Genome-wide identification analysis of the 4-Coumarate: CoA ligase (4CL) gene family expression profiles in Juglans regia and its wild relatives J. Mandshurica resistance and salt stress.

Persian walnut (Juglans regia) and Manchurian walnut (Juglans mandshurica) belong to Juglandaceae, which are vulnerable, temperate deciduous perennial trees with high economical, ecological, and industrial values. 4-Coumarate: CoA ligase (4CL) plays an essential function in plant development, growth, and stress. Walnut production is challenged by diverse stresses, such as salinity, drought, and diseases. However, the characteristics and expression levels of 4CL gene family in Juglans species resistance and under salt stress are unknown. Here, we identified 36 Jr4CL genes and 31 Jm4CL genes, respectively. Based on phylogenetic relationship analysis, all 4CL genes were divided into three branches. WGD was the major duplication mode for 4CLs in two Juglans species. The phylogenic and collinearity analyses showed that the 4CLs were relatively conserved during evolution, but the gene structures varied widely. 4CLs promoter region contained multiply cis-acting elements related to phytohormones and stress responses. We found that Jr4CLs may be participated in the regulation of resistance to anthracnose. The expression level and some physiological of 4CLs were changed significantly after salt treatment. According to qRT-PCR results, positive regulation was found to be the main mode of regulation of 4CL genes after salt stress. Overall, J. mandshurica outperformed J. regia. Therefore, J. mandshurica can be used as a walnut rootstock to improve salt tolerance. Our results provide new understanding the potential functions of 4CL genes in stress tolerance, offer the theoretical genetic basis of walnut varieties adapted to salt stress, and provide an important reference for breeding cultivated walnuts for stress tolerance.

One-step strategy for efficient Cr(VI) removal via phytate modified zero-valent iron: Accelerated electron transfer and enhanced coordination effect.

The toxic Cr(VI) from industrial wastewater pose serious threat to the human beings and eco-systems. To reduce the operation processes and enhance the removal efficiency of Cr(VI), targeted design of functionalized material is critical in practical applications. Herein, we developed a one-step strategy for simultaneous Cr(VI) reduction and total Cr capture by a novel phytate modified zero-valent iron (PA-ZVI). The reaction kinetics of Cr(VI) removal by PA-ZVI (0.2225 min-1) was 53 times higher compared to ZVI (0.0042 min-1). The Fe(0) content on the surface of PA-ZVI increased from 2.2% to 15.6% compared to ZVI. Meanwhile, Cr(VI) was liable to adsorb on the surface of PA-ZVI due to its lower adsorption energy compared with the original ZVI (-2.09 eV vs -0.85 eV). The incorporation of the phytate ligand promoted electron transfer from iron core to Cr(VI), leading to the rapid in-situ reduction of Cr(VI) adsorbed on the surface of PA-ZVI to Cr(III). PA-ZVI exhibited a satisfactory performance for Cr(VI) removal at a broad pH range (3-11) and in the presence of coexisting ions and humic acid. Moreover, the reactor with the addition of PA-ZVI achieved more than 90% Cr(VI) removal within 72 h in continuous flow experiments. The feasibility of PA-ZVI for the removal of Cr(VI) is also validated in authentic wastewater. This work provides novel ZVI materials that can effectively address decontamination challenges from Cr(VI) pollution.

Operator learning for urban water clarification hydrodynamics and particulate matter transport with physics-informed neural networks.

Computational fluid dynamics (CFD) can be a powerful tool for higher-fidelity water infrastructure planning and design. Despite decades of development and demonstration over a wide range of water systems such as clarification basins, activated sludge processes, ozone contactors, etc., CFD remains primarily used in academic research, with limited application in civil and environmental engineering practice. This limitation is contributed by its higher computational cost and demand for specialized user skills. This, however, need not be the case, if a robust and efficient surrogate model can be developed from CFD simulations and independently deployed for engineering purposes. Leveraging the emerging scientific machine learning (ML) techniques of physics-informed ML and operator learning, this study develops a composite neural network (CPNN) for learning the flow hydrodynamics and particulate matter (PM) transport and fate in clarification systems. The CPNN consists of a deep operator network (DeepONet) as an encoder and a physics-informed neural network (PINN) as a decoder. In contrast to common "black box" and lumped ML approaches, the developed CPNN directly incorporates physics principles into its architecture. Furthermore, the CPNN is designed for process-resolved and operator learning, enabling it to predict spatial hydrodynamics and PM concentration distribution (i.e., contours) across different basin geometrics and loading conditions. Compared to CFD simulation, the developed CPNN model has significantly higher computational efficiency (∼ milliseconds) while demonstrating robust predictive capability. For predicting basin hydrodynamics across 10,000 test cases, the trained CPNN model achieves an R2 above 0.8 for 66.4% of cases and an R2 above 0.4 for 89.2% of cases. A similar performance is also demonstrated by the CPNN in predicting basin PM concentration. Further investigation reveals that basin geometrics that trigger bi-modal flow solutions can be particularly challenging for ML. Additionally, this study visualizes the dependency of basin hydrodynamics and PM concentration on basin geometrics and loading conditions, providing valuable insights for optimizing basin configuration. Lastly, the potentials and benefits of web-based applications, e.g., DeepXtorm, as a user-friendly interface for the developed CPNN model is discussed. This study represents the initial step toward achieving real-time higher-fidelity water infrastructure planning, design, optimization, and regulation.

The role of PKP1 in tumor progression in melanoma: Analysis of a cell adhesion-related model.

The incidence rate of melanoma varies across regions, with Europe, the United States, and Australia having 10-25, 20-30, and 50-60 cases per 1 00 000 people. In China, patients with melanoma exhibit different clinical manifestations, pathogenesis, and outcomes. Current treatments include surgery, adjuvant therapy, and immune checkpoint inhibitors. Nonetheless, complications may arise during treatment. Melanoma development is heavily reliant on cell adhesion molecules (CAMs), and studying these molecules could provide new research directions for metastasis and progression. CAMs include the integrin, immunoglobulin, selectin, and cadherin families, and they affect multiple processes, such as maintenance, morphogenesis, and migration of adherens junction. In this study, a cell adhesion-related risk prognostic signature was constructed using bioinformatics methods, and survival analysis was performed. Plakophilin 1 (PKP1) was observed to be crucial to the immune microenvironment and has significant effects on melanoma cell proliferation, migration, invasion, and the cell cycle. This signature demonstrates high reliability and has potential for clinical applications.

Highly efficient adsorption of ciprofloxacin from aqueous solutions by waste cation exchange resin-based activated carbons: Performance, mechanism, and theoretical calculation.

This study focused on the preparation of a highly efficient activated carbon adsorbent from waste cation exchange resins through one-step carbonization to remove ciprofloxacin (CIP) from aqueous solutions. Scanning electron microscopy, X-ray diffraction, Fourier-transform infrared spectrometry, and X-ray photoelectron spectroscopy were used to characterize the physicochemical properties of the carbonized materials. The CIP removal efficiency, influencing factors, and adsorption mechanisms of CIP on the carbonized resins were investigated. Density functional theory (DFT) computations were performed to elucidate the adsorption mechanisms. The CIP removal reached 93 % when the adsorbent dosage was 300 mg/L at 25 °C. The adsorption capacity of the carbonized resins to CIP gradually decreased with an increasing pH from 3.0 to 7.0 and sharply declined with a pH from 7.0 to 11.0. The adsorption process better fitted by the pseudo second-order kinetic and Langmuir models, indicating that the interaction between CIP and the carbonized resins was monolayer adsorption. The maximum adsorption capacity fitted by the Langmuir model was 384.4 mg/g at 25 °C. Microstructural analysis showed that the adsorption of CIP on the carbonized resins was a joint effect of H-bonding, ion exchange, and graphite-N adsorption. Computational results signified the strong H-bonding and ion exchange interactions existed between CIP and carbonized resins. The high adsorption and reusability suggest that waste cation exchange resin-based activated carbons can be used as an effective and reusable adsorbent for removing CIP from aqueous solutions.

Machine Learning-Based Operational State Recognition and Compressive Property Prediction in Fused Filament Fabrication.

3D printing has exhibited significant potential in outer space and medical implants. To use this technology in the specific high-value scenarios, 3D-printed parts need to satisfy quality-related requirements. In this article, the influence of the filament feeder operating states of 3D printer on the compressive properties of 3D-printed parts is studied in the fused filament fabrication process. A machine learning approach, back-propagation neural network with a genetic algorithm (GA-BPNN) optimized by k-fold cross-validation, is proposed to monitor the operating states and predict the compressive properties. Vibration and current sensors are used in situ to monitor the operating states of the filament feeder, and a set of features are extracted and selected from raw sensor data in time and frequency domains. Results show that the operating states of the filament feeder significantly affected the compressive properties of the fabricated samples, the operating states were accurately recognized with 96.3% rate, and compressive properties were successfully predicted by the GA-BPNN. This proposed method has the potential for use in industrial applications after 3D printing without requiring any further quality control.

Decoding functional cell-cell communication events by multi-view graph learning on spatial transcriptomics.

Cell-cell communication events (CEs) are mediated by multiple ligand-receptor (LR) pairs. Usually only a particular subset of CEs directly works for a specific downstream response in a particular microenvironment. We name them as functional communication events (FCEs) of the target responses. Decoding FCE-target gene relations is: important for understanding the mechanisms of many biological processes, but has been intractable due to the mixing of multiple factors and the lack of direct observations. We developed a method HoloNet for decoding FCEs using spatial transcriptomic data by integrating LR pairs, cell-type spatial distribution and downstream gene expression into a deep learning model. We modeled CEs as a multi-view network, developed an attention-based graph learning method to train the model for generating target gene expression with the CE networks, and decoded the FCEs for specific downstream genes by interpreting trained models. We applied HoloNet on three Visium datasets of breast cancer and liver cancer. The results detangled the multiple factors of FCEs by revealing how LR signals and cell types affect specific biological processes, and specified FCE-induced effects in each single cell. We conducted simulation experiments and showed that HoloNet is more reliable on LR prioritization in comparison with existing methods. HoloNet is a powerful tool to illustrate cell-cell communication landscapes and reveal vital FCEs that shape cellular phenotypes. HoloNet is available as a Python package at https://github.com/lhc17/HoloNet.

[Recent Advances and Controversies in Minute Pulmonary Meningothelial-like Nodules].

Minute pulmonary meningothelial-like nodules (MPMNs) are benign small lesions in the lungs, with similar pathological characteristics to the meningeal epithelium. MPMNs have similar imaging manifestations to malignant tumors, which can lead to misdiagnosis in clinical practice. There is no consensus on the pathogenesis of MPMNs, with some suggest that MPMNs derive from reactive proliferation, while others suggest that MPMNs share a common origin and molecular mechanism with meningiomas in the central nervous system. Understanding the characteristics of MPMNs and studying their pathogenesis will help improve the understanding and diagnosis of MPMNs. In this article, we reviewed the clinical, pathological, imaging characteristics, differential diagnosis and pathogenesis of MPMNs. We also analyze the existing research advances regarding the pathogenesis and propose prospects for further research.
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Amphiregulin couples IL1RL1+ regulatory T cells and cancer-associated fibroblasts to impede antitumor immunity.

Regulatory T (Treg) cells and cancer-associated fibroblasts (CAFs) jointly promote tumor immune tolerance and tumorigenesis. The molecular apparatus that drives Treg cell and CAF coordination in the tumor microenvironment (TME) remains elusive. Interleukin 33 (IL-33) has been shown to enhance fibrosis and IL1RL1+ Treg cell accumulation during tumorigenesis and tissue repair. We demonstrated that IL1RL1 signaling in Treg cells greatly dampened the antitumor activity of both IL-33 and PD-1 blockade. Whole tumor single-cell RNA sequencing (scRNA-seq) analysis and blockade experiments revealed that the amphiregulin (AREG)-epidermal growth factor receptor (EGFR) axis mediated cross-talk between IL1RL1+ Treg cells and CAFs. We further demonstrated that the AREG/EGFR axis enables Treg cells to promote a profibrotic and immunosuppressive functional state of CAFs. Moreover, AREG mAbs and IL-33 concertedly inhibited tumor growth. Our study reveals a previously unidentified AREG/EGFR-mediated Treg/CAF coupling that controls the bifurcation of fibroblast functional states and is a critical barrier for cancer immunotherapy.

Topotactic fabrication of transition metal dichalcogenide superconducting nanocircuits.

Superconducting nanocircuits, which are usually fabricated from superconductor films, are the core of superconducting electronic devices. While emerging transition-metal dichalcogenide superconductors (TMDSCs) with exotic properties show promise for exploiting new superconducting mechanisms and applications, their environmental instability leads to a substantial challenge for the nondestructive preparation of TMDSC nanocircuits. Here, we report a universal strategy to fabricate TMDSC nanopatterns via a topotactic conversion method using prepatterned metals as precursors. Typically, robust NbSe2 meandering nanowires can be controllably manufactured on a wafer scale, by which a superconducting nanowire circuit is principally demonstrated toward potential single photon detection. Moreover, versatile superconducting nanocircuits, e.g., periodical circle/triangle hole arrays and spiral nanowires, can be prepared with selected TMD materials (NbS2, TiSe2, or MoTe2). This work provides a generic approach for fabricating nondestructive TMDSC nanocircuits with precise control, which paves the way for the application of TMDSCs in future electronics.

CRISPR/Cas9­mediated EZH2 knockout suppresses the proliferation and migration of triple­negative breast cancer cells.

Triple-negative breast cancer (TNBC) is an aggressive subtype of BC characterized by extensive intratumoral heterogeneity. Compared with other types of BC, TNBC is more prone to invasion and metastasis. The aim of the present study was to determine whether adenovirus-mediated clustered regulatory interspaced short palindromic repeats (CRISPR)/Cas9 system is capable of effectively targeting enhancer of zeste homolog 2 (EZH2) in TNBC cells and lay an experimental basis for the investigation of the CRISPR/Cas9 system as a gene therapy for BC. In the present study, EZH2 was knocked out in MDA-MB-231 cells using the CRISPR/Cas9 gene editing tool to create EZH2-knockout (KO) group (EZH2-KO group). Moreover, the GFP knockout group (control group), and a blank group (Blank group), were employed. The success of vector construction and EZH2-KO were verified by T7 endonuclease I (T7EI) restriction enzyme digestion, mRNA detection and western blotting. Changes in proliferation and migration ability of MDA-MB-231 cells following gene editing were detected by MTT, wound healing, Transwell and in vivo tumor biology assays. As indicated by the results of mRNA and protein detection, the mRNA and protein expression of EZH2 were significantly downregulated in the EZH2-KO group. The difference in EZH2 mRNA and protein between the EZH2-KO and the two control groups was statistically significant. MTT, wound healing and transwell assay suggested that the proliferation and migration ability of MDA-MB-231 cells in the EZH2-KO group were significantly decreased after EZH2 knockout. In vivo, the tumor growth rate in the EZH2-KO group was significantly lower than that in the control groups. In brief, the present study revealed that the biological functions of tumor cells were inhibited after EZH2 knockout in MDA-MB-231 cells. The aforementioned findings suggested that EZH2 can have a key role in the development of TNBC.

van der Waals Self-Epitaxial Growth of Inch-Sized Superconducting Niobium Diselenide Films.

Ultrathin superconducting films are the basis of superconductor devices. van der Waals (vdW) NbSe2 with noncentrosymmetry exhibits exotic superconductivity and shows promise in superconductor electronic devices. However, the growth of inch-scale NbSe2 films with layer regulation remains a challenge because vdW structural material growth is strongly dependent on the epitaxial guidance of the substrate. Herein, a vdW self-epitaxy strategy is developed to eliminate the substrate driving force in film growth and realize inch-sized NbSe2 film growth with thicknesses from 2.1 to 12.1 nm on arbitrary substrates. The superconducting transition temperature of 5.1 K and superconducting transition width of 0.30 K prove the top homogeneity and quality of superconductivity among all of the synthetic NbSe2 films. Coupled with a large area and substrate compatibility, this work paves the way for developing NbSe2 superconductor electronics.

Music with Different Tones Affects the Development of Brain Nerves in Mice in Early Life through BDNF and Its Downstream Pathways.

As a means of environmental enrichment, music environment has positive and beneficial effects on biological neural development. Kunming white mice (61 days old) were randomly divided into the control group (group C), the group of D-tone (group D), the group of A-tone (group A) and the group of G-tone (group G). They were given different tonal music stimulation (group A) for 14 consecutive days (2 h/day) to study the effects of tonal music on the neural development of the hippocampus and prefrontal cortex of mice in early life and its molecular mechanisms. The results showed that the number of neurons in the hippocampus and prefrontal cortex of mice increased, with the cell morphology relatively intact. In addition, the number of dendritic spines and the number of dendritic spines per unit length were significantly higher than those in group C, and the expressions of synaptic plasticity proteins (SYP and PSD95) were also significantly elevated over those in group C. Compared with group C, the expression levels of BDNF, TRKB, CREB, PI3K, AKT, GS3Kß, PLCγ1, PKC, DAG, ERK and MAPK genes and proteins in the hippocampus and prefrontal cortex of mice in the music groups were up-regulated, suggesting that different tones of music could regulate neural development through BDNF and its downstream pathways. The enrichment environment of D-tone music is the most suitable tone for promoting the development of brain nerves in early-life mice. Our study provides a basis for screening the optimal tone of neuroplasticity in early-life mice and for the treatment of neurobiology and neurodegenerative diseases.

One-Click-Based Perception for Interactive Image Segmentation.

Existing deep learning-based interactive image segmentation methods have significantly reduced the user's interaction burden with simple click interactions. However, they still require excessive numbers of clicks to continuously correct the segmentation for satisfactory results. This article explores how to harvest accurate segmentation of interested targets while minimizing the user interaction cost. To achieve the above goal, we propose a one-click-based interactive segmentation approach in this work. For this particularly challenging problem in the interactive segmentation task, we build a top-down framework dividing the original problem into a one-click-based coarse localization followed by a fine segmentation. A two-stage interactive object localization network is first designed, which aims to completely enclose the target of interest based on the supervision of object integrity (OI). Click centrality (CC) is also utilized to overcome the overlapping problem between objects. This coarse localization helps to reduce the search space and increase the focus of the click at a higher resolution. A principled multilayer segmentation network is then designed by a progressive layer-by-layer structure, which aims to accurately perceive the target with extremely limited prior guidance. A diffusion module is also designed to enhance the information flow between layers. Besides, the proposed model can be naturally extended to multiobject segmentation task. Our method achieves the state-of-the-art performance under one-click interaction on several benchmarks.

Acid-induced Poria cocos alkali-soluble polysaccharide hydrogel: Gelation behaviour, characteristics, and potential application in drug delivery.

Poria cocos alkali-soluble polysaccharide (PCAP), a water-insoluble ß-glucan, is the main component of the total dried sclerotia of Poria cocos. However, its gelation behaviour and properties have yet to be comprehensively studied. In this study, an acid-induced physical hydrogel based on natural PCAP is fabricated. The acid-induced gelation in PCAP is explored with respect to the pH and polysaccharide concentration. PCAP hydrogels are formed in the pH range of 0.3-10.5, and the lowest gelation concentration is 0.4 wt%. Furthermore, dynamic rheological, fluorescence, and cyclic voltammetry measurements are performed to elucidate the gelation mechanism. The results reveal that hydrogen bonds and hydrophobic interactions play a dominant role in gel formation. Subsequently, the properties of the PCAP hydrogels are investigated using rheological measurements, scanning electron microscopy, gravimetric analysis, free radical scavenging, MTT assays, and enzyme-linked immunosorbent assays. The PCAP hydrogels exhibit a porous network structure and cytocompatibility, in addition to good viscoelastic, thixotropic, water-holding, swelling, antioxidant, and anti-inflammatory activities. Furthermore, using rhein as a model drug for encapsulation, it is demonstrated that its cumulative release behaviour from the PCAP hydrogel is pH dependent. These results indicate the potential of PCAP hydrogels for application in biological medicine and drug delivery.

The Effect of the Microalgae Chlorella vulgaris on the Gut Microbiota of Juvenile Nile Tilapia (Oreochromis niloticus) Is Feeding-Time Dependent.

Chlorella vulgaris is one of the most commonly used microalgae in aquaculture feeds. It contains high concentrations of various kinds of nutritional elements that are involved in the physiological regulation of aquaculture animals. However, few studies have been conducted to illustrate their influence on the gut microbiota in fish. In this work, the gut microbiota of Nile tilapia (Oreochromis niloticus) (average weight is 6.64 g) was analyzed by high-throughput sequencing of the 16S rRNA gene after feeding with 0.5% and 2% C. vulgaris additives in diets for 15 and 30 days (average water temperature was 26 °C). We found that the impact of C. vulgaris on the gut microbiota of Nile tilapia was feeding-time dependent. Only by feeding for 30 days (not 15 days) did the addition of 2% C. vulgaris to diets significantly elevate the alpha diversity (Chao1, Faith pd, Shannon, Simpson, and the number of observed species) of the gut microbiota. Similarly, C. vulgaris exerted a significant effect on the beta diversity (Bray-Curtis similarity) of the gut microbiota after feeding for 30 days (not 15 days). During the 15-day feeding trial, LEfSe analysis showed that Paracoccus, Thiobacillus, Dechloromonas, and Desulfococcus were enriched under 2% C. vulgaris treatment. During the 30-day feeding trial, Afipia, Ochrobactrum, Polymorphum, Albidovulum, Pseudacidovorax, and Thiolamprovum were more abundant in 2% C. vulgaris-treated fish. C. vulgaris promoted the interaction of gut microbiota in juvenile Nile tilapia by increasing the abundance of Reyranella. Moreover, during the feeding time of 15 days, the gut microbes interacted more closely than those during the feeding time of 30 days. This work will be valuable for understanding how C. vulgaris in diets impacts the gut microbiota in fish.

Confined Assembly of Hydrated Vanadium Oxide into Hollow Mesoporous Carbon Nanospheres for Fast and Stable K+ Storage Capability.

The rational structural design of the electrode materials is significant to enhance the electrochemical performance for potassium ion storage, benefiting from the shortened ion diffusion distance, increased conductivity, and pseudo-capacitance promotion. Herein, hydrated vanadium oxide (HVO) nanosheets with enriched oxygen defects are well confined into hollow mesoporous carbon spheres (HMCS), producing Od -VOH@C nanospheres through one-step hydrothermal reaction. Attributed to the restricted growth in the HMCS, the HVO nanosheets are loosely packed, generating abundant interfacial boundaries and large specific areas. As a result, Od -VOH@C nanospheres show increased reaction kinetics and well buffer the volume effects for the K+ storage. Od -VOH@C delivers stable capacities of 138 mAh g-1 at 2.0 A g-1 over 10 000 cycles in half-cells attributed to the high pseudo-capacitance contribution. The K+ storage mechanism of insertion and conversion reaction is confirmed by ex situ X-ray diffraction, Raman, and X-ray photoelectron spectroscopy analyses. Moreover, the symmetric potassium-ion capacitors of Od -VOH@C//Od -VOH@C deliver a high energy density of 139.6 Wh kg-1 at the power density of 948.3 W kg-1 .

Biomimetic Convex Implant for Corneal Regeneration Through 3D Printing.

Blindness caused by corneal damage affects millions of people worldwide, and this number continues to rise. However, rapid epithelization and a stable epithelium process are the two biggest challenges for traditional corneal materials. These processes are related to corneal curvature, which is an important factor in determination of the corneal healing process and epithelial behavior during corneal damage. In this study, smooth 3D-printed convex corneal implants based on gelatin methacrylate and collagen are generated. As epithelium distribution and adhesion vary in different regions of the natural cornea, this work separates the surfaces into four regions and studies how cells sense topological cues on curvature. It is found that rabbit corneal epithelial cells (RCECs) seeded on steeper slope gradient surfaces on convex structures result in more aligned cell organization and tighter cell-substrate adhesion, which can also be verified through finite element simulation and signaling pathway analysis. In vivo transplantation of convex implants result in a better fit with adjacent tissue and stronger cell adhesion than flat implants, thereby accelerating corneal epithelialization and promoting collagen fibers and neural regeneration within 180 days. Taken together, printed convex corneal implants that facilitate corneal regeneration may offer a translational strategy for the treatment of corneal damage.

Accurate correction method and algorithm of fluorescence secondary inner filter effect (sIEF) in fluorescence quantitative analysis.

Fluorescence spectroscopy is a reliable and widely used analytical method. The fluorescence inner filter effect (IFE) is one of the main obstacles in the application of fluorescence spectroscopy and an error source in fluorescence analysis, resulting in the fluorescence spectrum distortion, the spectral shape distortion, and the nonlinearity between fluorescence intensity and fluorophore concentration. An optimized parameter reflecting the self-absorption effect - the fluorescence attenuation absorption index of secondary inner filter effect (sIFE) nopt - is proposed in this paper. Considering the received fluorescence in a direction perpendicular to the incident light, it is related to the solute-solvent system of the fluorescent substance, neither the geometric parameters of the cuvette and the light beam nor the concentration of the fluorescent substance. nopt can accurately reflect the degree to which the fluorescence is affected by the sIFE and correct for any non-ideality of the shapes of excitation/emission beams. The principle and determination method of nopt are explained in detail. Accordingly, an algorithm for the fluorescence spectroscopic correction by nopt is designed. To verify the method, the fluorescence spectra and absorbance spectra of the solutions of fluorescein sodium, rhodamine B, rhodamine 6G, and chlorophyll-a with a series of concentration gradients were measured, respectively. The influence of solvent effect on sIFE correction was also studied. The experiments show that different solute-solvent systems of the fluorescent substances have their own nopt. The novel algorithm can determine the nopt, correct the intensity attenuation and the peak red-shift of the fluorescence spectrum caused by the sIFE, expand the linear range of the concentration predicted by the fluorescence intensity, reduce the error of the prediction model, and improve the measurement accuracy.

CFSA-AGD: An accurate crosstalk fluorescence spectroscopic decomposition method for identifying and quantifying FDOMs in aquatic environments.

Fluorescent substances exist in various aquatic environments and other environmental media. It is a critical task to identify the components accurately and quantify their contents precisely. Based on the Crosstalk Fluorescence Spectroscopy Analysis (CFSA) model, a fluorescence spectroscopic decomposition using the Alternating Gradient Descent (AGD) algorithm is developed. By reducing the residual error of the model through alternating iterations, the CFSA-AGD method achieves unsupervised model training and automatic spectroscopic decomposition without extra experimental operations such as dilution or absorbance measurement, exempting from tedious modeling process. The objectives of this work are to validate that the CFSA-AGD method can comprehensively address the decomposition of fluorescence spectral crosstalk. Furthermore, the novel method is applied to the spectroscopic decomposition of natural FDOMs in aquatic environments as a standard tool. The spectral data analyzing the performance of this method is verified and compared with the conventional methods through the experiment on standard samples. The results indicate that CFSA-AGD has higher spectroscopic decomposition accuracy and gives more abundant information on the characteristic spectra with less residual error than parallel factor analysis. This means that the fluorescence spectra of natural FDOMs can be decomposed into the characteristic fluorescence emission spectra of single components with higher accuracy and the characteristic fluorescence absorption spectra that cannot be obtained by the conventional methods. Meanwhile, it improves the analytical precision of the contents (from R2 ≥ 0.9778 to R2 ≥ 0.9920) and reduces the ultimate residual error by two orders of magnitude (from 1.42 × 10-1 to 4.68 × 10-3) when the method is used to estimate the measured fluorescence spectra.