Review of Allelopathy in Green Tides: The Case of Ulva prolifera in the South Yellow Sea.

The proliferation of large green macroalgae in marine environments has led to the occurrence of green tides, particularly in the South Yellow Sea region of China, where Ulva prolifera has been identified as the primary species responsible for the world's largest green tide events. Allelopathy among plants is a critical factor influencing the dynamics of green tides. This review synthesizes previous research on allelopathic interactions within green tides, categorizing four extensively studied allelochemicals: fatty acids, aldehydes, phenols, and terpenes. The mechanisms by which these compounds regulate the physiological processes of green tide algae are examined in depth. Additionally, recent advancements in the rapid detection of allelochemicals are summarized, and their potential applications in monitoring green tide events are discussed. The integration of advanced monitoring technologies, such as satellite observation and environmental DNA (eDNA) analysis, with allelopathic substance detection is also explored. This combined approach addresses gaps in understanding the dynamic processes of green tide formation and provides a more comprehensive insight into the mechanisms driving these phenomena. The findings and new perspectives presented in this review aim to offer valuable insights and inspiration for researchers and policymakers.

Intravital observation of high-scattering and dense-labeling hepatic tissues using multi-photon fluorescence microscopy.

Achieving high-resolution and large-depth microscopic imaging in vivo under conditions characterized by high-scattering and dense-labeling, as commonly encountered in the liver, poses a formidable challenge. Here, through the optimization of multi-photon fluorescence excitation window, tailored to the unique optical properties of the liver, intravital microscopic imaging of hepatocytes and hepatic blood vessels with high spatial resolution was attained. It's worth noting that resolution degradation caused by tissue scattering of excitation light was mitigated by accounting for moderate tissue self-absorption. Leveraging high-quality multi-photon fluorescence microscopy, we discerned structural and functional alterations in hepatocytes during drug-induced acute liver failure. Furthermore, a reduction in indocyanine green metabolism rates associated with acute liver failure was observed using NIR-II fluorescence macroscopic imaging.

Brain Image Segmentation for Ultrascale Neuron Reconstruction via an Adaptive Dual-Task Learning Network.

Accurate morphological reconstruction of neurons in whole brain images is critical for brain science research. However, due to the wide range of whole brain imaging, uneven staining, and optical system fluctuations, there are significant differences in image properties between different regions of the ultrascale brain image, such as dramatically varying voxel intensities and inhomogeneous distribution of background noise, posing an enormous challenge to neuron reconstruction from whole brain images. In this paper, we propose an adaptive dual-task learning network (ADTL-Net) to quickly and accurately extract neuronal structures from ultrascale brain images. Specifically, this framework includes an External Features Classifier (EFC) and a Parameter Adaptive Segmentation Decoder (PASD), which share the same Multi-Scale Feature Encoder (MSFE). MSFE introduces an attention module named Channel Space Fusion Module (CSFM) to extract structure and intensity distribution features of neurons at different scales for addressing the problem of anisotropy in 3D space. Then, EFC is designed to classify these feature maps based on external features, such as foreground intensity distributions and image smoothness, and select specific PASD parameters to decode them of different classes to obtain accurate segmentation results. PASD contains multiple sets of parameters trained by different representative complex signal-to-noise distribution image blocks to handle various images more robustly. Experimental results prove that compared with other advanced segmentation methods for neuron reconstruction, the proposed method achieves state-of-the-art results in the task of neuron reconstruction from ultrascale brain images, with an improvement of about 49% in speed and 12% in F1 score.

Nanoscale Metal Particle Modified Single-Atom Catalyst: Synthesis, Characterization, and Application.

Single-atom catalysts (SACs) have attracted considerable attention in heterogeneous catalysis because of their well-defined active sites, maximum atomic utilization efficiency, and unique unsaturated coordinated structures. However, their effectiveness is limited to reactions requiring active sites containing multiple metal atoms. Furthermore, the loading amounts of single-atom sites must be restricted to prevent aggregation, which can adversely affect the catalytic performance despite the high activity of the individual atoms. The introduction of nanoscale metal particles (NMPs) into SACs (NMP-SACs) has proven to be an efficient approach for improving their catalytic performance. A comprehensive review is urgently needed to systematically introduce the synthesis, characterization, and application of NMP-SACs and the mechanisms behind their superior catalytic performance. This review first presents and classifies the different mechanisms through which NMPs enhance the performance of SACs. It then summarizes the currently reported synthetic strategies and state-of-the-art characterization techniques of NMP-SACs. Moreover, their application in electro/thermo/photocatalysis, and the reasons for their superior performance are discussed. Finally, the challenges and perspectives of NMP-SACs for the future design of advanced catalysts are addressed.

Deep learning in mesoscale brain image analysis: A review.

Mesoscale microscopy images of the brain contain a wealth of information which can help us understand the working mechanisms of the brain. However, it is a challenging task to process and analyze these data because of the large size of the images, their high noise levels, the complex morphology of the brain from the cellular to the regional and anatomical levels, the inhomogeneous distribution of fluorescent labels in the cells and tissues, and imaging artifacts. Due to their impressive ability to extract relevant information from images, deep learning algorithms are widely applied to microscopy images of the brain to address these challenges and they perform superiorly in a wide range of microscopy image processing and analysis tasks. This article reviews the applications of deep learning algorithms in brain mesoscale microscopy image processing and analysis, including image synthesis, image segmentation, object detection, and neuron reconstruction and analysis. We also discuss the difficulties of each task and possible directions for further research.

Digital light processing 3D printing for microfluidic chips with enhanced resolution via dosing- and zoning-controlled vat photopolymerization.

Conventional manufacturing techniques to fabricate microfluidic chips, such as soft lithography and hot embossing process, have limitations that include difficulty in preparing multiple-layered structures, cost- and labor-consuming fabrication process, and low productivity. Digital light processing (DLP) technology has recently emerged as a cost-efficient microfabrication approach for the 3D printing of microfluidic chips; however, the fabrication resolution for microchannels is still limited to sub-100 microns at best. Here, we developed an innovative DLP printing strategy for high resolution and scalable microchannel fabrication by dosing- and zoning-controlled vat photopolymerization (DZC-VPP). Specifically, we proposed a modified mathematical model to precisely predict the accumulated UV irradiance for resin photopolymerization, thereby providing guidance for the fabrication of microchannels with enhanced resolution. By fine-tuning the printing parameters, including optical irradiance, exposure time, projection region, and step distance, we can precisely tailor the penetration irradiance stemming from the photopolymerization of the neighboring resin layers, thereby preventing channel blockage due to UV overexposure or compromised bonding stability owing to insufficient resin curing. Remarkably, this strategy can allow the preparation of microchannels with cross-sectional dimensions of 20 µm × 20 µm using a commercial printer with a pixel size of 10 µm × 10 µm; this is significantly higher resolution than previous reports. In addition, this method can enable the scalable and biocompatible fabrication of microfluidic drop-maker units that can be used for cell encapsulation. In general, the current DZC-VPP method can enable major advances in precise and scalable microchannel fabrication and represents a significant step forward for widespread applications of microfluidics-based techniques in biomedical fields.

Encoding and Multiplexing Information Signals in Magnetic Multilayers with Fractional Skyrmion Tubes.

Tailored magnetic multilayers (MMLs) provide skyrmions with enhanced thermal stability, leading to the possibility of skyrmion-based devices for room-temperature applications. At the same time, the search for additional stable topological spin textures has been under intense research focus. Besides their fundamental importance, such textures may expand the information encoding capability of spintronic devices. However, fractional spin texture states within MMLs in the vertical dimension are yet to be investigated. In this work, we demonstrate numerically fractional skyrmion tubes (FSTs) in a tailored MML system. We subsequently propose to encode sequences of information signals with FSTs as information bits in a tailored MML device. Micromagnetic simulations and theoretical calculations are used to verify the feasibility of hosting distinct FST states within a single device, and their thermal stability is investigated. A multilayer multiplexing device is proposed, where multiple sequences of the information signals can be encoded and transmitted based on the nucleation and propagation of packets of FSTs. Finally, pipelined information transmission and automatic demultiplexing are demonstrated by exploiting the skyrmion Hall effect and introducing voltage-controlled synchronizers and width-based track selectors. The findings indicate that FSTs can be potential candidates as information carriers for future spintronic applications.

DiamondNet: A Neural-Network-Based Heterogeneous Sensor Attentive Fusion for Human Activity Recognition.

With the proliferation of intelligent sensors integrated into mobile devices, fine-grained human activity recognition (HAR) based on lightweight sensors has emerged as a useful tool for personalized applications. Although shallow and deep learning algorithms have been proposed for HAR problems in the past decades, these methods have limited capability to exploit semantic features from multiple sensor types. To address this limitation, we propose a novel HAR framework, DiamondNet, which can create heterogeneous multisensor modalities, denoise, extract, and fuse features from a fresh perspective. In DiamondNet, we leverage multiple 1-D convolutional denoising autoencoders (1-D-CDAEs) to extract robust encoder features. We further introduce an attention-based graph convolutional network to construct new heterogeneous multisensor modalities, which adaptively exploit the potential relationship between different sensors. Moreover, the proposed attentive fusion subnet, which jointly employs a global-attention mechanism and shallow features, effectively calibrates different-level features of multiple sensor modalities. This approach amplifies informative features and provides a comprehensive and robust perception for HAR. The efficacy of the DiamondNet framework is validated on three public datasets. The experimental results demonstrate that our proposed DiamondNet outperforms other state-of-the-art baselines, achieving remarkable and consistent accuracy improvements. Overall, our work introduces a new perspective on HAR, leveraging the power of multiple sensor modalities and attention mechanisms to significantly improve the performance.

Enhancing Total Optical Throughput of Microscopy with Deep Learning for Intravital Observation.

The significance of performing large-depth dynamic microscopic imaging in vivo for life science research cannot be overstated. However, the optical throughput of the microscope limits the available information per unit of time, i.e., it is difficult to obtain both high spatial and temporal resolution at once. Here, a method is proposed to construct a kind of intravital microscopy with high optical throughput, by making near-infrared-II (NIR-II, 900-1880 nm) wide-field fluorescence microscopy learn from two-photon fluorescence microscopy based on a scale-recurrent network. Using this upgraded NIR-II fluorescence microscope, vessels in the opaque brain of a rodent are reconstructed three-dimensionally. Five-fold axial and thirteen-fold lateral resolution improvements are achieved without sacrificing temporal resolution and light utilization. Also, tiny cerebral vessel dilatations in early acute respiratory failure mice are observed, with this high optical throughput NIR-II microscope at an imaging speed of 30 fps.

TCF7L2 acts as a molecular switch in midbrain to control mammal vocalization through its DNA binding domain but not transcription activation domain.

Vocalization is an essential medium for social signaling in birds and mammals. Periaqueductal gray (PAG) a conserved midbrain structure is believed to be responsible for innate vocalizations, but its molecular regulation remains largely unknown. Here, through a mouse forward genetic screening we identified one of the key Wnt/ß-catenin effectors TCF7L2/TCF4 controls ultrasonic vocalization (USV) production and syllable complexity during maternal deprivation and sexual encounter. Early developmental expression of TCF7L2 in PAG excitatory neurons is necessary for the complex trait, while TCF7L2 loss reduces neuronal gene expressions and synaptic transmission in PAG. TCF7L2-mediated vocal control is independent of its ß-catenin-binding domain but dependent of its DNA binding ability. Patient mutations associated with developmental disorders, including autism spectrum disorders, disrupt the transcriptional repression effect of TCF7L2, while mice carrying those mutations display severe USV impairments. Therefore, we conclude that TCF7L2 orchestrates gene expression in midbrain to control vocal production through its DNA binding but not transcription activation domain.

Voltage-Controlled Skyrmionic Interconnect with Multiple Magnetic Information Carriers.

Magnetic skyrmions have been in the spotlight since they were observed in technologically relevant systems at room temperature. More recently, there has been increasing interest in additional quasiparticles that may exist as stable/metastable spin textures in magnets, such as the skyrmionium and the antiskyrmionite (i.e., a skyrmion bag with two skyrmions inside) that have distinct topological characteristics. The next challenge and opportunity, at the same time, is to investigate the use of multiple magnetic quasiparticles as information carriers in a single device for next-generation nanocomputing. In this paper, we propose a spintronic interconnect device where multiple sequences of information signals are encoded and transmitted simultaneously by skyrmions, skyrmioniums, and antiskyrmionites. The proposed spintronic interconnect device can be pipelined via voltage-controlled magnetic anisotropy (VCMA) gated synchronizers that behave as intermediate registers. We demonstrate theoretically that the interconnect throughput and transmission energy can be effectively tuned by the VCMA gate voltage and appropriate electric current pulses. By carefully adjusting the device structure characteristics, our spintronic interconnect device exhibits comparable energy efficiency with copper interconnects in mainstream CMOS technologies. This study provides fresh insight into the possibilities of skyrmionic devices in future spintronic applications.

Multifunctional Hard Yet Flexible Coatings Fabricated Using a Universal Step-by-Step Strategy.

Hard yet flexible coatings with multi-functionalities are useful for foldable displays and marine industries but rare. In this study, a highly cross-linked multifunctional hybrid coating with ceramic-like hardness and polymer-like flexibility is reported. The coating is prepared via a step-by-step strategy, where two types of epoxy-oligosiloxane nanoclusters are first synthesized by sol-gel chemistry, and amine-terminated curing agents are used to cross-link them at room temperature. The coating is highly transparent (>92% transmittance), hard (6-7H), and flexible (10 mm bending diameter) because of the unique combination of siloxane nanoclusters and polymer networks. Meanwhile, since the coating contains fouling-resistant telomer and low-surface-tension liquid lubricant polydimethylsiloxane (PDMS), it exhibits excellent anti-biofouling and self-cleaning properties. The results indicate that the mechanical and antifouling properties of the coating can be easily tuned and prove that the step-by-step strategy is a promising and universal method. The novel coatings can meet the needs of applications in foldable displays, marine industries, and other fields.

Circulating tumor DNA predicts the outcome of chemotherapy in patients with lung cancer.

BACKGROUND: Circulating tumor DNA (ctDNA) has potential as a specific, noninvasive, and cost-effective new biomarker for patients with lung cancer. This study aimed to determine whether plasma ctDNA can be used to predict treatment outcomes in patients with lung cancer. METHODS: Pre- and in-treatment blood samples were collected from 14 patients with lung cancer receiving chemotherapy. Based on next-generation sequencing technology, we constructed a unique molecular identifier (UMI) library and performed targeted deep sequencing of 72 genes (15 000×). We used dVAF to evaluate the change level and trend of variant allele frequency (VAF). RESULTS: We identified MUC16, KMT2D, AMER1, and NTRK1 as the most-frequently mutated genes in ctDNA associated with lung cancer. Furthermore, we showed that the change trend of dVAF in patients with lung cancer undergoing chemotherapy was closely related to the changes in both tumor volume and tumor biomarkers, including CEA, CA125, NSE, and CK (Cytokeratin). Moreover, the ctDNA analysis revealed disease progression of SCLC patients earlier than did computed tomography. CONCLUSIONS: The dynamic detection of plasma ctDNA VAF has the potential value as a biomarker for evaluating the efficacy of chemotherapy in patients with SCLC and advanced NSCLC, and may predict the progression of lung cancer patients earlier than radiography.

[Effects of different storage conditions on edible quality and antioxidant activity of Polygonatum cyrtonema flowers].

The flower of Polygonatum cyrtonema has good edible and medicinal values. In this study, four samples of P. cyrtonema flowers from different regions were selected as test materials. The contents, composition and antioxidant activities of lipid-soluble pigments and alcohol-soluble components were determined under different light and temperature conditions, which help to reveal the discoloration reason and the composition variation patterns during storage. The results showed that light and temperature had different effects on the lipid-soluble pigments and alcohol-soluble components in the dried flowers during storage. After storage for 4 weeks, the contents of total chlorophyll, carotenoids, phenols and saponins in the samples exposed to light respectively decreased by 62.62%, 66.4%, 68.7% and 43.4% compared with those in the dark. The decreases in the contents of chlorophyll a, chlorophyll b, lutein, ß-carotene and zeaxanthin were 64.64%, 56.74%, 59.2%, 77.7% and 45.4%, respectively. The contents of pigments and components in the samples stored at-20 ℃ were significantly higher than those at room temperature and 4 ℃, indicating that low temperature was conductive to the stability of lipid-soluble pigments and alcohol-soluble components. The samples stored at low temperature and in the dark had the strongest free radical scavenging activity. The results suggest that P. cyrtonema dried flowers should be stored in low temperature environment without light, which can slow down the degradation of internal components. The study provides a theoretical basis for the production, processing and storage of P. cyrtonema flowers.

Cellular and Molecular Mechanisms of Pristimerin in Cancer Therapy: Recent Advances.

Seeking an efficient and safe approach to eliminate tumors is a common goal of medical fields. Over these years, traditional Chinese medicine has attracted growing attention in cancer treatment due to its long history. Pristimerin is a naturally occurring quinone methide triterpenoid used in traditional Chinese medicine to treat various cancers. Recent studies have identified alterations in cellular events and molecular signaling targets of cancer cells under pristimerin treatment. Pristimerin induces cell cycle arrest, apoptosis, and autophagy to exhibit anti-proliferation effects against tumors. Pristimerin also inhibits the invasion, migration, and metastasis of tumor cells via affecting cell adhesion, cytoskeleton, epithelial-mesenchymal transition, cancer stem cells, and angiogenesis. Molecular factors and pathways are associated with the anti-cancer activities of pristimerin. Furthermore, pristimerin reverses multidrug resistance of cancer cells and exerts synergizing effects with other chemotherapeutic drugs. This review aims to discuss the anti-cancer potentials of pristimerin, emphasizing multi-targeted biological and molecular regulations in cancers. Further investigations and clinical trials are warranted to understand the advantages and disadvantages of pristimerin treatment much better.

Organic Dots with Large π-Conjugated Planar for Cholangiography beyond 1500 nm in Rabbits: A Non-Radioactive Strategy.

Iatrogenic extrahepatic bile duct injury remains a dreaded complication while performing cholecystectomy. Although X-ray based cholangiography could reduce the incidence of biliary tract injuries, the deficiencies including radiation damage and expertise dependence hamper its further clinical application. The effective strategy for intraoperative cholangiography is still urgently required. Herein, a fluorescence-based imaging approach for cholangiography in the near-infrared IIb window (1500-1700 nm) using TT3-oCB, a bright aggregation-induced emission luminogen with large π-conjugated planar unit, is reported. In phantom studies, TT3-oCB nanoparticles exhibit high near-infrared IIb emission and show better image clarity at varying penetrating depths. When intrabiliary injected into the gallbladder or the common bile duct of the rabbit, TT3-oCB nanoparticles enable the real-time imaging of the biliary structure with deep penetrating capability and high signal-to-background ratio. Moreover, the tiny iatrogenic biliary injuries and the gallstones in established disease models could be precisely diagnosed by TT3-oCB nanoparticle assisted near-infrared IIb imaging. In summary, we reported a feasible application for aggregation-induced emission dots as biliary contrast agent and realized high-quality cholangiography in the near-infrared IIb window with precise diagnostic ability and nonradioactive damage, which could possibly be applied for intraoperative diagnosis.

Er3+ self-sensitized nanoprobes with enhanced 1525 nm downshifting emission for NIR-IIb in vivo bio-imaging.

Traditional sensitizer (Yb3+ or Nd3+) and activator (Er3+) co-doped lanthanide-based nanoprobes possessing emission of Er3+ at 1525 nm have attracted much attention in NIR-IIb bio-imaging. However, the 1525 nm fluorescence efficiency was not high enough in such co-doped systems due to the serious back energy transfer from the activator to the sensitizer, resulting in a lot of excitation energy loss. Herein, we have designed an efficient NIR-IIb nanoprobe Er3+ self-sensitized NaErF4:0.5%Tm3+@NaLuF4, where substantially all the excitation energy could contribute to Er3+ ions and most energy transfer processes were confined among Er3+ ions, avoiding the energy dissipation by heterogeneous sensitizer ions. The influence of the types of epitaxial heterogeneous shells, the doping effect and optimal doping concentration of Tm3+ ions, as well as the critical shell thickness for obtaining the surface quenching-assisted downshifting emission are systematically investigated to acquire the most efficient 1525 nm luminescence under 800 nm excitation. The quantum yield in the 1500-1700 nm region reached 13.92%, enabling high-resolution through-skull cerebrovascular microscopy imaging and large-depth in vivo physiological dynamic imaging with an extremely low excitation powder density of 35 mW cm-2. The designed nanoprobe can be potentially used for brain science research and clinical diagnosis.