Corrigendum: Research progress and trends in metabolomics of fruit trees.

[This corrects the article DOI: 10.3389/fpls.2022.881856.].

Correction: Carbazate-modified cross-linked dextran microparticles suppress the progression of osteoarthritis by ROS scavenging.

Correction for 'Carbazate-modified cross-linked dextran microparticles suppress the progression of osteoarthritis by ROS scavenging' by Yanfeng Ding, et al., Biomater. Sci., 2021, 9, 6236-6250. https://doi.org/10.1039/D1BM00743B.

Effects of Lactobacillus plantarum and Pediococcus acidilactici co-fermented feed on growth performance and gut microbiota of nursery pigs.

The fermented feed has been used extensively as a growth promoter in agricultural animal production. However, the effects of fermented feed on swine gut microbiota are still largely unknown. The work presented here aimed to investigate the growth performance and gut microbiota of nursery pigs receiving the LPF diet (10% Lactobacillus plantarum and Pediococcus acidilactici co-fermented feed + basal diet) compared with pigs receiving the NC diet (basal diet). The data showed LPF diet numerically improved average daily gain and significantly increased fecal acetate, butyrate, and total short-chain fatty acid (SCFA) concentrations. Furthermore, gut microbiota structure and membership significantly changed in response to the addition of fermented feed in the diet. Gut microbiota results indicated that LPF treatment significantly enriched SCFA-producing bacteria such as Megasphaera, Roseburia, Faecalibacterium, Blautia, Selenomonas, Dialister, Acidaminococcus, Ruminococcus, and Bifidobacterium. Some of these bacteria also had anti-inflammatory and other beneficial functions. Overall, these findings suggested that Lactobacillus plantarum and Pediococcus acidilactici co-fermented feed benefited growth performance and established potential health impacts on the gut microbiota of nursery pigs.

Research Progress and Trends in Metabolomics of Fruit Trees.

Metabolomics is an indispensable part of modern systems biotechnology, applied in the diseases' diagnosis, pharmacological mechanism, and quality monitoring of crops, vegetables, fruits, etc. Metabolomics of fruit trees has developed rapidly in recent years, and many important research results have been achieved in combination with transcriptomics, genomics, proteomics, quantitative trait locus (QTL), and genome-wide association study (GWAS). These research results mainly focus on the mechanism of fruit quality formation, metabolite markers of special quality or physiological period, the mechanism of fruit tree's response to biotic/abiotic stress and environment, and the genetics mechanism of fruit trait. According to different experimental purposes, different metabolomic strategies could be selected, such as targeted metabolomics, non-targeted metabolomics, pseudo-targeted metabolomics, and widely targeted metabolomics. This article presents metabolomics strategies, key techniques in metabolomics, main applications in fruit trees, and prospects for the future. With the improvement of instruments, analysis platforms, and metabolite databases and decrease in the cost of the experiment, metabolomics will prompt the fruit tree research to achieve more breakthrough results.

Application of indocyanine green and near-infrared fluorescence imaging for the assessment of peritoneal dialysis-related complications.

Background Ultrasound, computed tomographic peritoneography, methylene blue, and peritoneal scintigraphy are commonly used to identify peritoneal dialysis-related complications in clinical settings. This study aimed to investigate the diagnostic value of indocyanine green in peritoneal dialysis-related complications and to study the effect of indocyanine green on residual renal function and peritoneal function. Methods Twenty male Sprague-Dawley rats were used to establish models, including a pleural effusion model (A, n = 4), abdominal hernia model (B, n = 4), subcutaneous leakage model (C, n = 4), and control (D, n = 8). They were injected with a 20 mL mixture of peritoneal dialysate and indocyanine green at varying concentrations prepared for near-infrared fluorescence imaging. We compared the results of near-infrared-I and near-infrared-II imaging. Radiologists evaluated the image quality, morphology, and thickness of the peritoneum, and the residual renal function was assessed using haematoxylin and eosin staining. Results Lesions in each rat model group were observed by changing the body position and imaging parameters. Pathological kidney and peritoneal sections showed no changes. Meanwhile, near-infrared-I fluorescence imaging of ICG has a better signal-to-background ratio than near-infrared-II. Conclusion Near-infrared-I fluorescence imaging of ICG has a better SBR than near-infrared-II and it is sufficient for for diagnosing peritoneal dialysis-related complications and ICG has no impact on residual renal function and peritoneal function. This method has clinical application potential in promptly diagnosing peritoneal dialysis-related complications.

Corilagin attenuates osteoclastic osteolysis by enhancing HO-1 and inhibiting ROS.

Chinese herbal medicine has well-established therapeutic effects in various diseases. Corilagin (Cor), a gallic acid tannin in Phyllanthus niruri L., has anti-inflammatory and antioxidant effects in many diseases. However, its role in osteoclast-related bone diseases has not been determined. In vitro, bone marrow macrophages (BMMs) were extracted and isolated to differentiate into osteoclasts. The effects of Cor on osteoclast formation, bone resorption, and reactive oxygen species (ROS) production were performed. In addition, quantitative real-time polymerase chain reaction and western blot analysis were used to evaluate the effect of Cor on oxidative stress-related pathways, which are nuclear factors-κB ligand-receptor activator (RANKL) stimulates important downstream pathways. Furthermore, microcomputed tomography and bone histomorphometry were performed to analyze the therapeutic effect of Cor in mouse models of lipopolysaccharide (LPS)-mediated bone defects in vivo. Cor influenced the nuclear factor of activated T cells 1 (NFATc1) signaling pathway and reduced ROS in RANKL-treated osteoclasts, thereby inhibiting osteoclast formation and bone resorption. Moreover, Cor protected against LPS-mediated skull defects in vivo. In sum, our results confirm that Cor can inhibit osteoclastogenesis and intracellular oxidative stress. In addition, the inflammatory bone defect induced by LPS was also attenuated by Cor. Accordingly, Cor is a new candidate therapeutic agent for osteoclast-mediated osteolytic diseases.

Anti-inflammatory and immunomodulatory effects of the extracellular vesicles derived from human umbilical cord mesenchymal stem cells on osteoarthritis via M2 macrophages.

Osteoarthritis (OA) is a degenerative illness that greatly impacts the life quality of patients. Currently, the therapeutic approaches for OA are very limited in clinical. The extracellular vesicles (EVs) derived from different mesenchymal stem cells displayed a prominent therapeutic effect on OA. But most EVs have limited resources and the risks of host rejection, immunological response, and etc. Human umbilical cord mesenchymal stem cells (hUCMSCs) hold the advantages of easy availability, minimal immune rejection, and excellent immunomodulatory effects, although hUCMSCs-EVs have seldom been applied in OA. Herein, we investigated the potential immunomodulatory and anti-inflammatory effects of hUCMSCs-EVs on the treatment of OA. In our results, the treatment of hUCMSCs-EVs promoted the polarization of M2-type macrophages and the expression of anti-inflammation-related cytokines (IL-10). Notably, the supernate of M2 macrophages induced by hUCMSCs-EVs inhibited the level of inflammation-associated factors in OA chondrocytes caused by IL-1ß. Further, injection of hUCMSCs-EVs in the articular lumen ameliorated progression of OA and exerted chondroprotective potential based on the OA joint model created by the surgical transection of the anterior cruciate ligament (ACLT). In addition, we found five highly enriched miRNAs in hUCMSCs-EVs, including has-miR-122-5p, has-miR-148a-3p, has-miR-486-5p, has-miR-let-7a-5p, and has-miR-100-5p by High-throughput sequencing of miRNAs, with targeted genes mainly enriched in the PI3K-Akt signaling pathway. Furthermore, we also detected the protein abundance of hUCMSCs-EVs using liquidation chromatography with tandem quadrupole mass spectrometry (LC-MS/MS) analysis. Thus, our study indicates that hUCMSCs-EVs can alleviate cartilage degradation during the OA progression, mechanically may through delivering key proteins and modulating the PI3K-Akt signaling pathway mediated by miRNAs to promote polarization of M2 macrophage, exhibiting potent immunomodulatory potential. The current findings suggest that hUCMSCs-EVs might serve as a new reagent for the therapy of OA.

Analysis and identification of m6A RNA methylation regulators in metastatic osteosarcoma.

Osteosarcoma (OS) is characterized by rapid growth and early metastasis. However, its mechanism remains unclear. N6-methyladenosine (m6A) modification and its regulatory factors play essential roles in most cancers, including OS. In this study, we screened out 21 m6A modifiers using the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, followed by the identification of the critical m6A methylation modifiers. The results revealed that the expression levels of three m6A methylation regulators, namely RBM15, METTL3, and LRPPRC, were associated with the low survival rate of patients with OS. We further studied the independent prognostic factors by performing univariate and multivariate Cox analyses and found that metastasis was an independent prognostic factor for patients with OS. Furthermore, we found for the first time that RBM15 was specific for metastatic OS rather than non-metastatic OS. Moreover, the significant overexpression of RBM15 was validated in metastatic OS cell lines and in actual human clinical specimens. We also revealed that RBM15 promoted the invasion, migration, and metastasis of OS cells through loss-functional and gain-functional experiments and an animal metastatic model. In conclusion, RBM15 has a high correlation with OS metastasis formation and the decreased survival rate of patients with OS, and this may serve as a useful biomarker for predicting metastasis and prognosis of patients with OS.

Analysis of Longitudinal Binomial Data with Positive Association between the Number of Successes and the Number of Failures: An Application to Stock Instability Study.

Numerous methods have been developed for longitudinal binomial data in the literature. These traditional methods are reasonable for longitudinal binomial data with a negative association between the number of successes and the number of failures over time; however, a positive association may occur between the number of successes and the number of failures over time in some behaviour, economic, disease aggregation and toxicological studies as the numbers of trials are often random. In this paper, we propose a joint Poisson mixed modelling approach to longitudinal binomial data with a positive association between longitudinal counts of successes and longitudinal counts of failures. This approach can accommodate both a random and zero number of trials. It can also accommodate overdispersion and zero inflation in the number of successes and the number of failures. An optimal estimation method for our model has been developed using the orthodox best linear unbiased predictors. Our approach not only provides robust inference against misspecified random effects distributions, but also consolidates the subject-specific and population-averaged inferences. The usefulness of our approach is illustrated with an analysis of quarterly bivariate count data of stock daily limit-ups and limit-downs.

Carbazate-modified cross-linked dextran microparticles suppress the progression of osteoarthritis by ROS scavenging.

A series of modified polysaccharide microparticles have been fabricated and their potential application for scavenging reactive oxygen species (ROS) and their derivatives to achieve osteoarthritis (OA) treatment has been explored. These microparticles were cross-linked dextran (Sephadex) with different carbazate substitution ratios determined by the TNBS assay and elemental analysis. It has been demonstrated that they could effectively scavenge carbonylated proteins and ROS including hydroxyl radicals (˙OH), superoxide anions (˙O2-) and H2O2 and their derivatives with high efficiency, improve the viability of H2O2-treated chondrocytes by reducing their ROS levels, as well as lower their inflammatory factors. The above ability of antioxidation and inflammation resistance improved with the increase of carbazate substitution ratio. Significantly, this work provided the proof that modified Sephadex successfully alleviated the deterioration of cartilage and the progression of OA in vivo. The proposed microparticles showed a very promising capability for reducing ROS levels and further treating OA.

Conditional inference trees in the assessment of tree mortality rates in the transitional mixed forests of Atlantic Canada.

Long-term predictions of forest dynamics, including forecasts of tree growth and mortality, are central to sustainable forest-management planning. Although often difficult to evaluate, tree mortality rates under different abiotic and biotic conditions are vital in defining the long-term dynamics of forest ecosystems. In this study, we have modeled tree mortality rates using conditional inference trees (CTREE) and multi-year permanent sample plot data sourced from an inventory with coverage of New Brunswick (NB), Canada. The final CTREE mortality model was based on four tree- and three stand-level terms together with two climatic terms. The correlation coefficient (R2) between observed and predicted mortality rates was 0.67. High cumulative annual growing degree-days (GDD) was found to lead to increased mortality in 18 tree species, including Betula papyrifera, Picea mariana, Acer saccharum, and Larix laricina. In another ten species, including Abies balsamea, Tsuga canadensis, Fraxinus americana, and Fagus grandifolia, mortality rates tended to be higher in areas with high incident solar radiation. High amounts of precipitation in NB's humid maritime climate were also found to contribute to heightened tree mortality. The relationship between high GDD, solar radiation, and high mortality rates was particularly strong when precipitation was also low. This would suggest that although excessive soil water can contribute to heightened tree mortality by reducing the supply of air to the roots, occasional drought in NB can also contribute to increased mortality events. These results would have significant implications when considered alongside regional climate projections which generally entail both components of warming and increased precipitation.

Linking dynamic patterns of COVID-19 spreads in Italy with regional characteristics: a two level longitudinal modelling approach.

The current statistical modeling of coronavirus (COVID-19) spread has mainly focused on spreading patterns and forecasting of COVID-19 development; these patterns have been found to vary among locations. As the survival time of coronaviruses on surfaces depends on temperature, some researchers have explored the association of daily confirmed cases with environmental factors. Furthermore, some researchers have studied the link between daily fatality rates with regional factors such as health resources, but found no significant factors. As the spreading patterns of COVID-19 development vary a lot among locations, fitting regression models of daily confirmed cases or fatality rates directly with regional factors might not reveal important relationships. In this study, we investigate the link between regional spreading patterns of COVID-19 development in Italy and regional factors in two steps. First, we characterize regional spreading patterns of COVID-19 daily confirmed cases by a special patterned Poisson regression model for longitudinal count; the varying growth and declining patterns as well as turning points among regions in Italy have been well captured by regional regression parameters. We then associate these regional regression parameters with regional factors. The effects of regional factors on spreading patterns of COVID-19 daily confirmed cases have been effectively evaluated.

Prognostic Implications of the Complement Protein C1Q and Its Correlation with Immune Infiltrates in Osteosarcoma.

BACKGROUND: Osteosarcoma (OS) is the most widespread bone tumour among childhood cancers, and distant metastasis is the dominant factor in poor prognosis for patients with OS. Therefore, it is necessary to identify new prognostic biomarkers for identifying patients with aggressive disease. METHODS: Two OS datasets (GSE21257 and GSE33383) were downloaded from the Gene Expression Omnibus (GEO) and subsequently subjected to weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis (DGE) to screen candidate genes. A prognostic model was constructed using OS data derived from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) program to further screen key genes and perform gene ontology (GO) analysis. The prognostic values of key genes were assessed using the Kaplan-Meier (KM) plotter. The GEO dataset was used for immune infiltration analysis and association analysis of key genes. In addition, quantitative real-time polymerase chain reaction (qRT-PCR) was employed to validate the expression levels of potentially crucial genes in OS cell lines. RESULTS: In the present study, we found 114 genes with a highly significant correlation in the module and 44 downregulated genes; 25 candidate genes overlapped in the two parts of the genes. Among these, three key genes, C1QA, C1QB, and C1QC, were the most significant hub genes, which had the highest node degrees, were clustered into one group, and implicated in most significant biological processes (regulation of immune effector process). Moreover, these three key genes were negatively associated with the prognosis of OS and positively associated with three immune cells (follicular helper T cells, memory B cells, and CD8 T cells). Additionally, compared to non-metastatic OS cell lines, the expression of three key genes was significantly downregulated in metastatic OS cell lines. CONCLUSION: Our results revealed that three key genes (C1QA, C1QB, and C1QC) were implicated in tumour immune infiltration and may be promising biomarkers for predicting metastasis and prognosis of patients with OS.

Articular chondrocyte-derived extracellular vesicles promote cartilage differentiation of human umbilical cord mesenchymal stem cells by activation of autophagy.

BACKGROUND: Umbilical cord mesenchymal stem cell (HUCMSC)-based therapies were previously utilised for cartilage regeneration because of the chondrogenic potential of MSCs. However, chondrogenic differentiation of HUCMSCs is limited by the administration of growth factors like TGF-ß that may cause cartilage hypertrophy. It has been reported that extracellular vesicles (EVs) could modulate the phenotypic expression of stem cells. However, the role of human chondrogenic-derived EVs (C-EVs) in chondrogenic differentiation of HUCMSCs has not been reported. RESULTS: We successfully isolated C-EVs from human multi-finger cartilage and found that C-EVs efficiently promoted the proliferation and chondrogenic differentiation of HUCMSCs, evidenced by highly expressed aggrecan (ACAN), COL2A, and SOX-9. Moreover, the expression of the fibrotic marker COL1A and hypertrophic marker COL10 was significantly lower than that induced by TGF-ß. In vivo, C-EVs induced HUCMSCs accelerated the repair of the rabbit model of knee cartilage defect. Furthermore, C-EVs led to an increase in autophagosomes during the process of chondrogenic differentiation, indicating that C-EVs promote cartilage regeneration through the activation of autophagy. CONCLUSIONS: C-EVs play an essential role in fostering chondrogenic differentiation and proliferation of HUCMSCs, which may be beneficial for articular cartilage repair.

Ubiquitination of S4-RNase by S-LOCUS F-BOX LIKE2 Contributes to Self-Compatibility of Sweet Cherry 'Lapins'.

Recent studies have shown that loss of pollen-S function in S4' pollen from sweet cherry (Prunus avium) is associated with a mutation in an S haplotype-specific F-box4 (SFB4) gene. However, how this mutation leads to self-compatibility is unclear. Here, we examined this mechanism by analyzing several self-compatible sweet cherry varieties. We determined that mutated SFB4 (SFB4') in S4' pollen (pollen harboring the SFB4' gene) is approximately 6 kD shorter than wild-type SFB4 due to a premature termination caused by a four-nucleotide deletion. SFB4' did not interact with S-RNase. However, a protein in S4' pollen ubiquitinated S-RNase, resulting in its degradation via the 26S proteasome pathway, indicating that factors in S4' pollen other than SFB4 participate in S-RNase recognition and degradation. To identify these factors, we used S4-RNase as a bait to screen S4' pollen proteins. Our screen identified the protein encoded by S 4 -SLFL2, a low-polymorphic gene that is closely linked to the S-locus. Further investigations indicate that SLFL2 ubiquitinates S-RNase, leading to its degradation. Subcellular localization analysis showed that SFB4 is primarily localized to the pollen tube tip, whereas SLFL2 is not. When S 4 -SLFL2 expression was suppressed by antisense oligonucleotide treatment in wild-type pollen tubes, pollen still had the capacity to ubiquitinate S-RNase; however, this ubiquitin-labeled S-RNase was not degraded via the 26S proteasome pathway, suggesting that SFB4 does not participate in the degradation of S-RNase. When SFB4 loses its function, S4-SLFL2 might mediate the ubiquitination and degradation of S-RNase, which is consistent with the self-compatibility of S4' pollen.

Functional identification of lncRNAs in sweet cherry (Prunus avium) pollen tubes via transcriptome analysis using single-molecule long-read sequencing.

Sweet cherry (Prunus avium) is a popular fruit with high nutritional value and excellent flavor. Although pollen plays an important role in the double fertilization and subsequent fruit production of this species, little is known about its pollen tube transcriptome. In this study, we identified 16,409 transcripts using single-molecule sequencing. After filtering 292 transposable elements, we conducted further analyses including mRNA classification, gene function prediction, alternative splicing (AS) analysis, and long noncoding RNA (lncRNA) identification to gain insight into the pollen transcriptome. The filtered transcripts could be matched with 3,438 coding region sequences from the sweet cherry genome. GO and KEGG analyses revealed complex biological processes during pollen tube elongation. A total of 2043 AS events were predicted, 7 of which were identified in different organs, such as the leaf, pistil and pollen tube. Using BLASTnt and the Coding-Potential Assessment Tool (CPAT), we distinguished a total of 284 lncRNAs, among which 154 qualified as natural antisense transcripts (NATs). As the NATs could be the reverse complements of coding mRNA sequences, they might bind to coding sequences. Antisense transfection assays showed that the NATs could regulate the expression levels of their complementary sequences and even affect the growth conditions of pollen tubes. In summary, this research characterizes the transcripts of P. avium pollen and lays the foundation for elucidating the physiological and biochemical mechanisms underlying sexual reproduction in the male gametes of this species.

A Joint Poisson State-Space Modelling Approach to Analysis of Binomial Series with Random Cluster Sizes.

Serially correlation binomial data with random cluster sizes occur frequently in environmental and health studies. Such data series have traditionally been analyzed using binomial state-space or hidden Markov models without appropriately accounting for the randomness in the cluster sizes. To characterize correlation and extra-variation arising from the random cluster sizes properly, we introduce a joint Poisson state-space modelling approach to analysis of binomial series with random cluster sizes. This approach enables us to model the marginal counts and binomial proportions simultaneously. An optimal estimation of our model has been developed using the orthodox best linear unbiased predictors. This estimation method is computationally efficient and robust since it depends only on the first- and second- moment assumptions of unobserved random effects. Our proposed approach is illustrated with analysis of birth delivery data.

Tweedie family of generalized linear models with distribution-free random effects for skewed longitudinal data.

Generalized linear mixed models have played an important role in the analysis of longitudinal data; however, traditional approaches have limited flexibility in accommodating skewness and complex correlation structures. In addition, the existing estimation approaches generally rely heavily on the specifications of random effects distributions; therefore, the corresponding inferences are sometimes sensitive to the choice of random effect distributions under certain circumstance. In this paper, we incorporate serially dependent distribution-free random effects into Tweedie generalized linear models to accommodate a wide range of skewness and covariance structures for discrete and continuous longitudinal data. An optimal estimation of our model has been developed using the orthodox best linear unbiased predictors of random effects. Our approach unifies population-averaged and subject-specific inferences. Our method is illustrated through the analyses of patient-controlled analgesia data and Framingham cholesterol data.