A serine carboxypeptidase-like acyltransferase catalyzes consecutive four-step reactions of hydrolyzable tannin biosynthesis in Camellia oleifera.

Hydrolyzable tannins (HTs), a class of polyphenolic compounds found in dicotyledonous plants, are widely used in food and pharmaceutical industries because of their beneficial effects on human health. Although the biosynthesis of simple HTs has been verified at the enzymatic level, relevant genes have not yet been identified. Here, based on the parent ion-fragment ion pairs in the feature fragment data obtained using UPLC-Q-TOF-/MS/MS, galloyl phenolic compounds in the leaves of Camellia sinensis and C. oleifera were analyzed qualitatively and quantitatively. Correlation analysis between the transcript abundance of serine carboxypeptidase-like acyltransferases (SCPL-ATs) and the peak area of galloyl products in Camellia species showed that SCPL3 expression was highly correlated with HT biosynthesis. Enzymatic verification of the recombinant protein showed that CoSCPL3 from C. oleifera catalyzed the four consecutive steps involved in the conversion of digalloylglucose to pentagalloylglucose. We also identified the residues affecting the enzymatic activity of CoSCPL3 and determined that SCPL-AT catalyzes the synthesis of galloyl glycosides. The findings of this study provide a target gene for germplasm innovation of important cash crops that are rich in HTs, such as C. oleifera, strawberry, and walnut.

Translational modeling-based evidence for enhanced efficacy of standard-of-care drugs in combination with anti-microRNA-155 in non-small-cell lung cancer.

BACKGROUND: Elevated microRNA-155 (miR-155) expression in non-small-cell lung cancer (NSCLC) promotes cisplatin resistance and negatively impacts treatment outcomes. However, miR-155 can also boost anti-tumor immunity by suppressing PD-L1 expression. Therapeutic targeting of miR-155 through its antagonist, anti-miR-155, has proven challenging due to its dual molecular effects. METHODS: We developed a multiscale mechanistic model, calibrated with in vivo data and then extrapolated to humans, to investigate the therapeutic effects of nanoparticle-delivered anti-miR-155 in NSCLC, alone or in combination with standard-of-care drugs. RESULTS: Model simulations and analyses of the clinical scenario revealed that monotherapy with anti-miR-155 at a dose of 2.5 mg/kg administered once every three weeks has substantial anti-cancer activity. It led to a median progression-free survival (PFS) of 6.7 months, which compared favorably to cisplatin and immune checkpoint inhibitors. Further, we explored the combinations of anti-miR-155 with standard-of-care drugs, and found strongly synergistic two- and three-drug combinations. A three-drug combination of anti-miR-155, cisplatin, and pembrolizumab resulted in a median PFS of 13.1 months, while a two-drug combination of anti-miR-155 and cisplatin resulted in a median PFS of 11.3 months, which emerged as a more practical option due to its simple design and cost-effectiveness. Our analyses also provided valuable insights into unfavorable dose ratios for drug combinations, highlighting the need for optimizing dose regimens to prevent antagonistic effects. CONCLUSIONS: This work bridges the gap between preclinical development and clinical translation of anti-miR-155 and unravels the potential of anti-miR-155 combination therapies in NSCLC.

Microscopic and submicroscopic exploration of diplolepideae peristome structures in hygroscopic movement.

BACKGROUND: The Diplolepideae are the larger group within the Arthrodontae mosses, characterized by peristomes formed from residual cell walls. It is now understood that these peristomes exhibit diverse hygroscopic movements, playing a crucial role in spore release. However, the exact mechanism behind this movement remains unclear, lacking direct evidence. This study investigated the microscopic and submicroscopic structures of the peristomes in three Diplolepideae species: Hypopterygium fauriei (Besch.), Pylaisia levieri (Müll. Hal.) Arikawa and Regmatodon declinatus (Hook.) Brid. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were used to reveal the differences in their hygroscopic movement mechanisms. RESULTS: The three species exhibited distinct responses upon wetting: H. fauriei's exostome closed inwards, P. levieri' opened outwards, and R. declinatus' elongated significantly. These differences are attributed to the varying microfibril deposition in the exostome layers. Uniform deposition in the inner layer and minimal deposition in the outer layer enabled exostome opening upon wetting and closing when dry. Our findings suggest that the diastole and contraction of fine microfibrils in the exostome plates and ridges are the key drivers of hygroscopic movement. CONCLUSIONS: This study provides further evidence at both the structural and submicroscopic levels, contributing to the unraveling of the hygroscopic movement mechanism in Diplolepideae peristomes. This enhanced understanding sheds light on the relationship between peristome structure and function.

Exploring the role of biotic factors in regulating the spatial variability in land surface phenology across four temperate forest sites.

Land surface phenology (LSP), the characterization of plant phenology with satellite data, is essential for understanding the effects of climate change on ecosystem functions. Considerable LSP variation is observed within local landscapes, and the role of biotic factors in regulating such variation remains underexplored. In this study, we selected four National Ecological Observatory Network terrestrial sites with minor topographic relief to investigate how biotic factors regulate intra-site LSP variability. We utilized plant functional type (PFT) maps, functional traits, and LSP data to assess the explanatory power of biotic factors for the start and end of season (SOS and EOS) variability. Our results indicate that PFTs alone explain only 0.8-23.4% of intra-site SOS and EOS variation, whereas including functional traits significantly improves explanatory power, with cross-validation correlations ranging from 0.50 to 0.85. While functional traits exhibited diverse effects on SOS and EOS across different sites, traits related to competitive ability and productivity were important for explaining both SOS and EOS variation at these sites. These findings reveal that plants exhibit diverse phenological responses to comparable environmental conditions, and functional traits significantly contribute to intra-site LSP variability, highlighting the importance of intrinsic biotic properties in regulating plant phenology.

Resolved Raman sideband cooling of a single optically trapped cesium atom.

We developed a resolved Raman sideband cooling scheme that can efficiently prepare a single optically trapped cesium (Cs) atom in its motional ground states. A two-photon Raman process between two outermost Zeeman sublevels in a single hyperfine state is applied to reduce the phonon number. Our scheme is less sensitive to the variation in the magnetic field than the commonly used scheme where the two outermost Zeeman sublevels belonging to the two separate ground hyperfine states are taken. Fast optical pumping with less spontaneous emission guarantees the efficiency of the cooling process. After cooling for 50 ms, 82% of the Cs atoms populate their three-dimensional ground states. Our scheme improves the long-term stability of Raman sideband cooling in the presence of magnetic field drift and is thus suitable for cooling other trapped atoms or ions with abundant magnetic sublevels.

Detection of two homologous major QTLs and development of diagnostic molecular markers for sucrose content in peanut.

KEY MESSAGE: We identified two stable and homologous major QTLs for sucrose content in peanut, and developed breeder-friendly molecular markers for marker-assisted selection breeding. Sucrose content is a crucial quality trait for edible peanuts, and increasing sucrose content is a key breeding objective. However, the genetic basis of sucrose content in peanut remains unclear, and major quantitative trait loci (QTLs) for sucrose content have yet to be identified. In this study, a high-density genetic map was constructed based on whole-genome re-sequencing data from a peanut RIL population. This map consisted of 2,042 bins and 24,142 SNP markers, making it one of the most comprehensive maps to date in terms of marker density. Two major QTLs (qSCA06.2 and qSCB06.2) were identified, explaining 31.41% and 24.13% of the phenotypic variance, respectively. Notably, these two QTLs were located in homologous genomic regions between the A and B subgenomes. The elite allele of qSCA06.2 was exclusive to Valencia-type, while the elite allele of qSCB06.2 existed in other peanut types. Importantly, the distribution of alleles from two homologous QTLs in the RIL population and diverse germplasm accessions consistently demonstrated that only the combination of elite allelic genotypes from both QTLs/genes resulted in a significantly dominant phenotype, accompanied by a substantial increase in sucrose content. The newly developed diagnostic markers for these QTLs were confirmed to be reliable and could facilitate future breeding efforts to enhance sucrose content using marker-assisted selection techniques. Overall, this study highlights the co-regulation of sucrose content by two major homologous QTLs/genes and provides valuable insights into the genetic basis of sucrose in peanuts.

Identification of QTLs associated with very-long chain fatty acid (VLCFA) content via linkage mapping and BSA-seq in peanut.

KEY MESSAGE: Three major QTLs qA01, qB04.1 and qB05 for VLCFA content and their corresponding allele-specific markers will benefit peanut low VLCFA breeding, and a candidate gene Arahy.IF1JV3 was predicted. Peanut is a globally significant oilseed crop worldwide, and contains a high content (20%) of saturated fatty acid (SFA) in its seeds. As high level SFA intake in human dietary may increase the cardiovascular disease risk, reducing the SFA content in peanut is crucial for improving its nutritional quality. Half of the SFAs in peanut are very long-chain fatty acids (VLCFA), so reducing the VLCFA content is a feasible strategy to decrease the total SFA content. Luoaowan with extremely low VLCFA (4.80%) was crossed with Jihua16 (8.00%) to construct an F2:4 population. Three major QTLs including qA01, qB04.1 and qB05 for VLCFA content were detected with 4.43 ~ 14.32% phenotypic variation explained through linkage mapping. Meanwhile, three genomic regions on chromosomes B03, B04 and B05 were identified via BSA-seq approach. Two co-localized intervals on chromosomes B04 (100.10 ~ 103.97 Mb) and B05 (6.39 ~ 10.90 Mb) were identified. With markers developed based on SNP/InDel variations in qA01 between the two parents, the remaining interval was refined to 103.58 ~ 111.14 Mb. A candidate gene Arahy.IF1JV3 encoding a ß-ketoacyl-CoA synthase was found in qA01, and its expression level in Luoaowan was significantly lower than that in Jihua16. Allele-specific markers targeting qA01, qB04.1 and qB05 were developed and validated in F4 population, and an elite line with high oleic, low VLCFA (5.05%) and low SFA (11.48%) contents was selected. This study initially revealed the genetic mechanism of VLCFA content, built a marker-assisted selection system for low VLCFA breeding, and provided an effective method to decrease the SFA content in peanut.

Palladium-Catalyzed Cycloaddition Reactions of π-Allylpalladium 1,4-Dipoles with 1,3,5-Triazinanes: Access to Hexahydropyrimidines, 1,3-Oxazinanes, and 1,5-Diazocanes.

Palladium-catalyzed decarboxylation of 5-methylene-1,3-oxazinan-2-ones and 5-methylene-1,3-dioxan-2-ones to generate aza-π-allylpalladium and oxa-π-allylpalladium 1,4-dipoles for [4 + 2] cycloaddition reaction with 1,3,5-triazinanes was developed, affording a wide range of hexahydropyrimidine and 1,3-oxazinane derivatives in good to excellent yields (up to 99%). The acyclic sulfonamido-substituted allylic carbonates as aza-π-allylpalladium 1,4-dipole precursors also apply to the developed synthesized strategy, achieving the synthesis of hexahydropyrimidines. Moreover, the in situ-generated aza-π-allylpalladium 1,4-dipoles undergoing dimeric [4 + 4] cycloaddition were also demonstrated by the construction of 1,5-diazocane derivatives.

Arachidonic acid metabolism CYP450 pathway is deregulated in hepatocellular carcinoma and associated with microvascular invasion.

Arachidonic acid metabolism plays a crucial role in the development and progression of inflammatory and metabolic liver diseases. However, its role in hepatocellular carcinoma (HCC) remains unclear. In this study, we investigated the expression of key genes involved in the arachidonic acid metabolism pathway in HCC using a combination of bioinformatics, proteomics and immunohistochemistry analyses. Through a comprehensive analysis of publicly available datasets, clinical HCC tissues, and tissue microarrays, we compared the expression of hepatic arachidonic acid metabolic genes. We observed significant downregulation of cytochrome P450 (CYP450) pathway genes at both the messenger RNA and protein levels in HCC tissues compared to normal liver tissues. Furthermore, we observed a strong correlation between the deregulation of the arachidonic acid metabolism CYP450 pathway and the pathological features and prognosis of HCC. Specifically, the expression of CYP2C8/9/18/19 was significantly correlated with pathological grade (r = -.484, p < .0001), vascular invasion (r = -.402, p < .0001), aspartate transaminase (r = -.246, p = .025), gamma-glutamyl transpeptidase (r = -.252, p = .022), alkaline phosphatase (r = -.342, p = .002), alpha-fetoprotein (r = -.311, p = .004) and carbohydrate antigen 19-9 (r = -.227, p = .047). Moreover, we discovered a significant association between CYP450 pathway activity and vascular invasion in HCC. Collectively, these data indicate that arachidonic acid CYP450 metabolic pathway deregulation is implicated in HCC progression and may be a potential predictive factor for early recurrence in patients with HCC.

Removal of potentially toxic elements from water with the moss-tufa micro-filtration system.

Mosses are an integral component in the tufa sedimentary landscape. In this study, we investigated the use of the porous moss-tufa structure as a filtration system for removing potentially toxic elements (PTEs) from water samples. Three species of mosses that commonly grow on tufa were selected, and the PTEs filtered by the moss-tufa system were identified by inductively coupled plasma mass spectrometry. The bioconcentration factor (BCF) of mosses was calculated to compare the enrichment effects of different mosses on PTEs. Likewise, the level of PTEs flowing through the moss-tufa system was measured, and the water quality removal rate (C) was calculated accordingly. The results revealed that the moss-tufa system was mainly composed of Fissidens grandifrons Brid., Hydrogonium dixonianum P. C. Chen, and Cratoneuron filicinum (Hedw.) Spruce var. filicinum. Among these, Fissidens grandifrons Brid. reported the highest retention capacity for PTEs. Collectively, the moss-tufa filtration system displayed a strong retention capacity and removal rate of Mn, Pb, and Ni from the water sample. The removal of PTEs by the moss-tufa system was mainly based on the enrichment of mosses and the adsorption-retention ability of tufa. In conclusion, the moss-tufa micro-filtration system displayed the effective removal of PTEs from water samples and could be applied to control the levels of toxic elements in karst water bodies.

Evaluation of the Reliability of the CCM-300 Chlorophyll Content Meter in Measuring Chlorophyll Content for Various Plant Functional Types.

Chlorophyll fluorescence is a well-established method to estimate chlorophyll content in leaves. A popular fluorescence-based meter, the Opti-Sciences CCM-300 Chlorophyll Content Meter (CCM-300), utilizes the fluorescence ratio F735/F700 and equations derived from experiments using broadleaf species to provide a direct, rapid estimate of chlorophyll content used for many applications. We sought to quantify the performance of the CCM-300 relative to more intensive methods, both across plant functional types and years of use. We linked CCM-300 measurements of broadleaf, conifer, and graminoid samples in 2018 and 2019 to high-performance liquid chromatography (HPLC) and/or spectrophotometric (Spec) analysis of the same leaves. We observed a significant difference between the CCM-300 and HPLC/Spec, but not between HPLC and Spec. In comparison to HPLC, the CCM-300 performed better for broadleaves (r = 0.55, RMSE = 154.76) than conifers (r = 0.52, RMSE = 171.16) and graminoids (r = 0.32, RMSE = 127.12). We observed a slight deterioration in meter performance between years, potentially due to meter calibration. Our results show that the CCM-300 is reliable to demonstrate coarse variations in chlorophyll but may be limited for cross-plant functional type studies and comparisons across years.

Enhanced and Sustainable Removal of Indoor Formaldehyde by Naturally Porous Bamboo Activated Carbon Supported with MnOx: Synergistic Effect of Adsorption and Oxidation.

Novel bamboo activated carbon (BAC) catalysts decorated with manganese oxides (MnOx) were prepared with varying MnOx contents through a facile one-step redox reaction. Due to the physical anchoring effect of the natural macropore structure for catalyst active components, homogeneous MnOx nanoparticles (NPs), and high specific surface area over catalyst surface, the BAC@MnOx-N (N = 1, 2, 3, 4, 5) catalyst shows encouraging adsorption and catalytic oxidation for indoor formaldehyde (HCHO) removal at room temperature. Dynamic adsorption and catalytic activity experiments were conducted. The higher Smicro (733 m2/g) and Vmicro/Vt (82.6%) of the BAC@MnOx-4 catalyst could facilitate its excellent saturated and breakthrough adsorption capacity (5.24 ± 0.42 mg/g, 2.43 ± 0.22 mg/g). The best performer against 2 ppm HCHO is BAC@MnOx-4 catalyst, exhibiting a maximum HCHO removal efficiency of 97% for 17 h without any deactivation as RH = 0, which is higher than those of other MnOx-based catalysts. The average oxidation state and in situ DRIFTS analysis reveal that abundant oxygen vacancies on the BAC@MnOx-4 catalyst could be identified as surface-active sites of decomposing HCHO into the intermediate species (dioxymethylene and formate). This study provides a potential approach to deposit MnOx nanoparticles onto the BAC surface, and this hybrid BAC@MnOx material is promising for indoor HCHO removal at room temperature.

Identification of histopathological classification and establishment of prognostic indicators of gastric adenocarcinoma based on deep learning algorithm.

The aim of this study is to establish a deep learning (DL) model to predict the pathological type of gastric adenocarcinoma cancer based on whole-slide images(WSIs). We downloaded 356 histopathological images of gastric adenocarcinoma (STAD) patients from The Cancer Genome Atlas database and randomly divided them into the training set, validation set and test set (8:1:1). Additionally, 80 H&E-stained WSIs of STAD were collected for external validation. The CLAM tool was used to cut the WSIs and further construct the model by DL algorithm, achieving an accuracy of over 90% in identifying and predicting histopathological subtypes. External validation results demonstrated the model had a certain generalization ability. Moreover, DL features were extracted from the model to further investigate the differences in immune infiltration and patient prognosis between the two subtypes. The DL model can accurately predict the pathological classification of STAD patients, and provide certain reference value for clinical diagnosis. The nomogram combining DL-signature, gene-signature and clinical features can be used as a prognostic classifier for clinical decision-making and treatment.

[Research progress on Rhododendron molle in treatment of rheumatoid arthritis].

Rheumatoid arthritis(RA), as a chronic autoimmune disease, has a high incidence and disability rate, causing significant suffering to patients. Due to its complex pathogenesis, it has not been fully elucidated to date, and its treatment remains a challenging problem in the medical field. Although western medicine treatment options have certain efficacy, they require prolonged use and are expensive. Additionally, they carry risks of multiple infections and adverse reactions like malignancies. The Chinese herbal medicine Rhododendron molle is commonly used in folk medicine for its properties of dispelling wind, removing dampness, calming nerves, and alleviating pain in the treatment of diseases like rheumatic bone diseases. In recent years, modern clinical and pharmacological studies have shown that the diterpenoids in R. molle are effective components, exhibiting immune-regulatory, anti-inflammatory, and analgesic effects. This makes it a promising candidate for treating RA with a broad range of potential applications. However, R. molle has certain toxic properties that hinder its clinical application and lead to the wastage of its resources. This study reviewed recent research progress on the mechanism of R. molle in preventing and treating RA, focusing on its chemical components, anti-inflammatory and analgesic properties and summarized the adverse reactions associated with R. molle, aiming to offer new ideas for finding natural remedies for RA and methods to reduce toxicity while enhancing the effectiveness of R. molle. The study seeks to clarify the safety and efficacy of R. molle and its extracts, providing a theoretical basis for its application prospects and further promoting the development and utilization of R. molle resources.

Omics-driven advances in the understanding of regulatory landscape of peanut seed development.

Peanuts (Arachis hypogaea) are an essential oilseed crop known for their unique developmental process, characterized by aerial flowering followed by subterranean fruit development. This crop is polyploid, consisting of A and B subgenomes, which complicates its genetic analysis. The advent and progression of omics technologies-encompassing genomics, transcriptomics, proteomics, epigenomics, and metabolomics-have significantly advanced our understanding of peanut biology, particularly in the context of seed development and the regulation of seed-associated traits. Following the completion of the peanut reference genome, research has utilized omics data to elucidate the quantitative trait loci (QTL) associated with seed weight, oil content, protein content, fatty acid composition, sucrose content, and seed coat color as well as the regulatory mechanisms governing seed development. This review aims to summarize the advancements in peanut seed development regulation and trait analysis based on reference genome-guided omics studies. It provides an overview of the significant progress made in understanding the molecular basis of peanut seed development, offering insights into the complex genetic and epigenetic mechanisms that influence key agronomic traits. These studies highlight the significance of omics data in profoundly elucidating the regulatory mechanisms of peanut seed development. Furthermore, they lay a foundational basis for future research on trait-related functional genes, highlighting the pivotal role of comprehensive genomic analysis in advancing our understanding of plant biology.

Higher-order neurodynamical equation for simplex prediction.

It is demonstrated that higher-order patterns beyond pairwise relations can significantly enhance the learning capability of existing graph-based models, and simplex is one of the primary form for graphically representing higher-order patterns. Predicting unknown (disappeared) simplices in real-world complex networks can provide us with deeper insights, thereby assisting us in making better decisions. Nevertheless, previous efforts to predict simplices suffer from two issues: (i) they mainly focus on 2- or 3-simplices, and there are few models available for predicting simplices of arbitrary orders, and (ii) they lack the ability to analyze and learn the features of simplices from the perspective of dynamics. In this paper, we present a Higher-order Neurodynamical Equation for Simplex Prediction of arbitrary order (HNESP), which is a framework that combines neural networks and neurodynamics. Specifically, HNESP simulates the dynamical coupling process of nodes in simplicial complexes through different relations (i.e., strong pairwise relation, weak pairwise relation, and simplex) to learn node-level representations, while explaining the learning mechanism of neural networks from neurodynamics. To enrich the higher-order information contained in simplices, we exploit the entropy and normalized multivariate mutual information of different sub-structures of simplices to acquire simplex-level representations. Furthermore, simplex-level representations and multi-layer perceptron are used to quantify the existence probability of simplices. The effectiveness of HNESP is demonstrated by extensive simulations on seven higher-order benchmarks. Experimental results show that HNESP improves the AUC values of the state-of-the-art baselines by an average of 8.32%. Our implementations will be publicly available at: https://github.com/jianruichen/HNESP.

HoRDA: Learning higher-order structure information for predicting RNA-disease associations.

CircRNA and miRNA are crucial non-coding RNAs, which are associated with biological diseases. Exploring the associations between RNAs and diseases often requires a significant time and financial investments, which has been greatly alleviated and improved with the application of deep learning methods in bioinformatics. However, existing methods often fail to achieve higher accuracy and cannot be universal between multiple RNAs. Moreover, complex RNA-disease associations hide important higher-order topology information. To address these issues, we learn higher-order structure information for predicting RNA-disease associations (HoRDA). Firstly, the correlations between RNAs and the correlations between diseases are fully explored by combining similarity and higher-order graph attention network. Then, a higher-order graph convolutional network is constructed to aggregate neighbor information, and further obtain the representations of RNAs and diseases. Meanwhile, due to the large number of complex and variable higher-order structures in biological networks, we design a higher-order negative sampling strategy to gain more desirable negative samples. Finally, the obtained embeddings of RNAs and diseases are feed into logistic regression model to acquire the probabilities of RNA-disease associations. Diverse simulation results demonstrate the superiority of the proposed method. In the end, the case study is conducted on breast neoplasms, colorectal neoplasms, and gastric neoplasms. We validate the proposed higher-order strategies through ablative and exploratory analyses and further demonstrate the practical applicability of HoRDA. HoRDA has a certain contribution in RNA-disease association prediction.

Content-Aware Rectified Activation for Zero-Shot Fine-Grained Image Retrieval.

Fine-grained image retrieval mainly focuses on learning salient features from the seen subcategories as discriminative embedding while neglecting the problems behind zero-shot settings. We argue that retrieving fine-grained objects from unseen subcategories may rely on more diverse clues, which are easily restrained by the salient features learnt from seen subcategories. To address this issue, we propose a novel Content-aware Rectified Activation model, which enables this model to suppress the activation on salient regions while preserving their discrimination, and spread activation to adjacent non-salient regions, thus mining more diverse discriminative features for retrieving unseen subcategories. Specifically, we construct a content-aware rectified prototype (CARP) by perceiving semantics of salient regions. CARP acts as a channel-wise non-destructive activation upper bound and can be selectively used to suppress salient regions for obtaining the rectified features. Moreover, two regularizations are proposed: 1) a semantic coherency constraint that imposes a restriction on semantic coherency of CARP and salient regions, aiming at propagating the discriminative ability of salient regions to CARP, 2) a feature-navigated constraint to further guide the model to adaptively balance the discrimination power of rectified features and the suppression power of salient features. Experimental results on fine-grained and product retrieval benchmarks demonstrate that our method consistently outperforms the state-of-the-art methods.

A Combination of Magnoflorine and Spinosin Improves the Antidepressant effects on CUMS Mouse Model.

BACKGROUND: Depression is a common neuropsychiatric disease. As a famous traditional Chinese medicine with significant anti-depressive and sleep-promoting effects, Ziziphi Spinosae Semen (ZSS) has attracted the attention of many researchers. Although it is well known that Magnoflorine (MAG) and Spinosin (SPI) were the main active components isolated from ZSS, there is a lack of research on the combined treatment of depression with these two ingredients. METHODS: The shaking bottle method was used to simulate the human environment for detecting the changes in oil-water partition coefficient before and after the drug combination. Cell viability was evaluated by the MTT assay. To establish a mouse model of depression and insomnia by CUMS method, and then to explore the effect of combined administration of MAG and SPI on depression in CUMS model by observing behavior and analyzing pharmacokinetics. RESULTS: The change in LogP values affected the lipid solubility of MAG and increased the water solubility of SPI, allowing them to penetrate more easily through the blood-brain barrier into the brain. Compared with the model group, MAG-SPI with a concentration of 60 µM significantly increased cell survival rate. In both the TST and FST experiments, the mice showed a decrease in immobilization time. Pharmacokinetic results showed that the pharmacokinetic parameters, Cmax and AUC of MAG and SPI, were increased in the case of combination, which resulted in enhancement of their relative bioavailability and improvement of in vivo effects. CONCLUSIONS: The present study demonstrated that a combination of MAG and SPI had a synergistic antidepressant effect in CUMS mouse model.