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In this study, pectinase-extracted pectin (PPHP), mixed enzyme-extracted pectin (MPHP), and water-extracted pectin (WPHP) from Premna ligustrides Hemsl. leaves were prepared by pectinase-assisted extraction, pectinase and cellulase-assisted extraction and hot water extraction, respectively, and their molecular masses, monosaccharide compositions, infrared spectra, galacturonic acid contents, degrees of esterification were determined. In addition, their scavenging capacity against 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 2,2’-azinobis-(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) radical cation and Fe3+ reducing power were assayed, and their antibacterial effects on Bacillus subtilis, Escherichia coli and Staphylococcus aureus were explored. The results showed that the yields of WPHP, PPHP and MPHP were 5.11%, 6.45% and 8.91%, respectively. WPHP belonged to high-ester pectin, while MPHP and PPHP belonged to low-ester pectin. The weight-average molecular mass of pectin in the leaves of Premna ligustrides Hemsl was reduced by enzymatic treatment. The contents of total phenols and total flavonoids in MPHP were 17.09 and 26.46 mg/g, respectively, higher than those in WPHP and PPHP. All three pectins had strong scavenging capacities against DPPH radical and ABTS radical cation, among which MPHP had the strongest antioxidant activity. The results of in vitro antibacterial activity showed that MPHP had the best antibacterial effect on Bacillus subtilis, Escherichia coli and Staphylococcus aureus. These results provide a basis for further searching for the material basis of the antibacterial activity of pectin from Premna ligustroides Hemsl. leaves, and are of significance for the in-depth development and utilization of pectin from Premna ligustroides Hemsl. leaves.

China has the world’s largest fisheries industry that has provided a healthy and high-quality food source. Currently, guaranteeing national food security, implementing an all-encompassing approach to food, and establishing a diversified food supply system all pose a great demand for the high-quality development of China’s fisheries industry. This study explores the development status and trend of fisheries in China from the aspects of fishery resources and capture, aquaculture and marine ranching, and aquatic product processing and circulation, and examines major problems through industry research and extensive discussion. Industry development goals and key measures are further proposed. Results found that the pressure on offshore capture is too high, understanding of deep-sea and polar resources is insufficient, the independent capability of technologies and equipment is inadequate, the mechanized, automatic, and intelligent levels of aquaculture are low, high-quality feed and raw materials rely heavily on imports, the basic software and hardware capabilities of the intelligent fisheries are deficient, and the aquatic product processing capacity is lagging behind. Therefore, the following key measures are proposed: conservation and restoration of offshore fishery resources, development and scientific utilization of deep-sea fishery resources, construction and application of a new technology system for green and healthy aquaculture, research and application of deep-sea aquaculture platform technologies, construction and promotion of new aquaculture models, and green processing and high-value utilization of aquatic products.Through the high-quality development of fisheries, China is expected to become advantageous in fisheries science and technology by 2035, with a total output of 8.1×107 t of aquatic products. By 2050, intelligent fisheries is expected to be realized in China, outputting 1×108 t of aquatic products.

Background: Fritillaria ussuriensis is an endangered medicinal plant known for its notable therapeutic properties. Unfortunately, its population has drastically declined due to the destruction of forest habitats. Thus, effectively protecting F. ussuriensis from extinction poses a significant challenge. A profound understanding of its genetic foundation is crucial. To date, research on the complete mitochondrial genome of F. ussuriensis has not yet been reported. Results: The complete mitochondrial genome of F. ussuriensis was sequenced and assembled by integrating PacBio and Illumina sequencing technologies, revealing 13 circular chromosomes totaling 737,569 bp with an average GC content of 45.41%. A total of 55 genes were annotated in this mitogenome, including 2 rRNA genes, 12 tRNA genes, and 41 PCGs. The mitochondrial genome of F. ussuriensis contained 192 SSRs and 4,027 dispersed repeats. In the PCGs of F. ussuriensis mitogenome, 90.00% of the RSCU values exceeding 1 exhibited a preference for A-ended or U-ended codons. In addition, 505 RNA editing sites were predicted across these PCGs. Selective pressure analysis suggested negative selection on most PCGs to preserve mitochondrial functionality, as the notable exception of the gene nad3 showed positive selection. Comparison between the mitochondrial and chloroplast genomes of F. ussuriensis revealed 20 homologous fragments totaling 8,954 bp. Nucleotide diversity analysis revealed the variation among genes, and gene atp9 was the most notable. Despite the conservation of GC content, mitogenome sizes varied significantly among six closely related species, and colinear analysis confirmed the lack of conservation in their genomic structures. Phylogenetic analysis indicated a close relationship between F. ussuriensis and Lilium tsingtauense. Conclusions: In this study, we sequenced and annotated the mitogenome of F. ussuriensis and compared it with the mitogenomes of other closely related species. In addition to genomic features and evolutionary position, this study also provides valuable genomic resources to further understand and utilize this medicinal plant. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to develop a novel MRI-based paravertebral muscle quality (PVMQ) score for assessing muscle quality and to investigate its correlation with the degree of fat infiltration (DFF) and the vertebral bone quality (VBQ) score of paravertebral muscles. Additionally, the study compares the effectiveness of the PVMQ score and the VBQ score in assessing muscle quality and bone quality. Methods: PVMQ scores were derived from the ratio of paravertebral muscle signal intensity (SI) to L3 cerebrospinal fluid SI on T2-weighted MRI. Image J software assessed paravertebral muscle cross-sectional area (CSA) and DFF. Spearman rank correlation analyses explored associations between PVMQ, VBQ scores, DFF, and T-scores in both genders. Receiver operating characteristic (ROC) curves compared PVMQ and VBQ scores' effectiveness in distinguishing osteopenia/osteoporosis and high paraspinal muscle DFF. Results: In this study of 144 patients (94 females), PVMQ scores were significantly higher in osteoporosis and osteopenia groups compared to normals, with variations observed between genders (P < 0.05). PVMQ showed stronger positive correlation with VBQ scores and DFF in females than males (0.584 vs 0.445, 0.579 vs 0.528; P < 0.01). ROC analysis favored PVMQ over VBQ for low muscle mass in both genders (AUC = 0.767 vs 0.718, 0.793 vs 0.718). VBQ was better for bone mass in males (0.737/0.865 vs 0.691/0.858), whereas PVMQ excelled for females (0.808/0.764 vs 0.721/0.718). Conclusion: The novel PVMQ score provides a reliable assessment of paravertebral muscle quality and shows a strong correlation with VBQ scores and DFF, particularly in females. It outperforms VBQ scores in evaluating muscle mass and offers valuable insights for assessing bone mass in females. These findings underscore the potential of the PVMQ score as a dual-purpose tool for evaluating both muscle and bone health, informing future research and clinical practice. [ABSTRACT FROM AUTHOR]

Background: Variations exist in the response of patients with Crohn's disease (CD) to ustekinumab (UST) treatment, but the underlying cause remains unknown. Our objective was to investigate the involvement of immune cells and identify potential biomarkers that could predict the response to interleukin (IL) 12/23 inhibitors in patients with CD. Methods: The GSE207022 dataset, which consisted of 54 non-responders and 9 responders to UST in a CD cohort, was analyzed. Differentially expressed genes (DEGs) were identified and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Least absolute shrinkage and selection operator (LASSO) regression was used to screen the most powerful hub genes. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performances of these genes. Single-sample Gene Set Enrichment Analysis (ssGSEA) was used to estimate the proportions of immune cell types. These significantly altered genes were subjected to cluster analysis into immune cell-related infiltration. To validate the reliability of the candidates, patients prescribed UST as a first-line biologic in a prospective cohort were included as an independent validation dataset. Results: A total of 99 DEGs were identified in the integrated dataset. GO and KEGG analyses revealed significant enrichment of immune response pathways in patients with CD. Thirteen genes (SOCS3, CD55, KDM5D, IGFBP5, LCN2, SLC15A1, XPNPEP2, HLA-DQA2, HMGCS2, DDX3Y, ITGB2, CDKN2B and HLA-DQA1), which were primarily associated with the response versus nonresponse patients, were identified and included in the LASSO analysis. These genes accurately predicted treatment response, with an area under the curve (AUC) of 0.938. T helper cell type 1 (Th1) cell polarization was comparatively strong in nonresponse individuals. Positive connections were observed between Th1 cells and the LCN2 and KDM5D genes. Furthermore, we employed an independent validation dataset and early experimental verification to validate the LCN2 and KDM5D genes as effective predictive markers. Conclusions: Th1 cell polarization is an important cause of nonresponse to UST therapy in patients with CD. LCN2 and KDM5D can be used as predictive markers to effectively identify nonresponse patients. Trial registration: Trial registration number: NCT05542459; Date of registration: 2022-09-14; URL: https://www.clinicaltrials.gov. [ABSTRACT FROM AUTHOR]