Polysaccharides in fruits: Biological activities, structures, and structure-activity relationships and influencing factors-A review.

Fruits are a rich source of polysaccharides, and an increasing number of studies have shown that polysaccharides from fruits have a wide range of biological functions. Here, we thoroughly review recent advances in the study of the bioactivities, structures, and structure-activity relationships of fruit polysaccharides, especially highlighting the structure-activity influencing factors such as extraction methods and chemical modifications. Different extraction methods cause differences in the primary structures of polysaccharides, which in turn lead to different polysaccharide biological activities. Differences in the degree of modification, molecular weight, substitution position, and chain conformation caused by chemical modification can all affect the biological activities of fruit polysaccharides. Furthermore, we summarize the applications of fruit polysaccharides in the fields of pharmacy and medicine, foods, cosmetics, and materials. The challenges and perspectives for fruit polysaccharide research are also discussed.

Janus structure hydrogels: recent advances in synthetic strategies, biomedical microstructure and (bio)applications.

Janus structure hydrogels (JSHs) are novel materials. Their primary fabrication methods and various applications have been widely reported. JSHs are primarily composed of Janus particles (JNPs) and polysaccharide components. They exhibit two distinct physical or chemical properties, generating intriguing characteristics due to their asymmetric structure. Normally, one side (adhesive interface) is predominantly constituted of polysaccharide components, primarily serving excellent adhesion. On the other side (functional surface), they integrate diverse functionalities, concurrently performing a plethora of synergistic functions. In the biomedical field, JSHs are widely applied in anti-adhesion, drug delivery, wound healing, and other areas. It also exhibits functions in seawater desalination and motion sensing. Thus, JSHs hold broad prospects for applications, and they possess significant research value in nanotechnology, environmental science, healthcare, and other fields. Additionally, this article proposes the challenges and future work facing these fields.

Transcutaneous electrical acupoint stimulation reduces postoperative patients' length of stay and hospitalization costs: A systematic review and meta-analysis.

OBJECTIVE: To study the effects of transcutaneous electrical acupoint stimulation (TEAS) on length of stay (LOS) and hospitalization costs in postoperative inpatients. METHODS: Two researchers collectively searched PubMed, Embase, Cochrane Library, China Network Knowledge Infrastructure and Wanfang Database. The search time was set from the beginning to April 25, 2023, to identify randomized controlled trials articles that met the criteria. Statistical analyses were performed using the Stata software (version 16.0). The risk of bias was assessed using the Cochrane risk-of-bias tool, and publication bias was evaluated using a funnel plot and Egger's test. The quality of evidence was assessed according to the Grading of Recommendations Assessment, Development, and Evaluation approach. RESULTS: Thirty-four randomized controlled trials were included. The main results showed that TEAS reduced hospitalization costs (standardized mean difference (SMD)=-1.92; 95% confidence interval (CI) -3.40, -0.43), LOS (SMD=-1.00; 95% CI -1.30, -0.70) and postoperative LOS (SMD=-0.70; 95% CI -0.91, -0.49) in postoperative patients. Subgroup analyses further revealed that TEAS was effective in reducing both the overall and postoperative LOS in patients undergoing multiple surgical procedures. It is worth noting that the observed heterogeneity in the results may be attributed to variations in surgical procedures, stimulation frequencies, and stimulation points utilized in different trials. CONCLUSIONS: TEAS can help postoperative patients reduce their LOS and hospitalization cost. However, considering the bias identified and heterogeneity, the results of this review should be interpreted with caution.

Comprehensive Evolutionary Analysis of the SMXL Gene Family in Rosaceae: Further Insights into Its Origin, Expansion, Diversification, and Role in Regulating Pear Branching.

SMXL genes constitute a conserved gene family that is ubiquitous in angiosperms and involved in regulating various plant processes, including branching, leaf elongation, and anthocyanin biosynthesis, but little is known about their molecular functions in pear branching. Here, we performed genome-wide identification and investigation of the SMXL genes in 16 angiosperms and analyzed their phylogenetics, structural features, conserved motifs, and expression patterns. In total, 121 SMXLs genes were identified and were classified into four groups. The number of non-redundant SMXL genes in each species varied from 3 (Amborella trichopoda Baill.) to 18 (Glycine max Merr.) and revealed clear gene expansion events over evolutionary history. All the SMXL genes showed conserved structures, containing no more than two introns. Three-dimensional protein structure prediction revealed distinct structures between but similar structures within groups. A quantitative real-time PCR analysis revealed different expressions of 10 SMXL genes from pear branching induced by fruit-thinning treatment. Overall, our study provides a comprehensive investigation of SMXL genes in the Rosaceae family, especially pear. The results offer a reference for understanding the evolutionary history of SMXL genes and provide excellent candidates for studying fruit tree branching regulation, and in facilitating pear pruning and planting strategies.

Pancreatitis affects gut microbiota via metabolites and inflammatory cytokines: an exploratory two-step Mendelian randomisation study.

Previous studies have observed relationships between pancreatitis and gut microbiota; however, specific changes in gut microbiota abundance and underlying mechanisms in pancreatitis remain unknown. Metabolites are important for gut microbiota to fulfil their biological functions, and changes in the metabolic and immune environments are closely linked to changes in microbiota abundance. We aimed to clarify the mechanisms of gut-pancreas interactions and explore the possible role of metabolites and the immune system. To this end, we conducted two-sample Mendelian randomisation (MR) analysis to evaluate the casual links between four different types of pancreatitis and gut microbiota, metabolites, and inflammatory cytokines. A two-step MR analysis was conducted to further evaluate the probable mediating pathways involving metabolites and inflammatory cytokines in the causal relationship between pancreatitis and gut microbiota. In total, six potential mediators were identified in the causal relationship between pancreatitis and gut microbiota. Nineteen species of gut microbiota and seven inflammatory cytokines were genetically associated with the four types of pancreatitis. Metabolites involved in glucose and amino acid metabolisms were genetically associated with chronic pancreatitis, and those involved in lipid metabolism were genetically associated with acute pancreatitis. Our study identified alterations in the gut microbiota, metabolites, and inflammatory cytokines in pancreatitis at the genetic level and found six potential mediators of the pancreas-gut axis, which may provide insights into the precise diagnosis of pancreatitis and treatment interventions for gut microbiota to prevent the exacerbation of pancreatitis. Future studies could elucidate the mechanism underlying the association between pancreatitis and the gut microbiota.

Operation-robust SiO2-based memristive application in air.

In recent years, neuromorphic computing is recognized as a promising path to further improve the efficiency of integrated computing system in the post-Moore era, relying on its high parallelism. As a key fundamental element in hardware-implementing neuromorphic system, the synaptic device has made substantial research progress. Among these, SiO2 trapping-based memristive devices generally have systematically integrated merits, such as ease of fabrication and high CMOS process compatibility, but electrochemical activity to oxygen makes them unreliable for operating in air. Here, by using ultrathin Si3N4 as a physical isolation layer, we have obtained a robust memristive device based on SiO2 trapping although operating in air. Further study of Si3N4 thickness dependence has demonstrated that 7 nm is suggested as the most favorable thickness for reliable and flexible programming, and that an inherent isolating mechanism is 'switching-on' for an electron but 'switching-off' for large-sized oxygen molecules. Based on a device with 7 nm Si3N4, we have mimicked various modes of synaptic plasticities. These results could thus not only increase the prospects of using SiO2 trapping in memristive applications but also provide an effective path to improve the robustness of these SiO2-based applications against ambient air.

Recent progress on defect-engineering in ferroelectric HfO2: The next step forward via multiscale structural optimization.

The discovery of unconventional scale-free ferroelectricity in HfO2-based fluorite thin films has attracted great attention in recent years for their promising applications in low-power logic and nonvolatile memories. The ferroelectricity of HfO2 is intrinsically originated from the widely accepted ferroelectric metastable orthorhombic Pca21 phase. In the last decade, defect-doping/solid solution has shown excellent prospects in enhancing and stabilizing the ferroelectricity via isovalent or aliovalent defect-engineering. Here, the recent advances in defect-engineered HfO2-based ferroelectrics are first reviewed, including progress in mono-ionic doping and mixed ion-doping. Then, the defect-lattice correlation, the point-defect promoted phase transition kinetics, and the interface-engineered dynamic behaviour of oxygen vacancy are summarized. In addition, thin film preparation and ion bombardment doping are summarized. Finally, the outlook and challenges are discussed. A multiscale structural optimization approach is suggested for further property optimization. This article not only covers an overview of the state-of-art advances of defects in fluorite ferroelectrics, but also future prospects that may inspire their further property-optimization via defect-engineering.

Deciphering single-cell protein secretion and gene expressions by constructing cell-antibody conjugates.

Secreted proteins play critical roles in regulating immune responses, exerting cytotoxic effects on tumor cells, promoting inflammatory processes, and influencing cellular metabolism. Deciphering the intricate relationship between the heterogeneity of secreted proteins and their transcriptional states is pivotal in the study of cellular heterogeneity. Here we proposed a cell-antibody conjugate-based sequencing methodology (Cellab-seq) for joint characterization of secreted proteins and transcriptome. Cellab-seq utilizes a chemoenzymatic strategy to construct cell-antibody conjugates, which enables the capture of secreted proteins and their signal transduction with the incorporation of barcode detection antibodies. We applied Cellab-seq to investigate how gene expression influences the activity of secreted proteins in NK cells. Altogether, this strategy facilitates a nuanced understanding of cellular dynamics under diverse physiological conditions, ultimately contributing to the prevention, diagnosis and treatment of diseases.

Information quality of videos related to Helicobacter pylori infection on TikTok: Cross-sectional study.

BACKGROUND: Helicobacter pylori (H. pylori) poses serious threats to human health. TikTok (Douyin in Chinese), a major social media platform focused on sharing short videos, has demonstrated great potential in spreading health information, including information related to H. pylori infection. This study aims to evaluate the content and quality of the information shared in TikTok videos about H. pylori infection in mainland China. METHODS: We collected a sample of 116 videos in Chinese related to H. pylori infection from TikTok. Video contents were evaluated by the coding schema proposed by Goobie et al., and the Hexagonal Radar Schema was used to intuitively display the spotlight and weight of each aspect of the videos. The DISCERN questionnaire was used to evaluate the quality of the videos. RESULTS: We identified two major sources of videos related to H. pylori: individual users (n = 89) and organizational users (n = 27). Regarding content, the Hexagonal Radar Charts showed that more than 35% of the videos delivered moderate to high quality content (>1 point) in terms of definition, symptoms and management of the disease, whereas risk factors, evaluation and outcomes of the disease were less discussed. The DISCERN classification data showed that 0.9% of the videos were "very poor," 5.2% "poor," 68.7% "fair," 20.0% "good," and only 5.2% "excellent". Regarding total DISCERN scores, videos published by nonprofit organizations had the highest scores, followed by videos uploaded by health professionals. CONCLUSION: Although the overall quality of TikTok videos related to H. pylori infection was medium, users should be careful when obtaining information related to H. pylori infection on TikTok and opt for videos uploaded by nonprofit organizations and health professionals.

The quality and reliability of TikTok videos on non-alcoholic fatty liver disease: a propensity score matching analysis.

Background: Lifestyle modification is the cornerstone of non-alcoholic fatty liver disease (NAFLD) prevention and treatment. Short video platforms can facilitate easier access to health information for patients, thereby influencing lifestyle changes. An increasing number of individuals rely on online platforms to acquire health-related information about NAFLD. However, the quality of information regarding NAFLD on these platforms remains unclear. Objective: This study aimed to investigate the quality of information about NAFLD on TikTok. Methods: A total of 497 videos were retrieved from TikTok. The basic video information, including the video source, was extracted. Two independent raters evaluated the quality and reliability of the videos using the Global Quality Score system and a modified DISCERN tool. Propensity score matching (PSM) was used to compare video quality across sources. Results: NAFLD-related videos on TikTok were divided into three groups according to the uploader: health professionals, medical institutions, and science bloggers. Overall, the quality of NAFLD videos on TikTok was not satisfactory. Before PSM, there were no significant differences in video quality or content between the three groups. After PSM, the quality of NAFLD videos from health professionals was significantly better than the videos created by other groups. Besides, the videos of health professionals outperformed those of medical institutions and science bloggers in terms of the definition of disease, risk factors, and treatment, but were inferior to those of medical institutions considering the symptoms and tests of NAFLD. Conclusion: The quality of NAFLD-related videos on TikTok needs improvement. Compared with videos created by science bloggers and medical institutions, videos from health professionals may provide accurate guidance on the treatment and prevention of NAFLD.

LFA-1 knockout inhibited the tumor growth and is correlated with treg cells.

Cancer immunotherapy has been proven to be clinically effective in multiple types of cancers. Lymphocyte function-associated antigen 1 (LFA-1), a member of the integrin family of adhesion molecules, is expressed mainly on αß T cells. LFA-1 is associated with tumor immune responses, but its exact mechanism remains unknown. Here, two kinds of mice tumor model of LFA-1 knockout (LFA-1-/-) mice bearing subcutaneous tumor and Apc Min/+;LFA-1-/- mice were used to confirm that LFA-1 knockout resulted in inhibition of tumor growth. Furthermore, it also demonstrated that the numbers of regulatory T cells (Treg cells) in the spleen, blood, mesenteric lymph nodes were decreased in LFA-1-/- mice, and the numbers of Treg cells in mesenteric lymph nodes were also decreased in Apc Min/+;LFA-1-/- mice compared with Apc Min/+ mice. LFA-1 inhibitor (BIRT377) was administered to subcutaneous tumor-bearing LFA-1+/+ mice, and the results showed that the tumor growth was inhibited and the number of Treg cells was reduced. The analysis of TIMER tumor database indicated that LFA-1 expression is positively associated with Treg cells and TNM stage. Conclusively, this suggests that LFA-1 knockout would inhibit tumor growth and is correlated with Treg cells. LFA-1 may be one potential target for cancer immunotherapy. Video Abstract.

Doping-modulated lateral asymmetric Schottky diode as a high-performance self-powered synaptic device.

In the post-Moore era, the gradually saturated computational capability of conventional digital computers showing the opposite trend as the exponentially increasing data volumes imperatively required a platform or technology to break this bottleneck. Brain-inspired neuromorphic computing promises to inherently improve the efficiency of information processing and computation by means of the highly parallel hardware architecture to reduce global data transmission. Here, we demonstrate a compact device technology based on the barrier asymmetry to achieve zero-consumption self-powered synaptic devices. In order to tune the device behaviors, the typical chemical doping is used to tailor the asymmetry for energy harvesting. Finally, in our demonstrated devices, the open-circuit voltage (VOC) and power-conversion efficiency (PCE) can be modulated up to 0.77 V and 6%, respectively. Optimized photovoltaic features affords synaptic devices with an outstanding programming weight states, involving training facilitation, stimulus reinforce and consolidation. Based on self-powered system, this work further presents a highly available modulation scheme, which achieves excellent device behaviors while ensuring the zero-energy consumption.

Functional characterization of two flavone synthase II members in citrus.

Polymethoxylated flavones (PMFs), the main form of flavones in citrus, are derived from the flavone branch of the flavonoid biosynthesis pathway. Flavone synthases (FNSs) are enzymes that catalyze the synthesis of flavones from flavanones. However, the FNS in citrus has not been characterized yet. Here, we identified two type II FNSs, designated CitFNSII-1 and CitFNSII-2, based on phylogenetics and transcriptome analysis. Both recombinant CitFNSII-1 and CitFNSII-2 proteins directly converted naringenin, pinocembrin, and liquiritigenin to the corresponding flavones in yeast. In addition, transient overexpression of CitFNSII-1 and CitFNSII-2, respectively, in citrus peel significantly enhanced the accumulation of total PMFs, while virus-induced CitFNSII-1 and CitFNSII-2 genes silencing simultaneously significantly reduced the expression levels of both genes and total PMF content in citrus seedlings. CitFNSII-1 and CitFNSII-2 presented distinct expression patterns in different cultivars as well as different developmental stages. Methyl salicylate (MeSA) treatment reduced the CitFNSII-2 expression as well as the PMFs content in the peel of Citrus sinensis fruit but did not affect the CitFNSII-1 expression. These results indicated that both CitFNSII-1 and CitFNSII-2 participated in the flavone biosynthesis in citrus while the regulatory mechanism governing their expression might be specific. Our findings improved the understanding of the PMFs biosynthesis pathway in citrus and laid the foundation for further investigation on flavone synthesis regulation.

A Lightweight CP-ABE Scheme with Direct Attribute Revocation for Vehicular Ad Hoc Network.

Ciphertext-Policy Attribute-Based Encryption (CP-ABE) technology provides a new solution to address the security and fine-grained access control of traffic information in vehicular ad hoc networks (VANETs). However, in most CP-ABE schemes for VANETs, attribute revocation suffers from high system consumption and complex revocation operations, as well as from high computational overhead and low efficiency due to the use of bilinear pairwise operations. Based on this, this paper proposes a lightweight CP-ABE scheme that supports direct attribute revocation in VANETs. The scheme implements an agent-based direct attribute revocation mechanism by separating dynamic and static attributes of vehicle terminals, which reduces system consumption and simplifies the revocation operation process. The scheme uses scalar multiplication on elliptic curves instead of bilinear pairing operations and uses computational outsourcing techniques to reduce the terminal decryption cost and improve the efficiency of the scheme. The security and performance analysis shows that the overall efficiency of our scheme is better than the existing schemes under the premise of ensuring data confidentiality and integrity.

Digital microfluidics-based digital counting of single-cell copy number variation (dd-scCNV Seq).

Single-cell copy number variations (CNVs), major dynamic changes in humans, result in differential levels of gene expression and account for adaptive traits or underlying disease. Single-cell sequencing is needed to reveal these CNVs but has been hindered by single-cell whole-genome amplification (scWGA) bias, leading to inaccurate gene copy number counting. In addition, most of the current scWGA methods are labor intensive, time-consuming, and expensive with limited wide application. Here, we report a unique single-cell whole-genome library preparation approach based on digital microfluidics for digital counting of single-cell Copy Number Variation (dd-scCNV Seq). dd-scCNV Seq directly fragments the original single-cell DNA and uses these fragments as templates for amplification. These reduplicative fragments can be filtered computationally to generate the original partitioned unique identified fragments, thereby enabling digital counting of copy number variation. dd-scCNV Seq showed an increase in uniformity in the single-molecule data, leading to more accurate CNV patterns compared to other methods with low-depth sequencing. Benefiting from digital microfluidics, dd-scCNV Seq allows automated liquid handling, precise single-cell isolation, and high-efficiency and low-cost genome library preparation. dd-scCNV Seq will accelerate biological discovery by enabling accurate profiling of copy number variations at single-cell resolution.

M4Raw: A multi-contrast, multi-repetition, multi-channel MRI k-space dataset for low-field MRI research.

Recently, low-field magnetic resonance imaging (MRI) has gained renewed interest to promote MRI accessibility and affordability worldwide. The presented M4Raw dataset aims to facilitate methodology development and reproducible research in this field. The dataset comprises multi-channel brain k-space data collected from 183 healthy volunteers using a 0.3 Tesla whole-body MRI system, and includes T1-weighted, T2-weighted, and fluid attenuated inversion recovery (FLAIR) images with in-plane resolution of ~1.2 mm and through-plane resolution of 5 mm. Importantly, each contrast contains multiple repetitions, which can be used individually or to form multi-repetition averaged images. After excluding motion-corrupted data, the partitioned training and validation subsets contain 1024 and 240 volumes, respectively. To demonstrate the potential utility of this dataset, we trained deep learning models for image denoising and parallel imaging tasks and compared their performance with traditional reconstruction methods. This M4Raw dataset will be valuable for the development of advanced data-driven methods specifically for low-field MRI. It can also serve as a benchmark dataset for general MRI reconstruction algorithms.

Electromagnetic interference elimination via active sensing and deep learning prediction for radiofrequency shielding-free MRI.

At present, MRI scans are typically performed inside fully enclosed radiofrequency (RF) shielding rooms, posing stringent installation requirements and causing patient discomfort. We aim to eliminate electromagnetic interference (EMI) for MRI with no or incomplete RF shielding. In this study, a method of active sensing and deep learning EMI prediction is presented to model, predict, and remove EMI signal components from acquired MRI signals. Specifically, during each MRI scan, separate EMI-sensing coils placed in various locations are utilized to simultaneously sample external and internal EMI signals within two windows (for both conventional MRI signal acquisition and EMI characterization acquisition). A convolution neural network model is trained using the EMI characterization data to relate EMI signals detected by EMI-sensing coils to EMI signals in the MRI receive coil. This model is then used to retrospectively predict and remove EMI signal components detected by the MRI receive coil during the MRI signal acquisition window. This strategy was implemented on a low-cost ultralow-field 0.055 T permanent magnet MRI scanner without RF shielding. It produced final image signal-to-noise ratios that were comparable with those obtained using a fully enclosed RF shielding cage, and outperformed existing analytical EMI elimination methods (i.e., spectral domain transfer function and external dynamic interference estimation and removal [EDITER] methods). A preliminary experiment also demonstrated its applicability on a 1.5 T superconducting magnet MRI scanner with incomplete RF shielding. Altogether, the results demonstrated that the proposed method was highly effective in predicting and removing various EMI signals from both external environments and internal scanner electronics at both 0.055 T (2.3 MHz) and 1.5 T (63.9 MHz). The proposed strategy enables shielding-free MRI. The concept is relatively simple and is potentially applicable to other RF signal detection scenarios in the presence of external and/or internal EMI.