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BACKGROUND: Obesity, a multifactorial and complex health condition, has emerged as a significant global public health concern. Integrating machine learning techniques into obesity research offers great promise as an interdisciplinary field, particularly in the screening, diagnosis, and analysis of obesity. Nevertheless, the publications on using machine learning methods in obesity research have not been systematically evaluated. Hence, this study aimed to quantitatively examine, visualize, and analyze the publications concerning the use of machine learning methods in obesity research by means of bibliometrics. METHODS: The Web of Science core collection was the primary database source for this study, which collected publications on obesity research using machine learning methods over the last 20 years from January 1, 2004, to December 31, 2023. Only articles and reviews that fit the criteria were selected for bibliometric analysis, and in terms of language, only English was accepted. VOSviewer, CiteSpace, and Excel were the primary software utilized. RESULTS: Between 2004 and 2023, the number of publications on obesity research using machine learning methods increased exponentially. Eventually, 3286 publications that met the eligibility criteria were searched. According to the collaborative network analysis, the United States has the greatest volume of publications, indicating a significant influence on this research. coauthor's analysis showed the authoritative one in this field is Leo Breiman. Scientific Reports is the most widely published journal. The most referenced publication is "R: a language and environment for statistical computing." An analysis of keywords shows that deep learning, support vector machines, predictive models, gut microbiota, energy expenditure, and genome are hot topics in this field. Future research directions may include the relationship between obesity and its consequences, such as diabetic retinopathy, as well as the interaction between obesity and epidemiology, such as COVID-19. CONCLUSION: Utilizing bibliometrics as a research tool and methodology, this study, for the first time, reveals the intrinsic relationship and developmental pattern among obesity research using machine learning methods, which provides academic references for clinicians and researchers in understanding the hotspots and cutting-edge issues as well as the developmental trend in this field to detect patients' obesity problems early and develop personalized treatment plans.

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Kidney Stone Disease (KSD) constitutes a multifaceted disorder, emerging from a confluence of environmental and genetic determinants, and is characterized by a high frequency of occurrence and recurrence. Our objective is to elucidate potential causative proteins and identify prospective pharmacological targets within the context of KSD. This investigation harnessed the unparalleled breadth of plasma protein and KSD pooled genome-wide association study (GWAS) data, sourced from the United Kingdom Biobank Pharma Proteomics Project (UKBPPP) and the FinnGen database version R10. Through Mendelian randomization analysis, proteins exhibiting a causal influence on KSD were pinpointed. Subsequent co-localization analyses affirmed the stability of these findings, while enrichment analyses evaluated their potential for pharmacological intervention. Culminating the study, a phenome-wide association study (PheWAS) was executed, encompassing all phenotypes (2408 phenotypes) catalogued in the FinnGen database version R10. Our MR analysis identified a significant association between elevated plasma levels of proteins FKBPL, ITIH3, and SERPINC1 and increased risk of KSD based on genetic predictors. Conversely, proteins CACYBP, DAG1, ITIH1, and SEMA6C showed a protective effect against KSD, documented with statistical significance (PFDR<0.05). Co-localization analysis confirmed these seven proteins share genetic variants with KSD, signaling a shared genetic basis (PPH3 + PPH4 > 0.8). Enrichment analysis revealed key pathways including hyaluronan metabolism, collagen-rich extracellular matrix, and serine-type endopeptidase inhibition. Additionally, our PheWAS connected the associated proteins with 356 distinct diseases (PFDR<0.05), highlighting intricate disease interrelations. In conclusion, our research elucidated a causal nexus between seven plasma proteins and KSD, enriching our grasp of prospective therapeutic targets.

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Exploring the physical fractions of organic carbon and influencing mechanisms in grassland, forest, and farmland soils in wind erosion area can provide scientific basis for carbon sequestration, land utilization, wind prevention measure making, and fertility restoration of sloping farmland in the region. We examined the differentiation of aggregate organic carbon and density fractionation organic carbon in 0-15 cm soil layer across grassland, forest, and sloping farmland with 350 m long and 5° slope gradient in the wind erosion area of Meilisi District, Qiqihar, Heilongjiang, as well as the sloping farmland in the downhill section, middle section, and uphill section with every 100 m apart from the bottom to the top. The results showed that soil aggregates >2 mm were all destroyed across grassland, forest, and farmland soils, while the percentage of aggregates <0.053 mm was significantly higher than that of other sizes. The percentage of various soil aggregates, organic carbon content from density fractionations, and the proportion of organic carbon in the heavy fraction aggregates in farmland were significantly lower than that in grassland and forest soils. Soil aggregates in the uphill section of farmland were completely destroyed, and organic carbon content in various size aggregates and density fractionations gradually decreased with increasing slope. The proportion of organic carbon in the heavy fraction aggregates decreased, but that in light fraction aggregates increased gradually. Soil organic carbon and available potassium were key factors affecting aggregate stability, aggregate organic carbon content, and organic carbon content in density fractionations, while the loss of organic carbon in aggregate led to a decrease in aggregate stability. In summary, compared with grassland and forest soils, the stability of soil aggregates, the aggregate organic carbon content, the organic carbon content in density fractionations, and the proportion of organic carbon in heavy fraction aggregates in farmland all decreased in the wind erosion area of Northeast China. With the increases of slope, the aggregate organic carbon content, the organic carbon content in density fractionations, and the proportion of organic carbon in the heavy fraction aggregates in sloping farmland all decreased. Planting trees, conserving and expanding grassland area, and increasing the application of organic materials in sloping farmland in wind erosion area are effective approaches to stabilize and increase carbon storage, improve soil structure, and enhance soil quality.

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Neurodevelopmental disorders are currently one of the major complications faced by patients with congenital heart disease (CHD). Chronic hypoxia in the prenatal and postnatal preoperative brain may be associated with neurological damage and impaired long-term cognitive function, but the exact mechanisms are unknown. In this study, we find that delayed neuronal migration and impaired synaptic development are attributed to altered Atoh1 under chronic hypoxia. This is due to the fact that excessive Atoh1 facilitates expression of Kif21b, which causes excess in free-state α-tubulin, leading to disrupted microtubule dynamic stability. Furthermore, the delay in neonatal brain maturation induces cognitive disabilities in adult mice. Then, by down-regulating Atoh1 we alleviate the impairment of cell migration and synaptic development, improving the cognitive behavior of mice to some extent. Taken together, our work unveil that Atoh1 may be one of the targets to ameliorate hypoxia-induced neurodevelopmental disabilities and cognitive impairment in CHD.

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Background: This study aimed to assess the impact of the COVID-19 pandemic on the disease burden of Taiwan's notifiable infectious diseases (NIDs). We compared disease burdens between the pandemic and pre-pandemic year of 2020 (with non-pharmaceutical interventions (NPIs)) and 2010 (without NPIs), respectively, to understand the overall pandemic impact on NIDs in Taiwan. Methods: Forty-three national NIDs were analyzed using the Statistics of Communicable Diseases and Surveillance Report by estimating the premature death and disability via different transmission categories, sex, and age groups. The study evaluated the impact of diseases by assessing the years lost due to death (YLLs), the duration of living with disability (YLDs), and the overall disability-adjusted life years (DALYs) by measuring both the severity of the illness and its duration. Results: Taiwan recorded 1,577 (2010) and 1,260 (2020) DALYs per million population and lost 43 NIDs, decreasing 317 DALYs per million population. Tuberculosis, HIV/AIDS and acute hepatitis B/D were the leading causes of DALYs, accounting for 89% (2010) and 77% (2020). Conclusion: Overall, this study provided the first insight of changes in disease burdens in NIDs between pre- and post-COVID-19 based on a nationwide viewpoint for further preventive measures and interventions to be focused on specific diseases by associated health administrations and policies.

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We present the application of N-difluoroacetylglucosamine (GlcNDFA) in a chemical evolution strategy to synthesize oligosaccharides. In comparison to conventional N-trifluoroacetylglucosamine, GlcNDFA exhibits superior substrate compatibility with glycosyltransferases as well as stability in aqueous environments. Using our 16-step assembly line, GlcNDFA can be used to produce homogeneous dekaparin, a heparin-like medication, with a yield of 62.2%. This underscores the significant potential of GlcNDFA as a chemical evolution precursor in the precise synthesis of structurally defined polysaccharides.

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Ionizing radiation exposure can cause damage to diverse tissues and organs, with the hematopoietic system being the most sensitive. However, limited information is available regarding the radiosensitivity of various hematopoietic cell populations in the bone marrow due to the high heterogeneity of the hematopoietic system. In this study, we observed that granulocyte-macrophage progenitors, hematopoietic stem/progenitor cells, and B cells within the bone marrow showed the highest sensitivity, exhibiting a rapid decrease in cell numbers following irradiation. Nonetheless, neutrophils, natural killer (NK) cells, T cells, and dendritic cells demonstrated a certain degree of radioresistance, with neutrophils exhibiting the most pronounced resistance. By employing single-cell transcriptome sequencing, we investigated the early responsive genes in various cell types following irradiation, revealing that distinct gene expression profiles emerged between radiosensitive and radioresistant cells. In B cells, radiation exposure led to a specific upregulation of genes associated with mitochondrial respiratory chain complexes, suggesting a connection between these complexes and cell radiosensitivity. In neutrophils, radiation exposure resulted in fewer gene alterations, indicating their potential for distinct mechanisms in radiation resistance. Collectively, this study provides insights into the molecular mechanism for the heterogeneity of radiosensitivity among the various bone marrow hematopoietic cell populations.

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Al-Mg alloys are widely used as important engineering structural materials in aerospace engineering, transportation systems, and structural constructions due to their low density, high specific strength, corrosion resistance, welding capability, fatigue strength, and cost-effectiveness. However, the conventional Al-Mg alloys can no longer fully satisfy the demands of practical production due to difficulties caused by many defects. The high strength of Al-Mg alloys as non-heat treatment precipitation-strengthened alloys is achieved primarily by solid solution strengthening along with work hardening rather than precipitation strengthening. Therefore, severe plastic deformation (SPD) techniques can be often used to produce ultrafine-grained structures to fabricate ultra-high strength aluminum alloys. However, this approach often achieves the strengthening of material at the cost of reduced ductility. This paper comprehensively summarizes the various approaches of ultrafine/nanocrystalline materials for enhancing their plasticity, elaborates on the creation of a bimodal microstructure within the alloy, and discusses the formation of a nanotwin microstructure within the alloy and the incorporation of dispersed nanoparticles. The mechanisms underlying both the strengthening and toughening during large plastic deformation in aluminum alloys are summarized, and the future research direction of high-performance ultrafine crystalline and nanocrystalline Al-Mg aluminum alloys is prospected.

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Wearable electronics for long-term monitoring of physiological signals should be capable of removing sweat generated during daily motion, which significantly impacts signal stability, human comfort, and safety of the electronics. In this study, we developed a double-layer polyurethane (PU) membrane with sweat-directional transport ability that can be applied for monitoring strain signals. The PU membrane was composed of a hydrophilic, conductive layer and a relatively hydrophobic layer. The double-layer PU composite membrane exhibited varied pore size and opposite hydrophilicity on its two sides, enabling the spontaneous pumping of sweat from the hydrophobic side to the hydrophilic side, i.e., the directional transport of sweat. The membrane can be used as a strain sensor to monitor motion strain over a broad working range of 0% to 250% with high sensitivity (GF = 4.11). The sensor can also detect simple human movements even under sweating conditions. We believe that the strategy demonstrated here will provide new insights into the design of next-generation strain sensors.

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Marine oil exploration is important yet greatly increases the risk of oil leakage, which will result in severe environment pollution and economic losses. It is an urgent need to develop effective underoil adhesives. However, realizing underoil adhesion is even harder than those underwater, due to the stubborn attachment of a highly viscous oil layer on target surface. Here, inspired by endocytosis, a tough gel tape composed of zwitterionic polymer network and zwitterionic surfactants is developed. The amphiphilic surfactants can form micelle to capture the oil droplets and transport them from the interface to gel via electrostatic attraction of polymer backbone, mimicking the endocytosis and achieving robust underoil adhesion. Benefiting from the oil-resistance of polymer backbone, the gel further realizes a combination of i) long-term adhesion with high durability, ii) repeated adhesion in oil, and iii) renewable adhesion efficiency after exhausted use. The tape exhibits an ultra-high adhesive toughness of 2446.86 J m-2 to stainless steel in silicone oil after 30 days' oil-exposure; such value of adhesive toughness surpasses many of those achieved in underwater adhesion and is greater than underoil adhesion performance of commercial tape. The strategy illustrated here will motivate the design of sustainable and efficient adhesives for wet environments.

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BACKGROUND & AIMS: Malnutrition is prevalent among hospitalised patients, and increases the morbidity, mortality, and medical costs; yet nutritional assessments on admission are not routine. This study assessed the clinical and economic benefits of using an artificial intelligence (AI)-based rapid nutritional diagnostic system for routine nutritional screening of hospitalised patients. METHODS: A nationwide multicentre randomised controlled trial was conducted at 11 centres in 10 provinces. Hospitalised patients were randomised to either receive an assessment using an AI-based rapid nutritional diagnostic system as part of routine care (experimental group), or not (control group). The overall medical resource costs were calculated for each participant and a decision-tree was generated based on an intention-to-treat analysis to analyse the cost-effectiveness of various treatment modalities. Subgroup analyses were performed according to clinical characteristics and a probabilistic sensitivity analysis was performed to evaluate the influence of parameter variations on the incremental cost-effectiveness ratio (ICER). RESULTS: In total, 5763 patients participated in the study, 2830 in the experimental arm and 2933 in the control arm. The experimental arm had a significantly higher cure rate than the control arm (23.24% versus 20.18%; p = 0.005). The experimental arm incurred an incremental cost of 276.52 CNY, leading to an additional 3.06 cures, yielding an ICER of 90.37 CNY. Sensitivity analysis revealed that the decision-tree model was relatively stable. CONCLUSION: The integration of the AI-based rapid nutritional diagnostic system into routine inpatient care substantially enhanced the cure rate among hospitalised patients and was cost-effective. REGISTRATION: NCT04776070 (https://clinicaltrials.gov/study/NCT04776070).

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BACKGROUND: Central obesity was considered as a risk factor for falls among the older population. Waist circumference (WC), lipid accumulation product (LAP), visceral adiposity index (VAI), and the Chinese visceral adiposity index (CVAI) are considered as surrogate markers for abdominal fat deposition in increasing studies. Nevertheless, the longitudinal relationship between these indices and falls among the older population remains indistinct. This study aimed to explore the association between abdominal obesity indices and falls among older community-dwellers. METHODS: Our study included 3501 individuals aged ≥ 65 years from the Guangzhou Falls and Health Status Tracking Cohort at baseline in 2021 and then prospectively followed up in 2022. The outcome of interest was the occurrence of falls. The Kaplan-Meier curves and multivariable Cox regression analysis were used to explore the associations between abdominal obesity indices and falls. Moreover, the restricted cubic spline analysis (RCS) was conducted to test the non-linear relationships between abdominal obesity indices and hazards of falls incident. RESULTS: After a median follow-up period of 551 days, a total of 1022 participants experienced falls. The cumulative incidence rate of falls was observed to be higher among individuals with central obesity and those falling within the fourth quartile (Q4) of LAP, VAI, and CVAI. Participants with central obesity and those in Q4 of LAP, VAI, and CVAI were associated with higher risk of falls, with hazard ratios (HRs) of 1.422 (HR 95%CI: 1.255-1.611), 1.346 (1.176-1.541), 1.270 (1.108-1.457), 1.322 (1.154-1.514), respectively. Each 1-SD increment in WC, LAP, VAI, and CVAI was a significant increased risk of falls among participants. Subgroup analysis further revealed these results were basically stable and appeared to be significantly stronger among those females, aged 65-69 years, and with body mass index (BMI) ≥ 28 kg/m2. Additionally, RCS curves showed an overall upward trend in the risk of falls as the abdominal indices increased. CONCLUSIONS: Abdominal obesity indices, as WC, LAP, VAI, and CVAI were significantly associated with falls among older community-dwellers. Reduction of abdominal obesity indices might be suggested as the strategy of falls prevention.

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It has been demonstrated that observers can accurately estimate their self-motion direction (i.e., heading) from optic flow, which can be affected by attention. However, it remains unclear how attention affects the serial dependence in the estimation. In the current study, participants conducted two experiments. The results showed that the estimation accuracy decreased when attentional resources allocated to the heading estimation task were reduced. Additionally, the estimates of currently presented headings were biased toward the headings of previously seen headings, showing serial dependence. Especially, this effect decreased (increased) when the attentional resources allocated to the previously (currently) seen headings were reduced. Furthermore, importantly, we developed a Bayesian inference model, which incorporated attention-modulated likelihoods and qualitatively predicted changes in the estimation accuracy and serial dependence. In summary, the current study shows that attention affects the serial dependence in heading estimation from optic flow and reveals the Bayesian computational mechanism behind the heading estimation.

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Bile acids (BAs) are synthesized by the host liver from cholesterol and are delivered to the intestine, where they undergo further metabolism by gut microbes and circulate between the liver and intestines through various transporters. They serve to emulsify dietary lipids and act as signaling molecules, regulating the host's metabolism and immune homeostasis through specific receptors. Therefore, disruptions in BA metabolism, transport, and signaling are closely associated with cholestasis, metabolic disorders, autoimmune diseases, and others. Botanical triterpenoids and steroids share structural similarities with BAs, and they have been found to modulate BA metabolism, transport, and signaling, potentially exerting pharmacological or toxicological effects. Here, we have updated the research progress on BA, with a particular emphasis on new-found microbial BAs. Additionally, the latest advancements in targeting BA metabolism and signaling for disease treatment are highlighted. Subsequently, the roles of botanical triterpenoids in BA metabolism, transport, and signaling are examined, analyzing their potential pharmacological, toxicological, or drug interaction effects through these mechanisms. Finally, a research paradigm is proposed that utilizes the gut microbiota as a link to interpret the role of these important natural products in BA signaling.

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BACKGROUND: Aedes albopictus is a major arbovirus vector with small stagnant water containers being its oviposition sites. Mosquitoes search for these sites based on their olfactory cues (odor and moisture emanating from the water at the oviposition site), visual cues (size and color of the site), and gustatory cues (ion and nutrient concentration in that water). The gustatory mechanism through which mosquitoes search for oviposition sites remains unknown. METHODS: To investigate the role of taste receptors in Ae. albopictus oviposition site selection, we developed a laboratory model. This model assessed mosquito behavior in locating and detecting oviposition sites, using a location index to quantify site preference and detection time to measure response to water presence. We compared oviposition site-searching efficiency between mosquitoes with blocked and unblocked appendages, targeting the taste organs. Transcriptome sequencing was conducted to identify differentially expressed genes between water-exposed and unexposed mosquitoes. CRISPR/Cas9 technology was then employed to generate a mutant strain with a targeted gene knockout. RESULTS: There was no significant difference between the blocked and unblocked groups in the location index. In contrast, the detection time of the unblocked group differed significantly from all other groups, including those with blocked foreleg tarsus, midleg tarsus, hindleg tarsus, all tibia, and all tarsus. Transcriptome sequencing analyses of water-exposed and unexposed mosquitoes revealed that the taste-related gene gustatory receptor 11(gr11) was differentially expressed. This gene was knocked out with CRISPR/Cas9 technology to generate a pure mutant strain with 2- and 4-bp deletions, which exhibited a significantly longer detection time than the wild-type strain. CONCLUSIONS: This study reveals the role of Ae. albopictus gr11 in water detection at oviposition sites, thereby providing a theoretical basis and scientific guidelines for managing the breeding sites of these mosquitoes.

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Pseudorabies virus (PRV), an α-herpesvirus, induces immunosuppression and can lead to severe neurological diseases. N-methyl-D-aspartate receptor (NMDAR), an important excitatory nerve receptor in the central nervous system, is linked to various nervous system pathologies. The link between NMDAR and PRV-induced neurological diseases has not been studied. In vivo studies revealed that PRV infection triggers a reduction in hippocampal NMDAR expression, mediated by inflammatory processes. Extensive hippocampal neuronal degeneration was found in mice on the 6th day by hematoxylin-eosin staining, which was strongly correlated with increased NMDAR protein expression. In vitro studies utilizing the CCK-8 assay demonstrated that treatment with an NMDAR antagonist significantly heightened the cytotoxic effects of PRV on T lymphocytes. Notably, NMDAR inhibition did not affect the replication ability of PRV. However, it facilitated the accumulation of pro-inflammatory cytokines in PRV-infected T cells and enhanced the transcription of the CD25 gene through the secretion of interleukin-2 (IL-2), consequently exacerbating immunosuppression. In this study, we found that NMDAR has functional activity in T lymphocytes and is crucial for the inflammatory and immune responses triggered by PRV infection. These discoveries highlight the significant role of NMDAR in PRV-induced neurological disease pathogenesis.

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Pheromone receptor (PR)-mediated transduction of sex pheromones to electrophysiological signals is the basis for sex pheromone communication. Orthaga achatina, a serious pest of the camphor tree, uses a mixture of four components (Z11-16:OAc, Z11-16:OH, Z11-16:Ald, and Z3,Z6,Z9,Z12,Z15-23:H) as its sex pheromone. In this study, we identified five PR genes (OachPR1-5) by phylogenetic analysis. Further RT-PCR and qPCR experiments showed that PR1-3 were specifically expressed in male antennae, while PR4 was significantly female-biased in expression. Functional characterization using the XOE-TEVC assay demonstrated that PR1 and PR3 both responded strongly to Z11-16:OH, while PR1 and PR3 had a weak response to Z3,Z6,Z9,Z12,Z15-23:H and Z11-16:Ald, respectively. Finally, two key amino acid residues (N78 and R331) were confirmed to be essential for binding of PR3 with Z11-16:OH by molecular docking and site-directed mutagenesis. This study helps understand the sex pheromone recognition molecular mechanism of O. achatina.

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Understanding protein function is pivotal in comprehending the intricate mechanisms that underlie many crucial biological activities, with far-reaching implications in the fields of medicine, biotechnology, and drug development. However, more than 200 million proteins remain uncharacterized, and computational efforts heavily rely on protein structural information to predict annotations of varying quality. Here, we present a method that utilizes statistics-informed graph networks to predict protein functions solely from its sequence. Our method inherently characterizes evolutionary signatures, allowing for a quantitative assessment of the significance of residues that carry out specific functions. PhiGnet not only demonstrates superior performance compared to alternative approaches but also narrows the sequence-function gap, even in the absence of structural information. Our findings indicate that applying deep learning to evolutionary data can highlight functional sites at the residue level, providing valuable support for interpreting both existing properties and new functionalities of proteins in research and biomedicine.

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A cascade reaction of cyclopropyl alcohols, DABSO (1,4-diazoniabicyclo[2.2.2]octane-1,4-disulfinate), and N-(sulfonyl)acrylamides has been developed. This tandem process went through a cyclopropanol ring opening and Michael addition sequence. The γ-keto sulfinate generated from the reaction between cyclopropanol and DABSO serves as the nucleophilic reagent, and N-(sulfonyl)acrylamide is used as the Michael addition acceptor. By utilizing this strategy, multitudinous sulfone-bridged 1,7-dicarbonyl compounds that contain both a ß-sulfonyl amide unit and γ-keto sulfone skeleton were conveniently synthesized.

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BACKGROUND: Sanqi, the root of Panax notoginseng, has long been recognized for its therapeutic effects on cardiovascular diseases. Saponins, including ginsenosides and notoginsenosides, are the main bioactive components of P. notoginseng. The biosynthesis of saponins is closely related to the defense responses orchestrated by endogenous hormones. RESULTS: To provide new insights into the underlying role of phytohormone jasmonic acid (JA) in the synthesis and regulation of saponins, we performed an ultra-performance liquid chromatography analysis of different tissues of P. notoginseng aged 2-4 years. Moreover, by combined evaluation of saponin content and transcriptome profiling of each tissue, the spatial and temporal distribution of saponins was analyzed. N notoginsenoside R1, ginsenoside Rb1 and ginsenoside Rd accumulated in the underground tissues, including the root, tuqi, fibril and rhizome. In agreement with this data, the corresponding genes of the endogenous hormone JAs, especially coronatine insensitive 1 (COI1) and myelocytomatosis proteins 2 (MYC2), were predominantly expressed in the underground tissues. The tissue- and age-specific distribution of saponins was consistent with the expression of genes involved in JA biosynthetic, metabolic and signaling pathways. CONCLUSION: The present study has revealed the temporal and spatial effects of endogenous phtohormones in the synthesis and regulation of notoginsenosides, which will provide a significant impact on improving the ecological planting technology, cultivating new high-quality varieties and protecting the rare resources of medicinal P. notoginseng. © 2024 Society of Chemical Industry.