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Inefficient conversion of small molecule maltooligosaccharides into trehalose greatly affects the cost of the production of trehalose by double enzyme method [maltooligosyl trehalose synthase (MTSase) and maltooligosyl trehalose trehalohyrolase (MTHase)]. This study used directed evolution to increase oligosaccharide utilization by the cyclomaltodextrin glucanotransferase (CGTase) from Bacillus species G1. This enzyme was chosen for its adaptability and stability in trehalose production. Model analysis revealed that the hydrogen bond distance between the N33K mutant and maltose reduced from 2.6 Å to 2.3 Å, increasing maltose affinity and boosting transglycosylation activity by 2.1-fold compared to the wild type. Further mutations improved thermal stability and optimum temperature, resulting in the N33K/S211G mutant. Consistent results from repeated experiments showed that the N33K/S211G mutant increased trehalose yield by 32.6% using maltodextrin. The results enhanced the double-enzyme method formed by MTSase and MTHase for trehalose production. Overall, we have identified optimal catalytic conditions, demonstrating significant potential for industrial-scale trehalose production with enhanced efficiency and cost-effectiveness.

In the present study, the comprehensive quality of Congou black tea (CBT) including aroma, taste, and liquid color was investigated by a combination of gas chromatography electronic nose (GC-E-Nose), electronic tongue (E-tongue), and electronic eye (E-eye). An excellent discrimination of different quality grades of CBT was accomplished through the fusion of GC-E-Nose, E-tongue, and E-eye combined with orthogonal partial least squares discriminant analysis, with parameters of R2Y = 0.803 and Q2 = 0.740. Moreover, the quantitative evaluation of CBT quality was successfully achieved by partial least squares regression analysis, with the absolute error within 1.39 point, and the relative error within 1.62%. Additionally, 12 key variables were screened out by stepwise multiple linear regression analysis, which significantly contributed to the comprehensive quality score of CBT. Our results suggest that the fusion of multiple intelligent sensory technologies offers great potential and practicability in the quality evaluation of black tea.

Geographical regions profoundly influence the flavor characteristics of Congou black tea (CBT). In this study, 35 CBT samples from 7 geographical regions were comprehensively characterized by integrated multiple intelligent sensory technologies and untargeted metabolomics analysis. A satisfactory discrimination was achieved through the fusion of multiple intelligent sensory technologies (R2Y = 0.918, Q2 = 0.859). A total of 104 non-volatile and 169 volatile metabolites were identified by UHPLC-HRMS and GC–MS, respectively. Of these, 45 critical differential non-volatile metabolites and 76 pivotal differential volatile metabolites were pinpointed based on variable importance in projection >1 and p

Rolling plays an important role in shaping the characteristic quality of black tea. However, the dynamic alterations in volatile compounds during the rolling process remain unclear, which hampers the quality control of black tea. In this study, the dynamic changes of volatile compounds in Congou black tea throughout the rolling process were explored by a combination of GC-E-Nose and GC–MS analysis. The results of PCA and PLS-DA by GC-E-Nose revealed significant alterations in the volatile profiles, particularly at the 15-min rolling stage. A total of 82 volatile compounds including eight categories were identified in Congou black tea during the rolling process. The most abundant volatiles were aldehydes, alcohols, and esters. Through the integration of variable importance in the projection >1 and p

As a crucial stage in the processing of black tea, rolling plays a significant role in both the color transformation and the quality development of the tea. In this process, the production of theaflavins, thearubigins, and theabrownins is a primary factor contributing to the alteration in color of rolled leaves. Herein, tea pigments are selected as the key quality indicators during rolling of black tea, aiming to establish rapid detection methods for them. A machine vision system is employed to extract nine color feature variables from the images of samples subjected to varying rolling times. Then, the tea pigment content in the corresponding samples is determined using a UV-visible spectrophotometer. In the meantime, the correlation between color variables and tea pigments is discussed. Additionally, Z-score and PCA are used to eliminate the magnitude difference and redundant information in original data. Finally, the quantitative prediction models of tea pigments based on the images’ color features are established by using PLSR, SVR, and ELM. The data show that the Z-score–PCA–ELM model has the best prediction effect for tea pigments. The Rp values for the model prediction sets are all over 0.96, and the RPD values are all greater than 3.50. In this study, rapid determination methods for tea pigments during rolling of black tea are established. These methods offer significant technical support for the digital production of black tea.

Aroma plays a pivotal role in the quality of black tea. However, the acceptability of black tea is greatly limited by the green off-flavor (GOF) resulting from the inappropriate processing control. In this study, the key odorants causing GOF were investigated by volatolomics, and their dynamic changes and formation pathways were in-depth understood. Significant alterations in volatile metabolites were observed in the withering stage. A total of 14 key odorants were identified as contributors to GOF, including 2-methylpropanal, 3-methylbutanal, 1-hexanol, nonanal, (E, E)-2,4-heptadienal, benzaldehyde, linalool, (E, E)-3,5-octadiene-2-one, β-cyclocitral, phenylacetaldehyde, (E, E)-2,4-nonadienal, methyl salicylate, geraniol, and β-ionone. Among them, (E, E)-2,4-heptadienal (OAV = 3913), characterized by fatty, green, and oily aromas, was considered to be the most important contributor causing GOF. Moreover, it was found that lipid degradation served as the primary metabolic pathway for GOF. This study provides a theoretical foundation for off-flavor control and quality improvement of black tea.

Cold stress causes considerable damage to tender tea seedlings. Previous studies have explored changes in the physiological and biochemical factors of tea in response to cold stress; however, the mechanisms of cold resistance in ancient tea tree plants are unclear. The aim of this study was to analyze the effects of 0 °C cold stress for 15 days and 24 °C ambient temperature recovery for 5 days on the physiological and biochemical characteristics of two representative old tea varieties: Dali tea and Siqiu tea. The results revealed significant changes in antioxidant, photosynthetic efficiency, and physiological and biochemical indicators in response to cold stress, with the two species exhibiting different patterns. Cold stress decreased chlorophyll and carotene content, Fv/Fm, Y(II), non-photochemical quenching coefficient, photochemical quenching, and superoxide dismutase (SOD) activity, and increased intercellular CO2 concentration and ascorbate peroxidase activity. Siqiu tea showed a higher increase in soluble sugar content and antioxidant enzyme activity and a lower accumulation of malondialdehyde and minimal fluorescence (F0) than Dali, indicating a greater tolerance to cold stress. Based on partial least-squares discriminant analysis, six key differential physiological indicators of cold resistance—water-soluble sugar, F0, peroxidase, catalase, SOD, and gas conductance—were identified. Our findings provide technical support for identifying ways to protect ancient tea trees from extreme weather conditions.

Abstract Multi-enzyme complexes designed based on scaffold proteins are a current topic in molecular enzyme engineering. They have been gradually applied to increase the production of enzyme cascades, thereby achieving effective biosynthetic pathways. This paper reviews the recent progress in the design strategy and application of multi-enzyme complexes. First, the metabolic channels in the multi-enzyme complex have been introduced, and the construction strategies of the multi-enzyme complex emerging in recent years have been summarized. Then, the discovered enzyme cascades related to scaffold proteins are discussed, emphasizing on the influence of the linker on the fusion enzyme (fusion protein) and its possible mechanism. This review is expected to provide a more theoretical basis for the modification of multi-enzyme complexes and broaden their applications in synthetic biology.

We search for an optimal filter design for the estimation of stellar metallicity, based on synthetic photometry from Gaia XP spectra convolved with a series of filter-transmission curves defined by different central wavelengths and bandwidths. Unlike previous designs based solely on maximizing metallicity sensitivity, we find that the optimal solution provides a balance between the sensitivity and uncertainty of the spectra. With this optimal filter design, the best precision of metallicity estimates for relatively bright ( G ∼ 11.5) stars is excellent, σ _[Fe/H] = 0.034 dex for FGK dwarf stars, superior to that obtained utilizing custom sensitivity-optimized filters (e.g., SkyMapper v ). By selecting hundreds of high-probability member stars of the open cluster M67, our analysis reveals that the intrinsic photometric-metallicity scatter of these cluster members is only 0.036 dex, consistent with this level of precision. Our results clearly demonstrate that the internal precision of photometric-metallicity estimates can be extremely high, even providing the opportunity to perform chemical tagging for very large numbers of field stars in the Milky Way. This experiment shows that it is crucial to take into account uncertainty alongside the sensitivity when designing filters for measuring the stellar metallicity and other parameters.

Lipids are important tea aroma precursors. Due to the complexity of black tea processing involving both enzymatic and thermal reactions, the role of lipids in black tea aroma formation remained unclear. Herein, the dynamic changes of lipids and volatiles during black tea processing were simultaneously analyzed by lipidomics and volatolomics using ultra-high-performance liquid chromatography coupled to Q-Exactive Orbitrap mass spectrometry (UHPLC-Q-Exactive) and gas chromatography-tandem mass spectrometry (GC-MS/MS). The lipidomics method was validated in linearity, reproducibility, and recovery, which showed a high reliability. A total of 374 lipids and 88 volatiles were detected. Among them, 362 lipids and 29 fatty acid-derived volatiles (FADVs) were significantly altered depending on different processing stages. During the enzyme-driven stages of black tea processing (withering, rolling and fermentation), monogalactosyldiacylglycerol (MGDG), phosphatidylcholine (PC), and phosphatidylethanolamine (PE) were largely downregulated (

Rolling represents an essential stage in congou black tea processing. However, the influence of rolling pressure on tea flavor and non-volatile compounds remains unclear. Herein, a combination of untargeted metabolomics, tea pigments quantification, E-tongue, colorimeter and sensory evaluation was used to evaluate the effect of rolling pressure on black tea quality. As the rolling pressure increased, theaflavins (TFs), thearubigins (TRs), and theabrownins (TBs) significantly elevated. The tea metabolic profiles fluctuated and 47 metabolites were identified as key differential metabolites including flavan-3-ols, flavonol/flavone glycosides, phenolic acids, amino acids. These substances altered possibly due to the variations in enzymatic oxidation of tea phenolics and amino acids. Overall, black tea with moderate rolling pressure presented higher sweetness, lower bitterness, and higher quality index (10 TFs + TRs)/TBs. The results were verified by a validation batch. This study provided new insights into the regulation of rolling pressure and a guidance for black tea processing.

Shaking is an innovative technology employed in black tea processing to enhance flavor. However, the effects of shaking on the evolutionary mechanisms of volatile metabolites (VMs) remain unclear. In this study, we compared the effects of a shaking–withering method with those of traditional withering on the flavor and VMs transformation of black tea. The results showed that black tea treated with shaking exhibited excellent quality with floral and fruity aroma. Based on gas chromatography-tandem mass spectrometry, 128 VMs (eight categories) were detected. Combining variable importance projection with odor activity value analysis, eight key differential VMs were identified. Shaking could promote the oxidative degradation of fatty acids and carotenoids and modulate the biosynthesis of terpenoids to facilitate the formation of floral/fruity VMs (such as (Z)-hexanoic acid-3-hexenyl ester, ethyl hexanoate, trans-β-ionone, and decanal). Our findings provide theoretical guidance for the production of high-quality black tea with floral and fruity aromas.

ABSTRACTSopF, a newly discovered effector secreted by Salmonella pathogenicity island-1 type III secretion system (T3SS1), was reported to target phosphoinositide on host cell membrane and aggravate systemic infection, while its functional relevance and underlying mechanisms have yet to be elucidated. PANoptosis (pyroptosis, apoptosis, and necroptosis) of intestinal epithelial cells (IECs) has been characterized as a pivotal host defense to limit the dissemination of foodborne pathogens, whereas the effect of SopF on IECs PANoptosis induced by Salmonella is rather limited. Here, we show that SopF can attenuate intestinal inflammation and suppress IECs expulsion to promote bacterial dissemination in mice infected with Salmonella enterica serovar Typhimurium (S. Typhimurium). We revealed that SopF could activate phosphoinositide-dependent protein kinase-1 (PDK1) to phosphorylate p90 ribosomal S6 kinase (RSK) which down-regulated Caspase-8 activation. Caspase-8 inactivated by SopF resulted in inhibition of pyroptosis and apoptosis, but promotion of necroptosis. The administration of both AR-12 (PDK1 inhibitor) and BI-D1870 (RSK inhibitor) potentially overcame Caspase-8 blockade and subverted PANoptosis challenged by SopF. Collectively, these findings demonstrate that this virulence strategy elicited by SopF aggregates systemic infection via modulating IEC PANoptosis through PDK1-RSK signaling, which throws light on novel functions of bacterial effectors, as well as a mechanism employed by pathogens to counteract host immune defense.

Abstract Introduction This study is to examine the predictors of survival and to construct a nomogram for predicting the overall survival (OS) of primary bladder signet ring cell carcinoma (SRCC) patients based on the analysis of the Surveillance, Epidemiology, and End Results (SEER) database. Methods A total of 219 eligible patients diagnosed with SRCC were analyzed using the 2004–2015 data from SEER database. Univariate and multivariate Cox regression were used to determine independent prognostic factors, followed by development of a nomogram based on the multivariate Cox regression models. The consistency index (C-index), receiver operating characteristic (ROC) curve, and calibration curve were used to validate the prognostic nomogram. Results The nomograms indicated appreciable accuracy in predicting the OS, with C-index of 0.771 and 0.715, respectively. The area under the curve (AUC) of the nomogram was 0.713 for 1 year, 0.742 for 3 years, and 0.776 for 5 years in the training set, while was 0.730 for 1 year, 0.727 for 3 years, and 0.697 for 5 years in the validation set. The calibration curves revealed satisfactory consistency between the prediction of deviation correction and ideal reference line. Conclusions The prognostic nomogram developed in the analytical data of SEER it provided high accuracy and reliability in predicting the survival outcomes of primary bladder SRCC patients and could be used to comprehensively assess the risk of SRCC. Moreover, they could enable clinicians to make more precise treatment decisions for primary bladder SRCC patients.

To inhibit commutation failure (CF), in this paper, the influence factors of CF were analyzed, and considering different fault types and different valves, the mathematical expression of extinction angle was deduced. In addition, by analyzing existing control strategies for inhibiting CF, it is indicated that existing control strategies cannot quickly and accurately obtain the AC voltage amplitude and zero-crossing phase shift angle. To solve this problem, this paper proposed a fast AC voltage measurement method, and the zero-crossing phase shift angle can be calculated by AC voltage amplitude. On this basis, a commutation failure predictive control method (CFPCM) was proposed to inhibit CF. The CFPCM can adapt to all fault types. Finally, based on the CIGRE HVDC benchmark model, the commutation failure prevention module (CFPREV) and CFPCM simulation model were built using PSCAD/EMTDC to verify the effectiveness of the proposed CFPCM. The simulation results showed that the CFPCM can not only inhibit CF more effectively, but also reduce the fluctuation of DC current, AC voltage, and extinction angle with a fault occurred in the inverter AC system.

This paper aimed to explore the biochemical characteristics of fresh leaf raw materials of large-leaf cultivars. In this study, four different tenderness fresh tea leaves of single bud, one bud with one leaf, one bud with two leaves and one bud with three leaves picked from Yunnan large-leaf cultivars (Qingshui No.3, Xianggui Yinhao, Yunkang No.10, Yunkang No.14, Yuncha Purui) were selected as the research objects. The variation of raw material taste quality with tenderness of different varieties of Yunnan large-leaf cultivars was investigated by detecting the content of its main flavor substances (tea polyphenols, flavonoids, amino acids and soluble sugars, etc.). Multivariate statistical methods were used to explore the categories and key differential indexes of fresh leaves with different tenderness, meanwhile, fisher discriminant analysis was used to establish the discriminant models for different types of fresh leaves. The results showed that the higher the maturity of fresh leaves, the higher values of phenol ammonia ratio, simple catechins, flavonoid glycosides and peroxidase would be, and one bud with two leaves and one bud with three leaves were significantly higher than single bud and one bud with one leaf (P

Despite the importance of fixation in determining green tea quality, its role in reducing the bitter and astringent taste of this beverage remains largely unknown. Herein, an electromagnetic roller-hot-air–steam triple-coupled fixation (ERHSF) device was developed, and its operating parameters were optimized (steam volume: 20 kg/h; hot-air temperature: 90 °C; hot-air blower speed: 1200 r/min). Compared with conventional fixation treated samples, the ratio of tea polyphenols to free amino acids and ester-catechins to simple-catechins in ERHSF-treated samples was reduced by 11.0% and 3.2%, reducing bitterness and astringency of green tea; amino acids, soluble sugars, and chlorophyll contents were significantly increased, enhancing the freshness, sweetness, and greenness; the color indexes, such as L/L* value of brightness and -a/-a* value of greenness, were also improved, and ERHSF-treated samples had the highest sensory scores. These results provided theoretical support and technical guidance for precise quality improvement of summer-autumn green tea.

Introduction: Trehalose is a significant rare sugar known for its stable properties and ability to protect biomolecules from environmental factors.Methods: In this study, we present a novel approach utilizing a scaffold protein-mediated assembly method for the formation of a trehalose bi-enzyme complex. This complex consists of maltooligosyltrehalose synthase (MTSase) and maltooligosyltrehalose trehalohydrolase (MTHase), which work in tandem to catalyze the substrate and enhance the overall catalytic efficiency. Utilizing the specific interaction between cohesin and dockerin, this study presents the implementation of an assembly, an analysis of its efficiency, and an exploration of strategies to enhance enzyme utilization through the construction of a bi-enzyme complex under optimal conditions in vitro.Results and Discussion: The bi-enzyme complex demonstrated a trehalose production level 1.5 times higher than that of the free enzyme mixture at 40 h, with a sustained upward trend. Compared to free enzyme mixtures, the adoption of a scaffold protein-mediated bi-enzyme complex may improve cascade reactions and catalytic effects, thus presenting promising prospects.

Aroma is an indispensable factor that substantially impacts the quality assessment of black tea. This study aims to uncover the dynamic alterations in the sweet and floral aroma black tea (SFABT) throughout various manufacturing stages using a comprehensive analytical approach integrating gas chromatography electronic nose, gas chromatography–ion mobility spectrometry (GC-IMS), and gas chromatography–mass spectrometry (GC-MS). Notable alterations in volatile components were discerned during processing, predominantly during the rolling stage. A total of 59 typical volatile compounds were identified through GC-IMS, whereas 106 volatile components were recognized via GC-MS throughout the entire manufacturing process. Among them, 14 volatile compounds, such as linalool, β-ionone, dimethyl sulfide, and 1-octen-3-ol, stood out as characteristic components responsible for SFABT with relative odor activity values exceeding one. This study serves as an invaluable theoretical platform for strategic controllable processing of superior-quality black tea.

Storage time is one of the important factors affecting the aroma quality of Pu-erh tea. In this study, the dynamic changes of volatile profiles of Pu-erh teas stored for different years were investigated by combining gas chromatography electronic nose (GC-E-Nose), gas chromatography-mass spectrometry (GC–MS), and gas chromatography-ion mobility spectrometry (GC-IMS). GC-E-Nose combined with partial least squares-discriminant analysis (PLS-DA) realized the rapid discrimination of Pu-erh tea with different storage time (R2Y = 0.992, Q2 = 0.968). There were 43 and 91 volatile compounds identified by GC–MS and GC-IMS, respectively. A satisfactory discrimination (R2Y = 0.991, and Q2 = 0.966) was achieved by using PLS-DA based on the volatile fingerprints of GC-IMS. Moreover, according to the multivariate analysis of VIP > 1.2 and univariate analysis of p

In this study, four kinds of Longjing tea, the famous flat green tea and the protected geographical indication product in China, were used to explore the quality difference of the same green tea due to the cultivar, geographic origin, and storage time under the premise of consistent picking conditions and processing technology using the widely targeted metabolomics. Results showed that 483 flavonoid metabolites with 10 subgroups of flavonoids were screened and 118 differential flavonoid metabolites were identified. The number and subgroups of differential flavonoid metabolites produced by different cultivars of Longjing tea were the largest, followed by storage time, and third by the geographic origin. Glycosidification and methylation or methoxylation were the main structural modifications of differential flavonoid metabolites. This study has enriched the understanding of the effects of the cultivar, the geographic origin, and the storage time on the flavonoid metabolic profiles of Longjing tea, and provided worthy information for the traceability of green tea.

We report the discovery of a close binary J0606+2132 (Gaia DR3 3423365496448406272) with P _obs = 2.77 days containing a possible massive white dwarf (WD) or a neutron star (NS) using LAMOST spectroscopic data. By a joint fitting of the radial velocity from LAMOST and the light curve from TESS, we derived a circular Keplerian orbit with an inclination of i = 81.°31 ${}_{-7.85^\circ }^{+6.26^\circ }$ , which is consistent with that derived from $v\,\sin \,i$ . Together with the mass of the visible star, we derived the mass of the invisible object to be ${1.34}_{-0.40}^{+0.35}{M}_{\odot }$ . Spectral disentangling with the LAMOST medium-resolution spectra shows no absorption feature from an additional component, suggesting the presence of a compact object. No X-ray or radio pulsed signal is detected from ROSAT and FAST archive observations. J0606+2132 could evolve into either a Type Ia supernova or an NS through accretion-induced collapse if it is a WD or into an intermediate-mass X-ray binary if it is an NS.

Using integral field spectroscopy (IFS) from MaNGA, we study the resolved microstructures in a shocked region in the Criss-cross Nebula (CCN), with an unprecedentedly high resolution of ≲1000 au. We measure surface brightness maps for 34 emission lines, which can be broadly divided into three categories: (1) the [O iii ] λ 5007-like group including seven high-ionization lines and two [O ii ] auroral lines that uniformly present a remarkable lane structure, (2) the H α λ 6563-like group, including 23 low-ionization or recombination lines that present a clump-like structure, and (3) [O ii ] λ 3726 and [O ii ] λ 3729 showing high densities at both the [O iii ] λ 5007 lane and the H α clump. We use these measurements to constrain resolved shock models implemented in MAPPINGS V . We find our data can be reasonably well fitted by a model that includes a plane-parallel shock with a velocity of 133 ± 5 km s ^−1 , plus an isotropic two-dimensional Gaussian component, which is likely another clump of gas ionized by photons from the shocked region, and a constant background. We compare the electron density and temperature profiles as predicted by our model with those calculated using observed emission-line ratios. We find different line ratios to provide inconsistent temperature maps, and the discrepancies can be attributed to observational effects caused by limited spatial resolution and projection of the shock geometry, as well as contamination of the additional Gaussian component. Implications on shock properties and perspectives on future IFS-based studies of the CCN are discussed.

By combining spectra from the CALSPEC and NGSL, as well as spectroscopic data from the LAMOST Data Release 7 (DR7), we have analyzed and corrected the systematic errors of the Gaia DR3 BP/RP (XP) spectra. The errors depend on the normalized spectral energy distribution (simplified by two independent “colors”) and G magnitude. Our corrections are applicable in the range of approximately −0.5 < BP − RP < 2, 3 < G < 17.5, and E ( B − V ) < 0.8. To validate our correction, we conduct independent tests by comparisons with the MILES and LEMONY spectra. The results demonstrate that the systematic errors of BP − RP and G have been effectively corrected, especially in the near-ultraviolet. The consistency between the corrected Gaia XP spectra and the MILES and LEMONY is better than 2% in the wavelength range of 336–400 nm and 1% in redder wavelengths. A global absolute calibration is also carried out by comparing the synthetic Gaia photometry from the corrected XP spectra with the corrected Gaia DR3 photometry. Our study opens up new possibilities for using XP spectra in many fields. A Python package is publicly available to do the corrections (doi: https://doi.org/10.12149/101375 or https://github.com/HiromonGON/GaiaXPcorrection ).

The upcoming Chinese Space Station Telescope (CSST) slitless spectroscopic survey poses a challenge of flux calibration, which requires a large number of flux-standard stars. In this work, we design an uncertainty-aware residual attention network, the UaRA-net, to derive the CSST spectral energy distributions (SEDs) with a resolution of R = 200 over the wavelength range of 2500–10000 Å using LAMOST normalized spectra with a resolution of R = 2000 over the wavelength range of 4000–7000 Å. With the special structure and training strategy, the proposed model provides accurate predictions not only of SEDs, but also of their corresponding errors. The precision of the predicted SEDs depends on the effective temperature ( T _eff ), wavelength, and the LAMOST spectral signal-to-noise ratios (S/Ns), particularly in the GU band. For stars with T _eff = 6000 K, the typical SED precisions in the GU band are 4.2%, 2.1%, and 1.5% at S/N values of 20, 40, and 80, respectively. As T _eff increases to 8000 K, the precision increases to 1.2%, 0.6%, and 0.5%, respectively. The precision is higher at redder wavelengths. In the GI band, the typical SED precisions for stars with T _eff = 6000 K increase to 0.3%, 0.1%, and 0.1% at S/N values of 20, 40, and 80, respectively. We further verify our model using empirical MILES spectra and find a good performance. The proposed method will open up new possibilities for the optimal use of slitless spectra of the CSST and other surveys.

The Gaia Data Release 3 (DR3) mission has identified and provided about 440,000 binary systems with orbital solutions, offering a valuable resource for searching binaries including a compact component. By combining the Gaia DR3 data with radial velocities from the LAMOST spectroscopic survey, we identify three wide binaries possibly containing a compact object. For two of these sources with a main-sequence companion, no obvious excess is observed in the blue/red band of the Gaia DR3 XP spectra, and the LAMOST medium-resolution spectra exhibit clear single-lined features. The absence of an additional component from spectral disentangling analysis further suggests the presence of compact objects within these systems. On the other hand, the visible star of the third source is a stripped giant star. In contrast to most binaries including stripped stars, no emission line is detected in the optical spectra. The unseen star could potentially be a massive white dwarf or neutron star, but the possibility of an F-type dwarf star scenario cannot be ruled out. An examination of about 10 binaries containing white dwarfs or neutron stars using both kinematic and chemical methods suggests most of these systems are located in the thin disk of the Milky Way.

We present a comprehensive recalibration of narrowband/medium-band and broadband photometry from the Southern Photometric Local Universe Survey (S-PLUS) by leveraging two approaches: an improved Gaia XP synthetic photometry (XPSP) method with corrected Gaia XP spectra, and the stellar color regression (SCR) method with corrected Gaia Early Data Release 3 photometric data and spectroscopic data from LAMOST Data Release 7. Through the use of millions of stars as standards per band, we demonstrate the existence of position-dependent systematic errors, up to 23 mmag for the main survey region, in the S-PLUS iDR4 photometric data. A comparison between the XPSP and SCR methods reveals minor differences in zero-point offsets, typically within the range of 1–6 mmag, indicating the accuracy of the recalibration, and a twofold to threefold improvement in the zero-point precision. During this process, we also verify and correct for systematic errors related to CCD position. The corrected S-PLUS iDR4 photometric data will provide a solid data foundation for conducting scientific research that relies on high-precision calibration. Our results underscore the power of the XPSP method in combination with the SCR method, showcasing their effectiveness in enhancing calibration precision for wide-field surveys when combined with Gaia photometry and XP spectra, to be applied for other S-PLUS subsurveys.

During the early merger of the Milky Way, intermediate-mass black holes (BHs) in merged dwarf galaxies may have been ejected from the center of their host galaxies due to gravitational waves, carrying some central stars along. This process can lead to the formation of hypercompact star clusters, potentially hosting BHs in the mass range of 10 ^4 –10 ^5 solar masses. These clusters are crucial targets for identifying and investigating intermediate-mass BHs. However, no hypercompact star clusters in the Milky Way have been identified so far. In this paper, taking advantage of the high spatial resolution power of Gaia, we used data from Gaia Early Data Release (EDR) 3 and Large-Area Multi-Object Fiber Optic Spectroscopic Telescope Data Release 7, along with additional data from Pan-STARRS and the Sloan Digital Sky Survey, to conduct an initial screening of 6,138,049 sources using various parameters of Gaia EDR3. A total of 4786 sources were selected for in-depth analysis. Each of these sources was meticulously scrutinized by examining their images, spectra, and nearby celestial objects to exclude various false positives, such as contaminations, galaxies, wide binaries, or wrong matches. We finally identified one likely hypercompact star cluster candidate in the Milky Way, laying the foundation for further high-resolution imaging and spectral verification.

Utilizing high-cadence and continuous g - and r -band data over three nights acquired from the 3.6 m Canada–France–Hawaii Telescope, aiming to find short-duration microlensing events, we conduct a systematic search for variables, transients, and asteroids across a ∼1° field of view of the Andromeda galaxy (M31). We present a catalog of 5859 variable stars, yielding the most extensive compilation of short-period variable sources of M31. We also detected 19 flares, predominantly associated with foreground M dwarfs in the Milky Way. In addition, we discovered 17 previously unknown asteroid candidates, and we subsequently reported them to the Minor Planet Center. Lastly, we report a microlensing event candidate C-ML-1 and present a preliminary analysis.

Photometric stellar surveys now cover a large fraction of the sky, probe to fainter magnitudes than large-scale spectroscopic surveys, and are relatively free from the target selection biases often associated with such studies. Photometric-metallicity estimates that include narrow/medium-band filters can achieve comparable accuracy and precision to existing low-resolution spectroscopic surveys such as Sloan Digital Sky Survey/SEGUE and LAMOST. Here we report on an effort to identify likely members of the Galactic disk system among the very metal-poor (VMP; [Fe/H] ≤ −2) and extremely metal-poor (EMP; [Fe/H] ≤ −3) stars. Our analysis is based on an initial sample of ∼11.5 million stars with full space motions selected from the SkyMapper Southern Survey (SMSS) and Stellar Abundance and Galactic Evolution Survey (SAGES). After applying a number of quality cuts to obtain the best available metallicity and dynamical estimates, we analyze a total of ∼5.86 million stars in the combined SMSS/SAGES sample. We employ two techniques that, depending on the method, identify between 876 and 1476 VMP stars (6.9%−11.7% of all VMP stars) and between 40 and 59 EMP stars (12.4%−18.3% of all EMP stars) that appear to be members of the Galactic disk system on highly prograde orbits ( v _ϕ > 150 km s ^−1 ). The total number of candidate VMP/EMP disklike stars is 1496, the majority of which have low orbital eccentricities, ecc ≤ 0.4; many have ecc ≤ 0.2. The large fractions of VMP/EMP stars associated with the Milky Way disk system strongly suggest the presence of an early-forming “primordial” disk.

We combine photometric data from GALEX GR6+7 All-Sky Imaging Survey and Gaia Early Data Release 3 with stellar parameters from the SAGA and PASTEL catalogs to construct high-quality training samples for dwarfs (0.4 < BP − RP < 1.6) and giants (0.6 < BP − RP < 1.6). We apply careful reddening corrections using empirical temperature- and extinction-dependent extinction coefficients. Using the two samples, we establish a relationship between stellar loci (near-ultraviolet (NUV)−BP versus BP − RP colors), metallicity, and M _G . For a given BP − RP color, a 1 dex change in [Fe/H] corresponds to an approximately 1 magnitude change in NUV − BP color for solar-type stars. These relationships are employed to estimate metallicities based on NUV − BP, BP − RP, and M _G . Thanks to the strong metallicity dependence in the GALEX NUV band, our models enable a typical photometric-metallicity precision of approximately σ _[Fe/H] = 0.11 dex for dwarfs and σ _[Fe/H] = 0.17 dex for giants, with an effective metallicity range extending down to [Fe/H] = −3.0 for dwarfs and [Fe/H] = −4.0 for giants. We also find that the NUV-band-based photometric-metallicity estimate is not as strongly affected by carbon enhancement as previous photometric techniques. With the GALEX and Gaia data, we have estimated metallicities for about 5 million stars across almost the entire sky, including approximately 4.5 million dwarfs and 0.5 million giants. This work demonstrates the potential of the NUV band for estimating photometric metallicities, and sets the groundwork for utilizing the NUV data from space telescopes such as the upcoming Chinese Space Station Telescope.

We present a direct measurement of extinction curves using corrected Gaia XP spectra of the common sources in Gaia DR3 and LAMOST DR7. Our analysis of approximately 370,000 high-quality samples yielded a high-precision average extinction curve for the Milky Way. After incorporating infrared photometric data from Two Micron All Sky Survey and Wide-field Infrared Survey Explorer, the extinction curve spans wavelengths from 0.336 to 4.6 μ m. We determine an average R _55 of 2.730 ± 0.007, corresponding to R _V = 3.073 ± 0.009, and a near-infrared power-law index α of 1.935 ± 0.037. Our study confirmed some intermediate-scale structures within the optical range. One new feature was identified at 540 nm, and its intensity exhibited a correlation with extinction. This extinction curve can be used to investigate the characteristics of dust and enhance the extinction correction of Milky Way stars. A Python package for this extinction curve is available.

Gaia DR3 photometry and Blue Photometer (BP) and Red Photometer (RP) spectra have been widely used as reference in photometric calibrations. In this work, we check the spatial uniformity of Gaia DR3 photometry and BP/RP spectra by comparing the BP, RP, and G -band photometry with the synthetic ones from the BP/RP spectra. The discrepancies have a small dispersion of 1.07, 0.55, and 1.02 mmag for the BP, RP, and G bands, respectively. However, the discrepancies exhibit obvious spatial patterns, which are clearly associated with Gaia’s scanning law. The patterns observed in the BP and G bands are similar, with discrepancies between photometry and spectra being more pronounced in these bands compared to the RP band. A further independent test with the Dark Energy Survey DR2 photometry reveals that the spatial patterns are more likely attributed to the Gaia DR3 BP/RP spectra, particularly in the BP band. On one hand, our results confirm the high spatial uniformity of Gaia data at the mmag level. On the other hand, our results suggest that the spatial uniformity of Gaia DR3 BP/RP spectra is not as good as that of Gaia DR3 photometry, and could be further improved in the future.

We present a catalog of stellar parameters (effective temperature T _eff , surface gravity $\mathrm{log}g$ , age, and metallicity [Fe/H]) and elemental-abundance ratios ([C/Fe], [Mg/Fe], and [ α /Fe]) for some five million stars (4.5 million dwarfs and 0.5 million giant stars) in the Milky Way, based on stellar colors from the Javalambre Photometric Local Universe Survey (J-PLUS) DR3 and Gaia EDR3. These estimates are obtained through the construction of a large spectroscopic training set with parameters and abundances adjusted to uniform scales, and trained with a kernel principal component analysis. Owing to the seven narrow/medium-band filters employed by J-PLUS, we obtain precisions in the abundance estimates that are as good as or better than those derived from medium-resolution spectroscopy for stars covering a wide range of the parameter space: 0.10–0.20 dex for [Fe/H] and [C/Fe], and 0.05 dex for [Mg/Fe] and [ α /Fe]. Moreover, systematic errors due to the influence of molecular carbon bands on previous photometric-metallicity estimates (which only included two narrow/medium-band blue filters) have now been removed, resulting in photometric-metallicity estimates down to [Fe/H] ∼ −4.0, with typical uncertainties of 0.40 dex and 0.25 dex for dwarfs and giants, respectively. This large photometric sample should prove useful for the exploration of the assembly and chemical-evolution history of our Galaxy.

Vitamin C, a water-soluble vitamin with strong reducing power, cannot be synthesized by the human body and participates in a variety of important biochemical reactions. Vitamin C is widely used in the pharmaceutical, food, health care, beverage, cosmetics, and feed industries, with a huge market demand. The classical two-step fermentation method is the mainstream technology for vitamin C production. D-sorbitol is transformed into L-sorbose by Gluconobacter oxydans in the first step of fermentation; then, L-sorbose is transformed into 2-keto-L-gulonic acid (2-KGA) by a coculture system composed of Ketogulonicigenium vulgare and associated bacteria; and finally, 2-KGA is transformed into vitamin C through chemical transformation. The conversion of L-sorbose into 2-KGA in the second fermentation step is performed by K. vulgare. However, considering the slow growth and low 2-KGA production of K. vulgare when cultured alone, it is necessary to add an associated bacteria to stimulate K. vulgare growth and 2-KGA production. Although the mechanism by which the associated bacteria promote K. vulgare growth and 2-KGA production has extensively been studied, this remains a hot topic in related fields. Based on the latest achievements and research, this review summarizes the metabolic characteristics of K. vulgare and associated bacteria and elucidates the mechanism by which the associated bacteria promote the growth and 2-KGA production of K. vulgare.

Withering is an important processing stage in green tea, which contributes to the tea flavor quality. The aim of this work was to comprehensively investigate the changes of chemical features and flavor attributes in Longjing green teas produced with five different withering degrees (moisture content of 75.05, 72.53, 70.07, 68.00, and 64.78%, w.b.). Combined with human sensory evaluation, electronic tongue and chromatic differences analysis, an assessment of the relationship between the withering degree and the sensory quality of Longjing tea was obtained. By using a non-targeted metabolomics approach, 69 significantly differential metabolites were screened. As the withering degree increased, most free amino acids and catechin dimers were increased, largely attributed to the hydrolysis of proteins and catechin oxidative polymerization, respectively. The contents of organic acids as well as phenolic acids and derivatives were reduced. Interestingly, flavone C-glycosides decreased overall while flavonol O-glycosides increased. The correlation analysis revealed that metabolites such as theasinensin F, theasinensin B, theaflavin, theaflavin-3,3′-gallate, theaflavin-3′-gallate, malic acid, succinic acid, quinic acid, theanine glucoside and galloylglucose had a greater influence on the taste and color of tea infusion (|r| > 0.6, p

The time-frequency system has become national strategic resource.The application of time-frequency scientific data is related to communications, electricity, transportation, warfare, etc.It has important practical significance for the sorting, management control, and application analysis of time-frequency scientific data.Firstly, the classify and data sharing strategies of time-frequency scientific data were proposed, the detail of the structure about the time-frequency scientific data center management system and the quality control methods of time-frequency scientific data were discussed.Then the problems faced by the open sharing of time-frequency scientific data were analyzed and the solutions were given.Finally, several application directions of time-frequency scientific data were explained, and the management of time-frequency scientific data was summarized and prospected.

Tea’s biochemical compounds and flavor quality vary depending on its grade ranking. Dianhong Congou black tea (DCT) is a unique tea category produced using the large-leaf tea varieties from Yunnan, China. To date, the flavor characteristics and critical components of two grades of high-quality DCT, single-bud-grade DCT (BDCT), and special-grade DCT (SDCT) manufactured mainly with single buds and buds with one leaf, respectively, are far from clear. Herein, comparisons of two grades were performed by the integration of human sensory evaluation, an electronic tongue, chromatic differences, the quantification of major components, and metabolomics. The BDCT possessed a brisk, umami taste and a brighter infusion color, while the SDCT presented a comprehensive taste and redder liquor color. Quantification analysis showed that the levels of total polyphenols, catechins, and theaflavins (TFs) were significantly higher in the BDCT. Fifty-six different key compounds were screened by metabolomics, including catechins, flavone/flavonol glycosides, amino acids, phenolic acids, etc. Correlation analysis revealed that the sensory features of the BDCT and SDCT were attributed to their higher contents of catechins, TFs, theogallin, digalloylglucose, and accumulations of thearubigins (TRs), flavone/flavonol glycosides, and soluble sugars, respectively. This report is the first to focus on the comprehensive evaluation of the biochemical compositions and sensory characteristics of two grades of high-quality DCT, advancing the understanding of DCT from a multi-dimensional perspective.

Second-drying is a key process of green tea manufacturing, however, hitherto the effect of second-drying methods on green tea quality has not been assessed. In this study, we compared the effect of three heat transfer drying methods (heat radiation, heat convection, and heat conduction) on green tea quality. Gas chromatography-tandem dual mass spectrometry was used to detect volatile compounds, while absolute quantitative methods were used to detect the non-volatile ones. We identified 45 non-volatile metabolites, 101 volatile metabolites, and 15 objective flavor indicators. Seventeen differential non-volatiles and 8 differential volatiles were screened. Microwave second-drying in heat radiation was the optimal method for green tea flavor, as it can promote the retention of chlorophyll, the degradation of flavonoid glycosides, and the enrichment of amino acids, soluble sugars, nonanal, trans-β-ionone, linalool, and jasmone. The results provide a theoretical basis and technical guidance for the precise and directional processing of high-quality green tea.

Round green tea (RGT) is widely distributed and presents a high yield in China. The quality of RGT can be determined by its aroma; however, the transformation and formation of volatile metabolites during RGT processing remain unclear. In this study, 173 volatile compounds (nine categories) were identified totally from RGT via gas chromatography-mass spectrometry with infrared-assisted headspace-solid phase microextraction. These substances exhibited different changing trends during various procedures, with the most intense transformation occurring during fixation, followed by pan-frying and second drying; moreover, 51 substances were screened, mainly containing fatty acid-derived volatiles (i.e., (E)-2-hexen-1-ol, Hexanal, pentanal, hexanal) and glycoside-derived volatiles (i.e., linalool, geraniol, benzyl alcohol, benzaldehyde), and their evolution during processing was clarified. Furthermore, the effect of the second-drying temperature on volatile compound metabolism was clarified, and 90°C was the best temperature for RGT aroma. This research lays a foundation for in-depth quality control and the aroma formation mechanism of RGT.

Stellar chemical abundances are crucial and fundamental in astrophysics. However, they could suffer from substantial systematic errors according to several investigations but still lack calibrations in bulk. By using Gaia wide binaries, we find the temperature-dependent bias between the two binary components for [Fe/H] and [ α /Fe] measurements from the LAMOST low-resolution spectra and Gaia RVS spectra. At T _eff = 4000 K, the LAMOST [Fe/H] is significantly underestimated by approximately 0.4 dex when compared with its typical uncertainty of 0.1 dex. Its [ α /Fe] is overestimated by about 0.2 dex. For Gaia, the underestimation of [M/H] and overestimation of [ α /Fe] becomes pronounced near 7000 K with smaller magnitudes. We perform an internal calibration by minimizing the differences between the binary components and provide the correction curves. After corrections, the standard deviations of the residuals compared to the PASTEL catalog decrease from about 0.045/0.1 to 0.02/0.043 for LAMOST and Gaia, respectively. The chemical homogeneity of the open cluster M 44 is also improved by a factor of two. We stress that the underestimation of [Fe/H] could lead to an overestimation of binary fractions when selecting binary stars by the excess of luminosity. The method of this work could be applied to other data sets in the future. Our results will benefit statistic studies that use LAMOST and Gaia samples with a wide temperature range.

We present a spectroscopic analysis of T Tauri stars (TTSs) observed with the wide-field multifiber spectrograph LAMOST in the substellar associations Ori OB1a located in the Orion Star-forming Complex. Based on GAIA-DR3 data, we selected stars with proper motions and parallaxes expected for TTSs belonging to the young association. We perform a spectroscopic analysis to obtain the spectral types and measure the equivalent widths of Li i and H α to confirm the youth of the stars and estimate the accretion status. We also estimate extinctions, masses, and ages for the studied sample. Out of 342 TTSs with spectroscopic and kinematic properties indicating their membership of the subassociation, 2 are reported here for the first time. Finally, we detect four stellar kinematic groups located at different distances, two in the north fields and two in the south field. These groups also show different proper motions. This suggests that the star-forming scenario in this region is more complex than the traditional spatial-temporal scenario, in which a generation of stars triggers the formation of a new spatially differentiated generation of stars.

The Stellar Abundances and Galactic Evolution Survey (SAGES) of the northern sky is a specifically designed multiband photometric survey aiming to provide reliable stellar parameters with accuracy comparable to those from low-resolution optical spectra. It was carried out with the 2.3 m Bok telescope of Steward Observatory and three other telescopes. The observations in the u _s and v _s passband produced over 36,092 frames of images in total, covering a sky area of ∼9960 deg ^2 . The median survey completenesses of all observing fields for the two bands are u _s = 20.4 mag and v _s = 20.3 mag, respectively, while the limiting magnitudes with signal-to-noise ratio of 100 are u _s ∼ 17 mag and v _s ∼ 18 mag, correspondingly. We combined our catalog with the data release 1 (DR1) of the first Panoramic Survey Telescope And Rapid Response System (Pan-STARRS, PS1) catalog, and obtained a total of 48,553,987 sources that have at least one photometric measurement in each of the SAGES u _s and v _s and PS1 grizy passbands. This is the DR1 of SAGES, released in this paper. We compared our gri point-source photometry with those of PS1 and found an rms scatter of ∼2% difference between PS1 and SAGES for the same band. We estimated an internal photometric precision of SAGES to be of the order of ∼1%. Astrometric precision is better than 0.″2 based on comparison with DR1 of the Gaia mission. In this paper, we also describe the final end-user database, and provide some science applications.

We have found 50 new globular cluster (GC) candidates around M31 with Gaia Early Data Release 3 (EDR3), with the help of Pan-STARRS1 DR1 magnitudes and Pan-Andromeda Archaeological Survey (PAndAS) images. Based on the latest Revised Bologna Catalog and simbad , we trained two random forest (RF) classifiers, the first one to distinguish extended sources from point sources and the second one to further select GCs from extended sources. From 1.85 million sources of 16 ^m < g < 19.5 ^m and within a large area of ∼392 deg ^2 around M31, we selected 20,658 extended sources and 1934 initial GC candidates. After visual inspection of the PAndAS images, to eliminate the contamination from noncluster sources, particularly galaxies, we finally got 50 candidates. These candidates are divided into three types (a, b, and c), according to their projected distance D to the center of M31 and their probability of being a true GC, P _GC , which is calculated by our second RF classifier. Among these candidates, 14 are found to be associated (in projection) with the large-scale structures within the halo of M31. We also provide several simple parameter criteria for selecting extended sources effectively from Gaia EDR3, which can reach a completeness of 92.1% with a contamination fraction lower than 10%.

In this work, we perform the recalibration of Pan-STARRS1 (PS1) photometry by correcting for position-dependent systematic errors using the spectroscopy-based stellar color regression (SCR) method, the photometry-based SCR method, and the Gaia BP/RP synthetic photometry method. We confirm the significant large-scale and small-scale spatial variation of the magnitude offsets for all the grizy filters. We show that the PS1 photometric calibration precisions in the grizy filters are around 5–7 mmag when averaged over 14′ regions. We note a much larger calibration error up to 0.04 mag in the Galactic plane, which is probably caused by the systematic errors of the PS1 magnitudes in crowded fields. The results of the three methods are consistent with each other within 1–2 mmag or better for all the filters. We provide 2D maps and a Python package to correct for position-dependent magnitude offsets of PS1, which can be used for high-precision investigations and as a reference to calibrate other surveys.

The total-to-selective extinction ratio, R _V , is a key parameter for tracing the properties of interstellar dust, as it directly determines the variation of the extinction curve with wavelength. By utilizing accurate color excess measurements from the optical to the mid-infrared range, we have derived R _V values for approximately three million stars from LAMOST data release 7 using a forward-modeling technique. This extensive data set enables us to construct a comprehensive 2D R _V map of the Milky Way within the LAMOST footprint at a spatial resolution of ∼27.′5. Based on reliable sight lines of E ( B − V ) > 0.1, we find that R _V exhibits a Gaussian distribution centered around 3.25 with a standard deviation of 0.25. The spatial variability of R _V in the Galactic disk exhibits a wide range, spanning from small scales within individual molecular clouds to large scales up to kiloparsecs. A striking correlation is observed between the distribution of R _V and molecular clouds. Notably, we observe lower R _V values within the regions of nearby molecular clouds compared to their surrounding areas. Furthermore, we have investigated the relationships between R _V and various parameters, including dust temperature, dust emissivity spectral index, column densities and ratios of atomic and molecular hydrogen, as well as the gas-to-dust ratio. We find that these relationships vary with the level of extinction. These analyses provide new insights into the properties and evolution of dust grains in diverse interstellar environments and also hold significant importance for achieving accurate extinction corrections.

We present precise photometric estimates of stellar parameters, including effective temperature, metallicity, luminosity classification, distance, and stellar age, for nearly 26 million stars using the methodology developed in the first paper of this series, based on the stellar colors from the Stellar Abundances and Galactic Evolution Survey (SAGES) Data Release 1 and Gaia Early Data Release 3. The optimal design of stellar-parameter sensitive uv filters by SAGES has enabled us to determine photometric-metallicity estimates down to −3.5, similar to our previous results with the SkyMapper Southern Survey (SMSS), yielding a large sample of over five million metal-poor ([Fe/H] ≤ −1.0) stars and nearly one million very metal-poor ([Fe/H] ≤ −2.0) stars. The typical precision is around 0.1 dex for both dwarf and giant stars with [Fe/H] > −1.0, and 0.15–0.25/0.3–0.4 dex for dwarf/giant stars with [Fe/H] < −1.0. Using the precise parallax measurements and stellar colors from Gaia, effective temperature, luminosity classification, distance, and stellar age are further derived for our sample stars. This huge data set in the Northern sky from SAGES, together with similar data in the Southern sky from SMSS, will greatly advance our understanding of the Milky Way, in particular its formation and evolution.

We employ the corrected Gaia Early Data Release 3 photometric data and spectroscopic data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) DR7 to assemble a sample of approximately 0.25 million FGK dwarf photometric standard stars for the 12 J-PLUS filters using the stellar color regression (SCR) method. We then independently validate the J-PLUS DR3 photometry and uncover significant systematic errors: up to 15 mmag in the results from the stellar locus method and up to 10 mmag primarily caused by magnitude-, color-, and extinction-dependent errors of the Gaia XP spectra as revealed by the Gaia BP/RP (XP) synthetic photometry (XPSP) method. We have also further developed the XPSP method using the corrected Gaia XP spectra by B. Huang et al. and applied it to the J-PLUS DR3 photometry. This resulted in an agreement of 1–5 mmag with the SCR method and a twofold improvement in the J-PLUS zero-point precision. Finally, the zero-point calibration for around 91% of the tiles within the LAMOST observation footprint is determined through the SCR method, with the remaining approximately 9% of the tiles outside this footprint relying on the improved XPSP method. The recalibrated J-PLUS DR3 photometric data establish a solid data foundation for conducting research that depends on high-precision photometric calibration.