High-Sensitive Uncooled Mid-Wave Infrared Detector Based on TiS3 Nanoribbon.

High-sensitive uncooled mid-wave infrared (MWIR) photodetection with fast speed is highly desired for biomedical imaging, optical communication, and night vision technology. Low-dimensional materials with low dark current and broadband photoresponse hold great promise for use in MWIR detection. Here, this study reports a high-performance MWIR photodetector based on a titanium trisulfide (TiS3) nanoribbon. This device demonstrates an ultra-broadband photoresponse ranging from the visible spectrum to the MWIR spectrum (405-4275 nm). In the MWIR spectral range, the photodetector achieves competitive high photoresponsivity (R) of 21.1 A W-1, and an impressive specific detectivity (D*) of 5.9 × 1010 cmHz1/2 W-1 in ambient air. Remarkably, the photoresponse speed in the MWIR with τr = 1.3 ms and τd = 1.5 ms is realized which is much faster than the thermal time constant of 15 ms. These findings pave the way for highly sensitive, room-temperature MWIR photodetectors with exceptionally fast response speed.

A Tunable Graphene Superlattice with Deformable Periodical Nano-Gating.

Graphene superlattices have simple and controllable electronic band structures, which can also be electrostatically tuned. They have been widely studied for band engineering and strong correlated physics, and have led to the discovery of a variety of exciting phenomena. To experimentally study the physics of graphene superlattices in a systematic way, it is desirable to control the structure parameters, which barely exist at the moment, onsite. Here, a tunable superlattice with graphene and a deformable gating structure is demonstrated. The period and duty cycle of the nano-gating, and furthermore of the superlattice potential, can be tuned through altering the shape of the gating structure with piezo-actuators, offering a tunable band structure. The tuning of the electronic band structures of both a two-dimensional and a one-dimensional superlattice is demonstrated with numerical simulations, offering a new approach for tunable electronic and photonic devices.

Cordycepin Modulates Microglial M2 Polarization Coupled with Mitochondrial Metabolic Reprogramming by Targeting HKII and PDK2.

The microenvironment mediated by the microglia (MG) M1/M2 phenotypic switch plays a decisive role in the neuronal fate and cognitive function of Alzheimer's disease (AD). However, the impact of metabolic reprogramming on microglial polarization and its underlying mechanism remains elusive. This study reveals that cordycepin improved cognitive function and memory in APP/PS1 mice, as well as attenuated neuronal damage by triggering MG-M2 polarization and metabolic reprogramming characterized by increased OXPHOS and glycolysis, rather than directly protecting neurons. Simultaneously, cordycepin partially alleviates mitochondrial damage in microglia induced by inhibitors of OXPHOS and glycolysis, further promoting MG-M2 transformation and increasing neuronal survival. Through confirmation of cordycepin distribution in the microglial mitochondria via mitochondrial isolation followed by HPLC-MS/MS techniques, HKII and PDK2 are further identified as potential targets of cordycepin. By investigating the effects of HKII and PDK2 inhibitors, the mechanism through which cordycepin targeted HKII to elevate ECAR levels in the glycolysis pathway while targeting PDK2 to enhance OCR levels in PDH-mediated OXPHOS pathway, thereby inducing MG-M2 polarization, promoting neuronal survival and exerting an anti-AD role is elucidated.

Rapid Separation and API Grades Identification of Base Oil in Low Viscosity Gasoline Engine Oil SN 0W-16.

Using low viscosity engine oil is one of the most economical and easily achievable ways to improve fuel economy. Base oil is a main component in low viscosity engine oils, and therefore, the separation and identification of its are of great significance for oil product developers to prepare high-performance lubricants. However, the extraction methods reported for base oils mainly adopt membrane dialysis, which not only fails to completely separate the base oil but also wastes a large amount of solvent. The reason for this result is that the concentration of substances inside and outside the membrane cannot always be in an imbalanced state of permeation resulting from manual operation. Additionally, most studies primarily focus on the characterization of base oil components, while there are few reports on grade identification. For the above reasons, an economically effective separation technique of base oil from low viscosity gasoline engine oil SN 0W-16 is successfully established by combining improved Soxhlet extraction and a column chromatography separation method. By applying this method, the yield of extracting base oil generally exceeds 96%, and the solvent can also save more than 3 times. Besides, an exclusion method is built through several simple characterization steps including viscosity index (VI), FT-IR, size-exclusion chromatography (SEC), and hydrocarbon composition, which can quickly identify the American Petroleum Institute (API) grade and brand of the base oils.

Design, synthesis and bioactivity evaluation of the combination of evodiamine and erlotinib linked by indolequinone.

Compared with single-targeted therapy, the design and synthesis of heterozygous molecules is still a significant challenge for the discovery of antitumor drugs. Quinone oxidoreductase-1 (NQO1) is a potential target for selective cancer therapy due to its overexpression in many cancer cells and its unique bioredox properties. Based on the principle of combinatorial drug design, we successfully synthesized a new hybrid molecules 13 with an indolequinone structure. We found that the synthesized compounds exhibited much higher cytotoxicity against the tested cancer cells than free drugs. Further mechanism studies confirmed that compound 13 induced cell apoptosis was achieved by regulating p53-dependent mitochondrial pathway and cell cycle arrest at the G0/G1 phase.

Metabolomic analysis of black sesame seeds: Effects of processing and active compounds in antioxidant and anti-inflammatory properties.

Black sesame seeds (BSS) have been recognized as a functional food due to their nutritional and therapeutic value for many years. In China, BSS is traditionally processed and consumed through two methods, namely, nine steaming nine sun-drying and stir-frying. The present study aimed to evaluate the effects of these processing techniques on the antioxidant and anti-inflammatory activities of BSS. UPLC-QTOF/MS was used for untargeted metabolomics to analyze the composition changes. The results indicated that the different samples had good antioxidant and anti-inflammatory activities, but thermal treatment reduced their activities. Untargeted metabolomics identified a total of 196 metabolites. Molecular docking studies targeting proteins associated with inflammation (iNOS) demonstrated that compounds acting as inhibitors were significantly reduced under both treatments. These results indicate that both nine steaming nine sun-drying and stir-frying lead to substantial loss of antioxidant, anti-inflammatory, and bioactive metabolites in BSS, which provides an important reference for its rational utilization.

Near-Infrared Organic Photodetectors toward Skin-Integrated Photoplethysmography-Electrocardiography Multimodal Sensing System.

In the fast-evolving landscape of decentralized and personalized healthcare, the need for multimodal biosensing systems that integrate seamlessly with the human body is growing rapidly. This presents a significant challenge in devising ultraflexible configurations that can accommodate multiple sensors and designing high-performance sensing components that remain stable over long periods. To overcome these challenges, ultraflexible organic photodetectors (OPDs) that exhibit exceptional performance under near-infrared illumination while maintaining long-term stability are developed. These ultraflexible OPDs demonstrate a photoresponsivity of 0.53 A W-1 under 940 nm, shot-noise-limited specific detectivity of 3.4 × 1013 Jones, and cut-off response frequency beyond 1 MHz at -3 dB. As a result, the flexible photoplethysmography sensor boasts a high signal-to-noise ratio and stable peak-to-peak amplitude under hypoxic and hypoperfusion conditions, outperforming commercial finger pulse oximeters. This ensures precise extraction of blood oxygen saturation in dynamic working conditions. Ultraflexible OPDs are further integrated with conductive polymer electrodes on an ultrathin hydrogel substrate, allowing for direct interface with soft and dynamic skin. This skin-integrated sensing platform provides accurate measurement of photoelectric and biopotential signals in a time-synchronized manner, reproducing the functionality of conventional technologies without their inherent limitations.

Comparative antioxidant activity and untargeted metabolomic analyses of cherry extracts of two Chinese cherry species based on UPLC-QTOF/MS and machine learning algorithms.

P. pseudocerasus and P. tomentosa are the two native Chinese cherry species of high economic and ornamental worths. Little is known about the metabolic information of P. pseudocerasus and P. tomentosa. Effective means are lacking for distinguishing these two similar species. In this study, the differences in total phenolic content (TPC), total flavonoid content (TFC), and in vitro antioxidant activities in 21 batches of two species of cherries were compared. A comparative UPLC-QTOF/MS-based metabolomics coupled with three machine learning algorithms was established for differentiating the cherry species. The results demonstrated that P. tomentosa had higher TPC and TFC with average content differences of 12.07 times and 39.30 times, respectively, and depicted better antioxidant activity. Total of 104 differential compounds were identified by UPLC-QTOF/MS metabolomics. The major differential compounds were flavonoids, organooxygen compounds, and cinnamic acids and derivatives. Correlation analysis revealed differences in flavonoids content such as procyanidin B1 or isomer and (Epi)catechin. They could be responsible for differences in antioxidant activities between the two species. Among three machine learning algorithms, the prediction accuracy of support vector machine (SVM) was 85.7%, and those of random forest (RF) and back propagation neural network (BPNN) were 100%. BPNN exhibited better classification performance and higher prediction rate for all testing set samples than those of RF. The study herein found that P. tomentosa had higher nutritional value and biological functions, and thus considered for usage in health products. Machine models based on untargeted metabolomics can be effective tools for distinguishing these two species.

Sputtered binder-free Cu3N electrode materials for high-performance quasi-solid-state asymmetric supercapacitors.

Developing high-efficiency electrode materials is of great importance in manufacturing supercapacitor devices with superior electrochemical performance. Herein, we for the first time report a binder-free method for controllable growth of Cu3N electrode materials via magnetron sputtering for supercapacitor applications. Benefiting from their unique polyhedral structure and good electrical conductivity, Cu3N electrodes can achieve an areal capacity of 90.7 mC cm-2 at 1 mA cm-2 and outstanding cycling stability with a capacity retention of 97.4% after 20 000 cycles. In particular, the assembled Cu3N//active carbon quasi-solid-state asymmetric supercapacitor can exhibit a maximum energy density of 13.2 µW h cm-2 and a power density of 4.8 mW cm-2 with an operating voltage of 1.6 V. These remarkable performances demonstrate the great potential of sputtered Cu3N electrode materials for future energy storage applications.

Recent Insights into Sample Pretreatment Methods for Mycotoxins in Different Food Matrices: A Critical Review on Novel Materials.

Mycotoxins pollution is a global concern, and can pose a serious threat to human health. People and livestock eating contaminated food will encounter acute and chronic poisoning symptoms, such as carcinogenicity, acute hepatitis, and a weakened immune system. In order to prevent or reduce the exposure of human beings and livestock to mycotoxins, it is necessary to screen mycotoxins in different foods efficiently, sensitively, and selectively. Proper sample preparation is very important for the separation, purification, and enrichment of mycotoxins from complex matrices. This review provides a comprehensive summary of mycotoxins pretreatment methods since 2017, including traditionally used methods, solid-phase extraction (SPE)-based methods, liquid-liquid extraction (LLE)-based methods, matrix solid phase dispersion (MSPD), QuEChERS, and so on. The novel materials and cutting-edge technologies are systematically and comprehensively summarized. Moreover, we discuss and compare the pros and cons of different pretreatment methods and suggest a prospect.

Combined with UPLC-Triple-TOF/MS-based plasma lipidomics and molecular pharmacology reveals the mechanisms of schisandrin against Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD), a type of neurodegeneration disease, is characterized by Aß deposition and tangles of nerve fibers. Schisandrin is one of the main components of Fructus Schisandrae Chinensis. Researches showed that schisandrin can improve the cognitive impairment and memory of AD mice, but the specific mechanism has not been fully elucidated. PURPOSE: The purpose of this study is to investigate the possible mechanism of schisandrin in improving AD pathology. METHODS: The Morris water maze test was executed to detect spatial learning and memory. Ultra performance liquid chromatography-Triple time of flight mass spectrometry (UPLC-Triple-TOF/MS)-based plasma lipidomics was used to study the changes of plasma lipids. Moreover, we measured the levels of protein and mRNA expression of APOE and ABCA1 in the rat brains and in BV2 microglia. RESULTS: Our study found that schisandrin could improve learning and memory, and reduce Aß deposition in AD rats. Furthermore, we found that schisandrin can improve plasma lipid metabolism disorders. Therefore, we hypothesized schisandrin might act via LXR and the docking results showed that schisandrin interacts with LXRß. Further, we found schisandrin increased the protein and mRNA expression of LXR target genes APOE and ABCA1 in the brain of AD rats and in BV2 microglia. CONCLUSION: Our study reveals the neuroprotective effect and mechanism of schisandrin improves AD pathology by activating LXR to produce APOE and ABCA1.

Miniaturized infrared spectrometer based on the tunable graphene plasmonic filter.

Miniaturization of a conventional spectrometer is challenging because of the tradeoffs of size, cost, signal-to-noise ratio, and spectral resolution, etc. Here, a new type of miniaturized infrared spectrometer based on the integration of tunable graphene plasmonic filters and infrared detectors is proposed. The transmittance spectrum of a graphene plasmonic filter can be tuned by varying the Fermi energy of the graphene, allowing light incident on the graphene plasmonic filter to be dynamically modulated in a way that encodes its spectral information in the receiving infrared detector. The incident spectrum can then be reconstructed by using decoding algorithms such as ridge regression and neural networks. The factors that influence spectrometer performance are investigated in detail. It is found that the graphene carrier mobility and the signal-to-noise ratio are two key parameters in determining the resolution and precision of the spectrum reconstruction. The mechanism behind our observations can be well understood in the framework of the Wiener deconvolution theory. Moreover, a hybrid decoding (or recovery) algorithm that combines ridge regression and a neural network is proposed that demonstrates a better spectral recovery performance than either the ridge regression or a deep neural network alone, being able to achieve a sub-hundred nanometer spectral resolution across the 8∼14 µm wavelength range. The size of the proposed spectrometer is comparable to a microchip and has the potential to be integrated within portable devices for infrared spectral imaging applications.

A Blood-Responsive AIE Bioprobe for the Ultrasensitive Detection and Assessment of Subarachnoid Hemorrhage.

Subarachnoid hemorrhage (SAH) is a severe subtype of stroke caused by the rupturing of blood vessels in the brain. The ability to accurately assess the degree of bleeding in an SAH model is crucial for understanding the brain-damage mechanisms and developing therapeutic strategies. However, current methods are unable to monitor microbleeding owing to their limited sensitivities. Herein, a new bleeding assessment system using a bioprobe TTVP with aggregation-induced emission (AIE) characteristics is demonstrated. TTVP is a water-soluble, small-molecule probe that specifically interacts with blood. Taking advantage of its AIE characteristics, cell membranes affinity, and albumin-targeting ability, TTVP fluoresces in bleeding areas and detects the presence of blood with a high signal-to-noise (S/N) ratio. The degree of SAH bleeding in an endovascular perforation model is clearly evaluated based on the intensity of the fluorescence observed in the brain, which enables the ultrasensitive detection of mirco-bleeding in the SAH model in a manner that outperforms the current imaging strategies. This method serves as a promising tool for the sensitive analysis of the degree of bleeding in SAHs and other hemorrhagic diseases.

Melatonin in different food samples: Recent update on distribution, bioactivities, pretreatment and analysis techniques.

Melatonin (MLT) plays a significant role on maintaining the basic physiological functions and regulating various metabolic processes in plentiful organisms. Recent years have witnessed an increase in MLT's share in global market with its affluent functions. However, the worrisome quality issues and inappropriate or excessive application of MLT take place inevitably. In addition, its photosensitive properties, oxidation, complex substrate concentration and trace levels leave exact detection of MLT doubly difficult. Therefore, it is essential to exploit precise, sensitive and stable extraction and detection methods to resolve above questions. In this study, we reviewed the distribution and bioactivities of MLT and conducted a comprehensive overview of the developments of pretreatment and analysis methods for MLT in food samples since 2010. Commonly used pretreatment methods for MLT include not only traditional techniques, but also novel ones, such as solid-phase extraction, QuEChERS, microextraction by packed sorbent, solid phase microextraction, liquid phase microextraction, and so on. Analysis methods include liquid chromatography coupled with different detectors, GC methods, capillary electrophoresis, sensors, and so on. The advantages and disadvantages of different techniques have been compared and the development tendency was prospected.

In Situ Generation of Red-to-NIR Emissive Radical Cations in the Stomach for Gastrointestinal Imaging.

Red-to-near-infrared (NIR) fluorescent probes, with advantages such as high spatiotemporal resolution and in situ sensing abilities, are highly attractive for diagnosis of gastrointestinal diseases and targeted drug development. However, conventional red-to-NIR fluorophores with electron closed-shell structures require tedious synthetic procedures for preparation, and it is difficult to further decorate them with sensing groups. In this study, a series of easily prepared pyrroles with simple structures that can quickly be transformed into red-to-NIR emissive radical cations in acidic buffer solution and in vivo stomachs is developed. The in-situ-generated red-to-NIR emissive pyrrole radical cations in the stomach have excellent biocompatibility and stability and can be used not only for intravital gastrointestinal imaging with high spatiotemporal resolution, but also for dynamic monitoring of the gastric emptying process and assessment of anti-gastric-acid therapy. The acidity-induced generation of pyrrole radical cations is believed to provide a facile strategy for developing red-to-NIR fluorophores and studying gastrointestinal diseases.

Schisandrin alleviates the cognitive impairment in rats with Alzheimer's disease by altering the gut microbiota composition to modulate the levels of endogenous metabolites in the plasma, brain, and feces.

Schisandrin is one of the main active compounds isolated from the fruit of Schisandrae chinensis Fructus, which is scientifically proven to have beneficial effects on Alzheimer's disease (AD) treatment at the cellular and whole organism level. However, the oral availability of schisandrin is very low, thus implying that the underlying mechanism of therapeutic effect on AD treatment is yet to be clarified fully. Therefore, we speculated that the therapeutic effect of schisandrin on AD is mainly by regulating the imbalance of the gut microbiota (GM). In this study, behavioral experiments and H&E staining were used to confirm the pharmacological effects of schisandrin on rats with AD. 16S rDNA gene sequencing and feces, plasma, and brain metabolomics techniques were utilized to investigate the therapeutic effects and the underlying mechanisms of schisandrin on cognitive impairment in rats with AD. The results indicated that schisandrin improved cognitive impairment and hippocampal cell loss in rats. The UPLC-QTOF/MS-based metabolomics studies of the feces, plasma, and brain revealed that 44, 96, and 40 potential biomarkers, respectively, were involved in the treatment mechanism of schisandrin. Schisandrin improved the metabolic imbalance in rats with AD, and the metabolic changes mainly affected the primary bile acid biosynthesis, sphingolipid metabolism, glycerophospholipid metabolism, and unsaturated fatty acid biosynthesis. Schisandrin can improve the GM structure disorder and increase the abundance of beneficial bacteria in the gut of rats with AD. The predictive metagenomics analysis indicated that the altered GM was mainly involved in lipid metabolism, steroid hormone biosynthesis, arachidonic acid metabolism, biosynthesis of unsaturated fatty acids, and bacterial invasion of epithelial cells. Spearman's correlation analysis showed a significant correlation between affected bacteria and metabolites in various metabolic pathways. Overall, the data underline that schisandrin improves the cognitive impairment in rats with AD by affecting the composition of the GM community, thus suggesting the potential therapeutic effect of schisandrin on the brain-gut axis in rats with AD at the metabolic level.

Explore the Therapeutic Composition and Mechanism of Schisandra chinensis-Acorus tatarinowii Schott on Alzheimer's Disease by Using an Integrated Approach on Chemical Profile, Network Pharmacology, and UPLC-QTOF/MS-Based Metabolomics Analysis.

Background: Alzheimer's disease places a heavy economic burden to healthcare systems around the world. However, the effective treatments are still lacking. Traditional Chinese medicines (TCM) of Schisandra chinensis and Acorus tatarinowii Schott have the pharmacological effects of sedation and neuroprotection and have been clinically proven to be effective in the treatment of AD. However, their main anti-Alzheimer's compounds and functional mechanisms remain unclear. Purpose: To elucidate the main therapeutic components and possible mechanisms of Sc-At in AD using a comprehensive strategy combining metabolomics and network pharmacology. Methods: First, the UPLC-QTOF/MS method was used to identify the main chemical constituents of Schisandra chinensis and Acorus tatarinowii Schott alcohol extracts in vitro and in vivo. Secondly, the theoretical active ingredients, targets, and pathways of Sc-At for AD treatment were predicted by network pharmacology methods. Finally, plasma metabolomics were detected by UPLC-QTOF/MS to analyze the differential metabolites and metabolic pathways related to Sc-At. Based on the analyses above, the anti-AD mechanism of Sc-At was explored. Results: A total of 95 chemical components were identified in Sc-At extracts in vitro, and 34 prototype drug components were detected in rat plasma; network pharmacology screening identified 14 drug components in line with the principle of Lipinski, of which 10 were present for in vitro drug composition analysis. For these 10 components, 58 AD disease targets were predicted, and 85 AD-related KEGG signaling pathways were enriched. Six core biomarkers of Sc-At (cis-8,11,14,17-eicosatetraenoic acid, prostaglandin H2, sphingosine 1-phosphate, enol-phenylpyruvate, 3-methoxytyrosine, and pristanoyl-CoA) were regulated to a normal state during the treatment of AD. Conclusion: The mechanism of Sc-At for the treatment of AD can be achieved by the effect of the 10 compounds of Sc-At on TNF, MAPK8, MAPK14, PTGS1, and other targets, thereby affecting arachidonic acid metabolism, neurotransmitters, and sphingolipid metabolism.

Metabolomic analyses redefine the biological classification of pancreatic cancer and correlate with clinical outcomes.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by high heterogeneity, and the postoperative prognosis of different patients often varies greatly. Therefore, the classification of pancreatic cancer patients and precise treatment becomes particularly important. In our study, 1 H NMR spectroscopy was used to analyze the 76 PDAC serum samples and identify the potential metabolic subtypes. The metabolic characteristics of each metabolic subtype were screened out and the relationship between metabolic subtype and the long-term prognosis was further identified. The clinical stages of PDAC did not show the metabolic differences at the serum metabolomic level. And three metabolic subtypes, basic, choline-like and amino acid-enriched types, were defined by the hierarchical cluster analysis of the serum metabolites and the disturbed metabolic pathways. The characteristic metabolites of each PDAC subtype were identified, and the metabolite model was established to distinguish the PDAC patients in the different subtypes. Among the three metabolic subtypes, choline-like type displayed better long-term prognosis compared to the other two types of patients. Metabolic subtypes are of clinical importance and are closer to expressing the heterogeneity in the actual life activities of pancreatic cancer than molecular typing. The excavation of metabolic subtypes based on this will be more in line with clinical reality and more promising to guide clinical precision individualization treatment.

Surface and Interface Engineering of Zn Anodes in Aqueous Rechargeable Zn-Ion Batteries.

Rechargeable zinc-ion batteries (ZIBs) have shown great potential as an alternative to lithium-ion batteries. The ZIBs utilize Zn metal as the anode, which possesses many advantages such as low cost, high safety, eco-friendliness, and high capacity. However, on the other hand, the Zn anode also suffers from many issues, including dendritic growth, corrosion, and passivation. These issues are largely related to the surface and interface properties of the Zn anode. Many efforts have therefore been devoted to the modification of the Zn anode, aiming to eliminate the above-mentioned problems. This review gives a comprehensive summary on the mechanism behind these issues as well as the recent progress on Zn anode modification with focus on the strategies of surface and interface engineering, covering the design and application of both the Zn anode supports and surface protective layers, along with abundant examples. In addition, the promising research directions and perspective on these strategies are also presented.

Develop a stepwise integrated method to screen biomarkers of Baihe-Dihuang Tang on the treatment of depression in rats applying with composition screened, untargeted, and targeted metabolomics analysis.

Baihe-Dihuang Tang is a commonly prescribed remedy for depression. In this study, component screening with untargeted and targeted metabolomics was used to identify potential biomarkers for depression in chronic unpredictable mildly stressed rats. Using this novel identification method, the screening of organic acids, lily saponins, iridoids, and other ingredients formed the basis for subsequent metabolomics research. Baihe-Dihuang Tang supplementation in chronic unpredictable mild-stress-induced depression models, increased their body weight, sucrose preference, brain-derived neurotrophic factor deposition, and spatial exploring. Untargeted metabolomics revealed that Baihe-Dihuang Tang exerts its antidepressant effects by regulating the levels of lipids, organic acids, and its derivatives, and benzenoids in the brain, plasma, and urine of the depressed rats. Moreover, it also modulates the d-glutamine and d-glutamate metabolism and purine metabolism. Targeted metabolomics demonstrated significant reduction in l-glutamate levels in the brains of depressed rats. This could be a potential biomarker for depression. Baihe-Dihuang Tang alleviated depression by regulating the levels of l-glutamate, xanthine, and adenine in the brains of depressed rats. Together, these findings conclusively established the promising therapeutic effect of Baihe-Dihuang Tang on depression and also unraveled the underlying molecular mechanism of its potential antidepressant function.