Self-folding RCA product into a parallel monolayer DNA nanoribbon and woven into a nano-fence structure by a short bridge strand.

The universal programmed construction of patterned periodic self-assembled nanostructures is a technical challenge in DNA origami nanotechnology but has numerous potential applications in biotechnology and biomedicine. In order to circumvent the dilemma that traditional DNA origami requires a long unusual single-stranded virus DNA as the scaffold and hundreds or even thousands of short strands as staples, we report a method for constructing periodically-self-folded rolling circle amplification products (RPs). The repeating unit is designed to have 3 intra-unit duplexes (inDP1,2,3) and 2 between-unit duplexes (buDP1,2). Based on the complementary pairing of bases, RPs each can self-fold into a periodic grid-patterned ribbon (GR) without the help of any auxiliary oligonucleotide staple. Moreover, by using only an oligonucleotide bridge strand, the GRs are connected together into the larger and denser planar nano-fence-shaped product (FP), which substantially reduces the number of DNA components compared with DNA origami and eliminates the obstacles in the practical application of DNA nanostructures. More interestingly, the FP-based DNA framework can be easily functionalized to offer spatial addressability for the precise positioning of nanoparticles and guest proteins with high spatial resolution, providing a new avenue for the future application of DNA assembled framework nanostructures in biology, material science, nanomedicine and computer science that often requires the ordered organization of functional moieties with nanometer-level and even molecular-level precision.

In-situ Ti4+-doped modification of layer-structured Ni-rich LiNi0.83Co0.11Mn0.06O2 cathode materials for high-energy lithium-ion batteries.

The further commercialization of layer-structured Ni-rich LiNi0.83Co0.11Mn0.06O2 (NCM83) cathode for high-energy lithium-ion batteries (LIBs) has been challenged by severe capacity decay and thermal instability owing to the microcracks and harmful phase transitions. Herein, Ti4+-doped NCM83 cathode materials are rationally designed via a simple and low-cost in-situ modification method to improve the crystal structure and electrode-electrolyte interface stability by inhibiting irreversible polarizations and harmful phase transitions of the NCM83 cathode materials due to Ti4+-doped forms stronger metal-O bonds and a stable bulk structural. In addition, the optimal doping amount of the composite cathode material is also determined through the results of physical characterization and electrochemical performance testing. The optimized Ti4+-doped NCM83 cathode material presents wider Li+ ions diffusion channels (c = 14.1687 Å), lower Li+/Ni2+ mixing degree (2.68 %), and compact bulk structure. The cell assembled with the optimized Ti4+-doped NCM83 cathode material exhibits remarkable capacity retention ratio of 95.4 % after 100cycles at 2.0C and room temperature, and outstanding reversible discharge specific capacity of 148.2 mAh g-1 at 5.0C. Even under elevated temperature of 60 °C, it delivers excellent capacity retention ratio of 92.2 % after 100cycles at 2.0C, which is significantly superior to the 47.9 % of the unmodified cathode material. Thus, the in-situ Ti4+-doped strategy presents superior advantages in enhancing the structural stability of Ni-rich cathode materials for LIBs.

Tunable temperature-responsive photonic ionogels with dual signals output.

Photonic ionogels with dual electrical and optical output have been intensively studied. However, tunable temperature-responsive photonic ionogel assembled by thermosensitive nanogels has not been studied yet. Herein, an innovative approach to fabricate photonic ionogels has been developed for smart wearable devices with tunable temperature sensitivity and structural color. Firstly, poly(isopropylacrylamide-r-phenylmaleanilic acid) P(NIPAm-r-NPMA) nanogels self-assemble into photonic crystals in 2-hydroxyethyl acrylate (HEA), water, and the ionic liquid of 1-ethyl-3-methylimidazolium trifluoromethanesulfonate. And then robust photonic ionogels are developed through a polymerization of 2-hydroxyethyl acrylate crosslinked by poly(ethylene glycol) diacrylate (PEGDA). The incorporation of the ionic liquid, 1-ethyl-3-methylimidazolium trifluoromethanesulfonate, enhances the mechanical strength of photonic ionogels and tunes the temperature-sensitivity of the ionogels, making them adaptable to various environmental conditions. The findings demonstrate that these ionogels can serve dual functions in smart wearable devices, combining electrical and optical signal outputs due to the conductivity of the ionic liquid and structural color from the nanogel assembly. The resultant photonic ionogels exhibit exceptional substrate adhesion, mechanical stability, and fast resilience. More significantly, the nanogels within these ionogels serve as the building blocks of photonic crystals (PCs) endow with angle-independent coloration and enhance stretchability beyond 200 %, while the stretchability of the ionogles without the nanogels is only about 100 %. Our photonic ionogels with tunable temperature-sensitivity and dual outputs will open an avenue to the development of the innovative smart wearable devices.

Synthesis of nitrogen-doped amorphous carbon nanotubes from novel cobalt-based MOF precursors for improving potassium-ion storage capability.

Amorphous carbon materials with sophisticated morphologies, variable carbon layer structures, abundant defects, and tunable porosities are favorable as anodes for potassium-ion batteries (PIBs). Synthesizing amorphous carbon materials typically involves the pyrolysis of carbonaceous precursors. Nonetheless, there is still a lack of studies focused on achieving multifaceted structural optimizations of amorphous carbon through precursor formulation. Herein, nitrogen-doped amorphous carbon nanotubes (NACNTs) are derived from a novel composite precursor of cobalt-based metal-organic framework (CMOF) and graphitic carbon nitride (g-CN). The addition of g-CN in the precursor optimizes the structure of amorphous carbon such as morphology, interlayer spacing, nitrogen doping, and porosity. As a result, NACNTs demonstrate significantly improved electrochemical performance. The specific capacities of NACNTs after cycling at current densities of 100 mA/g and 1000 mA/g increased by 194 % and 230 %, reaching 346.6 mAh/g and 211.8 mAh/g, respectively. Furthermore, the NACNTs anode is matched with an organic cathode for full-cell evaluation. The full-cell attains a high specific capacity of 106 mAh/gcathode at a current density of 100 mA/g, retaining 90.5 % of the specific capacity of the cathode half-cell. This study provides a valuable reference for multifaceted structural optimization of amorphous carbon to improve potassium-ion storage capability.

Ethanol-responsive structural colors with multi-level information encryption based on the patterned three-layer inverse opal photonic crystal.

Stimulus-responsive inverse opal photonic crystals (IOPCs) with tunable structural colors show significant promise in information security. To improve upon the traditional bilayer structure with limited color information and single decoding mode, this work developed an ethanol-responsive structure with multi-level information encryption ability by inserting a functional layer into two shielding layers (red Layer A with a photonic stop band (PSB) at 640 nm and green Layer C with a PSB at 530 nm). The functional layer was composed of colorless Layer B, a quick response (QR) code pattern made of TiO2 nanoparticles, and a dense polymer. Due to the isolation of distinct layers, different reflectance values, and different PSB positions of the three-layer IOPC, the structural color of Layer B could only be "turned on" by wetting the entire structure when its PSB redshifted from 360 nm to 460 nm. Specifically, when either side was individually wetted, the PSB of Layer A or C redshifted to 825 nm or 685 nm, and the color of the QR code was dominated by the unwetted red or green layer. After the entire structure had been soaked, the blue QR code was decoded. Meanwhile, when the detecting angle increased from 5° to 60°, the PSBs of Layers B and C in the wetted three-layer IOPC blueshifted from 460 nm to 365 nm and from 685 nm to 540 nm, respectively, which resulted in a cascade decoding process with a single- or mixed-color output. This structure provides a good foundation for multi-level information encryption.

Formation of self-assembled fibril aggregates of trypsin-controllably hydrolyzed soy protein and its regulation on stability of high internal phase Pickering emulsions.

The mechanisms of trypsin hydrolysis time on the structure of soy protein hydrolysate fibril aggregates (SPHFAs) and the stability of SPHFAs-high internal phase Pickering emulsions (HIPPEs) were investigated. SPHFAs were prepared using soy protein hydrolysate (SPH) with different trypsin hydrolysis time (0 min-120 min) to stabilize SPHFAs-HIPPEs. The results showed that moderate trypsin hydrolysis (30 min, hydrolysis degree of 2.31 %) induced SPH unfolding and increased the surface hydrophobicity of SPH, thereby promoting the formation of flexible SPHFAs with maximal thioflavin T intensity and ζ-potential. Moreover, moderate trypsin hydrolysis improved the viscoelasticity of SPHFAs-HIPPEs, and SPHFAs-HIPPEs remained stable after storage at 25 °C for 80 d and heating at 100 °C for 1 h. Excessive trypsin hydrolysis (> 30 min) decreased the stability of SPHFAs-HIPPEs. In conclusion, moderate trypsin hydrolysis promoted the formation of flexible SPHFAs with high surface charge by inducing SPH unfolding, thereby promoting the stability of SPHFAs-HIPPEs.

QSAR: Using the Past to Study the Present.

Quantitative structure-activity relationships (QSAR) is a method for predicting the physical and biological properties of small molecules; it is in use in industry and public services. However, as any scientific method, it is challenged by more and more requests, especially considering its possible role in assessing the safety of new chemicals. To answer the question whether QSAR, by exploiting available knowledge, can build new knowledge, the chapter reviews QSAR methods in search of a QSAR epistemology. QSAR stands on tree pillars, i.e., biological data, chemical knowledge, and modeling algorithms. Usually the biological data, resulting from good experimental practice, are taken as a true picture of the world; chemical knowledge has scientific bases; so if a QSAR model is not working, blame modeling. The role of modeling in developing scientific theories, and in producing knowledge, is so analyzed. QSAR is a mature technology and is part of a large body of in silico methods and other computational methods. The active debate about the acceptability of the QSAR models, about the way to communicate them, and the explanation to provide accompanies the development of today QSAR models. An example about predicting possible endocrine-disrupting chemicals (EDC) shows the many faces of modern QSAR methods.

Support electron inductive effect of Pd-Mn/Ni foam catalyst for robust electrocatalytic hydrodechlorination.

Structural regulation of Pd-based electrocatalytic hydrodechlorination (EHDC) catalyst for constructing high-efficient cathode materials with low noble metal content and high atom utilization is crucial but still challenging. Herein, a support electron inductive effect of Pd-Mn/Ni foam catalyst was proposed via in-situ Mn doping to optimize the electronic structure of the Ni foam (NF), which can inductive regulation of Pd for improving the EHDC performance. The mass activity and current efficiency of Pd-Mn/NF catalyst are 2.91 and 1.34 times superior to that of Pd/NF with 2,4-dichlorophenol as model compound, respectively. The Mn-doped interlayer optimized the electronic structure of Pd by bringing the d-state closer to the Fermi level than Pd on the NF surface, which optimizied the binding of EHDC intermediates. Additionally, the Mn-doped interlayer acted as a promoter for generating H* and accelerating the EHDC reaction. This work presents a simple and effective regulation strategy for constructing high-efficient cathode catalyst for the EHDC of chlorinated organic compounds.

Deciphering environmental factors influencing phytoplankton community structure in a polluted urban river.

Tuojiang River Basin is a first-class tributary of the upper reaches of the Yangtze River-which is the longest river in China. As phytoplankton are sensitive indicators of trophic changes in water bodies, characterizing phytoplankton communities and their growth influencing factors in polluted urban rivers can provide new ideas for pollution control. Here, we used direct microscopic count and environmental DNA (eDNA) metabarcoding methods to investigate phytoplankton community structure in Tuojiang River Basin (Chengdu, Sichuan Province, China). The association between phytoplankton community structure and water environmental factors was evaluated by Mantel analysis. Additional environmental monitoring data were used to pinpoint major factors that influenced phytoplankton growth based on structural equation modeling. At the phylum level, the dominant phytoplankton taxa identified by the conventional microscopic method mainly belonged to Bacillariophyta, Chlorophyta, and Cyanophyta, in contrast with Chlorophyta, Dinophyceae, and Bacillariophyta identified by eDNA metabarcoding. In α-diversity analysis, eDNA metabarcoding detected greater species diversity and achieved higher precision than the microscopic method. Phytoplankton growth was largely limited by phosphorus based on the nitrogen-to-phosphorus ratios > 16:1 in all water samples. Redundancy analysis and structural equation modeling also confirmed that the nitrogen-to-phosphorus ratio was the principal factor influencing phytoplankton growth. The results could be useful for implementing comprehensive management of the river basin environment. It is recommended to control the discharge of point- and surface-source pollutants and the concentration of dissolved oxygen in areas with excessive nutrients (e.g., Jianyang-Ziyang). Algae monitoring techniques and removal strategies should be improved in 201 Hospital, Hongrihe Bridge and Colmar Town areas.

Glycated walnut meal peptide­calcium chelates (COS-MMGGED-Ca): Preparation, characterization, and calcium absorption-promoting.

This study isolated a novel peptide MMGGED with strong calcium-binding capacity from defatted walnut meal and synthesized a novel peptide­calcium chelate COS-MMGGED-Ca with high stability via glycation. Structural characterization and computer simulation identified binding sites, while in vitro digestion stability and calcium transport experiments explored the chelate's properties. Results showed that after glycation, COS-MMGGED bound Ca2+ with 88.75 ± 1.75 %, mainly via aspartic and glutamic acids. COS-MMGGED-Ca released Ca2+ steadily (60.27 %), with thermal denaturation temperature increased by 18 °C and 37 °C compared to MMGGED-Ca, indicating good processing performance. Furthermore, COS-MMGGED significantly enhanced Ca2+ transport across Caco-2 monolayers, 1.13-fold and 1.62-fold higher than CaCl2 and MMGGED, respectively, at 240 h. These findings prove glycation enhances structural properties, stability, calcium loading, and transport of peptide­calcium chelates, providing a scientific basis for developing novel efficient calcium supplements and high-value utilization of walnut meal.

Effect of structure on sensing performance of nitro explosives with high sensitivity and mechanism of two Tb(III) coordination polymers.

The use of a conjugate N-containing ligand resulted in the decreasing of structural dimensions from 2D network of [Tb(2-pyia)(Ac)(H2O)] (CP1) to 1D chain [Tb(2-pyia)(Ac)(IDP)] (CP2) (2-H2pyia = 5-(pyridin-2-ylmethoxy) isophthalic acid and IDP=imidazo[4,5-f]-[1,10] phenanthroline). Both of them exhibit the characteristic luminescence of Tb ions and could have high fluorescence sensing properties for cefixime and fluridine. The different sensing properties for nitro explosives are manifested as CP1 for nitrobenzene and CP2 for 4-nitrophenol due to the difference in structure. Furthermore, CP2 exhibits the ratiometric fluorescence sensing for Fe3+ ion with a low detection limit of 0.405 µM. The fluorescence sensing mechanism of the two Tb complexes for different analytes was investigated using experimental methods and theoretical calculations. CP1 was used for the detection of Flu residues in the actual system and better results were obtained. The work shows the introduction of the chelated ligand might affect the structural and sensing performance changes of coordination polymers.

AI Prediction of Structural Stability of Nanoproteins Based on Structures and Residue Properties by Mean Pooled Dual Graph Convolutional Network.

The structural stability of proteins is an important topic in various fields such as biotechnology, pharmaceuticals, and enzymology. Specifically, understanding the structural stability of protein is crucial for protein design. Artificial design, while pursuing high thermodynamic stability and rigidity of proteins, inevitably sacrifices biological functions closely related to protein flexibility. The thermodynamic stability of proteins is not always optimal when they are highest to perfectly perform their biological functions. Extensive theoretical and experimental screening is often required to obtain stable protein structures. Thus, it becomes critically important to develop a stability prediction model based on the balance between protein stability and bioactivity. To design protein drugs with better functionality in a broader structural space, a novel protein structural stability predictor called PSSP has been developed in this study. PSSP is a mean pooled dual graph convolutional network (GCN) model based on sequence characteristics and secondary structure, distance matrix, graph, and residue properties of a nanoprotein to provide rapid prediction and judgment. This model exhibits excellent robustness in predicting the structural stability of nanoproteins. Comparing with previous artificial intelligence algorithms, the results indicate this model can provide a rapid and accurate assessment of the structural stability of artificially designed proteins, which shows the great promises for promoting the robust development of protein design.

A critical review of persimmon-derived pectin: Innovations in extraction, structural characterization, biological potentials, and health-promoting effects.

Persimmon-derived pectin (PP) is a versatile dietary polysaccharide with considerable industrial and biological significance, demonstrating a range of functionalities and health-promoting benefits. This review explores the changes in PP during postharvest and processing, detailing structural alterations and extraction techniques for optimal characteristics. Key functional attributes of PP-such as emulsification, rheology, antioxidant capacity, immunomodulation, and gut microbiota regulation-highlight its potential applications in food, healthcare, pharmaceuticals, and cosmetics. The review also explores methods to enhance the functional properties of PP through synergistic interactions with polyphenols. A strategic roadmap for advancing PP research is proposed, connecting extraction methods, structural characteristics, and functional properties to tailor PP for specific applications in food science and technology. Overall, persimmon-derived pectin is positioned as a valuable food-derived bioactive ingredient with diverse capabilities, poised to drive innovation and advance nutritional science across multiple sectors.

Structural inequality and temporal brain dynamics across diverse samples.

BACKGROUND: Structural income inequality - the uneven income distribution across regions or countries - could affect brain structure and function, beyond individual differences. However, the impact of structural income inequality on the brain dynamics and the roles of demographics and cognition in these associations remains unexplored. METHODS: Here, we assessed the impact of structural income inequality, as measured by the Gini coefficient on multiple EEG metrics, while considering the subject-level effects of demographic (age, sex, education) and cognitive factors. Resting-state EEG signals were collected from a diverse sample (countries = 10; healthy individuals = 1394 from Argentina, Brazil, Colombia, Chile, Cuba, Greece, Ireland, Italy, Turkey and United Kingdom). Complexity (fractal dimension, permutation entropy, Wiener entropy, spectral structure variability), power spectral and aperiodic components (1/f slope, knee, offset), as well as graph-theoretic measures were analysed. FINDINGS: Despite variability in samples, data collection methods, and EEG acquisition parameters, structural inequality systematically predicted electrophysiological brain dynamics, proving to be a more crucial determinant of brain dynamics than individual-level factors. Complexity and aperiodic activity metrics captured better the effects of structural inequality on brain function. Following inequality, age and cognition emerged as the most influential predictors. The overall results provided convergent multimodal metrics of biologic embedding of structural income inequality characterised by less complex signals, increased random asynchronous neural activity, and reduced alpha and beta power, particularly over temporoposterior regions. CONCLUSION: These findings might challenge conventional neuroscience approaches that tend to overemphasise the influence of individual-level factors, while neglecting structural factors. Results pave the way for neuroscience-informed public policies aimed at tackling structural inequalities in diverse populations.

Welcoming Alejandro Buschiazzo, Dorothee Liebschner and Stephen Muench as Co-editors of Acta Crystallographica F - Structural Biology Communications.

The Section Editors welcome and introduce three new Co-editors to the journal and summarize their expertise in computational structural biology, experimental structural biology and cryo-electron microscopy.

Critical Analysis of the Scales Assessing Assistance Provided by Family Caregivers.

BACKGROUND: While the literature on caregiver-assessment scales often focuses on the quantitative and psychometric aspects of the scales, we wished to examine the discourse on caregiving, caregivers and care-recipients (particularly, people with dementia) produced by these scales. What discourse does it help to crystallise and naturalise by dint of being used widely, with unresolved ethical and political issues? METHODS: We analysed two well-known scales that are widely used in both research and clinical settings and conceived among others for people with dementia: Zarit and, offering a sharp contrast, the CRA. We performed semantic network analysis using EVOQ software (https://www.evoq.be/) to visualise the links between the terms. RESULTS: Whereas the Zarit scale is entirely built around a view of caregiving and the care-recipient as a burden, the CRA offers a different discourse. Instead of considering the provision of help as an emotional load, the desire to help is highlighted. Rather than considering the care-recipient as a weight, the recognition of his or her contribution to the relationship with the caregiver is suggested. Moreover, the caregiver is presented as a relative who is capable of active strategies in order to cope with the reality of care without becoming exhausted. CONCLUSIONS: The comparison of our two analyses shows the extent to which the scales produce a discourse which needs to be examined before use, given its epistemological, ethical and political significance. Clinicians and researchers need to make choices between the many existing instruments and be able to justify them. Their reasons should include not only the psychometric qualities of the chosen tool, but also the discourse that it underpins, so as to avoid contributing to the promotion of a vision of care and its givers and recipients that would be reductive, moving us further away from a caring society.

The mediating role of loneliness between psychological resilience and health-related quality of life among patients with nasopharyngeal carcinoma: a cross-sectional study using structural equation modeling.

BACKGROUND: Cancer patients' health-related quality of life (HRQoL) has always been a hot discussion spot. Loneliness and psychological resilience are considered to be significant psychosocial factors impacting the HRQoL of the cancer population. However, there is a lack of studies on the interrelationship among loneliness, resilience, and HRQoL in patients with nasopharyngeal carcinoma (NPC). This study aims to explore the relationship between resilience and HRQoL among NPC patients and to recognize the potential mediating role of loneliness in this relationship. METHODS: A cross-sectional study was performed in this study. A convenience sampling method was conducted to recruit participants. A total of 155 patients with nasopharyngeal carcinoma were required to complete the socio-demographic questionnaire, the Cancer Loneliness Scale (CLS), the 10-item Connor-Davidson Resilience Scale (CD-RISC-10), and the European Organization for Research and Treatment of Quality of Life Questionnaire C-30 (EORTC QLQ-C30) from April 2022 to August 2022 in a tertiary grade A hospital in Guangzhou, China. The multiple linear regression analysis was used to identify influencing factors, and structural equation modeling with the bootstrap method was performed to test the mediating role of loneliness. This study complied with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. RESULTS: HRQoL was at a median level among NPC patients, with a mean score of 64.19 (24.38) on the Global health status/quality of life (GHS/QoL) scale. Monthly household income (B = 4.973, P < 0.001), cancer stage (B=-4.342, P = 0.004), psychological resilience (B = 0.914, P < 0.001), and loneliness (B =-1.083, P < 0.001) were independent factors related to HRQoL, explaining 36.7% of the variance of HRQoL. Psychological resilience exerted its direct negative impact on loneliness (ß = -0.199, BC95%CI = -0.318/-0.089), and it also had a both direct and indirect positive impact on HRQoL (ß = 0.653, BC95%CI = 0.423/0.912; ß = 0.142, BC95%CI = 0.046/0.296). Loneliness exerted a partially mediating impact on the relationship between psychological resilience and HRQoL. CONCLUSIONS: NPC patients with higher monthly household, early stages of cancer, higher resilience, and lower loneliness show a better HRQoL. Resilience has an indirect positive impact on HRQoL by influencing loneliness in NPC patients. It is suggested that healthcare staff should strive to enhancing resilience and reducing loneliness as new strategies to promote NPC patients' HRQoL further.

Engineering Tk1656, a highly active l-asparaginase from Thermococcus kodakarensis, for enhanced activity and stability.

l-Asparaginases catalyze the hydrolysis of l-asparagine to l-aspartic acid and ammonia. These enzymes have potential applications in therapeutics and food industry. Tk1656, a highly active and thermostable l-asparaginase from Thermococcus kodakarensis, has been proved effective in selective killing of acute lymphocytic leukemia cells and in reducing acrylamide formation in baked and fried foods. However, it displayed <5 % activity under physiological conditions compared to the optimal activity at 85 °C and pH 9.5. We have attempted engineering of this valuable enzyme to improve the characteristics required for therapeutic and industrial applications. Based on the literature and crystal structure of Tk1656, nine specific mutant variants were designed, produced in Escherichia coli, and the purified mutant enzymes were compared with the wild-type. One of the mutants, K299L, displayed >20 % increase in activity at 85 °C. H158S substitution resulted in >5 °C increase in the optimal temperature. Similarly, a mesophilic-like mutation L56D, resulted in >5-fold increase in activity at pH 7.0 and 37 °C compared to that of the wild-type enzyme. The substrate specificity of the mutant variants remained unchanged. These results demonstrate that L56D and K299L variants of Tk1656 are the potent enzymes for therapeutics and acrylamide mitigation applications, respectively.

Review of the recent advances in polysaccharides from Ficus carica: Extraction, purification, structural characteristics, bioactivities and potential applications.

Ficus carica (F. carica), commonly referred to as the fig tree, has received considerable attention due to its delectable and nutritious fruits. F. carica polysaccharides (FPs) are one of the key bioactive constituents of F. carica, demonstrating various biological activities such as antioxidative, immunomodulatory, anti-inflammatory, and antitumor effects, among others. Nevertheless, the extraction and purification techniques for FPs still require innovations to address their structural characteristics in order to elucidate the intricate mechanisms affecting their biological activities. Given this, the current review systematically summarizes the recent advancements in FPs, covering extraction, purification, structural characteristics, bioactivities, structure-activity relationships (SARs), current applications, challenges and future prospects. The composition of FPs predominantly includes Glu, Gal, and Rha, with a broad molecular weight distribution (ranging from 21.9 kDa to 6890 kDa). The SARs analysis suggests that the bioactivities of FPs are closely linked to their monosaccharide composition, molecular weight, uronic acid content, and configuration characteristics, underscoring the significant role of FPs in driving the development of novel bioactive compounds in the health, food, and medical sectors. In conclusion, this review would contribute the valuable research insights and provide the updated information to foster the advancement of FPs for diverse therapeutic and industrial applications.