Peptide REF1 is a local wound signal promoting plant regeneration.

Plants frequently encounter wounding and have evolved an extraordinary regenerative capacity to heal the wounds. However, the wound signal that triggers regenerative responses has not been identified. Here, through characterization of a tomato mutant defective in both wound-induced defense and regeneration, we demonstrate that in tomato, a plant elicitor peptide (Pep), REGENERATION FACTOR1 (REF1), acts as a systemin-independent local wound signal that primarily regulates local defense responses and regenerative responses in response to wounding. We further identified PEPR1/2 ORTHOLOG RECEPTOR-LIKE KINASE1 (PORK1) as the receptor perceiving REF1 signal for plant regeneration. REF1-PORK1-mediated signaling promotes regeneration via activating WOUND-INDUCED DEDIFFERENTIATION 1 (WIND1), a master regulator of wound-induced cellular reprogramming in plants. Thus, REF1-PORK1 signaling represents a conserved phytocytokine pathway to initiate, amplify, and stabilize a signaling cascade that orchestrates wound-triggered organ regeneration. Application of REF1 provides a simple method to boost the regeneration and transformation efficiency of recalcitrant crops.

Isogenic human iPSC Parkinson's model shows nitrosative stress-induced dysfunction in MEF2-PGC1α transcription.

Parkinson's disease (PD) is characterized by loss of A9 dopaminergic (DA) neurons in the substantia nigra pars compacta (SNpc). An association has been reported between PD and exposure to mitochondrial toxins, including environmental pesticides paraquat, maneb, and rotenone. Here, using a robust, patient-derived stem cell model of PD allowing comparison of A53T α-synuclein (α-syn) mutant cells and isogenic mutation-corrected controls, we identify mitochondrial toxin-induced perturbations in A53T α-syn A9 DA neurons (hNs). We report a pathway whereby basal and toxin-induced nitrosative/oxidative stress results in S-nitrosylation of transcription factor MEF2C in A53T hNs compared to corrected controls. This redox reaction inhibits the MEF2C-PGC1α transcriptional network, contributing to mitochondrial dysfunction and apoptotic cell death. Our data provide mechanistic insight into gene-environmental interaction (GxE) in the pathogenesis of PD. Furthermore, using small-molecule high-throughput screening, we identify the MEF2C-PGC1α pathway as a therapeutic target to combat PD.

The RNA m6A reader YTHDC1 silences retrotransposons and guards ES cell identity.

The RNA modification N6-methyladenosine (m6A) has critical roles in many biological processes1,2. However, the function of m6A in the early phase of mammalian development remains poorly understood. Here we show that the m6A reader YT521-B homology-domain-containing protein 1 (YTHDC1) is required for the maintenance of mouse embryonic stem (ES) cells in an m6A-dependent manner, and that its deletion initiates cellular reprogramming to a 2C-like state. Mechanistically, YTHDC1 binds to the transcripts of retrotransposons (such as intracisternal A particles, ERVK and LINE1) in mouse ES cells and its depletion results in the reactivation of these silenced retrotransposons, accompanied by a global decrease in SETDB1-mediated trimethylation at lysine 9 of histone H3 (H3K9me3). We further demonstrate that YTHDC1 and its target m6A RNAs act upstream of SETDB1 to repress retrotransposons and Dux, the master inducer of the two-cell stage (2C)-like program. This study reveals an essential role for m6A RNA and YTHDC1 in chromatin modification and retrotransposon repression.

scDOT: enhancing single-cell RNA-Seq data annotation and uncovering novel cell types through multi-reference integration.

The proliferation of single-cell RNA-seq data has greatly enhanced our ability to comprehend the intricate nature of diverse tissues. However, accurately annotating cell types in such data, especially when handling multiple reference datasets and identifying novel cell types, remains a significant challenge. To address these issues, we introduce Single Cell annotation based on Distance metric learning and Optimal Transport (scDOT), an innovative cell-type annotation method adept at integrating multiple reference datasets and uncovering previously unseen cell types. scDOT introduces two key innovations. First, by incorporating distance metric learning and optimal transport, it presents a novel optimization framework. This framework effectively learns the predictive power of each reference dataset for new query data and simultaneously establishes a probabilistic mapping between cells in the query data and reference-defined cell types. Secondly, scDOT develops an interpretable scoring system based on the acquired probabilistic mapping, enabling the precise identification of previously unseen cell types within the data. To rigorously assess scDOT's capabilities, we systematically evaluate its performance using two diverse collections of benchmark datasets encompassing various tissues, sequencing technologies and diverse cell types. Our experimental results consistently affirm the superior performance of scDOT in cell-type annotation and the identification of previously unseen cell types. These advancements provide researchers with a potent tool for precise cell-type annotation, ultimately enriching our understanding of complex biological tissues.

An Interaction Landscape of Ubiquitin Signaling.

Intracellular signaling via the covalent attachment of different ubiquitin linkages to protein substrates is fundamental to many cellular processes. Although linkage-selective ubiquitin interactors have been studied on a case-by-case basis, proteome-wide analyses have not been conducted yet. Here, we present ubiquitin interactor affinity enrichment-mass spectrometry (UbIA-MS), a quantitative interaction proteomics method that makes use of chemically synthesized diubiquitin to enrich and identify ubiquitin linkage interactors from crude cell lysates. UbIA-MS reveals linkage-selective diubiquitin interactions in multiple cell types. For example, we identify TAB2 and TAB3 as novel K6 diubiquitin interactors and characterize UCHL3 as a K27-linkage selective interactor that regulates K27 polyubiquitin chain formation in cells. Additionally, we show a class of monoubiquitin and K6 diubiquitin interactors whose binding is induced by DNA damage. We expect that our proteome-wide diubiquitin interaction landscape and established workflows will have broad applications in the ongoing efforts to decipher the complex language of ubiquitin signaling.

YTHDF1 facilitates PRC1-mediated H2AK119ub in human ES cells.

Polycomb repressive complexes (PRCs) play critical roles in cell fate decisions during normal development as well as disease progression through mediating histone modifications such as H3K27me3 and H2AK119ub. How exactly PRCs recruited to chromatin remains to be fully illuminated. Here, we report that YTHDF1, the N6-methyladenine (m6 A) RNA reader that was previously known to be mainly cytoplasmic, associates with RNF2, a PRC1 protein that mediates H2AK119ub in human embryonic stem cells (hESCs). A portion of YTHDF1 localizes in the nuclei and associates with RNF2/H2AK119ub on a subset of gene loci related to neural development functions. Knock-down YTHDF1 attenuates H2AK119ub modification on these genes and promotes neural differentiation in hESCs. Our findings provide a noncanonical mechanism that YTHDF1 participates in PRC1 functions in hESCs.

Activation of the PI3K/AKT signaling pathway by ARNTL2 enhances cellular glycolysis and sensitizes pancreatic adenocarcinoma to erlotinib.

BACKGROUND: Pancreatic adenocarcinoma (PC) is an aggressive malignancy with limited treatment options. The poor prognosis primarily stems from late-stage diagnosis and when the disease has become therapeutically challenging. There is an urgent need to identify specific biomarkers for cancer subtyping and early detection to enhance both morbidity and mortality outcomes. The addition of the EGFR tyrosine kinase inhibitor (TKI), erlotinib, to gemcitabine chemotherapy for the first-line treatment of patients with advanced pancreatic cancer slightly improved outcomes. However, restricted clinical benefits may be linked to the absence of well-characterized criteria for stratification and dependable biomarkers for the prediction of treatment effectiveness. METHODS AND RESULTS: We examined the levels of various cancer hallmarks and identified glycolysis as the primary risk factor for overall survival in PC. Subsequently, we developed a glycolysis-related score (GRS) model to accurately distinguish PC patients with high GRS. Through in silico screening of 4398 compounds, we discovered that erlotinib had the strongest therapeutic benefits for high-GRS PC patients. Furthermore, we identified ARNTL2 as a novel prognostic biomarker and a predictive factor for erlotinib treatment responsiveness in patients with PC. Inhibition of ARNTL2 expression reduced the therapeutic efficacy, whereas increased expression of ARNTL2 improved PC cell sensitivity to erlotinib. Validation in vivo using patient-derived xenografts (PDX-PC) with varying ARNTL2 expression levels demonstrated that erlotinib monotherapy effectively halted tumor progression in PDX-PC models with high ARNTL2 expression. In contrast, PDX-PC models lacking ARNTL2 did not respond favorably to erlotinib treatment. Mechanistically, we demonstrated that the ARNTL2/E2F1 axis-mediated cellular glycolysis sensitizes PC cells to erlotinib treatment by activating the PI3K/AKT signaling pathway. CONCLUSIONS: Our investigations have identified ARNTL2 as a novel prognostic biomarker and predictive indicator of sensitivity. These results will help to identify erlotinib-responsive cases of PC and improve treatment outcomes. These findings contribute to the advancement of precision oncology, enabling more accurate and targeted therapeutic interventions.

Antimicrobial efficacy of aloe-emodin mediated photodynamic therapy against antibiotic-resistant Pseudomonas aeruginosa in vitro.

Multidrug-resistant Pseudomonas aeruginosa is a common pathogen that causes topical infections following burn injuries. Antimicrobial photodynamic therapy (aPDT) has emerged as a promising approach for treating antibiotic-resistant bacterial infections. The objective of this study was to evaluate the aPDT efficacy of aloe-emodin (AE), which is a photosensitizer extracted from traditional Chinese herbs, on antibiotic-sensitive and antibiotic-resistant P. aeruginosa in vitro. In this study, we confirmed the effectiveness of AE-mediated aPDT against both standard and MDR P. aeruginosa, explored the effects of irradiation time and AE concentration on bacterial survival in AE-mediated aPDT, and observed the structural damage of P. aeruginosa by using transmission electron microscope. Our results showed that neither AE nor light irradiation alone caused cytotoxic effects on P. aeruginosa. However, AE-mediated aPDT effectively inactivated both antibiotic-sensitive and antibiotic-resistant P. aeruginosa. The transmission electron microscope investigation showed that aPDT mediated by AE primarily caused damage to the cytoplasm and cell membrane. Our findings suggest that AE is a photosensitizer in the aPDT of MDR P. aeruginosa-caused topical infections following burn injuries. Future investigations will concentrate on the safety and efficacy of AE-mediated aPDT in animal models and clinical trials.

Functional validation of AaCaM3 response to high temperature stress in Amorphophallus albus.

Amorphophallus is a perennial monocotyledonous herbaceous plant native to the southwestern region of China, widely used in various fields such as food processing, biomedicine and chemical agriculture. However, Amorphophallus is a typical thermolabile plant, and the continuous high temperature in summer have seriously affected the growth, development and economic yield of Amorphophallus in recent years. Calmodulin (CaM), a Ca2+ sensor ubiquitous in eukaryotes, is the most important multifunctional receptor protein in plant cells, which affects plant stress resistance by participating in the activities of a variety of signaling molecules. In this study, the key gene AaCaM3 for the Ca2+-CaM regulatory pathway was obtained from A. albus, the sequence analysis confirmed that it is a typical calmodulin. The qRT-PCR results demonstrated that with the passage of heat treatment time, the expression of AaCaM3 was significantly upregulated in A. albus leaves. Subcellular localization analysis revealed that AaCaM3 localized on the cytoplasm and nucleus. Meanwhile, heterologous transformation experiments have shown that AaCaM3 can significantly improve the heat tolerance of Arabidopsis under heat stress. The promoter region of AaCaM3 was sequenced 1,338 bp by FPNI-PCR and GUS staining assay showed that the promoter of AaCaM3 was a high-temperature inducible promoter. Yeast one-hybrid analysis and Luciferase activity reporting system analysis showed that the AaCaM3 promoter may interact with AaHSFA1, AaHSFA2c, AaHSP70, AaDREB2a and AaDREB2b. In conclusion, this study provides new ideas for further improving the signal transduction network of high-temperature stress in Amorphophallus.

scDEA: differential expression analysis in single-cell RNA-sequencing data via ensemble learning.

The identification of differentially expressed genes between different cell groups is a crucial step in analyzing single-cell RNA-sequencing (scRNA-seq) data. Even though various differential expression analysis methods for scRNA-seq data have been proposed based on different model assumptions and strategies recently, the differentially expressed genes identified by them are quite different from each other, and the performances of them depend on the underlying data structures. In this paper, we propose a new ensemble learning-based differential expression analysis method, scDEA, to produce a more stable and accurate result. scDEA integrates the P-values obtained from 12 individual differential expression analysis methods for each gene using a P-value combination method. Comprehensive experiments show that scDEA outperforms the state-of-the-art individual methods with different experimental settings and evaluation metrics. We expect that scDEA will serve a wide range of users, including biologists, bioinformaticians and data scientists, who need to detect differentially expressed genes in scRNA-seq data.

DEP2: an upgraded comprehensive analysis toolkit for quantitative proteomics data.

SUMMARY: Mass spectrometry (MS)-based proteomics has become the most powerful approach to study the proteome of given biological and clinical samples. Advancements in sample preparation and MS detection have extended the application of proteomics but have also brought new demands on data analysis. Appropriate proteomics data analysis workflow mainly requires quality control, hypothesis testing, functional mining, and visualization. Although there are numerous tools for each process, an efficient and universal tandem analysis toolkit to obtain a quick overall view of various proteomics data is still urgently needed. Here, we present DEP2, an updated version of DEP we previously established, for proteomics data analysis. We amended the analysis workflow by incorporating alternative approaches to accommodate diverse proteomics data, introducing peptide-protein summarization and coupling biological function exploration. In summary, DEP2 is a well-rounded toolkit designed for protein- and peptide-level quantitative proteomics data. It features a more flexible differential analysis workflow and includes a user-friendly Shiny application to facilitate data analysis. AVAILABILITY AND IMPLEMENTATION: DEP2 is available at https://github.com/mildpiggy/DEP2, released under the MIT license. For further information and usage details, please refer to the package website at https://mildpiggy.github.io/DEP2/.

EnDecon: cell type deconvolution of spatially resolved transcriptomics data via ensemble learning.

MOTIVATION: Spatially resolved gene expression profiles are the key to exploring the cell type spatial distributions and understanding the architecture of tissues. Many spatially resolved transcriptomics (SRT) techniques do not provide single-cell resolutions, but they measure gene expression profiles on captured locations (spots) instead, which are mixtures of potentially heterogeneous cell types. Currently, several cell-type deconvolution methods have been proposed to deconvolute SRT data. Due to the different model strategies of these methods, their deconvolution results also vary. RESULTS: Leveraging the strengths of multiple deconvolution methods, we introduce a new weighted ensemble learning deconvolution method, EnDecon, to predict cell-type compositions on SRT data in this work. EnDecon integrates multiple base deconvolution results using a weighted optimization model to generate a more accurate result. Simulation studies demonstrate that EnDecon outperforms the competing methods and the learned weights assigned to base deconvolution methods have high positive correlations with the performances of these base methods. Applied to real datasets from different spatial techniques, EnDecon identifies multiple cell types on spots, localizes these cell types to specific spatial regions and distinguishes distinct spatial colocalization and enrichment patterns, providing valuable insights into spatial heterogeneity and regionalization of tissues. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://github.com/Zhangxf-ccnu/EnDecon. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Engineered disulfide reveals structural dynamics of locked SARS-CoV-2 spike.

The spike (S) protein of SARS-CoV-2 has been observed in three distinct pre-fusion conformations: locked, closed and open. Of these, the function of the locked conformation remains poorly understood. Here we engineered a SARS-CoV-2 S protein construct "S-R/x3" to arrest SARS-CoV-2 spikes in the locked conformation by a disulfide bond. Using this construct we determined high-resolution structures confirming that the x3 disulfide bond has the ability to stabilize the otherwise transient locked conformations. Structural analyses reveal that wild-type SARS-CoV-2 spike can adopt two distinct locked-1 and locked-2 conformations. For the D614G spike, based on which all variants of concern were evolved, only the locked-2 conformation was observed. Analysis of the structures suggests that rigidified domain D in the locked conformations interacts with the hinge to domain C and thereby restrains RBD movement. Structural change in domain D correlates with spike conformational change. We propose that the locked-1 and locked-2 conformations of S are present in the acidic high-lipid cellular compartments during virus assembly and egress. In this model, release of the virion into the neutral pH extracellular space would favour transition to the closed or open conformations. The dynamics of this transition can be altered by mutations that modulate domain D structure, as is the case for the D614G mutation, leading to changes in viral fitness. The S-R/x3 construct provides a tool for the further structural and functional characterization of the locked conformations of S, as well as how sequence changes might alter S assembly and regulation of receptor binding domain dynamics.

Particulate matters 2.5 induce tumor progression in lung cancer by increasing the activity of hnRNPA2B1 resulting in retarding mRNA decay of oxidative phosphorylation.

Particulate matter 2.5 (PM2.5) has been implicated in lung injury and various cancers, yet its precise mechanistic role remains elusive. To elucidate the key signaling pathways underpinning PM2.5-induced lung cancer progression, we embarked on a study examining the impact of PM2.5 both in vitro and in vivo. Lung cancer cell lines, A549 and H157, were employed for the in vitro investigations. Overexpression or knockdown techniques targeting the hnRNPA2B1 protein were implemented. Lung cancer cells were treated with a medium containing PM2.5 and subsequently prepared for in vitro evaluations. Cell growth, invasion, and migration were gauged using transwell and CCK-8 assays. Apoptosis was ascertained through flow cytometry and western blotting of pertinent proteins. Seahorse analyses probed the influence of PM2.5 on lung cancer energy metabolism. The RNA stability assay was employed to discern the impact of PM2.5 on the stability of oxidative phosphorylation-related genes in lung cancer. Our findings revealed that PM2.5 augmented cell proliferation, migration, and invasion rates. Similarly, a diminished apoptosis rate was observed in PM2.5-treated cells. Elevated expression of hnRNPA2B1 was detected in lung cancer cells exposed to PM2.5. Moreover, in cells treated with PM2.5, hnRNPA2B1 knockdown markedly curtailed cell proliferation by inducing G1-S cell cycle arrest and bolstered lung cancer cell apoptosis in vitro; it also curbed xenograft tumor growth. Mechanistically, our data suggest that PM2.5 undermines the stability of mRNA transcripts associated with oxidative phosphorylation (OXPHOS) and augments the formation of processing bodies (P-bodies), leading to an upsurge in OXPHOS levels. In conclusion, PM2.5 appears to drive lung cancer progression and migration by modulating the energy metabolism of lung cancer in a hnRNPA2B1-dependent manner.

Advances in lymphatic metastasis of non-small cell lung cancer.

Lung cancer is a deeply malignant tumor with high incidence and mortality. Despite the rapid development of diagnosis and treatment technology, abundant patients with lung cancer are still inevitably faced with recurrence and metastasis, contributing to death. Lymphatic metastasis is the first step of distant metastasis and an important prognostic indicator of non-small cell lung cancer. Tumor-induced lymphangiogenesis is involved in the construction of the tumor microenvironment, except promoting malignant proliferation and metastasis of tumor cells, it also plays a crucial role in individual response to treatment, especially immunotherapy. Thus, this article reviews the current research status of lymphatic metastasis in non-small cell lung cancer, in order to provide some insights for the basic research and clinical and translational application in this field.

Cell-type annotation with accurate unseen cell-type identification using multiple references.

The recent advances in single-cell RNA sequencing (scRNA-seq) techniques have stimulated efforts to identify and characterize the cellular composition of complex tissues. With the advent of various sequencing techniques, automated cell-type annotation using a well-annotated scRNA-seq reference becomes popular. But it relies on the diversity of cell types in the reference, which may not capture all the cell types present in the query data of interest. There are generally unseen cell types in the query data of interest because most data atlases are obtained for different purposes and techniques. Identifying previously unseen cell types is essential for improving annotation accuracy and uncovering novel biological discoveries. To address this challenge, we propose mtANN (multiple-reference-based scRNA-seq data annotation), a new method to automatically annotate query data while accurately identifying unseen cell types with the aid of multiple references. Key innovations of mtANN include the integration of deep learning and ensemble learning to improve prediction accuracy, and the introduction of a new metric that considers three complementary aspects to distinguish between unseen cell types and shared cell types. Additionally, we provide a data-driven method to adaptively select a threshold for identifying previously unseen cell types. We demonstrate the advantages of mtANN over state-of-the-art methods for unseen cell-type identification and cell-type annotation on two benchmark dataset collections, as well as its predictive power on a collection of COVID-19 datasets. The source code and tutorial are available at https://github.com/Zhangxf-ccnu/mtANN.

The mTORC1-eIF4F axis controls paused pluripotency.

Mouse embryonic stem cells (mESCs) can self-renew indefinitely and maintain pluripotency. Inhibition of mechanistic target of rapamycin (mTOR) by the kinase inhibitor INK128 is known to induce paused pluripotency in mESCs cultured with traditional serum/LIF medium (SL), but the underlying mechanisms remain unclear. In this study, we demonstrate that mTOR complex 1 (mTORC1) but not complex 2 (mTORC2) mediates mTOR inhibition-induced paused pluripotency in cells grown in both SL and 2iL medium (GSK3 and MEK inhibitors and LIF). We also show that mTORC1 regulates self-renewal in both conditions mainly through eIF4F-mediated translation initiation that targets mRNAs of both cytosolic and mitochondrial ribosome subunits. Moreover, inhibition of mitochondrial translation is sufficient to induce paused pluripotency. Interestingly, eIF4F also regulates maintenance of pluripotency in an mTORC1-independent but MEK/ERK-dependent manner in SL, indicating that translation of pluripotency genes is controlled differently in SL and 2iL. Our study reveals a detailed picture of how mTOR governs self-renewal in mESCs and uncovers a context-dependent function of eIF4F in pluripotency regulation.

Hematoxylin and Eosin Staining Helps Reduce Maternal Contamination in Short Tandem Repeat Genotyping for Hydatidiform Mole Diagnosis.

Short tandem repeat (STR) genotyping provides parental origin information about aneuploidy pregnancy loss and has become the current gold standard for hydatidiform mole diagnosis. STR genotyping diagnostic support most commonly relies on formalin-fixed paraffin-embedded samples, but maternal contamination is one of the most common issues based on traditional unstained sections. To evaluate the influence of hematoxylin and eosin (H&E) staining on DNA quality and STR genotyping, DNA was isolated from unstained, deparaffinized hydrated, and H&E-stained tissue sections (i.e. 3 groups) from each of 6 formalin-fixed paraffin-embedded placentas. The macrodissected view field, DNA quality, and polymerase chain reaction amplification efficiency were compared among groups. STR genotyping analysis was performed in both the test cohort (n = 6) and the validation cohort (n = 149). H&E staining not only did not interfere with molecular DNA testing of formalin-fixed paraffin-embedded tissue but also had a clearer macrodissected field of vision. In the test cohort, H&E-stained sections were the only group that did not exhibit maternal miscellaneous peaks in STR genotyping results. In the validation cohort, 138 (92.62%) cases yielded satisfactory amplification results without maternal contamination. Thus, H&E staining helped to reduce maternal contamination in STR genotyping for hydatidiform mole diagnosis, suggesting that H&E-stained sections can be incorporated into the hydatidiform mole molecular diagnostic workflow.

Safety and efficacy of histotripsy delivery through overlying gas-filled small bowel in an ex vivo swine model.

PURPOSE: To evaluate the safety and efficacy of performing histotripsy through overlying gas-filled bowel in an ex vivo swine model. METHODS: An ex vivo model was created to simulate histotripsy treatment of solid organs through gas-filled bowel. Spherical 2.5 cm histotripsy treatments were performed in agar phantoms for each of five treatment groups: 1) control with no overlying bowel (n = 6), 2) bowel 0 cm above phantom (n = 6), 3) bowel 1 cm above phantom (n = 6), 4) bowel 2 cm above phantom (n = 6), and 5) bowel 0 cm above the phantom with increased treatment amplitude (n = 6). Bowel was inspected for gross and microscopic damage, and treatment zones were measured. A ray-tracing simulation estimated the percentage of therapeutic beam path blockage by bowel in each scenario. RESULTS: All histotripsy treatments through partial blockage were successful (24/24). No visible or microscopic damage was observed to intervening bowel. Partial blockage resulted in a small increase in treatment volume compared to controls (p = 0.002 and p = 0.036 for groups with bowel 0 cm above the phantom, p > 0.3 for bowel 1 cm and 2 cm above the phantom). Gas-filled bowel was estimated to have blocked 49.6%, 35.0%, and 27.3% of the therapeutic beam at 0, 1, and 2 cm, respectively. CONCLUSION: Histotripsy has the potential to be applied through partial gas blockage of the therapeutic beam path, as shown by this ex vivo small bowel model. Further work in an in vivo survival model appears indicated.

Associations of vegetable and fruit intake, physical activity, and school bullying with depressive symptoms in secondary school students: the mediating role of internet addiction.

BACKGROUND: Few studies have simultaneously focused on the associations of vegetable and fruit intake, physical activity, school bullying, and Internet addiction (IA) with depressive symptoms. This study aimed to explore the direct and indirect effects of the above factors on depressive symptoms in adolescents by constructing a structural equation model (SEM). METHODS: This study was conducted in Qingdao from September to November 2021. A total of 6195 secondary school students aged 10-19 years were included in the analysis. Information on all variables was assessed using a self-administered questionnaire. An SEM was constructed with depressive symptoms as the endogenous latent variable, IA as the mediating variable, and vegetable and fruit intake, physical activity, and school bullying as the exogenous latent variables. The standardized path coefficients (ß) were the direct effects between the latent variables, and the indirect effects were obtained by the product of direct effects between relevant latent variables. RESULTS: The median value with the interquartile range of depressive symptom scores was 7 (3,12). Vegetable and fruit intake (ß=-0.100, P<0.001) and physical activity (ß=-0.140, P<0.001) were directly negatively related to depressive symptoms. While school bullying (ß=0.138, P<0.001) and IA (ß=0.452, P<0.001) were directly positively related to depressive symptoms. IA had the greatest impact on depressive symptoms. Vegetable and fruit intake, physical activity, and school bullying could not only directly affect depressive symptoms, but also indirectly affect depressive symptoms through the mediating effect of IA, the indirect effects and 95% confidence intervals (CIs) were -0.028 (-0.051, -0.007), -0.114 (-0.148, -0.089) and 0.095 (0.060, 0.157), respectively. The results of the multi-group analysis showed that the SEM we constructed still fit in boy and girl groups. CONCLUSIONS: The results indicated that vegetable and fruit intake, physical activity, school bullying, and IA had a significant direct impact on depressive symptoms, among which IA had the greatest impact. In addition, both vegetable and fruit intake, school bullying, and physical activity indirectly affected depressive symptoms through the mediating effect of IA. The impact of IA on depressive symptoms should be given extra attention by schools and parents. This study provides a scientific and effective basis for the prevention and control of adolescent depressive symptoms.