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Traditional clustering methods rely on pairwise affinity to divide samples into different subgroups. However, high-dimensional small-sample (HDLSS) data are affected by the concentration effects, rendering traditional pairwise metrics unable to accurately describe relationships between samples, leading to suboptimal clustering results. This article advances the proposition of employing high-order affinities to characterize multiple sample relationships as a strategic means to circumnavigate the concentration effects. We establish a nexus between different order affinities by constructing specialized decomposable high-order affinities, thereby formulating a uniform mathematical framework. Building upon this insight, a novel clustering method named uniform tensor clustering (UTC) is proposed, which learns a consensus low-dimensional embedding for clustering by the synergistic exploitation of multiple-order affinities. Extensive experiments on synthetic and real-world datasets demonstrate two findings: 1) high-order affinities are better suited for characterizing sample relationships in complex data and 2) reasonable use of different order affinities can enhance clustering effectiveness, especially in handling high-dimensional data.
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OBJECTIVE: Early diagnosis of laryngeal cancer (LC) is crucial, particularly in rural areas. Despite existing studies on deep learning models for LC identification, challenges remain in selecting suitable models for rural areas with shortages of laryngologists and limited computer resources. We present the intelligent laryngeal cancer detection system (ILCDS), a deep learning-based solution tailored for effective LC screening in resource-constrained rural areas. METHODS: We compiled a dataset comprised of 2023 laryngoscopic images and applied data augmentation techniques for dataset expansion. Subsequently, we utilized eight deep learning models-AlexNet, VGG, ResNet, DenseNet, MobileNet, ShuffleNet, Vision Transformer, and Swin Transformer-for LC identification. A comprehensive evaluation of their performances and efficiencies was conducted, and the most suitable model was selected to assemble the ILCDS. RESULTS: Regarding performance, all models attained an average accuracy exceeding 90 % on the test set. Particularly noteworthy are VGG, DenseNet, and MobileNet, which exceeded an accuracy of 95 %, with scores of 95.32 %, 95.75 %, and 95.99 %, respectively. Regarding efficiency, MobileNet excels owing to its compact size and fast inference speed, making it an ideal model for integration into ILCDS. CONCLUSION: The ILCDS demonstrated promising accuracy in LC detection while maintaining modest computational resource requirements, indicating its potential to enhance LC screening accuracy and alleviate the workload on otolaryngologists in rural areas.
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Herein, we have manufactured a newly designed bifunctional impedimetric and amperometric immunosensor for rapidly detecting erythromycin (ERY) in complicated environments and food stuffs. For this, bimetallic cobalt/cerium-layered double hydroxide nanosheets (CoCe-LDH NSs), which was derived from Co-based zeolite imidazole framework via the structure conversion, was simultaneously utilized as the bioplatform for anchoring the ERY-targeted antibody and for modifying the gold and screen printed electrode. Basic characterizations revealed that CoCe-LDH NSs was composed of mixed metal valences, enrich redox, and abundant oxygen vacancies, facilitating the adhesion on the electrode, the antibody adsorption, and the electron transfers. The manufactured impedimetric and amperometric immunosensor based on CoCe-LDH has showed the comparable sensing performance, having a wide linear detection range from 1.0 fg mL-1 to 1.0 ng mL-1 with the ultralow detection limit toward ERY. Also, the portable, visualized, and efficient analysis of ERY was then attained at the smartphone-assisted CoCe-LDH-based SPE.
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The practical application of α-Fe2O3 in water splitting is hindered by significant charge recombination and slow water oxidation. To address this issue, a CoSAs-g-C3N4/Fe2O3 (CoSAs: cobalt single atoms) photoanode was fabricated in this study through the co-modification of CoSAs and g-C3N4 to enhance photoelectrochemical (PEC) water splitting. The coupling between g-C3N4 and α-Fe2O3 resulted in the formation of a heterojunction, which provided a strong built-in electric field and an additional driving force to mitigate charge recombination. Moreover, g-C3N4 served as a suitable carrier for single atoms, which effectively anchored CoSAs through N/C coordination. The highly dispersed CoSAs provided abundant active sites, which further promoted surface holes extraction and oxidation kinetics, resulting in higher PEC performance and photostability. This study indicates the benefits of these collaborative strategies and provides more efficient designs for solar energy conversion in PEC systems.
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The joint groundwater pollution prevention and control (GPPC) strategy has been extensively implemented to address the coastal region groundwater pollution challenges in China. However, regional groundwater pollution control and treatment efficiency cannot achieve the expected results due to the lack of regional priority control orders and accurate restoration levels. Thus, this study developed a new region demarcation framework method for delineating GPPC zones, in tandem with a comprehensive pollution index method, the DRASTIC model, source apportionment. To validate the new methodological framework, a case study of groundwater pollution in Qinhuangdao, the western of Bohai Bay, China, was implemented to calculate pollution prevention and control zoning. In total, 340 groundwater samples from shallow aquifers with 9 target pollutants (NO3-, NO2-, NH4+, As, Cd, Cr, Cu, Pb, and Ni) were selected as the dataset for GPPC regionalization. The results showed that GPPC zoning further clarified the direction of groundwater pollution protection and management in Qinhuangdao. Compared to the traditional method, the new GPPC zoning better reflects groundwater mobility characteristics and pollution transport and enrichment patterns in terms of groundwater functional integrity and delineation. This new regional demarcation framework method contributes to providing support for the fine division of groundwater pollution zoning and precise pollution control for groundwater resource management in China.
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Background: The bulbs of Allium sativum are widely used as food or seasoning (garlic), while they have also been utilized as a famous traditional medicine since ancient eras for the treatment of scabies, tuberculosis, pertussis, diarrhea and dysentery, etc. However, very few studies focus on their abundant aerial parts, which are normally discarded during the harvest season. Methods: The hyperlipidemic mice model has been used to study the lipid-lowering effect of the aerial parts in this article. 180 mice were randomly divided into 18 groups, including blank control (BC), model (Mod), positive control (PC), and low-, medium-, and high-dose groups of the crude extract, petroleum ether, ethyl acetate, n-butanol, and residual water extracts (corresponding to CE, PEE, EAE, NBE, WE), with 10 mice in each group. The preventive effects of the extracts on hyperlipidemic mice lasted for four weeks. Ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS) and gas chromatography tandem mass spectrometry (GC-MS/MS) were used to analyze the chemical components of NBE and PEE respectively. Results: The results of the mice experiment showed that n-butanol extract (NBE) and petroleum ether extract (PEE) from the aerial parts could significantly reduce the contents of total cholesterol (TC), triglycerides (TG), low density lipoprotein cholesterol (LDL-C), alanine transaminase (ALT) and aspartate transaminase (AST) in serum of hyperlipidemic mice, and increase the contents of high density lipoprotein cholesterol (HDL-C). They could enhance the activity of superoxide dismutase (SOD) in liver and reduce the level of malondialdehyde (MDA). At the same time, they could improve steatosis and inflammation of liver cells. The results of phytochemical components analysis showed that NBE was rich in organic acids, flavonoids and nitrogen-containing constituents, while PEE contained organic sulfur compounds, aliphatic acids and derivatives, alkaloids, phytosterols, etc. Conclusion: These results support that the aerial parts of A. sativum are an interesting source of bioactive ingredients that may be useful in the prevention and treatment of hyperlipidemia.
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Background: Lung cancer is a malignant tumor, for which pulmonary nodules are considered to be significant indicators. Early recognition and timely treatment of pulmonary nodules can contribute to improving the survival rate of patients with cancer. Positron emission tomography-computed tomography (PET/CT) is a noninvasive, fusion imaging technique that can obtain both functional and structural information of lung regions. However, studies of pulmonary nodules based on computer-aided diagnosis have primarily focused on the nodule level due to a reliance on the annotation of nodules, which is superficial and unable to contribute to the actual clinical diagnosis. The aim of this study was thus to develop a fully automated classification framework for a more comprehensive assessment of pulmonary nodules in PET/CT imaging data. Methods: We developed a two-stage multimodal learning framework for the diagnosis of pulmonary nodules in PET/CT imaging. In this framework, Stage I focuses on pulmonary parenchyma segmentation using a pretrained U-Net and PET/CT registration. Stage II aims to extract, integrate, and recognize image-level and feature-level features by employing the three-dimensional (3D) Inception-residual net (ResNet) convolutional block attention module architecture and a dense-voting fusion mechanism. Results: In the experiments, the proposed model's performance was comprehensively validated using a set of real clinical data, achieving mean scores of 89.98%, 89.21%, 84.75%, 93.38%, 86.83%, and 0.9227 for accuracy, precision, recall, specificity, F1 score, and area under curve values, respectively. Conclusions: This paper presents a two-stage multimodal learning approach for the automatic diagnosis of pulmonary nodules. The findings reveal that the main reason for limiting model performance is the nonsolitary property of nodules in pulmonary nodule diagnosis, providing direction for future research.
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BACKGROUND: Rhodococcus equi (R. equi) is a Gram-positive zoonotic pathogen that frequently leads to illness and death in young horses (foals). This study presents the complete genome sequence of R. equi strain BJ13, which was isolated from a thoroughbred racehorse breeding farm in Beijing, China. RESULTS: The BJ13 genome has a length of 5.30 Mb and consists of a complete chromosome and a plasmid measuring 5.22 Mb and 0.08 Mb, respectively. We predicted 4,929 coding gene open reading frames, along with 52 tRNAs and 12 rRNAs. Through analysis of mobile genetic elements, we identified 6 gene islands and 1 prophage gene. Pathogenic system analysis predicted the presence of 418 virulence factors and 225 drug resistance genes. Secretion system analysis revealed the prediction of 297 secreted proteins and 1,106 transmembrane proteins. BJ13 exhibits genomic features, virulence-associated genes, potential drug resistance, and a virulence plasmid structure that may contribute to the evolution of its pathogenicity. Lastly, the pathogenicity of the isolated strain was assessed through animal experiments, which resulted in inflammatory reactions or damage in the lungs, liver, and spleen of mice. Moreover, by the 7th day post-infection, the mortality rate of the mice reached 50.0%, indicating complex immune regulatory mechanisms, including overexpression of IL-10 and increased production of pro-inflammatory cytokines like TNF-α. These findings validate the strong pathogenicity of the isolated strain and provide insights for studying the pathogenic mechanisms of Rhodococcus equi infection. CONCLUSIONS: The complete genome sequence of R. equi strain BJ13 provides valuable insights into its genomic characteristics, virulence potential, drug resistance, and secretion systems. The strong pathogenicity observed in animal experiments underscores the need for further investigation into the pathogenic mechanisms of R. equi infection.
Subject(s)
Actinomycetales Infections , Genome, Bacterial , Horse Diseases , Rhodococcus equi , Whole Genome Sequencing , Rhodococcus equi/pathogenicity , Rhodococcus equi/genetics , Animals , Horses , Horse Diseases/microbiology , Actinomycetales Infections/veterinary , Actinomycetales Infections/microbiology , Virulence/genetics , Mice , Virulence Factors/genetics , FemaleABSTRACT
Fine-root architecture is critical feature reflecting root explorative and exploitative strategies for soil resources and soil space occupancy. Yet, studies on the variation of fine-root architecture across different species are scare and little work has been done to integrate the potential drivers on these variations along a biogeographical gradient in arid ecosystems. We measured root branching intensity, topological index, and root branching ratios as well as morphological traits (root diameter and length) in dry valley along a 1000 km latitudinal gradient. Influence of phylogeny, environmental factors on fine-root architecture and trade-offs among root traits were evaluated. With increasing latitude, the topological index and second to third root order branching ratio decreased, whereas first-to-second branching ratio increased. Root branching intensity was associated with short and thin fine roots, but has no significant latitudinal pattern. As a whole, soil microbial biomass was the most important driver in the variation of root branching intensity, and soil texture was the strongest predictor of topological index. Additionally, mean annual temperature was an important factor influencing first-to-second branching ratio. Our results suggest variations in fine-root architectures were more dependent on environmental variables than phylogeny, signifying that fine-root architecture is sensitive to environmental variations.
Subject(s)
Plant Roots , China , Plant Roots/anatomy & histology , Soil/chemistry , Ecosystem , Soil Microbiology , PhylogenyABSTRACT
Both sulfur (S) supply and legume-rhizobium symbiosis can significantly contribute to enhancing the efficiency of phytoremediation of heavy metals (HMs). However, the regulatory mechanism determining the performance of legumes at lead (Pb) exposure have not been elucidated. Here, we cultivated black locust (Robinia pseudoacacia L.), a leguminous woody pioneer species at three S supply levels (i.e., deficient, moderate, and high S) with rhizobia inoculation and investigated the interaction of these treatments upon Pb exposure. Our results revealed that the root system of Robinia has a strong Pb accumulation and anti-oxidative capacity that protect the leaves from Pb toxicity. Compared with moderate S supply, high S supply significantly increased Pb accumulation in roots by promoting the synthesis of reduced S compounds (i.e., thiols, phytochelatin), and also strengthened the antioxidant system in leaves. Weakened defense at deficient S supply was indicated by enhanced oxidative damage. Rhizobia inoculation alleviated the oxidative damage of its Robinia host by immobilizing Pb to reduce its absorption by root cells. Together with enhanced Pb chelation in leaves, these mechanisms strengthen Pb detoxification in the Robinia-rhizobia symbiosis. Our results indicate that appropriate S supply can improve the defense of legume-rhizobia symbiosis against HM toxicity.
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Circulating tumor cells (CTCs) are recognized as promising targets for liquid biopsy, which play an important role in early diagnosis and efficacy monitoring of cancer. However, due to the extreme scarcity of CTCs and partial size overlap between CTCs and white blood cells (WBCs), the separation and detection of CTCs from blood remain a big challenge. To address this issue, we fabricated a microfluidic chip by integrating a passive contraction-expansion array (CEA) inertial sorting zone and an active magnetophoresis zone with the trapezoidal groove and online coupled it with inductively coupled plasma mass spectrometry (ICP-MS) for rapid separation and precise detection of MCF-7 cells (as a model CTC) in blood samples. In the integrated microfluidic chip, most of the small-sized WBCs can be rapidly removed in the circular CEA inertial sorter, while the rest of the magnetically labeled WBCs can be further captured in the trapezoidal groove under the magnetic field. As a result, the rapid separation of MCF-7 cells from blood samples was achieved with an average recovery of 91.6% at a sample flow rate of 200 µL min-1. The developed online integrated inertial-magnetophoresis microfluidic chip-ICP-MS system has been applied for the detection of CTCs in real clinical blood samples with a fast analysis speed (5 min per 1 mL blood). CTCs were detected in all 24 blood samples from patients with different types of cancer, exhibiting excellent application potential in clinical diagnosis.
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Large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities in various tasks and attracted increasing interest as a natural language interface across many domains. Recently, large vision-language models (VLMs) that learn rich vision-language correlation from image-text pairs, like BLIP-2 and GPT-4, have been intensively investigated. However, despite these developments, the application of LLMs and VLMs in image quality assessment (IQA), particularly in medical imaging, remains unexplored. This is valuable for objective performance evaluation and potential supplement or even replacement of radiologists' opinions. To this end, this study introduces IQAGPT, an innovative computed tomography (CT) IQA system that integrates image-quality captioning VLM with ChatGPT to generate quality scores and textual reports. First, a CT-IQA dataset comprising 1,000 CT slices with diverse quality levels is professionally annotated and compiled for training and evaluation. To better leverage the capabilities of LLMs, the annotated quality scores are converted into semantically rich text descriptions using a prompt template. Second, the image-quality captioning VLM is fine-tuned on the CT-IQA dataset to generate quality descriptions. The captioning model fuses image and text features through cross-modal attention. Third, based on the quality descriptions, users verbally request ChatGPT to rate image-quality scores or produce radiological quality reports. Results demonstrate the feasibility of assessing image quality using LLMs. The proposed IQAGPT outperformed GPT-4 and CLIP-IQA, as well as multitask classification and regression models that solely rely on images.
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Parasite infection not only triggers the immune response of the host but also potentially affects the reproductive status, thereby influencing the population size. Therefore, understanding the impact of parasite infection on host immune and reproductive systems has long been an important issue in ecological research. To address this, we conducted field surveys (2021-2023) to investigate Capillaria hepatica infection status in Brandt's vole (Lasiopodomys brandtii) and performed controlled experiments in semi-natural enclosures and indoor laboratories. The results showed a negative correlation between the population size of Brandt's vole and the infection rate. To further explore the regulatory mechanisms, transcriptomic and proteomic analyses were performed on the infected BALB/c mice. The study found that post-infection with Capillaria hepatica, up-regulated genes and proteins in the mice liver were primarily associated with immune functions, while down-regulated genes and proteins were related to metabolic functions such as retinol metabolism. Through validation experiments supplementing retinol to the host infected with Capillaria hepatica, it was found that infection with Capillaria hepatica leads to a decrease in systemic available retinol levels, disrupting the expression of the hypothalamic-pituitary-gonadal (HPG) axis hormones, affecting the expression of CYP17A1, thereby regulating testosterone secretion related to spermatogenesis. This process results in abnormal spermatogenesis in the testes, thereby impacting the reproductive capacity of mice. This suggests that Capillaria hepatica regulates resource allocation in hosts, striking a "trade-off" between reproduction and survival, thereby exerting control over population size. These discoveries are crucial for comprehending the interaction between Capillaria hepatica and hosts, as well as their impacts on host reproduction and immune systems, and provide a scientific basis for controlling the transmission of Capillaria hepatica.
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A glucose-responsive insulin delivery system that sustains blood glucose equilibrium for an extended duration can address the low therapeutic window of insulin in diabetes treatment. Herein, insulin is loaded in a water-in-oil-in-water (W1/O/W2) gelled multiple emulsion using poly (4-vinylphenylboronic acid) (PVPBA) homopolymer as an effective emulsifier. The gelled multiple emulsion exhibits a high encapsulation efficiency (99%), enhanced stability and remarkable shear-thinning behavior, making it easy to inject. Under hyperglycemic conditions, the gelled emulsion system instantly binds to glucose molecules and reduces the hydrogen bonds of the PVPBA homopolymer, resulting in insulin release. In a streptozotocin-induced type 1 diabetic mouse model, a single subcutaneous injection of the gelled emulsion rapidly responds to high blood glucose concentration (BGC) and release insulin in a glucose dependent manner, thus prolonging the antihyperglycemic effect compared with free insulin.
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BACKGROUND: Sinistral portal hypertension (SPH) may occurs in patients with pancreatic carcinoma after pancreaticoduodenectomy (PD) with spleno-mesenterico-portal (S-M-P) cofluence resection. This study aimed to evaluate outcomes with the bifurcated allogeneic vein replacement in the prevention of SPH in pancreatic carcinoma patients. MATERIALS AND METHODS: A total of 81 patients were included. We retrospectively collected clinicopathological data from 66 patients underwent PD with S-M-P confluence resection in our hospital from Jan. 2011 to Dec. 2021, compared the correlation between different venous reconstruction methods using log-rank tests and clinical outcomes through univariate and multivariate analyses. Secondly, we prospectively collected clinical data and outcomes of 15 patients who underwent splenic vein reconstruction from Jan. 2021 to Jan. 2023. RESULTS: In the retrospective study, 43 cases received reconstruction by bifurcated allogeneic vein (Reconstruction group) and 23 cases received simply SV ligation (Ligation group). The preoperative platelet counts and spleen volume were similar between two groups (P>0.05). Nevertheless, at 1 month, 3 months and 6 months after operation, the related indexes of SPH such as platelet count, spleen volume, spleen volume ratio and esophagogastric varices (EGV) grade in Reconstruction group were better than those in Ligation group (P<0.05). 6 months after surgery, the incidence of SPH in Ligation group was significantly higher than in Reconstruction group (36.4% vs. 8.1%, respectively). In the prospective study, the incidence of SPH in patients undergoing SV reconstruction was 6.7% (1/15). CONCLUSION: Without compromising surgical outcomes, reconstruction of the S-M-P confluence by bifurcated allogeneic vein is a better method to avoid SPH in patients with advanced pancreatic carcinoma.
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Diabetes retinopathy (DR) is a critical clinical disease with that causes irreversible visual damage in adults, and may even lead to permanent blindness in serious cases. Early identification and treatment of DR is critical. Our aim was to train and externally validate a prediction nomogram for early prediction of DR. 2381 patients with type 2 diabetes mellitus (T2DM) were retrospective study from the First Affiliated Hospital of Xinjiang Medical University in Xinjiang, China, hospitalised between Jan 1, 2019 and Jun 30, 2022. 962 patients with T2DM from the Suzhou BenQ Hospital in Jiangsu, China hospitalised between Jul 1, 2020 to Jun 30, 2022 were considered for external validation. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression was performed to identify independent predictors and establish a nomogram to predict the occurrence of DR. The performance of the nomogram was evaluated using a receiver operating characteristic curve (ROC), a calibration curve, and decision curve analysis (DCA). Neutrophil, 25-hydroxyvitamin D3 [25(OH)D3], Duration of T2DM, hemoglobin A1c (HbA1c), and Apolipoprotein A1 (ApoA1) were used to establish a nomogram model for predicting the risk of DR. In the development and external validation groups, the areas under the curve of the nomogram constructed from the above five factors were 0.834 (95%CI 0.820-0.849) and 0.851 (95%CI 0.829-0.874), respectively. The nomogram demonstrated excellent performance in the calibration curve and DCA. This research has developed and externally verified that the nomograph model shows a good predictive ability in assessing DR risk in people with type 2 diabetes. The application of this model will help clinicians to intervene early, thus effectively reducing the incidence rate and mortality of DR in the future, and has far-reaching significance in improving the long-term health prognosis of diabetes patients.
Subject(s)
Diabetes Mellitus, Type 2 , Diabetic Retinopathy , Nomograms , Humans , Diabetes Mellitus, Type 2/complications , Diabetic Retinopathy/diagnosis , Male , Female , Middle Aged , Retrospective Studies , Aged , ROC Curve , Risk Factors , China/epidemiologyABSTRACT
BACKGROUND: In Chinese Pharmacopeia, Picrasma quassioides (PQ) stems and leaves are recorded as Kumu with antimicrobial, anti-cancer, anti-parasitic effects, etc. However, thick stems are predominantly utilized as medicine in many Asian countries, with leaves rarely used. By now, the phytochemistry and bioactivity of PQ leaves are not well investigated. METHODS: An Orbitrap Elite mass spectrometer was employed to comprehensively investigate PQ stems and leaves sourced from 7 different locations. Additionally, their bioactivities were evaluated against 5 fungi, 6 Gram-positive bacteria and 9 Gram-negative bacteria, a tumor cell line (A549), a non-tumor cell line (WI-26 VA4) and N2 wild-type Caenorhabditis elegans. RESULTS: Bioassay results demonstrated the efficacy of both leaves and stems against tumor cells, several bacteria and fungi, while only leaves exhibited anthelmintic activity against C. elegans. A total of 181 compounds were identified from PQ stems and leaves, including 43 ß-carbolines, 20 bis ß-carbolines, 8 canthinone alkaloids, 56 quassinoids, 12 triterpenoids, 13 terpenoid derivatives, 11 flavonoids, 7 coumarins, and 11 phenolic derivatives, from which 10 compounds were identified as indicator components for quality evaluation. Most alkaloids and triterpenoids were concentrated in PQ stems, while leaves exhibited higher levels of quassinoids and other carbohydrate (CHO) components. CONCLUSION: PQ leaves exhibit distinct chemical profiles and bioactivity with the stems, suggesting their suitability for medicinal purposes. So far, the antibacterial, antifungal, and anthelmintic activities of PQ leaves were first reported here, and considering PQ sustainability, the abundant leaves are recommended for increased utilization, particularly for their rich content of PQ quassinoids.
Subject(s)
Caenorhabditis elegans , Phytochemicals , Picrasma , Plant Leaves , Plant Stems , Plant Leaves/chemistry , Picrasma/chemistry , Animals , Plant Stems/chemistry , Caenorhabditis elegans/drug effects , Phytochemicals/pharmacology , Phytochemicals/isolation & purification , Humans , Cell Line, Tumor , Molecular Structure , Antineoplastic Agents, Phytogenic/pharmacology , Alkaloids/pharmacology , Quassins/pharmacology , Quassins/chemistry , Quassins/isolation & purification , Anthelmintics/pharmacology , Anthelmintics/chemistry , Fungi/drug effects , Flavonoids/pharmacology , Flavonoids/analysisABSTRACT
Yersinia enterocolitica is a globally distributed food-borne gastrointestinal pathogen. The O-antigen variation-determined serotype is an important characteristic of Y. enterocolitica, allowing intraspecies classification for diagnosis and epidemiology purposes. Among the 11 serotypes associated with human yersiniosis, O:3, O:5,27, O:8, and O:9 are the most prevalent, and their O-antigen gene clusters have been well defined. In addition to the O-antigen, several virulence factors are involved in infection and pathogenesis of Y. enterocolitica strains, and these are closely related to their biotypes, reflecting pathogenic properties. In this study, we identified the O-AGC of a Y. enterocolitica strain WL-21 of serotype O:10, and confirmed its functionality in O-antigen synthesis. Furthermore, we analyzed in silico the putative O-AGCs of uncommon serotypes, and found that the O-AGCs of Y. enterocolitica were divided into two genetic patterns: (1) O-AGC within the hemH-gsk locus, possibly synthesizing the O-antigen via the Wzx/Wzy dependent pathway, and (2) O-AGC within the dcuC-galU-galF locus, very likely assembling the O-antigen via the ABC transporter dependent pathway. By screening the virulence genes against genomes from GenBank, we discovered that strains representing different serotypes were grouped according to different virulence gene profiles, indicating strong links between serotypes and virulence markers and implying an interaction between them and the synergistic effect in pathogenicity. Our study provides a framework for further research on the origin and evolution of O-AGCs from Y. enterocolitica, as well as on differences in virulent mechanisms among distinct serotypes.
Subject(s)
Multigene Family , O Antigens , Serogroup , Virulence Factors , Yersinia Infections , Yersinia enterocolitica , Yersinia enterocolitica/genetics , Yersinia enterocolitica/pathogenicity , Yersinia enterocolitica/classification , O Antigens/genetics , Virulence Factors/genetics , Virulence/genetics , Yersinia Infections/microbiology , Humans , Food Microbiology , Bacterial Proteins/genetics , SerotypingABSTRACT
Dwarfing is a pivotal agronomic trait affecting both yield and quality. Citrus species exhibit substantial variation in plant height, among which internode length is a core element. However, the molecular mechanism governing internode elongation remains unclear. Here, we unveiled that the transcriptional cascade consisting of B-BOX DOMAIN PROTEIN 22 (BBX22) and ELONGATED HYPOCOTYL 5 (HY5) finely tunes plant height and internode elongation in citrus. Loss-of-function mutations of BBX22 in an early-flowering citrus (Citrus hindsii "SJG") promoted internode elongation and reduced pigment accumulation, whereas ectopic expression of BBX22 in SJG, sweet orange (C. sinensis), pomelo (C. maxima) or heterologous expression of BBX22 in tomato (Solanum lycopersicum) significantly decreased internode length. Furthermore, exogenous application of gibberellin A3 (GA3) rescued the shortened internode and dwarf phenotype caused by BBX22 overexpression. Additional experiments revealed that BBX22 played a dual role in regulation internode elongation and pigmentation in citrus. On the one hand, it directly bound to and activated the expression of HY5, GA metabolism gene (GA2 OXIDASE 8, GA2ox8), carotenoid biosynthesis gene (PHYTOENE SYNTHASE 1, PSY1) and anthocyanin regulatory gene (Ruby1, a MYB DOMAIN PROTEIN). On the other hand, it acted as a cofactor of HY5, enhancing the ability of HY5 to regulate target genes expression. Together, our results reveal the critical role of the transcriptional cascade consisting of BBX22 and HY5 in controlling internode elongation and pigment accumulation in citrus. Unraveling the crosstalk regulatory mechanism between internode elongation and fruit pigmentation provides key genes for breeding of novel types with both dwarf and health-beneficial fortification in citrus.
Subject(s)
Citrus , Fruit , Gene Expression Regulation, Plant , Pigmentation , Plant Proteins , Citrus/genetics , Citrus/growth & development , Citrus/anatomy & histology , Citrus/metabolism , Plant Proteins/genetics , Plant Proteins/metabolism , Gene Expression Regulation, Plant/drug effects , Pigmentation/genetics , Fruit/genetics , Fruit/growth & development , Fruit/metabolism , Gibberellins/metabolism , Gibberellins/pharmacology , Transcription Factors/metabolism , Transcription Factors/genetics , Basic-Leucine Zipper Transcription Factors/metabolism , Basic-Leucine Zipper Transcription Factors/genetics , PhenotypeABSTRACT
As a novel measure, dynamic functional connectivity (dFC) provides insight into the dynamic nature of brain networks and their interactions in resting-state, surpassing traditional static functional connectivity in pathological conditions such as depression. Since a comprehensive review is still lacking, we then reviewed forty-five eligible papers to explore pathological mechanisms of major depressive disorder (MDD) from perspectives including abnormal brain regions and functional networks, brain state, topological properties, relevant recognition, along with longitudinal studies. Though inconsistencies could be found, common findings are: (1) From different perspectives based on dFC, default-mode network (DMN) with its subregions exhibited a close relation to the pathological mechanism of MDD. (2) With a corrupted integrity within large-scale functional networks and imbalance between them, longer fraction time in a relatively weakly-connected state may be a possible property of MDD concerning its relation with DMN. Abnormal transition frequencies between states were correlated to the severity of MDD. (3) Including dynamic properties in topological network metrics enhanced recognition effect. In all, this review summarized its use for clinical diagnosis and treatment, elucidating the non-stationary of MDD patients' aberrant brain activity in the absence of stimuli and bringing new views into its underlying neuro mechanism.