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The study aimed to discuss the association between sleep duration and the risk of hyperhomocysteinemia (Hhcy). This cross-sectional study included 4173 adults (≥ 20 years) from the National Health and Nutrition Examination Survey 2005–2006. According to their sleep duration, participants were divided into five subgroups. Multivariate logistic regression analysis models and restrictive cubic spline regressions were used to explore the association between sleep duration and the risk of Hhcy. Compared with the participants who sleep 7 h, sleep deprivation (≤ 5 h) increased the risk of Hhcy, odds ratio (OR) 1.68 (95% confidence interval (CI) 1.06–2.68); Excessive sleep (≥ 9 h) also increased the risk of Hhcy, OR 1.86 (95% CI 1.09–3.14) after adjusting for a series of confounding factors in the entire population. The risk of Hhcy was distributed in a U-shape with sleep duration. Similar results were demonstrated in obese populations. The association between sleep duration and the risk of Hhcy is U-shaped. Both sleep deprivation and excessive sleep can increase the risk of Hhcy. [ABSTRACT FROM AUTHOR]

Deep convolutional neural networks often perform poorly when faced with datasets that suffer from quantity imbalances and classification difficulties. Despite advances in the field, existing two-stage approaches still exhibit dataset bias or domain shift. To counter this, a phased progressive learning schedule has been proposed that gradually shifts the emphasis from representation learning to training the upper classifier. This approach is particularly beneficial for datasets with larger imbalances or fewer samples. Another new method a coupling-regulation-imbalance loss function is proposed, which combines three parts: a correction term, focal loss, and LDAM loss. This loss is effective in addressing quantity imbalances and outliers, while regulating the focus of attention on samples with varying classification difficulties. These approaches have yielded satisfactory results on several benchmark datasets, including Imbalanced CIFAR10, Imbalanced CIFAR100, ImageNet-LT, and iNaturalist 2018, and can be easily generalized to other imbalanced classification models. Deep convolutional neural networks often perform poorly when faced with datasets that suffer from quantity imbalances and classification difficulties. Despite advances in the field, existing two-stage approaches still exhibit dataset bias or domain shift. To counter this, a phased progressive learning schedule has been proposed that gradually shifts the emphasis from representation learning to training the upper classifier. This approach is particularly beneficial for datasets with larger imbalances or fewer samples. Another new method a coupling-regulation-imbalance loss function is proposed, which combines three parts: a correction term, focal loss, and LDAM loss. This loss is effective in addressing quantity imbalances and outliers, while regulating the focus of attention on samples with varying classification difficulties. These approaches have yielded satisfactory results on several benchmark datasets, including Imbalanced CIFAR10, Imbalanced CIFAR100, ImageNet-LT, and iNaturalist 2018, and can be easily generalized to other imbalanced classification models. [ABSTRACT FROM AUTHOR]

Preterm labor, a condition associated with various risk factors such as a history of prior preterm birth (PTB) and multiple pregnancies, has recently seen an increasing focus on its potential link with dyslipidemia. This study aims to investigate the relationship between dyslipidemia in expectant mothers and the risks of PTB. We studied 6963 mothers who gave birth at the International Peace Maternal and Child Health Hospital of Shanghai Jiaotong University School of Medicine in 2020, among which, 437 women had PTB. We extracted clinical and lipid data from electronic records, using multivariable logistic regression and restricted cubic spline models to explore the link between lipid concentrations (by quartiles) in pregnancy stages and PTB risk. The PTB rate was 6.3%. Early pregnancy in the PTB group showed elevated ApoA, ApoB, CHOL, LDL, and TG levels compared to controls (all P < 0.05). Late pregnancy showed no notable lipid differences. Multivariable analysis revealed elevated ApoA, TG, higher age, BMI ≥ 28 kg/m2, hypertension, assisted reproductive technology and gestational diabetes as PTB risk factors (all P < 0.05). After adjustments, higher ApoA, ApoB, CHOL and TG levels correlated with increased PTB risk. Using the lowest quartile, the adjusted ORs for early pregnancy's highest quartile of ApoA, ApoB, CHOL and TG were 1.348, 1.442, 1.442 and 2.156, respectively. Our findings indicate that dyslipemia in early pregnancy, including elevated levels of ApoA, ApoB, CHOL and TG, are associated with PTB. Managing lipid abnormalities during pregnancy may help reduce the risk of PTB. [ABSTRACT FROM AUTHOR]

Recently, fully transformer-based trackers have achieved impressive tracking results, but this also brings a great deal of computational complexity. Some researchers have applied token pruning techniques to fully transformer-based trackers to diminish the computational complexity, but this leads to missing contextual information that is important for the regression task in the tracker. In response to the above issue, this paper proposes a token fusion method that speeds up inference while avoiding information loss and thus improving the robustness of the tracker. Specifically, the input of the transformer's encoder contains search tokens and exemplar tokens, and the search tokens are divided into tracking object tokens and background tokens according to the similarity between search tokens and exemplar tokens. The tokens with greater similarity to the exemplar tokens are identified as tracking object tokens, and those with smaller similarity to the exemplar tokens are identified as background tokens. The tracking object tokens contain the discriminative features of the tracking object, for the sake of making the tracker pay more attention to the tracking object tokens while reducing the computational effort. All the tracking object tokens are kept, and then, the background tokens are weighted and fused to form new background tokens according to the attention weight of the background tokens to prevent the loss of contextual information. The token fusion method presented in this paper not only provides efficient inference of the tracker but also makes the tracker more robust. Extensive experiments are carried out on popular tracking benchmark datasets to verify the validity of the token fusion method. [ABSTRACT FROM AUTHOR]

Nanjing Yunjin, a traditional Chinese silk weaving craft, is celebrated globally for its unique local characteristics and exquisite workmanship, forming an integral part of the world's intangible cultural heritage. However, with the advancement of information technology, the experiential knowledge of the Nanjing Yunjin production process is predominantly stored in text format. As a highly specialized and vertical domain, this information is not readily convert into usable data. Previous studies on a knowledge graph-based Nanjing Yunjin Question-Answering System have partially addressed this issue. However, knowledge graphs need to be constantly updated and rely on predefined entities and relationship types. Faced with ambiguous or complex natural language problems, knowledge graph information retrieval faces some challenges. Therefore, this study proposes a Nanjing Yunjin Question-Answering System that integrates Knowledge Graphs and Retrieval Augmented Generation techniques. In this system, the ROBERTA model is first utilized to vectorize Nanjing Yunjin textual information, delving deep into textual semantics to unveil its profound cultural connotations. Additionally, the FAISS vector database is employed for efficient storage and retrieval of Nanjing Yunjin information, achieving a deep semantic match between questions and answers. Ultimately, related retrieval results are fed into the Large Language Model for enhanced generation, aiming for more accurate text generation outcomes and improving the interpretability and logic of the Question-Answering System. This research merges technologies like text embedding, vectorized retrieval, and natural language generation, aiming to overcome the limitations of knowledge graphs-based Question-Answering System in terms of graph updating, dependency on predefined types, and semantic understanding. System implementation and testing have shown that the Nanjing Yunjin Intelligent Question-Answering System, constructed on the basis of Knowledge Graphs and Retrieval Augmented Generation, possesses a broader knowledge base that considers context, resolving issues of polysemy, vague language, and sentence ambiguity, and efficiently and accurately generates answers to natural language queries. This significantly facilitates the retrieval and utilization of Yunjin knowledge, providing a paradigm for constructing Question-Answering System for other intangible cultural heritages, and holds substantial theoretical and practical significance for the deep exploration and discovery of the knowledge structure of human intangible heritage, promoting cultural inheritance and protection. [ABSTRACT FROM AUTHOR]

In this study, the preparation of robust and transparent poly(butenyl sorbate) (PBS) membranes (PBS-R) was studied in terms of their CO2/CH4 separation performance. The organocatalytic group transfer polymerization of butenyl sorbate was used for the synthesis of PBS with a designed molecular weight and a moderate molecular weight distribution. For the first time, facile fabrication of PBS-R was achieved through thiol-ene addition between the butenyl groups of PBS and dithiols under 365-nm ultraviolet irradiation. The mechanical properties and CO2/CH4 separation performance of the PBS-R membranes were controlled by introducing an amino-triazole functional group and regulating the length and bulkiness of the dithiol spacers during thiol-ene addition. The amino and triazole groups of the PBS-R membrane showed high affinity to CO2, thereby increasing the CO2/CH4 permselectivity from 9.18 to 10.8 and the CO2 permeability from 127 to 142 barrer. The effect of tensile strength on CO2 permeability was evaluated by preparing PBS-R membranes using dithiols with two rigid benzene rings as spacers and flexible spacers. In addition, the effect of the spacer structure on the permselectivity of PBS-R was investigated using 1,4-butanedithiol, 2,2′-oxydiethanethiol, 1,8-octanedithiol, 1,4-benzenedithiol, and 4,4′-thiobisbenzenethiol. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Phased progressive learning with coupling-regulation-imbalance loss for imbalanced data classification" published in the journal Neural Computing & Applications. The correction addresses an error in the primary affiliation details for one of the authors, Liang Xu. The correct affiliation should be the School of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230026, People's Republic of China. The original article has been corrected. The publisher, Springer Nature, remains neutral regarding jurisdictional claims and institutional affiliations. [Extracted from the article]

Alternaria alternata is a prevalent postharvest pathogen that generates diverse mycotoxins, notably alternariol (AOH) and alternariol monomethyl ether (AME), which are recurrent severe contaminants. Nitrogen sources modulate fungal growth, development, and secondary metabolism, including mycotoxin production. The GATA transcription factor AreA regulates nitrogen source utilization. However, little is known about its involvement in the regulation of nitrogen utilization in A. alternata. To examine the regulatory mechanism of AaAreA on AOH and AME biosynthesis in A. alternata, we analyzed the impact of diverse nitrogen sources on the fungal growth, conidiation and mycotoxin production. The use of a secondary nitrogen source (NaNO3) enhanced mycelial elongation and sporulation more than the use of a primary source (NH4Cl). NaNO3 favored greater mycotoxin accumulation than did NH4Cl. The regulatory roles of AaAreA were further clarified through gene knockout. The absence of AaAreA led to an overall reduction in growth in minimal media containing any nitrogen source except NH4Cl. AaAreA positively regulates mycotoxin biosynthesis when both NH4Cl and NaNO3 are used as nitrogen sources. Subcellular localization analysis revealed abundant nuclear transport when NaNO3 was the sole nitrogen source. The regulatory pathway of AaAreA was systematically revealed through comprehensive transcriptomic analyses. The deletion of AaAreA significantly impedes the transcription of mycotoxin biosynthetic genes, including aohR, pksI and omtI. The interaction between AaAreA and aohR, a pathway-specific transcription factor gene, demonstrated that AaAreA binds to the aohR promoter sequence (5'-GGCTATGGAAA-3'), activating its transcription. The expressed AohR regulates the expression of downstream synthase genes in the cluster, ultimately impacting mycotoxin production. This study provides valuable information to further understand how AreA regulates AOH and AME biosynthesis in A. alternata, thereby enabling the effective design of control measures for mycotoxin contamination. [ABSTRACT FROM AUTHOR]

We revisit the masses of heavy quarkonium double-gluon hybrid mesons with exotic quantum numbers JPC = 1−+ and 2+− in the framework of the QCD sum rules. Considering the double-gluon hybrid meson operators in the octet-octet color structure, we have constructed two independent interpolating currents with JPC = 1−+ and five independent currents with JPC = 2+−. For the interpolating currents with antisymmetric glueball operator, there exist non-local divergences in one kind of additional Feynman diagrams of the tri-gluon condensate, which will give important contributions to the sum rule stabilities and mass predictions. We use the diagrammatic renormalization to cancel out such divergences. At the leading order of αs, the two-point correlation functions and spectral densities can be expressed in the analytic form of the generalized hypergeometric functions and Meijer’s G-functions. After performing the numerical analysis, we predict the masses of the 1−+ and 2+− charmonium double-gluon hybrid mesons to be around 6.1 − 7.2 GeV and 6.3 − 6.4 GeV, respectively. For the bottomonium systems, their masses are predicted to be 13.7 − 14.3 GeV and 12.6 − 13.3 GeV for the 1−+ and 2+− channels, respectively. Besides, it is possible to hunt for these charmonium hybrids in the radiative decays of bottomonium mesons in BelleII experiment. Further investigations on these hybrid states in various theoretical and phenomenological methods are also anticipated in the future. [ABSTRACT FROM AUTHOR]

Carbon fiber reinforced silicon carbide matrix composites (Cf/SiC composites) are lightweight, high strength, wear-resistant, and heat-resistant, making them widely used in aerospace and other industries. However, machining holes in Cf/SiC composites is a great challenge due to the anisotropy and high hardness of the material. In this paper, a brazed diamond grinding rod was employed to grind 1 mm diameter holes in Cf/SiC composites, and the influence of grinding parameters on grinding force, hole entrance/exit defects, and hole wall quality was investigated. In addition, the material removal mechanism of Cf/SiC composites and the wear mechanism of the diamond grinding rod were explored. The findings showed that the damage at the hole entrance and exit predominantly manifests as tearing and burring. The damage factor at the hole exit is 3.5% larger than that at the hole entrance, and the damage factor at both the hole entrance and exit reduces with the growth of spindle speed and the decrease of feed rate. In addition, the diameter errors of the hole entrances and exits are all less than 10%, and the entrance diameter is 2.9% larger than the exit. The hole wall defects include fiber fracture, silicon carbide matrix peeling, and inherent porosity, with poorer surface quality at fiber orientation angles (FOA) of 90° to 180°. The main wear mechanisms were identified as abrasive wear and the spalling of abrasive grains. [ABSTRACT FROM AUTHOR]

Purpose: Joint destruction is a major burden and an unsolved problem in rheumatoid arthritis (RA) patients. We designed an intra-articular mesoporous silica nanosystem (MSN-TP@PDA-GlcN) with anti-inflammatory and joint protection effects. The nanosystem was synthesized by encapsulating triptolide (TP) in mesoporous silica nanoparticles and coating it with pH-sensitive polydopamine (PDA) and glucosamine (GlcN) grafting on the PDA. The nano-drug delivery system with anti-inflammatory and joint protection effects should have good potency against RA. Methods: A template method was used to synthesize mesoporous silica (MSN). MSN-TP@PDA-GlcN was synthesized via MSN loading with TP, coating with PDA and grafting of GlcN on PDA. The drug release behavior was tested. A cellular inflammatory model and a rat RA model were used to evaluate the effects on RA. In vivo imaging and microdialysis (MD) system were used to analyze the sustained release and pharmacokinetics in RA rats. Results: TMSN-TP@PDA-GlcN was stable, had good biocompatibility, and exhibited sustained release of drugs in acidic environments. It had excellent anti-inflammatory effects in vitro and in vivo. It also effectively repaired joint destruction in vivo without causing any tissue toxicity. In vivo imaging and pharmacokinetics experiments showed that the nanosystem prolonged the residence time, lowered the Cmax value and enhanced the relative bioavailability of TP. Conclusions: These results demonstrated that MSN-TP@PDA-GlcN sustained the release of drugs in inflammatory joints and produced effective anti-inflammatory and joint protection effects on RA. This study provides a new strategy for the treatment of RA. [ABSTRACT FROM AUTHOR]

Fatigue is a physiological phenomenon experienced by the human body when it undergoes prolonged physical and mental exertion, which can have detrimental effects on both health and work productivity. Previous research has demonstrated that arctigenin (ArcG) has the ability to enhance the physical performance of mice during exercise. In this study, five ArcG derivatives containing different dipeptides coupled via an ethoxy linker were synthesized and tested for their activities to improve exercise performance in mice. All of the derivatives extended the exhaustion distance of mice in the running wheel test. Derivative Z-B-4 exhibited the highest activity, showing that the mice ran a distance 1.3-fold greater than that of the ArcG group and 3.4-fold greater than that of the sport control group. Furthermore, Z-B-4 was found to increase the concentrations of superoxide dismutase (SOD) and catalase (CAT), while simultaneously decreasing levels of lactic acid (LA) and blood urea nitrogen (BUN) during exercise. This study provides new references and promising lead compounds for the development of antifatigue agents. [ABSTRACT FROM AUTHOR]

Purpose: The synergistic effects of combining arsenic compounds with imatinib against chronic myeloid leukemia (CML) have been established using in vitro data. We conducted a clinical trial to compare the efficacy of the arsenic realgar–indigo naturalis formula (RIF) plus imatinib with that of imatinib monotherapy in patients with newly diagnosed chronic phase CML (CP-CML). Methods: In this multicenter, randomized, double-blind, phase 3 trial, 191 outpatients with newly diagnosed CP-CML were randomly assigned to receive oral RIF plus imatinib (n = 96) or placebo plus imatinib (n = 95). The primary end point was the major molecular response (MMR) at 6 months. Secondary end points include molecular response 4 (MR4), molecular response 4.5 (MR4.5), progression-free survival (PFS), overall survival (OS), and adverse events. Results: The median follow-up duration was 51 months. Due to the COVID-19 pandemic, the recruitment to this study had to be terminated early, on May 28, 2020. The rates of MMR had no significant statistical difference between combination and imatinib arms at 6 months and any other time during the trial. MR4 rates were similar in both arms. However, the 12-month cumulative rates of MR4.5 in the combination and imatinib arms were 20.8% and 10.5%, respectively (p = 0.043). In core treatment since the 2-year analysis, the frequency of MR4.5 was 55.6% in the combination arm and 38.6% in the imatinib arm (p = 0.063). PFS and OS were similar at five years. The safety profiles were similar and serious adverse events were uncommon in both groups. Conclusion: The results of imatinib plus RIF as a first-line treatment of CP-CML compared with imatinib might be more effective for achieving a deeper molecular response (Chinadrugtrials number, CTR20170221). [ABSTRACT FROM AUTHOR]

Wireless sensor network (WSN) location is a significant research area. In complex environments like forests, inaccurate signal intensity ranging is a major challenge. To address this issue, this paper presents a reliable WSN distance measurement-positioning algorithm for forest environments. The algorithm divides the positioning area into several sub-regions based on the discrete coefficient of the collected signal strength. Then, using the fitting method based on the signal intensity value of each sub-region, the algorithm derives the reference points of the logarithmic distance path loss model and path loss index. Finally, the algorithm locates target nodes using anchor nodes in different regions. Additionally, to enhance the positioning accuracy, weight values are assigned to the positioning result based on the discrete coefficient of the signal intensity in each sub-region. Experimental results demonstrate that the proposed WSN algorithm has high precision in forest environments. [ABSTRACT FROM AUTHOR]

Functionalized conjugated microporous polymers (CMPs) containing amino, imino, and hydrazine groups are synthesized by the Sonogashira–Hagihara coupling reaction. Notably, the porosities, thermal stabilities, and morphologies of the CMPs can be controlled by the introduction of functional groups. Here, the relationships between the functional groups and photocatalytic performance are discussed for the first time. The CMP nanowires exhibit excellent photocatalytic performance in organic pollutant degradation: the degradation rate obtained by CMP-I3 bearing naphthalene groups via an imine bond is > 99.99%, and ~ 99.71% of the degradation activity is maintained after five cycles. Notably, the excellent photocatalytic properties of CMP-I3 are imparted by the introduction of the naphthalene groups, which reduced the band gap. The improved charge-transfer activity accounts for the highest and lowest photocurrent intensity and resistance achieved, respectively. Furthermore, the photocatalytic mechanism of CMPs reveals that the superoxide anion is the main active substance in the photocatalytic degradation of dyes. [ABSTRACT FROM AUTHOR]

Prognostic features in advanced perihilar cholangiocarcinoma (pCCA) patients who received first-line hepatic arterial infusion chemotherapy (HAIC) are unknown. The purpose of our study was to develop an applicable score based on serum inflammatory-tumor biomarkers to predict the survival of advanced pCCA patients who received first-line HAIC. In total, 106 advanced pCCA patients were enrolled as the training cohort. The optimal cutoff values of baseline variables were defined by the receiver operating characteristic method or according to previous publications. According to the results of Cox regression analysis, baseline neutrophil-to-lymphocyte ratio (NLR) > 3.19, carcinoembryonic antigen (CEA) > 10 ng/mL, and carbohydrate antigen 19-9 (CA19-9) > 200 U/mL were identified as independent survival predictors, which were used to develop the NLCECA score (NLR, CEA, and CA19-9). When including the NLCECA score in the multivariate analysis, the NLCECA score was the only independent predictor of survival. The risk of survival decreased by 111.9% for each 1-point increase in the NLCECA score. Additionally, the NLCECA score could also predict survival in another 33 patients in the validation cohort (P < 0.001). In summary, the NLCECA score is a potential biomarker system for predicting the survival of advanced pCCA patients who received first-line HAIC. [ABSTRACT FROM AUTHOR]

In this study, BiVO4/CuWO4 nanocomposites with S-scheme heterojunction structure were prepared firstly and the properties were analyzed by various techniques. The sonocatalytic activity was evaluated by the degradation of tetracycline (TET). Under the optimum experimental conditions of initial concentration of TET = 25 mg/L, composite ratio of BiVO4 and CuWO4 = 15%, catalyst addition = 1 g/L, ultrasonic time = 120 min, ultrasonic power = 500 W, pH = 7, the experiment results showed that BiVO4/CuWO4 sonocatalyst removed TET by 81.05 ± 2.92%. K2S2O8 was verified to enhance the sonocatalytic performance of BiVO4/CuWO4 efficiently, and the removal ratio of TET could reach 91.25 ± 1.95% within 120 min by using BiVO4/CuWO4 and K2S2O8. The free radical (ROS) quenching experiment and TA-PL technology proved that the main free radical of degradation was ·OH. The potential sonocatalytic mechanism showed that the enhanced catalytic efficiency was due to the construction of S-scheme heterojunctions, which improved electron–hole pair (e−–h+) separation efficiency and rapid kinetics. The speculated TET degradation route of TET included intermediate products was proposed and four reused experiments proved that BiVO4/CuWO4 had good recyclability. In conclusion, the prepared BiVO4/CuWO4 composites with S-type heterojunction mechanism have more possibilities in wastewater treatment, which provides a helpful guide for the synthesis and application of composite sonocatalysts. [ABSTRACT FROM AUTHOR]

The rapid development of industrialization generated an urgent requirement for the catalytic conversion of CO2 into high-value-added chemical products. Herein, a class of novel bifunctional metalloporphyrin-based hyper-crosslinked ionic polymer (ImHCP-Co) was synthesized via one-pot Friedel–Crafts alkylation and quaternization reactions. The obtained bifunctional ImHCP-Co showed a high BET surface area and sufficient CO2 adsorption capacity. Relying on the synergistic effect of the electrophilic and nucleophilic functionalities, the as-prepared ImHCP-Co showed an excellent performance in CO2 cycloaddition using epichlorohydrin as the substrate (99% conversion and 99% selectivity) and can be carried out without any solvents or cocatalysts to afford a high turnover number. Importantly, it could also convert various epoxide substrates into the corresponding cyclic carbonates and can maintain 82.5% of its catalytic ability after 5 cycles. The catalytic mechanism was systematically explained by DFT calculation and proved the cooperative effect of Co2+ centers and nucleophilic Cl− in the catalytic process. This study provides a new avenue for the design and preparation of HCP-based multifunctional catalysts used for the treatment of greenhouse gases. [ABSTRACT FROM AUTHOR]

Mitochondrial transcription termination factor 3 (MTERF3) negatively regulates mitochondrial DNA transcription. However, its role in hepatocellular carcinoma (HCC) progression remains elusive. Here, we investigate the expression and function of MTERF3 in HCC. MTERF3 is overexpressed in HCC tumor tissues and higher expression of MTERF3 positively correlates with poor overall survival of HCC patients. Knockdown of MTERF3 induces mitochondrial dysfunction, S-G2/M cell cycle arrest and apoptosis, resulting in cell proliferation inhibition. In contrast, overexpression of MTERF3 promotes cell cycle progression and cell proliferation. Mechanistically, mitochondrial dysfunction induced by MTERF3 knockdown promotes ROS accumulation, activating p38 MAPK signaling pathway to suppress HCC cell proliferation. In conclusion, ROS accumulation induced by MTERF3 knockdown inhibits HCC cell proliferation via p38 MAPK signaling pathway suggesting a promising target in HCC patients. Targeting mitochondrial transcription termination factor MTERF3 induces mitochondrial dysfunction and inhibits the proliferation via activating ROS-dependent p38 MAPK pathway in hepatocellular carcinoma. [ABSTRACT FROM AUTHOR]

Prunus mume is an important medicinal plant with ornamental and edible value. Its flowers contain phenylpropanoids, flavonoids and other active components, that have important medicinal and edible value, yet their molecular regulatory mechanisms in P. mume remain unclear. In this study, the content of total flavonoid and total phenylpropanoid of P. mume at different developmental periods was measured first, and the results showed that the content of total flavonoid and total phenylpropanoid gradually decreased in three developmental periods. Then, an integrated analysis of transcriptome and metabolome was conducted on three developmental periods of P. mume to investigate the law of synthetic accumulation for P. mume metabolites, and the key enzyme genes for the biosynthesis of phenylpropanoids and flavonoids were screened out according to the differentially expressed genes (DEGs). A total of 14,332 DEGs and 38 differentially accumulate metabolites (DAMs) were obtained by transcriptomics and metabolomics analysis. The key enzyme genes and metabolites in the bud (HL) were significantly different from those in the half-opening (BK) and full-opening (QK) periods. In the phenylpropanoid and flavonoid biosynthesis pathway, the ion abundance of chlorogenic acid, naringenin, kaempferol, isoquercitrin, rutin and other metabolites decreased with the development of flowers, while the ion abundance of cinnamic acid increased. Key enzyme genes such as HCT, CCR, COMT, CHS, F3H, and FLS positively regulate the downstream metabolites, while PAL, C4H, and 4CL negatively regulate the downstream metabolites. Moreover, the key genes FLS (CL4312-2, CL4312-3, CL4312-4, CL4312-5, CL4312-6) regulating the synthesis of flavonols are highly expressed in bud samples. The dynamic changes of these metabolites were validated by determining the content of 14 phenylpropanoids and flavonoids in P. mume at different developmental periods, and the transcription expression levels of these genes were validated by real-time PCR. Our study provides new insights into the molecular mechanism of phenylpropanoid and flavonoid accumulation in P. mume. [ABSTRACT FROM AUTHOR]

Photonic quantum computation plays an important role and offers unique advantages. Two decades after the milestone work of Knill-Laflamme-Milburn, various architectures of photonic processors have been proposed, and quantum advantage over classical computers has also been demonstrated. It is now the opportune time to apply this technology to real-world applications. However, at current technology level, this aim is restricted by either programmability in bulk optics or loss in integrated optics for the existing architectures of processors, for which the resource cost is also a problem. Here we present a von-Neumann-like architecture based on temporal-mode encoding and looped structure on table, which is capable of multimode-universal programmability, resource-efficiency, phase-stability and software-scalability. In order to illustrate these merits, we execute two different programs with varying resource requirements on the same processor, to investigate quantum signature of chaos from two aspects: the signature behaviors exhibited in phase space (13 modes), and the Fermi golden rule which has not been experimentally studied in quantitative way before (26 modes). The maximal program contains an optical interferometer network with 1694 freely-adjustable phases. Considering current state-of-the-art, our architecture stands as the most promising candidate for real-world applications., (© 2024. The Author(s).)