Computational approaches for detecting disease-associated alternative splicing events.

Alternative splicing (AS) is a key transcriptional regulation pathway. Recent studies have shown that AS events are associated with the occurrence of complex diseases. Various computational approaches have been developed for the detection of disease-associated AS events. In this review, we first describe the metrics used for quantitative characterization of AS events. Second, we review and discuss the three types of methods for detecting disease-associated splicing events, which are differential splicing analysis, aberrant splicing detection and splicing-related network analysis. Third, to further exploit the genetic mechanism of disease-associated AS events, we describe the methods for detecting genetic variants that potentially regulate splicing. For each type of methods, we conducted experimental comparison to illustrate their performance. Finally, we discuss the limitations of these methods and point out potential ways to address them. We anticipate that this review provides a systematic understanding of computational approaches for the analysis of disease-associated splicing.

Nobiletin enhances mitochondrial function by regulating SIRT1/PGC-1α signaling in porcine oocytes during in vitro maturation.

Nobiletin is a natural flavonoid found in citrus fruits with beneficial effects, including anti-inflammatory, anti-cancer and anti-oxidation effects. The aim of this study was to investigate whether nobiletin improves mitochondrial function in porcine oocytes and examine the underlying mechanism. Oocytes enclosed by cumulus cells were cultured in TCM-199 for 44 h with 0.1% dimethyl sulfoxide (control), or supplemented with 5, 10, 25, and 50 µM of nobiletin (Nob5, Nob10, Nob25, and Nob50, respectively). Oocyte maturation rate was significantly enhanced in Nob10 (70.26 ± 0.45%) compared to the other groups (control: 60.12 ± 0.47%; Nob5: 59.44 ± 1.63%; Nob25: 63.15 ± 1.38%; Nob50: 46.57 ± 1.19%). The addition of nobiletin reduced the levels of reactive oxygen species and increased glutathione levels. Moreover, Nob10 promoted mitochondrial biogenesis by upregulating the protein levels of sirtuin 1 (SIRT1) and peroxisome proliferator-activated receptor-gamma coactivator 1α (PGC-1α). This resulted in an increase in the number of active mitochondria, mitochondrial DNA copy number, mitochondrial membrane potential, and ATP production, thereby enhancing mitochondrial function. The protein level of p53 decreased, followed by the phosphorylation of B-cell lymphoma 2, suggesting a reduction in mitochondria-mediated apoptosis in the Nob10 group. Additionally, the release of cytochrome c from the mitochondria was significantly diminished along with a decrease in the protein expression of caspase 3. Thus, nobiletin has a great potential to promote the in vitro maturation of porcine oocytes by suppressing oxidative stress and promoting mitochondrial function through the upregulation of the SIRT1/PGC-1α signaling pathway.

An integrated brain-specific network identifies genes associated with neuropathologic and clinical traits of Alzheimer's disease.

Alzheimer's disease (AD) has a strong genetic predisposition. However, its risk genes remain incompletely identified. We developed an Alzheimer's brain gene network-based approach to predict AD-associated genes by leveraging the functional pattern of known AD-associated genes. Our constructed network outperformed existing networks in predicting AD genes. We then systematically validated the predictions using independent genetic, transcriptomic, proteomic data, neuropathological and clinical data. First, top-ranked genes were enriched in AD-associated pathways. Second, using external gene expression data from the Mount Sinai Brain Bank study, we found that the top-ranked genes were significantly associated with neuropathological and clinical traits, including the Consortium to Establish a Registry for Alzheimer's Disease score, Braak stage score and clinical dementia rating. The analysis of Alzheimer's brain single-cell RNA-seq data revealed cell-type-specific association of predicted genes with early pathology of AD. Third, by interrogating proteomic data in the Religious Orders Study and Memory and Aging Project and Baltimore Longitudinal Study of Aging studies, we observed a significant association of protein expression level with cognitive function and AD clinical severity. The network, method and predictions could become a valuable resource to advance the identification of risk genes for AD.

CellBRF: a feature selection method for single-cell clustering using cell balance and random forest.

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) offers a powerful tool to dissect the complexity of biological tissues through cell sub-population identification in combination with clustering approaches. Feature selection is a critical step for improving the accuracy and interpretability of single-cell clustering. Existing feature selection methods underutilize the discriminatory potential of genes across distinct cell types. We hypothesize that incorporating such information could further boost the performance of single cell clustering. RESULTS: We develop CellBRF, a feature selection method that considers genes' relevance to cell types for single-cell clustering. The key idea is to identify genes that are most important for discriminating cell types through random forests guided by predicted cell labels. Moreover, it proposes a class balancing strategy to mitigate the impact of unbalanced cell type distributions on feature importance evaluation. We benchmark CellBRF on 33 scRNA-seq datasets representing diverse biological scenarios and demonstrate that it substantially outperforms state-of-the-art feature selection methods in terms of clustering accuracy and cell neighborhood consistency. Furthermore, we demonstrate the outstanding performance of our selected features through three case studies on cell differentiation stage identification, non-malignant cell subtype identification, and rare cell identification. CellBRF provides a new and effective tool to boost single-cell clustering accuracy. AVAILABILITY AND IMPLEMENTATION: All source codes of CellBRF are freely available at https://github.com/xuyp-csu/CellBRF.

GRP78 acts as a cAMP/PKA signaling modulator through the MC4R pathway in porcine embryonic development.

Glucose-regulated protein 78 (GRP78) binds to and stabilizes melanocortin 4 receptor (MC4R), which activates protein kinase A (PKA) by regulating G proteins. GRP78 is primarily used as a marker for endoplasmic reticulum stress; however, its other functions have not been well studied. Therefore, in this study, we aimed to investigate the function of GRP78 during porcine embryonic development. The developmental quality of porcine embryos, expression of cell cycle proteins, and function of mitochondria were evaluated by inhibiting the function of GRP78. Porcine oocytes were activated to undergo parthenogenesis, and blastocysts were obtained after 7 days of in vitro culture. GRP78 function was inhibited by adding 20 µM HA15 to the in vitro culture medium. The inhibition in GRP78 function led to a decrease in G proteins release, which subsequently downregulated the cyclic adenosine monophosphate (cAMP)/PKA pathway. Ultimately, inhibition of GRP78 function induced the inhibition of CDK1 and cyclin B expression and disruption of the cell cycle. In addition, inhibition of GRP78 function regulated DRP1 and SIRT1 expression, resulting in mitochondrial dysfunction. This study provides new insights into the role of GRP78 in porcine embryonic development, particularly its involvement in the regulation of the MC4R pathway and downstream cAMP/PKA signaling. The results suggest that the inhibition of GRP78 function in porcine embryos by HA15 treatment may have negative effects on embryo quality and development. This study also demonstrated that GRP78 plays a crucial role in the functioning of MC4R, which releases the G protein during porcine embryonic development.

Understanding the application of covalent adaptable networks in self-repair materials based on molecular simulation.

Covalent adaptable networks (CANs) are widely used in the field of self-repair materials. They are a group of covalently cross-linked associative polymers that undergo reversible chemical reactions, and can be further divided into dissociative CANs (Diss-CANs) and associative CANs (Asso-CANs). Self-repair refers to the ability of a material to repair itself without external intervention, and can be classified into self-adhesion and self-healing according to the utilization of open stickers. Unlike conventional materials, the viscoelastic properties of CANs are influenced by both the molecular structure and reaction kinetics, ultimately affecting their repair performance. To gain deeper insight into the repair mechanism of CANs, we conducted simulations by using the hybrid MC/MD algorithm, as previously proposed in our research. Interestingly, we observed a significant correlation between reaction kinetics and repair behavior. Asso-CANs exhibited strong mechanical strength and high creep resistance, rendering them suitable as self-adhesion materials. On the other hand, Diss-CANs formed open stickers that facilitated local relaxation, aligning perfectly with self-healing processes. Moreover, the introduction of crosslinkers in the form of small molecules enhanced the repair efficiency. Theoretically, it was found that the repair timescale of Asso-CANs is slower than that of Diss-CANs with identical molecular structures. Our study not only clarifies the similarities and differences between Diss-CANs and Asso-CANs in terms of their self-repairing capabilities, but more importantly, it provides valuable insights guiding the effective utilization of CANs in the development of self-repair materials.

Enhancing spinal cord stimulation-induced pain inhibition by augmenting endogenous adenosine signalling after nerve injury in rats.

BACKGROUND: The mechanisms for spinal cord stimulation (SCS) to alleviate chronic pain are only partially known. We aimed to elucidate the roles of adenosine A1 and A3 receptors (A1R, A3R) in the inhibition of spinal nociceptive transmission by SCS, and further explored whether 2'-deoxycoformycin (dCF), an inhibitor of adenosine deaminase, can potentiate SCS-induced analgesia. METHODS: We used RNAscope and immunoblotting to examine the distributions of adora1 and adora3 expression, and levels of A1R and A3R proteins in the spinal cord of rats after tibial-spared nerve injury (SNI-t). Electrophysiology recording was conducted to examine how adenosine receptor antagonists, virus-mediated adora3 knockdown, and dCF affect SCS-induced inhibition of C-fibre-evoked spinal local field potential (C-LFP). RESULTS: Adora1 was predominantly expressed in neurones, whereas adora3 is highly expressed in microglial cells in the rat spinal cord. Spinal application of antagonists (100 µl) of A1R (8-cyclopentyl-1,3-dipropylxanthine [DPCPX], 50 µM) and A3R (MRS1523, 200 nM) augmented C-LFP in SNI-t rats (DPCPX: 1.39 [0.18] vs vehicle: 0.98 [0.05], P=0.046; MRS1523: 1.21 [0.07] vs vehicle: 0.91 [0.03], P=0.002). Both drugs also blocked inhibition of C-LFP by SCS. Conversely, dCF (0.1 mM) enhanced SCS-induced C-LFP inhibition (dCF: 0.60 [0.04] vs vehicle: 0.85 [0.02], P<0.001). In the behaviour study, dCF (100 nmol 15 µl-1, intrathecal) also enhanced inhibition of mechanical hypersensitivity by SCS in SNI-t rats. CONCLUSIONS: Spinal A1R and A3R signalling can exert tonic suppression and also contribute to SCS-induced inhibition of spinal nociceptive transmission after nerve injury. Inhibition of adenosine deaminase may represent a novel adjuvant pharmacotherapy to enhance SCS-induced analgesia.

TissueNexus: a database of human tissue functional gene networks built with a large compendium of curated RNA-seq data.

Mapping gene interactions within tissues/cell types plays a crucial role in understanding the genetic basis of human physiology and disease. Tissue functional gene networks (FGNs) are essential models for mapping complex gene interactions. We present TissueNexus, a database of 49 human tissue/cell line FGNs constructed by integrating heterogeneous genomic data. We adopted an advanced machine learning approach for data integration because Bayesian classifiers, which is the main approach used for constructing existing tissue gene networks, cannot capture the interaction and nonlinearity of genomic features well. A total of 1,341 RNA-seq datasets containing 52,087 samples were integrated for all of these networks. Because the tissue label for RNA-seq data may be annotated with different names or be missing, we performed intensive hand-curation to improve quality. We further developed a user-friendly database for network search, visualization, and functional analysis. We illustrate the application of TissueNexus in prioritizing disease genes. The database is publicly available at https://www.diseaselinks.com/TissueNexus/.

Benzofuran Derivatives from Cortex Mori Radicis and Their Cholinesterase-Inhibitory Activity.

The phytochemical investigation of Cortex Mori Radicis led to the isolation and identification of a new prenylated benzofuranone (1) and four ring-opening derivatives (2-5) named albaphenol A-E, as well as nigranol A (6), together with ten 2-arylbenzofuran derivatives (7-16). The characterization of the structures of the new compounds and the structural revision of nigranol A (6) were conducted using the comprehensive analysis of spectroscopic data (1D/2D NMR, HRESIMS, CD, and XRD). Compounds 1-16 were tested for their inhibitory effects on acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). Compounds 1 and 4 showed weak BChE-inhibitory activity (IC50 45.5 and 61.0 µM); six 2-arylbenzofuran derivatives showed more-potent BChE-inhibitory activity (IC50 2.5-32.8 µM) than the positive control galantamine (IC50 35.3 µM), while being inactive or weakly inhibitory toward AChE. Cathafuran C (14) exhibited the most potent and selective inhibitory activity against BChE in a competitive manner, with a Ki value of 1.7 µM. The structure-activity relationships of the benzofuran-type stilbenes were discussed. Furthermore, molecular docking and dynamic simulations were performed to clarify the interactions of the inhibitor-enzyme complex.

Y-box binding protein 1 influences zygotic genome activation by regulating N6-methyladenosine in porcine embryos.

Y-box binding protein 1 (YBX1) is a member of the family of DNA- and RNA-binding proteins that play crucial roles in multiple aspects, including RNA stabilization, translational repression, and transcriptional regulation; however, its roles in embryo development remain less known. In this study, to investigate the function of YBX1 and its mechanism of action in porcine embryo development, YBX1 was knocked down by microinjecting YBX1 siRNA at the one-cell stage. YBX1 is located in the cytoplasm during embryonic development. The mRNA level of YBX1 was increased from the four-cell stage to the blastocyst stage but was significantly decreased in YBX1 knockdown embryos compared with the control. Moreover, the percentage of blastocysts was decreased following YBX1 knockdown compared with the control. Defecting YBX1 expression increased maternal gene mRNA expression and decreased zygotic genome activation (ZGA) gene mRNA expression and histone modification owing to decreased levels of N6-methyladenosine (m6A) writer N6-adenosine-methyltransferase 70 kDa subunit (METTL3) and reader insulin-like growth factor 2 mRNA-binding protein (IGF2BP1). In addition, IGF2BP1 knockdown showed that YBX1 regulated the ZGA process through m6A modification. In conclusion, YBX1 is essential for early embryo development because it regulates the ZGA process.

Perspective on Iron-Based Phosphate Cathode for Commercial Sodium-Ion Cells.

Sodium (Na)-ion batteries (SIBs) have been considered as a potential device for large-scale energy storage. To date, some start-up companies have released their first-generation SIBs cathode materials. Among them, phosphate compounds, particularly iron (Fe)-based mixed phosphate compounds, present great potential for commercial SIBs owing to its low cost, environment friendly. In this perspective, a brief historical retrospect is first introduce to the development of Fe-based mixed phosphate cathodes in SIBs. Then, the recent development about this kind of cathode has been summarized. One of the iron-based phosphate materials, Na3 Fe2 (PO4 )P2 O7 , is used as an example to roughly calculate the energy density and estimate the cost at the cell level to highlight their advantages. Finally, some strategies are put up to further increase the energy density of SIBs. This timely perspective aims to educate the community on the critical benefits of the Fe-based mixed phosphate cathode and provide an up-to-date overview of this emerging field.

REBET: a method to determine the number of cell clusters based on batch effect removal.

In single-cell RNA-seq (scRNA-seq) data analysis, a fundamental problem is to determine the number of cell clusters based on the gene expression profiles. However, the performance of current methods is still far from satisfactory, presumably due to their limitations in capturing the expression variability among cell clusters. Batch effects represent the undesired variability between data measured in different batches. When data are obtained from different labs or protocols batch effects occur. Motivated by the practice of batch effect removal, we considered cell clusters as batches. We hypothesized that the number of cell clusters (i.e. batches) could be correctly determined if the variances among clusters (i.e. batch effects) were removed. We developed a new method, namely, removal of batch effect and testing (REBET), for determining the number of cell clusters. In this method, cells are first partitioned into k clusters. Second, the batch effects among these k clusters are then removed. Third, the quality of batch effect removal is evaluated with the average range of normalized mutual information (ARNMI), which measures how uniformly the cells with batch-effects-removal are mixed. By testing a range of k values, the k value that corresponds to the lowest ARNMI is determined to be the optimal number of clusters. We compared REBET with state-of-the-art methods on 32 simulated datasets and 14 published scRNA-seq datasets. The results show that REBET can accurately and robustly estimate the number of cell clusters and outperform existing methods. Contact: H.D.L. (hongdong@csu.edu.cn) or Q.S.X. (qsxu@csu.edu.cn).

GTFtools: a software package for analyzing various features of gene models.

MOTIVATION: Gene-centric bioinformatics studies frequently involve the calculation or the extraction of various features of genes such as splice sites, promoters, independent introns and untranslated regions (UTRs) through manipulation of gene models. Gene models are often annotated in gene transfer format (GTF) files. The features are essential for subsequent analysis such as intron retention detection, DNA-binding site identification and computing splicing strength of splice sites. Some features such as independent introns and splice sites are not provided in existing resources including the commonly used BioMart database. A package that implements and integrates functions to analyze various features of genes will greatly ease routine analysis for related bioinformatics studies. However, to the best of our knowledge, such a package is not available yet. RESULTS: We introduce GTFtools, a stand-alone command-line software that provides a set of functions to calculate various gene features, including splice sites, independent introns, transcription start sites (TSS)-flanking regions, UTRs, isoform coordination and length, different types of gene lengths, etc. It takes the ENSEMBL or GENCODE GTF files as input and can be applied to both human and non-human gene models like the lab mouse. We compare the utilities of GTFtools with those of two related tools: Bedtools and BioMart. GTFtools is implemented in Python and not dependent on any third-party software, making it very easy to install and use. AVAILABILITY AND IMPLEMENTATION: GTFtools is freely available at www.genemine.org/gtftools.php as well as pyPI and Bioconda.

AlzCode: a platform for multiview analysis of genes related to Alzheimer's disease.

MOTIVATION: Alzheimer's disease (AD) is a complex brain disorder with risk genes incompletely identified. The candidate genes are dominantly obtained by computational approaches. In order to obtain biological insights of candidate genes or screen genes for experimental testing, it is essential to assess their relevance to AD. A platform that integrates different types of omics data and approaches would facilitate the analysis of candidate genes and is in great need. RESULTS: We report AlzCode, a platform for multiview analysis of genes related to AD. First, this platform integrates a rich collection of functional genomic data, including expression data of AD samples (gene expression, single-cell RNA-seq data and protein expression), AD-specific biological networks (co-expression networks and functional gene networks), neuropathological and clinical traits (CERAD score, Braak staging score, Clinical Dementia Rating, cognitive function and clinical severity) and general data such as protein-protein interaction, regulatory networks, sequence similarity and miRNA-target interactions. These data provide basis for analyzing genes from different views. Second, the platform integrates multiple approaches designed for the various types of data. We implement functions to analyze both individual genes and gene sets. We also compare AlzCode with two existing platforms for AD analysis, which are Agora and AD Atlas. We pinpoint the features of each platform and highlight their differences. This platform would be valuable to the understanding of AD genetics and pathological mechanisms. AVAILABILITY AND IMPLEMENTATION: AlzCode is freely available at: http://www.alzcode.xyz. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The heterophilicic epitopes in conserved HA regions of human and avian influenza viruses can produce antibodies that bound to kidney tissue.

Influenza virus infection can cause kidney damage. However, the link between influenza infection and disease is still unclear. The purpose of this study was to analyze the relationship between heterophilic epitopes on H5N1 hemagglutinin (HA) and disease. The monoclonal antibody (mAb) against H5N1 was prepared, mAbs binding to human kidney tissue were screened, and the reactivities of mAbs with five different subtypes of influenza virus were detected. Design and synthesize the peptides according to the common amino acid sequence of these antigens, and analyze the distribution of the epitope on the crystal structure of HA. Immunological methods were used to detect whether the heterophilic epitopes could induce the production of antibodies that cross-react with kidney tissue. The results showed that H5-30 mA b binding to human kidney tissue recognized the heterophilic epitope 191-LVLWGIHHP-199 on the head of HA. The key amino acid were V192, L193, W194 and I196, which were highly conserved in human and avian influenza virus HA. The heterophilic epitope could induce mice to produce different mAbs binding to kidney tissue. Such heterophilic antibodies were also detected in the serum of the patients. It can provide materials for the mechanism of renal diseases caused by influenza virus infection.

Differentially expressed platelet activation-related genes in dogs with stage B2 myxomatous mitral valve disease.

BACKGROUND: Peripheral blood carries a reservoir of mRNAs that regulate cardiac structure and function potential. Although it is well recognized that the typical symptoms of Myxomatous Mitral Valve Disease (MMVD) stage B2 are long-standing hemodynamic disorder and cardiac structure remodeling caused by mitral regurgitation, the transcriptomic alterations in blood from such dogs are not understood. RESULTS: In the present study, comparative high-throughput transcriptomic profiling of blood was performed from normal control (NC) and naturally-occurring MMVD stage B2 (MMVD) dogs. Using Weighted Gene Co-expression Network Analyses (WGCNA), Gene Ontology (GO), and Kyoto Encyclopedia of Gene and Genomes (KEGG), we identified that the turquoise module was the most highly correlated with echocardiographic features and found 64 differentially expressed genes (DEGs) that were significantly enriched in platelet activation related pathways. Therefore, from the turquoise module, we selected five DEGs (MDM2, ROCK1, RIPK1, SNAP23, and ARHGAP35) that, according to real-time qPCR, exhibited significant enrichment in platelet activation related pathways for validation. The results showed that the blood transcriptional abundance of MDM2, ROCK1, RIPK1, and SNAP23 differed significantly (P < 0.01) between NC and MMVD dogs. On the other hand, Correlation Analysis revealed that MDM2, ROCK1, RIPK1, and SNAP23 genes negatively regulated the heart structure parameters, and followed the same trend as observed in WGCNA. CONCLUSION: We screened four platelet activation related genes, MDM2, ROCK1, RIPK1, and SNAP23, which may be considered as the candidate biomarkers for the diagnosis of MMVD stage B2. These findings provided new insights into MMVD pathogenesis.

High Temperature-Induced m6A Epigenetic Changes Affect Early Porcine Embryonic Developmental Competence in Pigs.

N6-methyladenosine (m6A), the most prevalent modification in eukaryotic messenger RNA (mRNA), plays a key role in various developmental processes in mammals. Three proteins that affect RNA m6A modification have been identified: methyltransferases, demethylases, and m6A-binding proteins, known as "writer," "eraser," and "reader" proteins, respectively. However, changes in the m6A modification when early porcine embryos are exposed to stress remain unclear. In this study, we exposed porcine oocytes to a high temperature (HT, 41°C) for 10 h, after which the mature oocytes were parthenogenetically activated and cultured for 7 days to the blastocyst stage. HT significantly decreased the rates of the first polar body extrusion and blastocyst formation. Further detection of m6A modification found that HT can lead to increased expression levels of "reader," YTHDF2, and "writer," METTL3, and decreased expression levels of "eraser," FTO, resulting in an increased level of m6A modification in the embryos. Additionally, heat shock protein 70 (HSP70) is upregulated under HT conditions. Our study demonstrated that HT exposure alters m6A modification levels, which further affects early porcine embryonic development.

ZSCAN4 Regulates Zygotic Genome Activation and Telomere Elongation in Porcine Parthenogenetic Embryos.

Zinc finger and SCAN domain-containing 4 (ZSCAN4), a DNA-binding protein, maintains telomere length and plays a key role in critical aspects of mouse embryonic stem cells, including maintaining genomic stability and defying cellular senescence. However, the effect of ZSCAN4 in porcine parthenogenetic embryos remains unclear. To investigate the function of ZSCAN4 and the underlying mechanism in porcine embryo development, ZSCAN4 was knocked down via dsRNA injection in the one-cell stage. ZSCAN4 was highly expressed in the four- and five- to eight-cell stages in porcine embryos. The percentage of four-cell stage embryos, five- to eight-cell stage embryos, and blastocysts was lower in the ZSCAN4 knockdown group than in the control group. Notably, depletion of ZSCAN4 induced the protein expression of DNMT1 and 5-Methylcytosine (5mC, a methylated form of the DNA base cytosine) in the four-cell stage. The H3K27ac level and ZGA genes expression decreased following ZSCAN4 knockdown. Furthermore, ZSCAN4 knockdown led to DNA damage and shortened telomere compared with the control. Additionally, DNMT1-dsRNA was injected to reduce DNA hypermethylation in ZSCAN4 knockdown embryos. DNMT1 knockdown rescued telomere shortening and developmental defects caused by ZSCAN4 knockdown. In conclusion, ZSCAN4 is involved in the regulation of transcriptional activity and is essential for maintaining telomere length by regulating DNMT1 expression in porcine ZGA.

Effectiveness of nurse-led multidisciplinary interventions in primary health care: A systematic review and meta-analysis.

AIM: This review aimed to synthesize the available evidence on the effectiveness of nurse-led multidisciplinary interventions in primary health care. METHODS: The following Chinese and English databases were searched for relevant articles: PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang and Chinese Biomedical Literature Database (CBM), from the establishment of the databases until the last updating search 1 April 2022. Two researchers screened the studies independently and extracted the data. Meta-analysis was performed using the RevMan 5.3 software. RESULTS: A total of 12 studies were included in this review. It was found that nurse-led multidisciplinary interventions significantly shortened patients' length of stay in hospital (standardized mean differences [SMD] = -1.28, 95%CI: -2.03 to -0.54; P<0.001) and decreased incidences of complications (RR = 0.24, 95%CI:0.10 to 0.54; P = 0.0006) compared to the control group, and lowered patients' anxiety levels (SMD = -1.21, 95%CI: -1.99 to -0.44; P<0.01) and depression levels (SMD = -1.85, 95%CI: -3.42 to -0.28; P<0.0001). Furthermore, the results of subgroup analysis indicated that nurse-led multidisciplinary interventions had significant effects on patients' self-management ability (SMD = 4.45, 95%CI:2.45 to 6.44; P<0.0001) and quality of life (SMD = 1.01, 95%CI: 0.63 to 1.40; P<0.0001) compared to the control group. CONCLUSIONS: Nurse-led multidisciplinary interventions had strong effects in primary health care, contributing to shorten patients' length of stay in hospital, decrease incidences of complications and reduce the levels of anxiety and depression. Moreover, nurse-led multidisciplinary interventions also improved patients' self-management ability and quality of life.

An Investigation into the Performance and Mechanisms of Soymilk-Sized Handmade Xuan Paper at Different Concentrations of Soymilk.

Invaluable paper relics that embody a rich traditional culture have suffered damage, requiring urgent restoration. In this context, the utilization of soymilk as a sizing agent holds great significance and reverence. This study investigates the use of soymilk as a sizing agent for Xuan paper and evaluates its effects on various properties and the long-term behavior of the paper. The findings reveal that the application of soymilk as a sizing agent for Xuan paper imparts distinct properties, including hydrophobicity, improved mechanical properties, and unique chromaticity. These characteristics-arising from the papillae on the surface of the Xuan paper, the protein folding of the soy protein, and hydrogen-bonding interactions between the soy protein and paper fibers-play a crucial role in shaping the paper's unique attributes. From a physicochemical perspective, the aging process leads to multiple changes in paper properties. These changes include acidification, which refers to a decrease in pH, as well as a decline in mechanical strength, an increase in chromaticity, and a decrease in the degree of polymerization (DP) of the paper. The Ekenstam equation is employed to predict the lifespan of the paper, showing longer lifespans for Sheng Xuan paper and a negative correlation between soymilk concentration and lifespan in soymilk-sized paper. Our work provides valuable insights for the preservation and maintenance of paper, highlighting the potential benefits and challenges of using soymilk for surface sizing.