Elliptical spiral zone plate fabrication using direct laser writing for generating an elliptical perfect vortex beam.

We report and fabricate a novel, to our knowledge, vortex beam generator called elliptical spiral zone plate (ESZP) using direct laser writing (DLW), which can generate the elliptical perfect vortex beam (EPVB). It is shown that the radius of the EPVB can be adjusted by tuning the control parameters of the ESZP. It is verified through the interference experiment and the Hermitian-Gaussian light field that the topological charge of the EPVB is consistent with the design. In addition, we integrate the ESZP at the tip of the single-mode fiber. Our work may set the scene for applications in fiber optical tweezers, optical communications, and integrated optics.

A multi-module structure labelled molecular network orients the chemical profiles of traditional Chinese medicine prescriptions: Xiaoyao San, as an example.

Ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) technology has emerged as a crucial tool for identifying components in traditional Chinese medicine (TCM). However, the characterization of the chemical profiles of TCM prescriptions (TCMPs) which often consist of multiple herbal medicines and contain diverse structural types, presents several challenges, such as component overlapping and time-consuming. In this study, a novel strategy known as the multi-module structure labelled molecular network (MSLMN), which integrates molecular networking, database annotation, and cluster analysis techniques, has been successfully proposed, which facilitates the identification of chemical constituents by leveraging a high-structural similarity ion list derived from the MSLMN. It has been effectively applied to analyze the chemical profile of Xiaoyao San (XYS), a classical TCMP. Through the MSLMN method, a total of 302 chemical constituents were identified, covering nine structural types in XYS. Furthermore, a validated and quantitative analytical method using UHPLC-QqQ-MS/MS technology was developed for 31 identified chemicals, encompassing all eight herbal medicines present in XYS, and the developed analytical approach was applied to investigate the content distribution across 40 different batches of commercially available XYS. In total, the proposed strategy has practical significance for improving the insight into the chemical profile of XYS and serves as a valuable approach for handling complex system data based on UHPLC-MS, particularly for TCMPs.

A Multifunctional Flexible Tactile Sensor Based on Resistive Effect for Simultaneous Sensing of Pressure and Temperature.

Flexible tactile sensors with multifunctional sensing functions have attracted much attention due to their wide applications in artificial limbs, intelligent robots, human-machine interfaces, and health monitoring devices. Here, a multifunctional flexible tactile sensor based on resistive effect for simultaneous sensing of pressure and temperature is reported. The sensor features a simple design with patterned metal film on a soft substrate with cavities and protrusions. The decoupling of pressure and temperature sensing is achieved by the reasonable arrangement of metal layers in the patterned metal film. Systematically experimental and numerical studies are carried out to reveal the multifunctional sensing mechanism and show that the proposed sensor exhibits good linearity, fast response, high stability, good mechanical flexibility, and good microfabrication compatibility. Demonstrations of the multifunctional flexible tactile sensor to monitor touch, breathing, pulse and objects grabbing/releasing in various application scenarios involving coupled temperature/pressure stimuli illustrate its excellent capability of measuring pressure and temperature simultaneously. These results offer an effective tool for multifunctional sensing of pressure and temperature and create engineering opportunities for applications of wearable health monitoring and human-machine interfaces.

Pedestrian detection algorithm integrating large kernel attention and YOLOV5 lightweight model.

In the context of intelligent driving, pedestrian detection faces challenges related to low accuracy in target recognition and positioning. To address this issue, a pedestrian detection algorithm is proposed that integrates a large kernel attention mechanism with the YOLOV5 lightweight model. The algorithm aims to enhance long-term attention and dependence during image processing by fusing the large kernel attention module with the C3 module. Furthermore, it addresses the lack of long-distance relationship information in channel and spatial feature extraction and representation by introducing the Coordinate Attention mechanism. This mechanism effectively extracts local information and focused location details, thereby improving detection accuracy. To improve the positioning accuracy of obscured targets, the alpha CIOU bounding box regression loss function is employed. It helps mitigate the impact of occlusions and enhances the algorithm's ability to precisely localize pedestrians. To evaluate the effectiveness of trained model, experiments are conducted on the BDD100K pedestrian dataset as well as the Pascal VOC dataset. Experimental results demonstrate that the improved attention fusion YOLOV5 lightweight model achieves an average accuracy of 60.3%. Specifically, the detection accuracy improves by 1.1% compared to the original YOLOV5 algorithm, and the accuracy performance index reaches 73.0%. These findings strongly indicate the proposed algorithm in significantly enhancing the accuracy of pedestrian detection in road scenes.

The role of circadian clock genes in colorectal carcinoma: Novel insights into regulatory mechanism and implications in clinical therapy.

Colorectal cancer (CRC) is a lethal malignancy with limited treatment strategies. Accumulating evidence indicates that CRC tumorigenesis, progression and metastasis are intimately associated with circadian clock, an inherent 24-h cycle oscillation of biochemical, physiological functions in almost every eukaryote. In the present review, we summarize the altered expression level of circadian genes in CRC and the prognosis associated with gene abundance switch. We illustrate the function and potential mechanisms of circadian genes in CRC pathogenesis and progression. Moreover, circadian based-therapeutic strategies including chronotherapy, therapeutics targeting potential circadian components, and melatonin treatment in CRC are also highlighted.

BdCV1-Encoded P3 Silencing Suppressor Identification and Its Roles in Botryosphaeria dothidea, Causing Pear Ring Rot Disease.

Pear ring rot disease is an important branch disease, caused by Botryosphaeria dothidea. With the discovery of fungal viruses, the use of their attenuated properties for biological control provides a new strategy for the biological control of fungal disease. RNA silencing is a major antiviral defense mechanism in plants, insects, and fungi. Viruses encode and utilize RNA silencing suppressors to suppress host defenses. Previous studies revealed that Botryosphaeria dothidea chrysovirus 1 (BdCV1) exhibited weak pathogenicity and could activate host gene silencing by infecting B. dothidea. The aim of our study was to investigate whether BdCV1 can encode a silencing suppressor and what effect it has on the host. In this study, the capability of silencing inhibitory activity of four BdCV1-encoded proteins was analyzed, and the P3 protein was identified as a BdCV1 RNA silencing suppressor in the exotic host Nicotiana benthamiana line 16c. In addition, we demonstrated that P3 could inhibit local silencing, block systemic RNA silencing, and induce the necrosis reaction of tobacco leaves. Furthermore, overexpression of P3 could slow down the growth rate and reduce the pathogenicity of B. dothidea, and to some extent affect the expression level of RNA silencing components and virus-derived siRNAs (vsiRNAs). Combined with transcriptomic analysis, P3 had an effect on the gene expression and biological process of B. dothidea. The obtained results provide new theoretical information for further study of interaction between BdCV1 P3 as a potential silencing suppressor and B. dothidea.

Three-dimensional printing of a beam expander to enable the combination of hundred-micron optical elements and a single-mode fiber.

We use a flexible two-photon photopolymerization direct laser writing to fabricate an integrated diffractive lens system on a fiber tip to expand the output beam of the fiber. The results show that the micro-integrated beam expander based on double lenses (axial size of about 100 µm) has a magnification of 5.9 and a loss of 0.062 dB. Subsequently, we demonstrate the fabrication of a spiral phase plate (diffractive optical elements) and micro-lens arrays (refractive optical elements) on an integrated beam expander, and their optical properties are measured and analyzed, respectively. This Letter is an exploration of the future integrated micro-optical systems on an optical fiber tip.

The PcMYB44-mediated miR397-PcLACs module regulates defence-induced lignification in pear resistance to fungal disease.

Diseases caused by Alternaria alternata and Botryosphaeria dothidea diminish pear yield and quality, and restrict the pear agricultural industry. Lignification is a conserved mechanism for plant resistance against pathogen invasion. The regulatory mechanisms underlying defence-induced lignification in pear in response to fungal pathogen infection remain unknown. In this study, analysis of lignification level and lignin content in pear revealed that A. alternata and B. dothidea induced lignification, and transcriptomics showed that lignin biosynthesis was affected. To explore whether laccases (LACs) mediated by miR397 regulate lignification in pear, we investigated the role of PcmiR397 in repressing the expression of PcLACs using 5'-RNA ligase-mediated-RACE and co-transformation in tobacco. Opposite expression patterns for PcmiR397 and PcLAC target genes were observed in pear in response to pathogens. Transient transformation in pear demonstrated that silencing PcmiR397 and overexpressing a single PcLAC enhanced resistance to pathogens via lignin synthesis. To further reveal the mechanism underpinning the PcMIR397 response of pear to pathogens, the PcMIR397 promoter was analysed, and pMIR397-1039 was found to be inhibited by pathogen infection. The transcription factor PcMYB44 was up-regulated, and it bound to the PcMIR397 promoter and inhibited transcription following pathogen infection. The results demonstrate the role of PcmiR397-PcLACs in broad-spectrum resistance to fungal disease, and the potential role of PcMYB44 involved in the miR397-PcLAC module in regulating defence-induced lignification. The findings provide valuable candidate gene resources and guidance for molecular breeding to improve resistance to fungal disease in pear.

A compounds annotation strategy using targeted molecular networking for offline two-dimensional liquid chromatography-mass spectrometry analysis: Yupingfeng as a case study.

Component overlapping and long-time consumption hinder the data processing of offline two-dimensional liquid chromatography mass spectrometry (offline 2D-LC MS) system. Although molecular networking has been commonly employed in data processing of liquid chromatography mass spectrometry (LC-MS), its application in offline 2D-LC MS is challenged by voluminous and redundant data. In light of this, for the first time, a data deduplication and visualization strategy combining hand-in-hand alignment with targeted molecular networking (TMN) for compounds annotation of offline 2D-LC MS data was developed and applied to the chemical profile of Yupingfeng (YPF), a classical traditional Chinese medicine (TCM) prescription, as a case study. Firstly, an offline 2D-LC MS system was constructed for the separation and data acquisition of YPF extract. Then the data of 12 fractions derived from YPF were deconvoluted and aligned as a whole data file by hand-in-hand alignment, resulting in a 49.2% reduction in component overlapping (from 17951 to 9112 ions) and an improvement in the MS2 spectrum quality of precursor ions. Subsequently, the MS2-similarity adjacency matrix of focused parent ions was computed by a self-building Python script, which realized the construction of an innovative TMN. Interestingly, the TMN was found to be able to efficiently distinguish and visualize the co-elution, in-source fragmentations and multi-type adduct ions in a clustering network. Consequently, a total of 497 compounds were successfully identified depending on only seven TMN analysis guided by product ions filtering (PIF) and neutral loss filtering (NLF) for the targeted compounds in YPF. This integrated strategy improved the efficiency of targeted compound discovery in offline 2D-LC MS data, also shown a huge scalability in accurate compound annotation of complex samples. In conclusion, our study developed available concepts and tools while providing a research paradigm for efficient and rapid compound annotation in complex samples such as TCM prescriptions, with YPF as an example.

Catalytic mechanism of N-containing biochar on volatile-biochar interaction for the same origin pyrolysis.

Nitrogen, as a common element, is widely present in biomass. The effects of nitrogenous substances on the same origin pyrolysis of biomass and the consequences of N-containing biochar on the catalytic process of volatiles are important for further analyzing the pyrolysis mechanism of biomass. In this research, N-containing biochar was prepared under different conditions, and the interaction between N-containing biochar and biomass pyrolysis volatiles at 400-700 °C was studied. The results show that N-containing biochar can simultaneously participate in reactions as adsorbents, catalysts, and reactants. Its catalytic effect is obviously different for various N configurations. Pyridinic N and pyrrolic N can promote the cracking of lignin into methoxy phenol compounds and promote the further cracking of 5-hydroxymethylfurfural. Graphitic N and oxidized N can promote the further decomposition of phenol and the conversion of D-xylose into small-molecule ketones. In addition, oxidized N can also inhibit the cracking of lignin to produce guaiacol. In the long-term interaction, the highly active pyridinic N tends to convert to a more stable graphitic N.

Acousto-dielectric tweezers for size-insensitive manipulation and biophysical characterization of single cells.

The intrinsic biophysical properties of cells, such as mechanical, acoustic, and electrical properties, are valuable indicators of a cell's function and state. However, traditional single-cell biophysical characterization methods are hindered by limited measurable properties, time-consuming procedures, and complex system setups. This study presents acousto-dielectric tweezers that leverage the balance between controllable acoustophoretic and dielectrophoretic forces applied on cells through surface acoustic waves and alternating current electric fields, respectively. Particularly, the balanced acoustophoretic and dielectrophoretic forces can trap cells at equilibrium positions independent of the cell size to differentiate between various cell-intrinsic mechanical, acoustic, and electrical properties. Experimental results show our mechanism has the potential for applications in single-cell analysis, size-insensitive cell separation, and cell phenotyping, which are all primarily based on cells' intrinsic biophysical properties. Our results also show the measured equilibrium position of a cell can inversely determine multiple biophysical properties, including membrane capacitance, cytoplasm conductivity, and acoustic contrast factor. With these features, our acousto-dielectric tweezing mechanism is a valuable addition to the resources available for biophysical property-based biological and medical research.

Colorectal cancer: Metabolic interactions reshape the tumor microenvironment.

Colorectal cancer (CRC) is one of the most common cancers worldwide, which ranks third in terms of incidence and the second leading cause of cancer-related mortality. Metabolic reprogramming within the tumor microenvironment (TME) has been proved intimately involved in the initiation and malignant progression of CRC. Signal messengers, including cytokines, metabolites, and exosomes among others, derived from cancer cells can be utilized by the surrounding cells within the TME to induce metabolic alteration and cancer-associated transformation. In turn, the cargos secreted from cancer-associate cells further provide the nutrition and energy supply for cancer cells, supporting their metabolic reprogramming to promote proliferation, migration, metastasis, and radiochemoresistance. In this review, we focus on the main cellular components in the TME: CAFs, TAMs, lymphocytes and neutrophils, and enumerate and integrate how the metabolic interactions between these components and cancer cells reshape TME to foster CRC malignancy.

Preparation and formation mechanism of biomass-based graphite carbon catalyzed by iron nitrate under a low-temperature condition.

Graphite is a widely used industrial material, which experienced a marked shortage caused by the growing demand for electrode anode material and the increased costs for raw material. Graphitic carbon from biomass is a promising approach that will result in low-cost and efficient preparation. Herein, Fe(NO3)3 was selected as the catalyst for pine sawdust, and the effects of temperature and iron content on the graphitization of biochar were investigated. Additionally, the formation mechanism of the graphitic crystallite structure was explored. Results showed that the formation of pyrolysis gas increased with the increase in the amount of catalyst added or pyrolysis temperature. The change in pyrolysis gas, such as H2 and CO, was a critical auxiliary factor reflecting the conversion process. As temperature was increased from 600 °C to 800 °C, the solid products showed high graphitization and low solid yield. Graphite structure mainly formed at 700 °C because of the formation of Fe nanoparticles. The increase in the amount of catalyst could provide more reaction sites and promote the contact between Fe and C, showing that amorphous carbon is dissolved on Fe nanoparticles and precipitated into ordered graphitic carbon. On this basis, a mechanism of "carbon dissolution-precipitation" was proposed to explain the formation of graphite structure, and the whole pyrolysis process included the transformation of the iron element were analyzed.

Molecular characterization of a new fusarivirus infecting Botryosphaeria dothidea, the causal agent of pear ring rot disease.

Here, a novel mycovirus, tentatively designated as "Botryosphaeria dothidea fusarivirus 2" (BdFV2), was discovered in Botryosphaeria dothidea strain JZ-3. The complete genome sequence is 6,271 nucleotides (nt) in length, excluding the poly(A) tail, and contains two putative open reading frames (ORFs). The larger ORF1 encodes a polypeptide of 1,552 amino acids (aa) with conserved RNA-dependent RNA polymerase (RdRp) domains and a viral helicase domain. The ORF1-encoded polypeptide shares 19.47-78.70% sequence identity with those of other fusariviruses and shares the highest sequence identity (78.70%) with the corresponding protein aa sequences of Neofusicoccum luteum fusarivirus 1 (NlFV1) isolate CBS110299. The small ORF2 encodes a hypothetical protein with 479 aa, which is predicted to contain a chromosome segregation protein SMC domain of unknown function. Sequence alignments and phylogenetic analysis indicated that BdFV2 is a distinct member of the recently established family Fusariviridae. BdFV2 appears to be a novel fusarivirus infecting a pathogenic B. dothidea strain that causes pear ring rot disease.

A Knowledge Graph Entity Disambiguation Method Based on Entity-Relationship Embedding and Graph Structure Embedding.

The purpose of knowledge graph entity disambiguation is to match the ambiguous entities to the corresponding entities in the knowledge graph. Current entity ambiguity elimination methods usually use the context information of the entity and its attributes to obtain the mention embedding vector, compare it with the candidate entity embedding vector for similarity, and perform entity matching through the similarity. The disadvantage of this type of method is that it ignores the structural characteristics of the knowledge graph where the entity is located, that is, the connection between the entity and the entity, and therefore cannot obtain the global semantic features of the entity. To improve the Precision and Recall of entity disambiguation problems, we propose the EDEGE (Entity Disambiguation based on Entity and Graph Embedding) method, which utilizes the semantic embedding vector of entity relationship and the embedding vector of subgraph structure feature. EDEGE first trains the semantic vector of the entity relationship, then trains the graph structure vector of the subgraph where the entity is located, and balances the weights of these two vectors through the entity similarity function. Finally, the balanced vector is input into the graph neural network, and the matching between the entities is output to achieve entity disambiguation. Extensive experimental results proved the effectiveness of the proposed method. Among them, on the ACE2004 data set, the Precision, Recall, and F1 values of EDEGE are 9.2%, 7%, and 11.2% higher than baseline methods.

A five-dimensional data collection strategy for multicomponent discovery and characterization in Traditional Chinese Medicine: Gastrodia Rhizoma as a case study.

Establishing the identity of bioactive compounds to control the quality of Traditional Chinese Medicines is made more challenging by the complexity of the metabolite matrix, the existence of isomers, and the range of compound concentration and polarity observed between individual samples of the same plant in a multicomponent preparation. In addition, LC-MS analysis has limited capability for the separation and analysis of potentially important trace compounds and isomers, which hinders the comprehensive metabolite characterization of functional foods and Traditional Natural Medicine. To facilitate and improve the chemical composition characterization and enhance metabolite discernment, a comprehensive strategy was developed which integrates ion mobility mass spectrometry (IMS) with offline two-dimensional liquid chromatography based on hydrophilic interaction chromatography (HILIC) and conventional reversed phase (RP) C18 chromatography. Through application of the HILIC × RP offline 2D-LC approach, trace compounds were enriched and separated promoting a more efficient and detailed analysis of the matrix complexity. Comprehensive non-targeted multidimensional data (Rt1D, Rt2D, MS, CCS and MS/MS) and data-independent-acquisition (DIA) mass data of the metabolites in complex food and drug samples were obtained in the IMS-DIA-MS/MS mode on a Waters-SYNAPT G2-Si mass spectrometer with an ESI source. Through the application of high-efficiency neutral loss (NLs) and diagnostic product ions (DPIs) filter strategies, information from DIA mass data permitted the rapid detection and identification of compounds. The identification coverage of metabolites with low-quality MS/MS data was also improved. In the absence of analytical standards, Collision Cross Section (CCS) prediction and matching strategies based on theoretical chemical structures provided a method to distingish isomers. To demonstrate the efficacy of the technique this comprehensive strategy was applied to the compound characterization of Gastrodia Rhizoma (GR). Characterization of 272 compounds was achieved, including 146 unreported compounds. The results affirm that this comprehensive five-dimensional data collection strategy has the capacity to support the in-depth study of the high level of chemical diversity in Traditional Chinese Medicines.

Transcriptome-wide and expression analysis of the NAC gene family in pepino (Solanum muricatum) during drought stress.

Solanum muricatum (Pepino) is an increasingly popular solanaceous crop and is tolerant of drought conditions. In this study, 71 NAC transcription factor family genes of S. muricatum were selected to provide a theoretical basis for subsequent in-depth study of their regulatory roles in the response to biological and abiotic stresses, and were subjected to whole-genome analysis. The NAC sequences obtained by transcriptome sequencing were subjected to bioinformatics prediction and analysis. Three concentration gradient drought stresses were applied to the plants, and the target gene sequences were analyzed by qPCR to determine their expression under drought stress. The results showed that the S. muricatum NAC family contains 71 genes, 47 of which have conserved domains. The protein sequence length, molecular weight, hydrophilicity, aliphatic index and isoelectric point of these transcription factors were predicted and analyzed. Phylogenetic analysis showed that the S. muricatum NAC gene family is divided into seven subfamilies. Some NAC genes of S. muricatum are closely related to the NAC genes of Solanaceae crops such as tomato, pepper and potato. The seedlings of S. muricatum were grown under different gradients of drought stress conditions and qPCR was used to analyze the NAC expression in roots, stems, leaves and flowers. The results showed that 13 genes did not respond to drought stress while 58 NAC genes of S. muricatum that responded to drought stress had obvious tissue expression specificity. The overall expression levels in the root were found to be high. The number of genes at extremely significant expression levels was very large, with significant polarization. Seven NAC genes with significant responses were selected to analyze their expression trend in the different drought stress gradients. It was found that genes with the same expression trend also had the same or part of the same conserved domain. Seven SmNACs that may play an important role in drought stress were selected for NAC amino acid sequence alignment of Solanaceae crops. Four had strong similarity to other Solanaceae NAC amino acid sequences, and SmNAC has high homology with the Solanum pennellii. The NAC transcription factor family genes of S. muricatum showed strong structural conservation. Under drought stress, the expression of NAC transcription factor family genes of S. muricatum changed significantly, which actively responded to and participated in the regulation process of drought stress, thereby laying foundations for subsequent in-depth research of the specific functions of NAC transcription factor family genes of S. muricatum.

Acoustohydrodynamic tweezers via spatial arrangement of streaming vortices.

Acoustics-based tweezers provide a unique toolset for contactless, label-free, and precise manipulation of bioparticles and bioanalytes. Most acoustic tweezers rely on acoustic radiation forces; however, the accompanying acoustic streaming often generates unpredictable effects due to its nonlinear nature and high sensitivity to the three-dimensional boundary conditions. Here, we demonstrate acoustohydrodynamic tweezers, which generate stable, symmetric pairs of vortices to create hydrodynamic traps for object manipulation. These stable vortices enable predictable control of a flow field, which translates into controlled motion of droplets or particles on the operating surface. We built a programmable droplet-handling platform to demonstrate the basic functions of planar-omnidirectional droplet transport, merging droplets, and in situ mixing via a sequential cascade of biochemical reactions. Our acoustohydrodynamic tweezers enables improved control of acoustic streaming and demonstrates a previously unidentified method for contact-free manipulation of bioanalytes and digitalized liquid handling based on a compact and scalable functional unit.

Correction: Acoustic tweezers based on circular, slanted-finger interdigital transducers for dynamic manipulation of micro-objects.

Correction for 'Acoustic tweezers based on circular, slanted-finger interdigital transducers for dynamic manipulation of micro-objects' by Putong Kang et al., Lab Chip, 2020, 20, 987-994, DOI: .