (GIIC) layers decrease gradually, and the bond property between the fiber and matrix interface layer becomes worse, because the accumulation of dense fiber bundles reduces the matrix penetration ability of cracks. However, the flexural properties increased first and then decreased, and reached the best flexural properties at 64.9%. When the fiber mass fraction is too high, the interlamellar bonding properties will decrease, and the fiber bundles will compress and affect each other. The delamination phenomenon will occur between the layers of the composites, which affects the overall bearing strength and stress limit of the composites. The results of the study show that the composites prepared by VIHPS have excellent mechanical properties, and the content of carbon fiber plays an important role in the influencing factors of the interlaminar and in-layer properties of composites.

Plasmonic superlattice membrane exhibits remarkable functional properties that are emerging from engineered assemblies of well-defined “meta-atoms,” which is featured as a conceptual new category of two-dimensional optical metamaterials. The ability to build plasmonic membranes over macroscopic surfaces but with nanoscale ordering is crucial for systematically controlling the light-matter interactions and represents considerable advances for the bottom-up fabrication of soft optoelectronic devices and circuits. Through rational design, novel nanocrystals, and by engineering the packing orders, the hybridized plasmon signature can be customized, promoting controllable near-field confinement for surface-enhanced Raman scattering (SERS) based detection. However, building such 2D architectures has proven to be remarkably challenging due to the complicated interparticle forces and multiscale interactions during self-assembly. Here, we report on the fabrication of ultralong-nanobrick-based giant plasmonic superlattice membranes as high-performance SERS substrates for ultrasensitive and label-free protein detection. Using aspect-ratio controllable short-to-ultralong nanobricks as building blocks, we construct three distinctive plasmonic membranes by polymer-ligand-based strategy in drying-mediated self-assembly at the air/water interfaces. The plasmonic membranes exhibit monolayered morphology with nanoscale assembled ordering but macroscopic lateral dimensions, inducing enhanced near-field confinement and uniform hot-spot distribution. By choosing 4-aminothiophenol and bovine serum albumin (BSA) as a model analyte, we establish an ultrasensitive assay for label-free SERS detection. The detection limit of BSA can reach 15 nM, and the enhancement factor reached 4.3 × 105, enabling a promising avenue for its clinical application in ultrasensitive biodiagnostics.

To solve the mismatch between the comprehensive mechanical properties of the spinal fusion cage and body, a fusion cage inner hole design method based on controllable TPMS-P to characterize the inner hole structure is proposed to solve the related problems. Firstly, the method of TPMS-P parameterization was used to construct the bionic porous structure model, which was designed as the linear gradual internal porous structure model. Then, we optimized the topology of the obtained porous structure implants to achieve precise control of the overall comprehensive mechanical properties of the fusion cage structure and obtain an optimized model that matched the mechanical properties of the fusion cage. To verify whether the method met the requirements, its simulation model was established. The porous structure was fabricated by selective laser processing, and its properties were tested and analyzed. The results show that its yield strength is 79.83 MPa, which match well with spinal bone tissue.

O-GlcNAcase (OGA) is the only enzyme responsible for removing N-acetyl glucosamine (GlcNAc) attached to serine and threonine residues on proteins. This enzyme plays a key role in O-GlcNAc metabolism. However, the structural features of the sugar moiety recognized by human OGA (hOGA) remain unclear. In this study, a set of glycopeptides with modifications on the GlcNAc residue, were prepared in a recombinant full-length human OGT-catalyzed reaction, using chemoenzymatically synthesized UDP-GlcNAc derivatives. The resulting glycopeptides were used to evaluate the substrate specificity of hOGA toward the sugar moiety. This study will provide insights into the exploration of probes for O-GlcNAc modification, as well as a better understanding of the roles of O-GlcNAc in cellular physiology.

Chromatography is a powerful and generally applicable method for the analytical separation and quantification of the chemical constituents in complex mixtures because chromatographic separation can provide high selectivity by isolating all analytes from interferences. Multiway analysis based on the multilinear model is an increasingly widely used method for interference-free and fast determination of the chemical constituents also in complex mixtures because multilinear mathematical separation can provide high selectivity by extracting the pure signal of the analyte from the mixed signal of a real sample. By combining chromatographic separation with mathematical separation, multiway calibration method, multiway standard additions method, and multiway internal standard method can be established. Chromatography assisted by multiway analysis can reduce the requirements for complete chromatographic separation, save elution time, and decrease the consumption of the mobile phase, particularly when the peak coelution problem is difficult to solve. This review presents the fundamentals and analytical applications of multilinear mathematical separation in chromatography.

Nicotiana tabacum L. (NTL) is an important agricultural and economical crop. Its maturity is one of the key factors affecting its quality. Traditionally, maturity is discriminated visually by humans, which is subjective and empirical. In this study, we concentrated on detecting as many compounds as possible in NTL leaves from different maturity grades using ultra-performance liquid chromatography ion trap time-of-flight mass spectrometry (UPLC-IT-TOF/MS). Then, the low-dimensional embedding of LC-MS dataset by t-distributed stochastic neighbor embedding (t-SNE) clearly showed the separation of the leaves from different maturity grades. The discriminant models between different maturity grades were established using orthogonal partial least squares discriminant analysis (OPLS-DA). The quality metrics of the models are R2Y = 0.939 and Q2 = 0.742 (unripe and ripe), R2Y = 0.900 and Q2 = 0.847 (overripe and ripe), and R2Y = 0.972 and Q2 = 0.930 (overripe and unripe). The differential metabolites were screened by their variable importance in projection (VIP) and p-Values. The existing tandem mass spectrometry library of plant metabolites, the user-defined library of structures, and MS-FINDER were combined to identify these metabolites. A total of 49 compounds were identified, including 12 amines, 14 lipids, 10 phenols, and 13 others. The results can be used to discriminate the maturity grades of the leaves and ensure their quality.

Numerous studies have been conducted on lower back injury caused by deeper stooped posture, which is associated with the back muscle flexion–relaxation phenomenon (FRP). Individual flexibility also affects FRP; individuals with high flexibility have the benefit of delayed FRP occurrence. This study attempted to determine the most efficient measurement of flexibility for evaluating the occurrence and degree of FRP when participants flexed their trunk forward. We recruited 40 male university students who were grouped on the basis of three flexibility measurements (toe-touch test, TTT; sit-and-reach test, SRT; modified Schober’s test, MST) into three levels (high, middle and low). Muscle activation (thoracic and lumbar erector spinae, TES and LES, respectively; hamstring, HMS) and lumbosacral angle (LSA) were recorded when the trunk flexed forward from 0° (upright) to 15°, 30°, 45°, 60°, 75° and 90°. The results indicated that trunk angle had a significant effect on three muscle activation levels and LSA. The effects of muscles and LSA varied depending on flexibility measurement. TTT significantly discriminated LES electromyography findings between high and low flexibility groups, whereas MST and SRT distinguished between high and non-high flexibility groups. The TTT values positively correlated with the time of LES FRP occurrence, showing that the higher the TTT, the slower the occurrence of FRP. This is beneficial in delaying or avoiding excessive loading on the passive tissue of the lumbar spine when performing a deeper trunk flexion.

Surface-enhanced Raman scattering (SERS) greatly increases the detection sensitivity of Raman scattering. However, its real applications are often degraded due to the unrepeatable preparation of SERS substrates. Herein presented is a very facile and cost-effective method to reproducibly produce a novel type of SERS substrate, a monolayer photonic crystal (PC). With a building block of laboratory-prepared monodisperse SiO2 particles deposited with space-tunable silver nanobulges (SiO2@nAg), a PC substrate was first assembled at the air–water interface through needle tip flowing, then transferred onto a silicon slide by a pulling technique. The transferred monolayer PCs were characterized by SEM and AFM to have a hexagonal close-packed lattice. They could increase Raman scattering intensity by up to 2.2 × 107-fold, as tested with p-aminothiophenol. The relative standard deviations were all below 5% among different substrates or among different locations on the same substrate. The excellent reproducibility was ascribed to the highly ordered structure of PCs, while the very high sensitivity was attributed to the strong hotspot effect caused by the appropriately high density of nanobulges deposited on SiO2 particles and by a closed lattice. The PC substrates were validated to be applicable to the SERS assay of trace thiol pesticides. Thiram pesticide is an example determined in apple juice samples at a concentration 102-fold lower than the food safety standard of China. This method is extendable to the analysis of other Raman-active thiol chemicals in different samples, and the substrate preparation approach can be modified for the fabrication of more PC substrates from other metallic nanobulge-deposited particles rather than silica only.

Improving nitrogen use efficiency (NUE) is very important for crops throughout the world. Rice mainly utilizes ammonium as an N source, but it also has four NRT2 genes involved in nitrate transport. The OsNRT2.3b transporter is important for maintaining cellular pH under mixed N supplies. Overexpression of this transporter driven by a ubiquitin promoter in rice greatly improved yield and NUE. This strategy for improving the NUE of crops may also be important for other cereals such as wheat and barley, which also face the challenges of nutrient uptake balance. To test this idea, we constructed transgenic barley lines overexpressing OsNRT2.3b. These transgenic barley lines overexpressing the rice transporter exhibited improved growth, yield, and NUE. We demonstrated that NRT2 family members and the partner protein HvNAR2.3 were also up-regulated by nitrate treatment (0.2 mM) in the transgenic lines. This suggests that the expression of OsNRT2.3b and other HvNRT2 family members were all up-regulated in the transgenic barley to increase the efficiency of N uptake and usage. We also compared the ubiquitin (Ubi) and a phloem-specific (RSs1) promoter-driven expression of OsNRT2.3b. The Ubi promoter failed to improve nutrient uptake balance, whereas the RSs1 promoter succeed in increasing the N, P, and Fe uptake balance. The nutrient uptake enhancement did not include Mn and Mg. Surprisingly, we found that the choice of promoter influenced the barley phenotype, not only increasing NUE and grain yield, but also improving nutrient uptake balance.

The semi- and thiosemicarbazones of benzophenone derivatives (L1–L6) had been synthesized and their respective Cu(II) complexes (1–6) were obtained as precipitates by interaction with CuCl2 in ethanolic solution. All these compounds were characterized by 1H and 13C NMR, IR, UV–Vis and elemental analysis (CHN). The structures of L1 and L4 were further elucidated by X-ray crystallography. Antifungal activities of the ligands and Cu(II) complexes were carried out to ascertain their effectiveness in the inhibition of Fusarium oxysporum f. sp. cubense tropical race 4 (Foc TR4), a highly virulent pathogen against Cavendish banana in tropical region. A few of the complexes showed noteworthy inhibition on the growth of Foc TR4 with complex 6 was the most potent antifungal agent.

The growth and development of plants are sensitive to their surroundings. Although numerous studies have analyzed plant transcriptomic variation, few have quantified the effect of combinations of factors or identified factor-specific effects. In this study, we performed RNA sequencing (RNA-seq) analysis on tobacco leaves derived from 10 treatment combinations of three groups of ecological factors, i.e., climate factors (CFs), soil factors (SFs), and tillage factors (TFs). We detected 4980, 2916, and 1605 differentially expressed genes (DEGs) that were affected by CFs, SFs, and TFs, which included 2703, 768, and 507 specific and 703 common DEGs (simultaneously regulated by CFs, SFs, and TFs), respectively. GO and KEGG enrichment analyses showed that genes involved in abiotic stress responses and secondary metabolic pathways were overrepresented in the common and CF-specific DEGs. In addition, we noted enrichment in CF-specific DEGs related to the circadian rhythm, SF-specific DEGs involved in mineral nutrient absorption and transport, and SF- and TF-specific DEGs associated with photosynthesis. Based on these results, we propose a model that explains how plants adapt to various ecological factors at the transcriptomic level. Additionally, the identified DEGs lay the foundation for future investigations of stress resistance, circadian rhythm and photosynthesis in tobacco.

Lagerstroemia indica is an important ornamental tree worldwide. The development of cultivars with colorful leaves and increased ornamental value represents one of the current main research topics. We investigated the anthocyanin profiles in two contrasting cultivars for leaf color phenotypes and explored the underlying molecular basis. Both cultivars display purple-red young leaves (Stage 1), and when the leaves mature (Stage 2), they turn green in HD (Lagerstroemia Dynamite) but remain unchanged in ZD (Lagerstroemia Ebony Embers). Seven different anthocyanins were detected, and globally, the leaves of ZD contained higher levels of anthocyanins than those of HD at the two stages with the most pronounced difference observed at Stage 2. Transcriptome sequencing revealed that in contrast to HD, ZD tends to keep a higher activity level of key genes involved in the flavonoid−anthocyanin biosynthesis pathways throughout the leaf developmental stages in order to maintain the synthesis, accumulation, and modification of anthocyanins. By applying gene co-expression analysis, we detected 19 key MYB regulators were co-expressed with the flavonoid−anthocyanin biosynthetic genes and were found strongly down-regulated in HD. This study lays the foundation for the artificial manipulation of the anthocyanin biosynthesis in order to create new L. indica cultivars with colorful leaves and increased ornamental value.

Our previous studies showed that microRNA-15a (miR-15a) was closely related to intramuscular fat (IMF) deposition in chickens; however, its regulatory mechanism remains unclear. Here, we evaluated the expression characteristics of miR-15a and its relationship with the expression of acetyl-CoA acyltransferase 1 (ACAA1), acyl-CoA oxidase 1 (ACOX1) and sterol carrier protein 2 (SCP2) by qPCR analysis in Gushi chicken breast muscle at 6, 14, 22, and 30 weeks old, where we performed transfection tests of miR-15a mimics in intramuscular preadipocytes and verified the target gene of miR-15a in chicken fibroblasts (DF1). The miR-15a expression level at 30 weeks increased 13.5, 4.5, and 2.7-fold compared with the expression levels at 6, 14, and 22 weeks, respectively. After 6 days of induction, miR-15a over-expression significantly promoted intramuscular adipogenic differentiation and increased cholesterol and triglyceride accumulation in adipocytes. Meanwhile, 48 h after transfection with miR-15a mimics, the expression levels of ACAA1, ACOX1 and SCP2 genes decreased by 56.52%, 31.18% and 37.14% at the mRNA level in intramuscular preadipocytes. In addition, the co-transfection of miR-15a mimics and ACAA1, ACOX1 and SCP2 3′UTR (untranslated region) dual-luciferase vector significantly inhibited dual-luciferase activity in DF1 cells. Taken together, our data demonstrate that miR-15a can reduce fatty acid oxidation by targeting ACAA1, ACOX1, and SCP2, which subsequently indirectly promotes the differentiation of chicken intramuscular preadipocytes.

Demanded as an essential trace element that supports cell growth and basic functions, iron can be harmful and cancerogenic though. By exchanging between its different oxidized forms, iron overload induces free radical formation, lipid peroxidation, DNA, and protein damages, leading to carcinogenesis or ferroptosis. Iron also plays profound roles in modulating tumor microenvironment and metastasis, maintaining genomic stability and controlling epigenetics. in order to meet the high requirement of iron, neoplastic cells have remodeled iron metabolism pathways, including acquisition, storage, and efflux, which makes manipulating iron homeostasis a considerable approach for cancer therapy. Several iron chelators and iron oxide nanoparticles (IONPs) has recently been developed for cancer intervention and presented considerable effects. This review summarizes some latest findings about iron metabolism function and regulation mechanism in cancer and the application of iron chelators and IONPs in cancer diagnosis and therapy.

Cancer-specific drug delivery represents an attractive approach to preventing undesirable side effects and increasing the accumulation of the drug in tumors. The surface modification of selenium nanoparticles (SeNPs) with targeting moieties thus represents an effective strategy for cancer therapy. In this study, SeNPs were modified with folic acid (FA), whose receptors were overexpressed on the surface of cancer cells, including human cervical carcinoma HeLa cells, to fabricate tumor-targeting delivery carrier FA-SeNPs nanoparticles. Then, the anticancer drug doxorubicin (DOX) was loaded onto the surface of the FA-SeNPs for improving the antitumor efficacy of DOX in human cervical carcinoma therapy. The chemical structure characterization of FA-Se@DOX showed that DOX was successfully loaded to the surface of FA-SeNPs to prepare FA-Se@DOX nanoparticles. FA-Se@DOX exhibited significant cellular uptake in human cervical carcinoma HeLa cells (folate receptor overexpressing cells) in comparison with lung cancer A549 cells (folate receptor deficiency cells), and entered HeLa cells mainly by the clathrin-mediated endocytosis pathway. Compared to free DOX or Se@DOX at the equivalent dose of DOX, FA-Se@DOX showed obvious activity to inhibit HeLa cells’ proliferation and induce the apoptosis of HeLa cells. More importantly, FA-Se@DOX could specifically accumulate in the tumor site, which contributed to the significant antitumor efficacy of FA-Se@DOX in vivo. Taken together, FA-Se@DOX may be one novel promising drug candidate for human cervical carcinoma therapy.

Hepatocellular cancer (HCC) is a lethal malignancy with poor prognosis and easy recurrence. There are few agents with minor toxic side effects that can be used for treatment of HCC. Evodiamine (Evo), one of the major bioactive components derived from fructus Evodiae, has long been shown to exert anti-hepatocellular carcinoma activity by suppressing activation of nuclear factor-κB (NF-κB) and mitogen-activated protein kinase (MAPK). In addition, in the Nucleotide-Binding Oligomerization Domain 1 (NOD1) pathway, NOD1 could initiate NF-κB-dependent and MAPK-dependent gene transcription. Recent experimental studies reported that the NOD1 pathway was related to controlling development of various tumors. Here we hypothesize that Evo exerts anti-hepatocellular carcinoma activity by inhibiting NOD1 to suppress NF-κB and MAPK activation. Therefore, we proved the anti-hepatocellular carcinoma activity of Evo on HCC cells and detected the effect of Evo on the NOD1 pathway. We found that Evo significantly induced cell cycle arrest at the G2/M phase, upregulated P53 and Bcl-2 associated X proteins (Bax) proteins, and downregulated B-cell lymphoma-2 (Bcl-2), cyclinB1, and cdc2 proteins in HCC cells. In addition, Evo reduced levels of NOD1, p-P65, p-ERK, p-p38, and p-JNK, where the level of IκBα of HCC cells increased. Furthermore, NOD1 agonist γ-D-Glu-mDAP (IE-DAP) treatment weakened the effect of Evo on suppression of NF-κB and MAPK activation and cellular proliferation of HCC. In an in vivo subcutaneous xenograft model, Evo also exhibited excellent tumor inhibitory effects via the NOD1 signal pathway. Our results demonstrate that Evo could induce apoptosis remarkably and the inhibitory effect of Evo on HCC cells may be through suppressing the NOD1 signal pathway in vitro and in vivo.

Non-alcoholic fatty liver disease (NAFLD) is one of the most prevalent chronic liver diseases worldwide with an unclear mechanism. Long non-coding RNAs (lncRNAs) have recently emerged as important regulatory molecules. To better understand NAFLD pathogenesis, lncRNA and messenger RNA (mRNA) microarrays were conducted in an NAFLD rodent model. Potential target genes of significantly changed lncRNA were predicted using cis/trans-regulatory algorithms. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were then performed to explore their function. In the current analysis, 89 upregulated and 177 downregulated mRNAs were identified, together with 291 deregulated lncRNAs. Bioinformatic analysis of these RNAs has categorized these RNAs into pathways including arachidonic acid metabolism, circadian rhythm, linoleic acid metabolism, peroxisome proliferator-activated receptor (PPAR) signaling pathway, sphingolipid metabolism, steroid biosynthesis, tryptophan metabolism and tyrosine metabolism were compromised. Quantitative polymerase chain reaction (qPCR) of representative nine mRNAs and eight lncRNAs (named fatty liver-related lncRNA, FLRL) was conducted and this verified previous microarray results. Several lncRNAs, such as FLRL1, FLRL6 and FLRL2 demonstrated to be involved in circadian rhythm targeting period circadian clock 3 (Per3), Per2 and aryl hydrocarbon receptor nuclear translocator-like (Arntl), respectively. While FLRL8, FLRL3 and FLRL7 showed a potential role in PPAR signaling pathway through interaction with fatty acid binding protein 5 (Fabp5), lipoprotein lipase (Lpl) and fatty acid desaturase 2 (Fads2). Functional experiments showed that interfering of lncRNA FLRL2 expression affected the expression of predicted target, circadian rhythm gene Arntl. Moreover, both FLRL2 and Arntl were downregulated in the NAFLD cellular model. The current study identified lncRNA and corresponding mRNA in NAFLD, providing new insight into the pathogenesis of NAFLD. Moreover, we identified a new lncRNA FLRL2, that might participate NAFLD pathogenesis mediated by Arntl.

A high beam quality hundred picoseconds single-longitudinal-mode (SLM) laser is demonstrated based on stimulated Brillouin scattering (SBS) pulse compression and aberration compensation. Flash-lamp-pumped Q-switched Nd3+:Y3Al5O12 (Nd:YAG) SLM laser with Cr4+:Y3Al5O12 (Cr4+:YAG) as a saturable absorber is used as the seed source. By combining master-oscillator-power-amplifier (MOPA), a compact single-cell with FC-770 as working medium is generated as pulse compressor. The 7.8 ns SLM laser is temporally compressed to about 450 ps, and 200 mJ energy is obtained at 1064 nm without optical damage. The energy stability is better than 3% with beam quality factor M2 less than 1.8, which makes this laser system an attractive source for scientific and industrial applications.