Vitis vinifera L. cultivars , and one wild (Vitis vinifera subsp. sylvestris) genotype exposed to water deficit (WD) for nine days under semi-controlled conditions in the greenhouse. Sampling for biochemical and gene expression analyses was performed at days six and nine from the beginning of WD treatment. The WD affected the accumulation of metabolites with a significant increase in abscisic acid (ABA), salicylic acid (SA), and proline in the leaves of the stressed genotypes when the WD continued for nine days. Lipid peroxidation (MDA) was not significantly different from that of the control plants after six days of WD, whereas it was significantly lower (297.40 nmol/g dw) in the stressed plants after nine days. The cultivar ‘Istrian Malvasia’ responded rapidly to the WD and showed the highest and earliest increase in ABA levels . ‘Graševina’ differed significantly from the other genotypes in SA content at both time points analyzed . Proline level increased significantly under WD (up to 5-fold at day nine), and proline variation was not genotype driven. The expression of aquaporin genes  was down-regulated in all genotypes, coinciding with the accumulation of ABA. The gene NCED1 (9-cis-epoxycarotenoid dioxygenase) related to ABA was up-regulated in all genotypes under stress conditions and served as a reliable marker of drought stress. This work suggests that the stress response in metabolite synthesis and accumulation is complex, treatment- and genotype-dependent.The biochemical response and gene expression in different grapevine cultivars to water deficit are still not well understood. In this study, we investigated the performance of four traditional Croatian  Vitis vinifera L.) is generally well adapted to dry conditions [Recent climate changes, characterized by increased temperatures and exacerbated droughts, are having a significant impact on various agricultural sectors, particularly in the semi-arid and arid Mediterranean regions . Unfortunditions ,5, it caNCED1 and NCED2 (9-cis-epoxycarotenoid dioxygenase), have been identified as reliable markers of drought stress [NCED1 and NCED2 in different grapevine cultivars during the water deficit.The morphological signs of drought stress often become apparent only after significant damage has already occurred. Therefore, it is important to identify reliable markers of drought stress at the physiological, biochemical and genetic levels . Phytohot stress ,12, althTIP2;1 and PIP2;1 are particularly important for regulation of water transport under drought conditions [Changes in the hydraulic pathway, including regulation of aquaporins (AQPs), are also involved in the response to water deficit stress. AQPs are cell membrane proteins that facilitate the transport of water and small molecules across plasma membranes. The expression patterns of individual AQP genes and their involvement in isohydric/anisohydric strategies under drought conditions have not been fully elucidated . Tonoplanditions ,15. In anditions .One approach to adapt to climate change is the utilization of traditional grapevine cultivars that are adapted to specific environmental conditions. However, there is a lack of studies investigating the molecular variability related to water regulation in traditional cultivars. Adaptation to drought of traditional cultivars, or cultivars specific to a certain region, were mostly examined from phenological or physiological perspectives ,18,19,20Vitis vinifera subsp. sylvestris (hereafter referred to as V. sylvestris) genotype. These cultivars were grown on their own roots in a greenhouse in 5-L pots. ‘Graševina’ is the predominant cultivar in the continental part of Croatia, whereas ‘Istrian Malvasia’ and ‘Plavac mali crni’ are commonly grown in the northern (Istria) and southern  coastal regions, respectively. ‘Tribidrag’ is regaining importance in Croatia due to its recent genetic discovery of synonymy with the American cultivar ‘Zinfandel’ and the Italian cultivar ‘Primitivo’. The V. sylvestris differs to some extent from cultivars in terms of its genomic constitution, and information about its drought tolerance is limited. We conducted metabolite profiling focusing on ABA, SA, MDA and proline, and analyzed the expression of selected genes related to AQP and ABA biosynthesis. This is the first research on the response of different grape varieties to drought in Croatia.In this study, we aimed to investigate the effects of water deficit at two time-points (six and nine days) on four traditional Croatian grapevine cultivars  and one wild Stress-related metabolites  were analyzed in five grapevine genotypes at two time points (six and nine days) of water deficit treatment.p < 0.001).A two-way ANOVA analysis revealed a significant genotype and treatment effect at both time points on metabolite accumulation during water deficit . A signiAfter six days of stress, IM had significantly higher ABA content (1.6- to 1.9-fold) compared with the other genotypes and, together with PMC, showed early accumulation under stress A. At theAt nine days, increase in ABA (3.9-fold) and proline (5-fold) under WD showed to be only treatment-dependent. SA was still significantly higher in GR (1.4- to 3-fold) compared with the other genotypes. MDA accumulation was mainly genotype driven in this experiment. MDA content between treatments (WW vs. WD) significantly differed only upon nine days of water deficit (~0.6-fold decrease in WD). The highest MDA content between genotypes upon nine days was observed in PMC , followeAt both time points, water deficit led to a significant increase in ABA, SA and proline, while a significant decrease was observed for MDA only, at the second time point.When control and water deficit treatments were compared between genotypes, there was a significant increase in ABA content at IM, PMC, and TR at six days A. This iIM and PMC showed significantly higher proline content in vines with water deficit at six (IM: 3.6-fold increase/PMC: 1.5-fold increase) and nine days (IM: 8-fold increase/PMC: 6.4-fold increase) C. A signResults for the biochemical markers normalized to the corresponding controls are shown in NCED1 and NCED2) and the AQPs  is shown in NCED2, TIP2;1, and PIP2;1) in all genotypes at both time points. Two genotypes, PMC and IM, exhibited significant down-regulation of NCED2 at six days; earlier than the other genotypes. In addition, PMC and IM exhibited stronger signals for the down-regulation of AQP genes. NCED1 transcript level showed a tendency to overexpress under drought conditions compared to controls, but a significant increase in expression was observed only in PMC after nine days of water deficit.The expression level of selected genes related to the biosynthesis of ABA  is more likely related to WD at day 6. The same could be concluded for the ABA biosynthetic genes NCED2 and NCED1, whereas positioning of NCED1 suggested its increased expression under stress, especially after six days of drought, and thus its strong contribution to the drought response compared with NCED2. PCA used to consider the correlations between the stress-responsive metabolites, the selected gene expressions and the studied genotypes evaluated after six and nine days of drought treatment showed that PC1 accounted for 41.60% and PC2 for 19.12% of the variability and together explained 60.72% of the total variability. ABA, SA, and proline were positioned close to prolonged drought conditions (day nine) compared to controls and early drought conditions (day six of water deficit initiation). MDA was close to control and early drought response scores, indicating that no significant lipid peroxidation occurred under drought. The positioning of aquaporin genes  was studied at two time points, under six- and nine-days of water deficit in a greenhouse. As in previous studies [The stress response of four grapevine cultivars  and one wild grapevine genotype . The significant increase in ABA at the first time point and the nonsignificant changes between genotypes after prolonged stress confirm ABA as one of the first signaling molecules in water deficit. After reaching the peak, de novo synthesis of ABA no longer occurs ,30. DeguTriticum aestivum [The rapid accumulation of ABA, observed for IM and PMC, is similar to that reported for the isohydric cultivar of aestivum . Degu etaestivum  observedaestivum . Poa ligularis and the lowest in the highly tolerant xerophytic species Papostypa speciosa [The correlations between an increase in endogenous ABA content and drought tolerance of plants are somewhat controversial in the literature and obviously depend on plant species, cultivar, and developmental stage. Positive correlations between ABA content and drought tolerance were found in sunflower and switchgrass, suggesting that constitutively high ABA content in tolerant cultivars confers an improved ability to cope with water deficit . On the speciosa . Degu etspeciosa  highlighArabidopsis thaliana  exhibit stomatal closure and improved drought tolerance [SA is a phytohormone that plays an important role in drought tolerance via promoting the accumulation of osmolytes such as proline or maintaining antioxidant activity ,33. SA iolerance ,36. Since SA is a phenolic acid with demonstrated antioxidant activity, its increased concentration in the plant could enhance a ROS-scavenging capacity . HoweverProline is involved in membrane stability by supporting growth and productivity under water deficit. It is one of the most reactive amino acids produced during water deficit and, together with sugars, plays a role in osmotic adjustment . The higMalondialdehyde (MDA), a product of lipid peroxidation, is an indicator of oxidative stress, which is expected to be high during drought . In our The antioxidant activity could be enhanced by the significant effects (genotype and treatment) observed in this experiment for SA. Proline is also important for ROS signaling, protects against oxidative stress, and delays aging in plants . In geneThe metabolic response observed here under drought stress suggests an early ABA accumulation and a prominent role of proline, as ABA can induce proline biosynthesis . AlthougNCED1 and NCED2 genes are related to this metabolite; both can be a good marker at different stages. The genes could be more sensitive and used as markers in early stages of drought stress. ABA and aquaporins are related because ABA can regulate the closure of AQPs by alkalinization of xylem sap and membrane depolarizations [NCED1 in PMC, and a tendency toward up-regulation in TR and SYL. In this regard, NCED1 proved to be a better marker than ABA concentration [NCED1 in leaves of ‘Grenache’ and ‘Shiraz’ grapevines under water deficit. The complete down-regulation of NCED2, a key enzyme for de novo biosynthesis of ABA, may indicate that its activity is higher in roots, since its high expression was observed in the self-rooted rootstock 1103P [ABA is a metabolite and izations . The resntration , as it cntration  which reck 1103P . Saud etck 1103P  also fouck 1103P ,47.PIP2;1, have previously been observed to be more up-regulated at early stages of water deficit [AQP genes, particularly  deficit  or after deficit ,48. The  deficit  in leave deficit . AQP gen deficit . ResultsVitis vinifera subsp. vinifera L.: ‘Plavac mali crni’ (PMC), ‘Istrian Malvasia’ (IM), ‘Graševina’ (GR), and ‘Tribidrag’ (TR) and a Vitis vinifera subsp. sylvestris genotype IJK88 (SYL). Grapevines were propagated from hardwood virus free (Vitis vinifera L.) cuttings. Cuttings of TR were from the grapevine collection of the IAC in Split, PMC and GR from the University of Zagreb, Faculty of Agriculture, while cuttings of IM were obtained from Vivai Cooperativi Rauscedo (VCR) Italy. Cuttings of the wild SYL genotype were taken from the natural habitat in Paklenica National Park in Croatia, previously genotyped and confirmed as belonging to Vitis vinifera subsp. sylvestris [Water deficit studies were conducted during 2021 in an experimental greenhouse of the Institute of Adriatic Crops and Karst Reclamation in Split, Croatia (IAC) on four cultivars of lvestris . Own-rooDisease control (against powdery mildew) was regularly applied before water deficit treatment.Each cultivar consisted of 18 plants arranged in a completely randomized design. The water deficit experiment was conducted from 31 May to 9 June 2021. Nine plants were subjected to the water deficit treatment (WD) via withholding water, while the corresponding controls of nine plants were irrigated to field capacity (WW). At the time of sampling, shoots were ~100 cm long, had 15–20 leaves, and were free of fruit. 2) and stored at −80 °C. Leaf samples for biochemical and gene expression analyses were collected from individual plants on two different days: 6 June 2021 (day six) and 9 June 2021 (day nine). Samples were collected from the fifth fully developed leaf (day six) and the sixth fully developed leaf (day nine) from the shoot tip of the stressed plants and corresponding controls. Each leaf was divided into two halves with scissors and the petiole and central vein were removed. One half of the leaf was used for metabolite analysis, while the other half was used for gene expression analysis. For each biological replicate, the leaf halves of three plants were divided, providing a total of three biological replicates per treatment and corresponding controls. All collected leaves were snap-frozen in liquid nitrogen (Nv/v ethanol. Lyophilized tissue (30 mg) was homogenized using a Mixer Mill Retsch MM 400 for 3.5 min at 30 Hz, extracted in 70% v/v ethanol (1.3 mL), incubated for 30 min at 4 °C, and centrifuged at 16,000× g at 4 °C for 10 min. A volume of 100 µL of the extract was mixed with 1000 µL of the reaction mixture , and then heated to 95 °C for 20 min. Proline levels were measured at 520 nm using a UV–VIS spectrophotometer  and calculated using a standard curve : 0.04, 0.1, 0.2, 0.4, 1.0, 1.5 mM). The proline content was expressed in µmol g−1 dw (dry weight). Measurements were performed in three biological replicates. For each biological replicate, three technical replicates were performed.Proline concentrations were assayed according to , with sov/v TCA was added, and the suspension was centrifuged at 13,000 rpm at 4 °C for 10 min. The reaction mixture  and MDA reagent (0.5% w/v thiobarbituric acid (TBA) in 20% v/v TCA, Sigma Aldrich, Saint Louis, MO, USA) was incubated at 95 °C for 25 min and centrifuged at 13,000 rpm and 4 °C for 10 min. The absorbance of supernatants was measured at 532 and 600 nm, and the content of MDA was calculated using an extinction coefficient of 155 mM−1 cm−1. MDA content was expressed as nmol MDA g−1 dw. Measurements were performed in three biological replicates. For each biological replicate, three technical replicates were performed.Lipid peroxidation was determined via the malonaldehyde (MDA) method according to , with a 6 was purchased from Sigma-Aldrich, Darmstadt, Germany; (+)-cis, trans abscisic acid-d6 from Trc. MiliQ® water ; and HPLC gradient-grade methanol  were used with analytical-grade formic acid (FA)  for mobile phase preparation.SA and ABA were purchased from Fluka, and (+)-cis, trans abscisic acid was purchased from Duchefa-Biochemie. The internal isotope-labeled standard salicylic acid-dv/v methanol containing 1% v/v acetic acid. A total of 40 μL of salicylic acid-d6 and abscisic acid-d6 as internal standards (1 μg/mL) was added to each sample, followed by homogenization for 2 min at 30 Hz, and then 60 min equilibration in the cold chamber. After centrifugation , the supernatant was collected and filtered  into vials. A total of 100 μL of the clear solution was injected into a Zorbax XDP C18 column  .Concentrations of SA and ABA in leaves were determined using LC–MS/MS analysis, as previously described . In briev/v formic acid (FA) in water (solvent A) and methanol (solvent B). The gradient was applied as follows: 0 min 50% A, 5–15 min 50% A-0% A, 15–17 min 0% A, 17.1–22 min 60% A. Flow rate was 0.3 mL/min.LC–MS/MS analysis was carried out using an Agilent Technologies 1200 series HPLC system equipped with a binary pump, a vacuum membrane degasser, an automated autosampler, and an injector interfaced with a 6420 triple quadropole mass spectrometer with an electrospray ionization source (ESI) . Solvents for the analysis were 0.1% m/z 263-153 for ABA (quantifying ion), m/z 263-219 for ABA , m/z 137-93 for SA, m/z 269-159 for ABA-d6, and m/z 141-97 for SA-d6. Fragmentor voltages were 100 V for ABA and ABA-d6 and 70 V for SA and SA-d6. Collision energy was set at 15 V for SA, 12 V for SA-d6, 3 V for ABA quantifying and ABA-d6, and 2 V for ABA qualifying transition. All data acquisition and processing were performed using Agilent MassHunter software . ABA and SA were calculated based on previously prepared calibration curves as previously described [−1 dw.The electrospray ionization source was operated in the negative mode, and samples were detected in the multiple reaction monitoring (MRM) mode with a dwell time of 10 ms per MRM transition. The desolvation gas temperature was 350 °C with a flow rate of 6.0 L/min. The capillary voltage was 3.5 kV. The collision gas was nitrogen. The MRM transitions of precursor to product ion pairs were TM RNA MiniPrep Kit  according to [For total RNA isolation, leaf tissue was homogenized in liquid nitrogen using a mortar and pestle. Then, 50 mg of the homogenized material was pulverized with zirconium oxide beads  in a Retsch MM400 mixing mill  in three cycles of 1 min at 30 Hz. To the homogenized samples obtained, 800 µL of CTAB buffer was added and total RNA was isolated using a Direct-zolrding to , with slGene-specific primers were designed using primer-BLAST  or previt-test with mean standard error bars (±SE). These data analyses were performed using the STATISTICA v. 14.0 programme . p values < 0.05 were considered statistically significant throughout. Principal component analysis (PCA) was used to group genotypes based on biochemical and gene expression data using mean values in XLSTAT . Relative gene expression (fold change) was calculated using the comparative 2−ΔΔCt method [TRU5 and TIP4-1 as reference genes. Statistical analysis of the data obtained was performed using the t-test to determine the differences between the control and treated groups. Results are presented as mean ± SE of four independent experiments.Two-way analysis of variance (ANOVA) was used to analyze the effects of genotype, water treatment (WW and WD), and their interactions on the accumulation of stress metabolites in grapevine leaves. A post-hoc Tukey-HSD test was used to separate the means. The significance of differences in biochemical and transcriptomic analyses between the genotype under treatment and the corresponding control was determined using the t method  with TRUVitis vinifera L. genotypes exposed to water withholding for nine days. Prompt metabolite accumulation was observed for ABA, SA and proline, of which ABA had the strongest and earliest signals. Parallel with up-regulation of NCED1 gene, ABA proved to be a reliable marker for early detection of water deficit in grapevines. Among metabolites, only lipid peroxidation (MDA) had lower values and a delayed response under water deficit which points out significance in prompt adjustment of water and stomatal conductance, cellular osmosis, and antioxidant activity during first days of water deficit in grapevines. Metabolite changes in this study were driven by water regime with a significant impact of genotype. However, additional and combined physiological studies are necessary to obtain a broader picture on genotype adaptation to water deficit.The data present evidence on the dynamic response of five


Triple-negative breast cancer (TNBC) is the most heterogenous and aggressive subtype of breast cancer. Chemotherapy remains the standard treatment option for patients with TNBC owing to the unavailability of acceptable targets and biomarkers in clinical practice. Novel biomarkers and targets for patient stratification and treatment of TNBC are urgently needed. It has been reported that the overexpression of DNA damage-inducible transcript 4 gene (DDIT4) is associated with resistance to neoadjuvant chemotherapy and poor prognosis in patients with TNBC. In this study, we aimed to identify novel biomarkers and therapeutic targets using RNA sequencing (RNA-seq) and data mining using data from public databases.RNA sequencing (RNA-Seq) was performed to detect the different gene expression patterns in the human TNBC cell line HS578T treated with docetaxel or doxorubicin. Sequencing data were further analyzed by the R package “edgeR” and “clusterProfiler” to identify the profile of differentially expressed genes (DEGs) and annotate gene functions. The prognostic and predictive value of DDIT4 expression in patients with TNBC was further validated by published online data resources, including TIMER, UALCAN, Kaplan–Meier plotter, and LinkedOmics, and GeneMANIA and GSCALite were used to investigate the functional networks and hub genes related to DDIT4, respectively.Through the integrative analyses of RNA-Seq data and public datasets, we observed the overexpression of DDIT4 in TNBC tissues and found that patients with DDIT4 overexpression showed poor survival outcomes. Notably, immune infiltration analysis showed that the levels of DDIT4 expression correlated negatively with the abundance of tumor-infiltrating immune cells and immune biomarker expression, but correlated positively with immune checkpoint molecules. Furthermore, DDIT4 and its hub genes  involved in the activation of apoptosis, cell cycle, and EMT pathways. Eventually, we found ADM, ENO1, PLOD1, and CEBPB showed poor overall survival in BC patients.In this study, we found that DDIT4 expression is associated with the progression, therapeutic efficacy, and immune microenvironment of patients with TNBC, and DDIT4 would be as a potential prognostic biomarker and therapeutic target. These findings will help to identify potential molecular targets and improve therapeutic strategies against TNBC. Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer. It is characterized by the absence of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2  expression and accounts for 10–20% of all breast cancers .. paclitaxel alone among patients with TNBC, despite no concern of safety and tolerability with longer follow-up [In the past decade, Lehmann et al. identified six molecular subtypes of TNBC (TNBC type-6) based on the mRNA expression profiles , namely ollow-up . The parTP53 pathogenic mutations were detected in primary and metastatic TNBC, respectively. Remarkably, the amplification of MYC, PIK3CA, KRAS, BRAF, EGFR, CCNE1, and MDM2 and mutations of CDKN2A/B and PTEN are frequently detected in TNBC, which indicates that the co-activation of intrinsically oncogenic signaling networks predominantly drives the evolution of this disease [Indeed, driver alterations have been recognized to be more streamlined and heterogenous, and over 80 to 90% of  disease , 13. In  disease , 15. In  disease , 17.DDIT4 gene located in chromosome 10 (10q22.1) is 2.1 kb in length, containing three exons and two introns [However, the usage of the current classification system for TNBC is less useful in routine clinical practice owing to the complex technology requirements of the platform and low affordability. Therefore, novel biomarkers need to be identified to stratify patients with TNBC for targeting therapy, immunotherapy, or combined chemotherapy. Reportedly, the abrogation of metabolic activity triggered by the aberrant activation of the PI3K/AKT/mTOR pathway in cancer cells may result in the deregulation of genes involved in DNA damage and immune response, including DNA damage inducible transcript 4 (DDIT4). The  introns . DDIT4 p introns , 20. Con introns , 21. Mecme 10 10q.1 is 2.1 introns , breast  introns , lung ca introns , and bla introns , which s introns . In this2. The HS578T cells were seeded in 6-well culture plates at 2.5 × 105 cells/well and were treated with 2 μM docetaxel or doxorubicin for 24 h.Docetaxel and doxorubicin were purchased from Sigma . Human TNBC HS578T cells were purchased from the American Type Culture Collection . Cells were cultured in RPMI-DMEM  with 10% fetal bovine serum (FBS), 1% penicillin, and 1% streptomycin at 37 °C with 5% CORNA was isolated and purified using TRIzol  in accordance with the manufacturer’s protocol. RNA purity was assessed using the NanoPhotometer® spectrophotometer . One microgram of RNA per sample was used as the input for RNA sample preparation. Sequencing libraries were generated using the NEBNext® UltraTM RNA Library Prep Kit for Illumina®  in accordance with the manufacturer’s instructions, and index codes were added to attribute sequences to each sample. Briefly, mRNA was purified from total RNA using poly-T oligo-attached magnetic beads. Fragmentation was conducted using divalent cations at an elevated temperature in NEBNext first-strand synthesis reaction buffer (5X). The first-strand cDNA was synthesized using a random hexamer primer and M-MuLV reverse transcriptase (RNase H-). The second-strand cDNA synthesis was subsequently performed using DNA polymerase I and RNase H. The remaining overhangs were converted into blunt ends using exonuclease/polymerase. After the adenylation of the 3′ ends of DNA fragments, NEBNext Adaptor with a hairpin loop structure was ligated to prepare the samples for hybridization. To select cDNA fragments, preferentially spanning 250 ~ 300 bp, the library fragments were purified using the AMPure XP system . Following this, 3 µL of USER Enzyme  was added with size-selected, adaptor-ligated cDNA at 37 °C for 15 min, followed by treatment for 5 min at 95 °C before PCR. PCR was performed using Phusion high-fidelity DNA polymerase, universal PCR primers, and Index (X) primer. The PCR products were purified (AMPure XP system), and the library quality was assessed on the Agilent Bioanalyzer 2100 system.Finally, the clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumina) according to the manufacturer’s instructions. Following this, the library preparations were sequenced on an Illumina NovaSeq platform by Shanghai Genechem Co., Ltd. .Raw data (raw reads) in the fastq format were first processed using in-house perl scripts. In this step, clean data (clean reads) were obtained by removing reads containing adapter or ploy-N. Concurrently, the Q20, Q30, and GC contents were calculated from the clean data. The downstream analyses were based on clean data with high quality.https://www.ncbi.nlm.nih). In this study, the GSE62931 dataset included data from 53 TNBC and 53 non-TNBC (ER + /PR +) samples.The GEO database is a high-throughput microarray and sequence functional genomic database . The P value less than 0.05 were considered significantly enriched by the differentially expressed genes. KEGG is a database resource for understanding the high-level functions and utilities of the biological system, such as the cell, organism, and ecosystem, from molecule-level information, especially large-scale molecular datasets generated via genome sequencing and other high-through put experimental technologies (http://www.genome.jp/kegg/). We used the clusterProfiler R package to test the statistical enrichment of differentially expressed genes in KEGG pathways.Gene Ontology (GO) enrichment analysis of differentially expressed genes was implemented using the clusterProfiler R package , in whicP < 0.05 was regarded as an indicator of statistically significant results.The UALCAN platform is an online portal based on The Cancer Genome Atlas (TCGA) that allows users to conduct comprehensive analysis of gene expression . We detehttps://www.kmplot.com) is a database that can be used to investigate the associations between key genes and prognosis for breast cancer, ovarian cancer, lung cancer, and gastric cancer [The Kaplan–Meier plotter (c cancer . Accordihttps://cistrome.shinyapps.io/timer/) database [p < 0.05 as the cutoff for statistical significance.The TIMER database was used to estimate the number of tumor-infiltrating immune cells (TIICs) in different cancer types using samples from the TCGA . FPKM data were further converted into TPM data for correlation analysis between the expression of DDIT4 and immune checkpoint-related genes of interest. Analyses were conducted using R v3.6.3 and the software packages ggplot2 and heatmap. In all, the expression patterns of ten immune checkpoint-related genes were evaluated using Spearman correlation, and p < 0.05 was considered significant.Breast cancer RNA-seq-based gene expression data  were obtained from TCGA (http://www.linkedomics.org) hosts multi-omics data and clinical data from 32 different cancer types and 11,158 individuals obtained from the TCGA project [P < 0.05 was considered statistically significant.LinkedOmics (https://www.genemania.org) was used to predict protein–protein interaction (PPI) networks and the potential function of DDIT4 [GeneMANIA  were used. To identify the potential genes related to sensitivity to docetaxel and doxorubicin in TNBC, we first performed differential expression analysis using the RNA-seq data of HS578T cells treated with docetaxel or doxorubicin. The results showed the presence of 3902 DEGs in docetaxel-treated HS578T cells Fig. A, of whiTo explore the underlying biological function and signaling pathways, functional enrichment analysis for these DEGs was performed as previously described. Specifically, the BP group genes were enriched in anatomical structure development, movement of cell or subcellular component, cell motility, and localization of cell. In addition, the CC group genes were primarily related to extracellular region, plasma membrane, membrane, and cell periphery. The MF group genes were primarily enriched in ion binding, nucleic acid binding transcription factor activity, translation factor activity, RNA binding, and protein transporter activity Fig. C. The KEConcurrently, 8727 DEGs were identified in doxorubicin-treated HS578T cells . Further, DDIT4 overexpression was associated with worse OS (HR = 1.34 (1.11–1.62), p < 0.01), PPS (HR = 1.43 (1.13–1.8), p < 0.01), DMFS (HR = 1.3 (1.12–1.52), p < 0.001), and RFS (HR = 1.5 (1.35–1.66), p < 0.001) in breast cancer. Overall, the findings imply that the mRNA expression of DDIT4 was significantly correlated with the poor prognosis of patients with breast cancer and TNBC.To determine the role of DDIT4 in TNBC, we first evaluated its expression levels and diagnostic and prognostic value in patients with TNBC. TIMER data revealed that the mRNA expression of DDIT4 was significantly higher in breast cancer tissues than in normal tissues Fig. . Followip < 0.05), CD8+ T cells , and CD4+ T cells . No significant association was observed between tumor purity and the infiltration of macrophages, neutrophils, and dendritic cells. We also analyzed the correlation between the DDIT4 transcription level and immune cell infiltration in breast cancer. The level of DDIT4 expression correlated positively with the infiltration of CD4+ T cells , neutrophils , and dendritic cells  and negatively with tumor purity  , ENO1 , PLOD1 , and CEBPB  were considered as hub genes; the expression of these genes was strongly associated with DDIT4 expression in breast cancer.To gain additional insights into the biological significance of DDIT4, we investigated the potential role of DDIT4 in breast cancer by analyzing the mRNA sequencing data of 1093 patients with breast cancer, obtained from the TCGA database, using the LinkFinder module in LinkedOmics. As shown in Fig. To further explore the function of DDIT4 and its hub genes in greater detail, we constructed PPI networks using the GeneMANIA tools. DDIT4 and its hub genes showed interactions with 20 genes Fig. A. GO anaFurthermore, we demonstrated that DDIT4 and its hub genes participate in the activation of the apoptosis, cell cycle, and EMT pathways Fig. . FinallyChemotherapy remains the standard treatment for TNBC. However, in recent years, immune checkpoint inhibitors (ICIs) have exhibited a sustained clinical response in various tumor types, including breast cancer . AlthougIn this study, we performed the RNA-seq of docetaxel- and doxorubicin-treated TNBC cells and sought to explore new genes that potentially contribute to the regulation of chemoresistance and immune response in TNBC. Based on the comparison of data from GO and KEGG analyses and DEG enrichment between the drug-treated and control TNBC cell groups, we found that several cellular process and networks were enriched in the docetaxel- and doxorubicin-treated TNBC cells, including cell motility, cellular metabolic process, collagen-containing extracellular matrix, mTOR signaling pathway, p53 signaling pathway, oxidative phosphorylation, and PI3K − Akt signaling pathway Figs. . NotablyIn the present study, the overexpression of DDIT4 was detected in approximately half of the pan-cancer datasets in the TIMER database Fig. , and theTo obtain further insights into the impact of DDIT4 overexpression on the immune microenvironment, we further analyzed the correlation of DDIT4 expression with the infiltration of immune cells in TNBC from the data published in the TIMER database. According to the analysis of data from TIMER, the abnormal expression of DDIT4 may alter the tumor microenvironment and immune response, which can significantly affect clinical outcomes. We confirmed that the overexpression of DDIT4 was associated with decreased immune cell infiltration in TNBC Fig. . AlthougADM, ENO1, PLOD1, and CEBPB. The PPI network of these genes are enriched in processes and pathways related to chemokine activity, cell cycle regulation, and PPAR signaling (Fig. We also identified several genes showing significant expression correlation with DDIT4, including ing Fig. . SimilarAutophagy is an important survival mechanism that allows cells to adapt their demands to poor growth environments and maintain cellular homeostasis . EvidencThis study had several limitations. First, the research was based solely on transcriptomic and bioinformatic analysis, and the potential biological mechanism needs further investigation and application to other types of cancers. Second, we intend to further investigate the protein expression level of DDIT4 and its role in the pathogenesis and progression of TNBC.To summarize, we demonstrated a potential association between DDIT4 gene expression and the immunosuppressive microenvironment in TNBC. Results from this study can help identify potential biomarkers and targets for overcoming drug resistance and facilitating the clinical management of TNBC.


Pancreatic ductal adenocarcinoma (PDAC) is a devastating cancer, and the therapy options for PDAC remain restricted. The distinctive tumor immunological microenvironment (TIME) of PDAC, comprising a high number of stromal cells and a limited infiltration of cytotoxic T lymphocytes (CTLs), rendered immunotherapy ineffective. The protein level of ubiquitin-specific protease 43 (USP43) was a prognostic predictor in numerous cancers; however, its function in PDAC is limited. This article focuses on the influence of USP43 expression on PDAC prognosis and TIME alteration.  Based on TCGA database and tissue microarray staining, the expression of USP43 in PDAC was evaluated. The association between USP43 and prognosis was then investigated using tissue samples and online databases. In PDAC tumor tissues, the correlation between USP43 expression and clinicopathological characteristics, immune cell infiltration, and prognosis was investigated. The expression of USP43 in PDAC cell lines was evaluated using quantitative polymerase chain reaction. Using a cell counting kit-8 (CCK-8) and a cell colony formation test, the viability of the cells was determined. On the basis of online databases and tissue samples, the link between USP43 and immune cell infiltration around PDAC was also examined. For statistical analyses, the software GraphPad, R, and SPSS 26.0 were utilized. P < 0.001). High USP43 expression was associated with poor overall survival in both the TCGA database and the tissue microarray of PDAC patients . USP43 overexpression promoted PANC-1 cell proliferation (P = 0.0018), but USP43 knockdown decreased PANC02 cell proliferation (P < 0.001). According to the TCGA database, USP43 is associated with T cell activation and inhibits CD8+ T cell activation in PDAC, as proven by a study of cell lines. Moreover, in both TCGA and PDAC cell lines, USP43 expression was negatively linked with the chemokine signaling pathway.  The expression of USP43 was considerably higher in PDAC compared to normal pancreatic tissue in both the TCGA database and the tissue microarrays of PDAC patients (+ T cell enrichment, and the cytokine signal pathway. Future multicenter studies are needed to confirm our findings and their potential application in the treatment of PDAC patients. Overexpression of USP43 is a potential prognostic indicator for PDAC patients. USP43 is a potential biomarker associated with T cell activation, suppression of CD8 Pancreatic ductal adenocarcinoma (PDAC) is a fatal illness that accounts for ∼90% of pancreatic adenocarcinoma and has a 5-year survival rate of 10% . PDAC isPDAC has a distinct tumor immune microenvironment (TIME) with up to 80% nontumor stroma that includes extracellular matrix proteins  and stromal cells , endothelial cells) –11. ThesMost proteins undergo acetylation, methylation, phosphorylation, glycosylation, sumoylation, or ubiquitination after synthesis. One of these alterations is ubiquitination, which enables a small molecule of ubiquitin to attach to lysine residues of target proteins; dysregulation of ubiquitination may contribute to the development of malignancies , 17. UbiIn this study, we will investigate the expression of USP43 in PDAC and the relationship between USP43 and patient survival, as well as the effect of USP43 expression on TIME and the likely pathways involved in tumorigenesis and progression.This study included a total of 38 PDAC patients treated at the First Affiliated Hospital of Dalian Medical University from June 2019 to December 2021. Participants in this trial had R0 pancreaticoduodenectomy, and all tumor tissues were pathologically confirmed to be PDAC without any prior neoadjuvant therapy. The following clinicopathological characteristics were analyzed: age, gender, T and N stages (according to the 8th edition of the TNM staging system), stage (according to the 2022 version of the NCCN guideline), grade, surrounding organ infiltration, and surrounding fat infiltration. Four plasma tumor indicators, CA19-9, CA125, CEA, and AFP, were investigated. Before enrolment, all patients signed written consents based on their knowledge of the study's nature. The median age of the patients was 64 years old, and overall survival (OS) ranged from 6 to 39 months.https://xenabrowser.net/datapages/, accessed December 16, 2022) including TCGA (The Cancer Genome Atlas) and GTEx (Genotype-Tissue Expression). In total, 183 samples of PAAD tissues from TCGA, and 167 samples of normal pancreatic tissues from the GTEx dataset were included in this study.The expression levels of USP43 in various types of cancers were analyzed with the online database . USP43 primary antibody  was used in staining. Then, stained samples were analyzed using standard light microscopy.Thirty-eight PDAC patients' tumor tissues and normal tissues were provided by Dalian Medical University's First Affiliated Hospital in accordance with Dalian's ethics committee for human research (registration number is PJ-KS-KY-2021-203) and the patient's written consent was taken. The newly dissected tissue (about 3 mm thick) was preserved with 4% paraformaldehyde at room temperature overnight. Afterward, the tissue was washed with running tap water for 5 min before being dehydrated with 75% alcohol, 85% alcohol, and 95% alcohol for 5 min each, followed by three times with 100% alcohol for 5 min each. The tissue was cleared in xylene twice for 5 min each time and then immersed in paraffin three times for 5 min each time. The paraffin-embedded tissue was sectioned on a microtome at 5–8 Each sample was examined twice by two pathologists who were blinded to the experiment. The expression of USP43 was thus evaluated as follows: the intensity of staining was scored as 0 (negative), 1 (weak), 2 (moderate), and 3 (strong), and the proportions of positive cells were categorized as 0 (<5%), 1 (5%–<25%), 2 (25%–<50%), 3 (50%–<75%), and 4 (75%–100%). The multiplication for intensity and proportion was used to evaluate the level of USP43 expression. ImageJ (version 1.52) was used for the analysis and the cutoff value of USP43 was 2.75. A score <2.75 was defined as low expression, while a score >2.75 was defined as high expression.Using the same method, each section was stained with different immune cell markers as follows: CD4  for helper T lymphocytes (Th cells), CD8  for cytotoxic T lymphocytes (CTLs), CD68  for macrophage, CD163  for M2-polarized macrophages, FOXP3  for Tregs. We selected six areas with abundant immune cell infiltration at a high-power field (HFP) (400x), and counted positive cells number in each field, and calculated the average count per HFP.2 at 37°C in Dulbecco's modified Eagle's medium  containing 10% fetal bovine serum  and 1% penicillin–streptomycin .Human pancreatic cancer cell lines  and HEK293T cell line were purchased from Cell Bank of Chinese Academy of Sciences . Murine pancreatic cancer cell line (PANC02) was purchased from BeNa Culture Collection . Cells were cultured in a humidified incubator with 5% COμg of lentiviral shRNA or USP43 plasmid , 3 μg of viral packaging plasmid pPAX2, and 1 μg of envelope plasmid pMD2.G to produce lentivirus. Transfection was performed with LipoFiter Liposomal Transfection Reagent  and Opti-MEM . During the first 24 hr after infection, no FBS was added to DMEM. We then changed the growth medium with DMEM containing 10% FBS and cultured HEK293T cells for another 24 hr. The virus was collected after being filtered via 0.45 μm filters. When the cancer cells  covered 70%–80% of the dishes, they were infected with the virus in the presence of polybrene , and 48 hr after infection, the cells were chosen with 0.5 μg/ml puromycin . USP43 overexpression system was constructed in PANC-1 cells using Lentiviral . PANC02 cells were infected with pPLK/GFP + Puro-Usp43 shRNA using the same method .Lentiviral particles generated with a standardized protocol were used to produce the highly purified plasmids. Take 100 mm cell-culture dish as an example, HEK293T cells were transfected with 4 β-ACTIN/β-Actin levels concentrations. Sequences of primers are reported in Total RNA was extracted using RNAiso Plus . According to the manufacturer's instructions, cDNA was synthesized from mRNA using Hifair III 1st Strand cDNA Synthesis SuperMix for quantitative polymerase chain reaction (qPCR) . All samples mRNA expression were quantified using the Applied Biosystems® 7,500 Fast system  to determine the comparative CT and were normalized to μl of the abovementioned medium to every well and everyday. After 5–10 days, cell colony had formed and fixed with 4% paraformaldehyde  for 20 min and stained using crystal violet  for 5 min. Then, the pictures were taken under a digital camera and the cell colony formation rate was calculated.For cell colony formation assays, we utilized DMEM with 10% FBS and 1% penicillin–streptomycin, then we resuspended and counted the cells. Mix of 2 ml medium and 500 cells were added to one well of six-well plate. Repeat it three times for each cell line. We added 100 μl cell suspension containing 2,500 cells. The following day, 10 μl of CCK-8 solution  was added to the medium of the first two pairs of wells. Then, continue to culture them for 2 hr in the incubator. After the crystals were completely melted, the absorbance at OD 450 nm was measured to calculate cell proliferation. Each group was replicated three times, and each replication was monitored at four-time points.After cell lines were digested and centrifuged, they were resuspended, counted using a cell counting plate. Each well in a 96-well plate was filled with 100 χ2 test, and the Kaplan–Meier technique and log-rank test were used to compute and assess the survival analysis. The Cox proportional hazards model was used to conduct univariate and multivariate Cox regression analysis. Student's t-test (paired or unpaired) was used to compare two groups; one-way ANOVA was used to compare more than two groups. Bars and error represent mean ± standard deviations (SD) of replicate measurements. Using the web program Cutoff Finder [https://www.xiantao.love/), and SPSS 26.0 statistical tools were utilized for statistical analyses (IBM). P-values < 0.001 ( ∗∗∗), <0.01 ( ∗∗), or <0.05 ( ∗) were considered statistically significant.The clinical data were examined and compared using the f Finder , optimalP < 0.001, P = 0.046, HR = 1.76, P = 0.041, HR = 1.95, P = 0.02, HR = 1.83, Using the TCGA database, the expression of USP43 was studied in 33 types of cancer in order to compare the expression of USP43 between tumor and normal tissues. USP43 expression was higher in tumor tissues than in normal tissues in several types of tumors, including pancreatic adenocarcinoma (PAAD), rectum adenocarcinoma (READ), colon adenocarcinoma (COAD), cholangiocarcinoma (CHOL), stomach adenocarcinoma (STAD), and esophageal carcinoma (ESCA). The difference between PAAD tumor tissue and normal tissues is significant among these malignancies  and high CA19-9 level (P = 0.049) in tumor tissues, indicating that it may be a prognostic factor.To verify that the expression of USP43 significantly higher in tumor tissues, 38 PDAC tissues and 38 para-PDAC tissues were obtained from our hospital in this study. Interestingly, compared with normal tissue, the USP43 expression was significantly higher in tumor PDAC (P = 0.019), CA19-9 (P = 0.005), and CA125 (P = 0.046), were substantially linked with increasing risk of death in patients with PDAC (P = 0.014) and lymphocyte in plasma (P = 0.039) were strongly linked with a reduced risk of mortality. Then, we build a multivariate Cox regression model for variables that were significant in the univariate analysis and show that only USP43 expression and CA19-9 were independent survival predictors  based on USP43 expression by examining the TCGA database, and numerous cytokine genes were negatively correlated with USP43 . In addi+ T cells. IHC staining of other markers revealed no significant association (We examined the IHC stain of immune cell markers such as CD4, CD8, CD68, CD163, and FOXP3 in PDAC tissue to understand the immune-related function of the USP43 gene. The IHC results revealed that elevated USP43 expression was correlated negatively with CD8 expression . The higociation . We usedociation , with a ociation . This fiPatients with PDAC have a poor prognosis, highlighting the need to develop innovative therapeutic strategies for this aggressive illness . USPs arIn our study, we used the TCGA database and tissue microarrays of PDAC patients to assess the expression of USP43 in PDAC and para-PDAC/normal tissues. USP43 was shown to be overexpressed in PDAC tissues, and its high expression was related to decreased survival. High USP43 expression in tumor tissues was substantially associated with surrounding organ infiltration and elevated CA19-9 levels. Multiple Cox regression analysis also demonstrated that USP43 expression and CA19-9 level were independent predictive markers of PDAC, indicating that USP43 may be an essential adjunct in the diagnosis of PDAC. Experiments in vitro established that USP43 enhanced the proliferation of PDAC and that the overexpression or knockdown of USP43 promoted or inhibited the proliferation of PDAC, respectively. Therefore, elevated USP43 expression in PDAC patients suggested a poorer prognosis. USP43 malfunction may be one of the variables that influence the evolution of PDAC. Despite the complexity and diversity of USP43's underlying processes in PDAC patients, it remains an essential gene in carcinogenesis and development.+ T cells was related to prolonged OS and RFS [+ T cells results in low immunogenicity of PDAC, which is regarded as a significant factor in the failure of checkpoint immunotherapy in PDAC [+ T cells may be able to predict the response of PDAC to ICIs treatment [+, CD4+, and CD8+ T cells were independently related to tumor recurrence, according to previous literature [+, CD4+, and CD8+ T cells predicted a favorable OS [+ T cells and NK cells can promote pyroptosis in cancer cells, and that pyroptosis of cancer cells might simultaneously trigger stronger anticancer immunity [+ T cells and NK cells, might predict an increase in OS in samples with overexpression of pyroptosis and iron-induced targets [+ T cell infiltration through IHC staining of tissue microarray and TCGA database. This also confirmed previous studies and further emphasized the anticancer effect of CD8+ T cell in PDAC.PDAC is characterized by a large number of stromal components and stromal cell infiltration which compose an immunosuppressive microenvironment. TIME of PDAC typically lacks of intratumor effector lymphocytes and results in a weak response to immunotherapy , 32, 33. and RFS –37. Poor in PDAC . Thus, treatment . On the terature , 41. Onerable OS . It has immunity –44. Simi targets . In thisMany studies have shown that CAFs possess the ability of promoting tumor proliferation and metastasis by secreting various cytokines , 47. TheIn this research, we did not verify the relationship between USP43 expression and immune cells in vivo. In a more ideal situation, tumor cells should be implanted in mice. Second, the lack of clinical cases decreased the statistical power. Finally, the findings reported here need to be validated in further biological experiments.In conclusion, our research indicates that the deubiquitinate function of USP43 may serve as a possible prognostic marker for PDAC. In addition, we discuss the possible role of USP43 in the development of TIME in PDAC. The transformation of a “cold tumor” into a “hot tumor” makes ICIs for PDAC conceivable , 49. The


Dendritic cells (DCs), central participants in the allergic immune response, can capture and present allergens leading to allergic inflammation in the immunopathogenesis of allergic rhinitis (AR). In addition to initiating antigen-specific immune responses, DCs induce tolerance and modulate immune homeostasis. As a special type of DCs, tolerogenic DCs (tolDCs) achieve immune tolerance mainly by suppressing effector T cell responses and inducing regulatory T cells (Tregs). TolDCs suppress allergic inflammation by modulating immune tolerance, thereby reducing symptoms of AR. Activation of the TLR4/IRAK4/NF-κB signaling pathway contributes to the release of inflammatory cytokines, and inhibitors of this signaling pathway induce the production of tolDCs to alleviate allergic inflammatory responses. This review focuses on the relationship between tolDCs and TLR4/IRAK4/NF-κB signaling pathway with AR. WhethDCs play an integral role in the pathogenesis and treatment of allergic rhinitis (AR). DCs recognize pathogen-associated molecular patterns (PAMPs) or lipopolysaccharide (LPS) through Toll-like receptor 4 (TLR4) expressed on their membrane to trigger signaling cascades , 6, 8. T2DCs can be categorized into conventional DCs (cDCs) and plasmacytoid DCs (pDCs) according to their morphological features and function , 11. pCDBoth pDCs and cDCs play important roles in immune regulation. The regulatory function of DCs depends on their activation state, which might impact their ability to induce immunity or tolerance , 16. TheIn addition to participating in the immune response, DCs are important modulators of central and peripheral tolerance . The ina3TolDCs are generally regarded as a type of steady-state semi-mature DCs, including most imDCs and some cells with advanced maturation states , 33, 34.TolDCs promote tolerance by facilitating the induction and expansion of different subsets of regulatory lymphocytes . They ca+ DCs, which produce TGFβ and retinoic acid, can induce the differentiation of naïve T cells into Tregs and Tr1 cells, thus further regulating the function of tolDCs  . IL-10 cf tolDCs . Heme oxf tolDCs . Vitaminf tolDCs Figure 2f tolDCs . Becausef tolDCs , 24.4TLRs are 1 class of transmembrane proteins synthesized in the endoplasmic reticulum , 53. TLR5DCs are one of the most important immune cells that express TLR4 . There aLPS primarily signals through TLR4 and thus may be involved in MyD88, IRAK4 and NF-κB signaling. As a cell wall component of all Gram-negative bacteria, LPS largely contributes to the induction of tolDCs by upregulating anti-inflammatory cytokines such as IL-10 and TGF-β , 75, 76.NF-κB can be activated through canonical and non-canonical signaling pathways . Activat6DCs trigger allergic inflammation or contribute to immune tolerance to sensitizing allergens at different maturation stages, locations, and environments . The natin vivo, and they found that induced such tolDCs increased the number of Tregs in the lungs of ovalbumin-induced asthmatic mice, which could help to attenuate the Th2-mediated allergic immune response and treat allergic asthma. It is worth noting that the dosages of LPS need to be strictly controlled when inducing tolDCs, because the maturation of DCs by LPS is highly dose-dependent and also depends on the type of LPS used. Higher dosages induce an inflammatory DC phenotype rather than a tolerogenic one. Hong et al. (TolDCs are beneficial in suppressing allergic inflammation and relieving allergic symptoms in AR, and may be a potential therapeutic target for AR. Suppression of allergic immune responses by tolDCs inducing allergen-specific blocking antibodies, immunosuppressive cytokines, Tregs, and Bregs is an alternative way to treat AR . Inductig et al.  modulateg et al.  demonstrg et al.  showed tg et al.  showed tg et al. . All the7With abundant leucine repeats, TLRs regulate Th1/Th2 immune balance through DCs, mast cells and Tregs , 60. Thein vivo, and its activity is a prerequisite for the establishment of an innate immune response, the loss of which will lead to exacerbation of the infection (IRAK4, a serine/threonine kinase, is an intermediate in the TLR4/NF-κB signaling pathway that transduces signals from TLR4 by bridging MyD88 , 97. IRAnfection . Korppi nfection  showed tnfection  showed tnfection . Becausenfection , 103. Denfection . ActivatNF-κB was originally thought to be a transcription factor that regulates immunoglobulin gene expression, and its optimal function may be to regulate the development and activation of the immune system . FurtherMultiple drugs can treat AR via TLR4/IRAK4/NF-κB signaling pathway. Wu et al.  showed t8The immune response of DCs in AR towards immunity or tolerance is essential for the treatment of AR. We can induce DCs with tolerance function on demand, and inducing tolDCs to act on specific targets is expected to be a scalable immunotherapy for AR. Knocking down the expression of costimulatory molecules and MHC class II with inhibitors of the TLR4/IRAK4/NF-κB signaling pathway to induce tolDCs is a feasible approach. NF-κB inhibitors that induce tolDCs are already in clinical trials . We can Despite the great potential of tolDCs-based immunotherapies, the mechanism of their immunomodulatory activity is unclear , and furIn conclusion, the potential of tolDCs applied to the treatment of AR is enormous.CK: Writing – original draft. XL: Writing – original draft. PL: Writing – review & editing. YL: Writing – review & editing. YN: Writing – review & editing. XZ: Writing – review & editing. HZ: Supervision, Writing – review & editing. JL: Funding acquisition, Supervision, Writing – review & editing. SQ: Supervision, Writing – review & editing.


IQ M = 108.5; SD = 13.5) were randomized to 14 weeks of adapted acceptance and commitment therapy group treatment (NeuroACT) or treatment as usual. The intervention was feasible. Perceived stress and quality of life (primary outcomes), alongside psychological inflexibility, cognitive fusion, cognitive and behavioral avoidance, and autistic mannerism were statistically significantly improved in NeuroACT compared with treatment as usual (d = 0.70–0.90). Clinically significant changes in perceived stress and quality of life were in favor of NeuroACT. Between-group altered depression, anxiety, sleep problems, one quality of life measure, functional impairment, social aspects of autism, and executive difficulties were statistically non-significant. Dropout was slightly higher in NeuroACT. NeuroACT may be a promising treatment for autistic adults with co-existing stress and reduced quality of life. More extensive studies are warranted to evaluate NeuroACT further.Autistic adults are at risk of stress-related psychiatric disorders and reduced life quality due to social, cognitive, and perceptual challenges. Mental health interventions adapted to autistic adults are scarce. Acceptance and commitment therapy has preliminarily indicated health benefits in autistic adults, although it has not been robustly evaluated. Overall, 39 adults  with autism spectrum disorder and normal intellectual ability , while 19 autistic adults had ordinary care. The acceptance and commitment therapy group treatment program seemed logical and reasonable to the participants. Also, when comparing the participants in the NeuroACT group with those in the ordinary care group, the NeuroACT participants reported less stress and higher quality of life. Compared to the ordinary care group, they could also manage distressing thoughts better, perceived themselves as more flexible, and did not avoid stressful situations as much as before. However, there was no significant difference between the groups in depression, anxiety, sleep problems, social aspects of autism, everyday functioning, or executive challenges. Slightly more NeuroACT participants did not finish the treatment than ordinary care participants. In conclusion, the NeuroACT program may be a treatment for autistic adults who feel stressed and have reduced quality of life. More studies are needed to see how helpful the NeuroACT program is for autistic adults. Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by challenges in social interaction, repetitive and restricted behavior and interest, and sensory hyper- and hyposensitivity . ASD is Many autistic individuals cannot tolerate or have limited effects from pharmacological treatments intended to impact psychiatric symptoms . MoreoveAcceptance and commitment therapy (ACT) is a psychotherapy method within the CBT umbrella that combines mindfulness procedures and behavioral change techniques . ACT hasIn ACT, psychological flexibility is the ability to do what is essential to oneself while handling mental obstacles that would otherwise be in the way . PsycholInterventions based on ACT have been evaluated for parents of autistic children , autistiThe current pilot RCT study evaluated the feasibility and preliminary effectiveness of an ACT group protocol (NeuroACT) adapted for autistic adults in a psychiatric outpatient setting compared with treatment as usual (TAU). The research questions were as follows: (1) Is the study procedure and the NeuroACT protocol feasible ? (2) What are the effects of NeuroACT on perceived stress and quality of life (primary outcomes) compared with TAU? (3) What are the effects of NeuroACT on psychiatric symptoms  and functional impairment (secondary outcomes) compared with TAU? (4) What are the effects of NeuroACT on ACT-related variables ) compared with TAU? (5) How does NeuroACT affect the individual’s perception of his or her autistic core challenges, such as social motivation, social awareness, social cognition, communication, autistic mannerism , and executive difficulties (secondary outcomes), compared with TAU?M = 13.2, SD = 5.1 for pre-treatment and M = 17.0, SD = 4.8 for post-treatment, 0.05 significance level, and 0.8 statistical power). The calculation indicated the need for 30 participants in each treatment group  to reduce the risk of Type 2-error. However, due to organizational changes within the psychiatric clinic, the study was prematurely aborted, reaching a total of 39 participants.The study design was a randomized two-group controlled pilot trial with repeated measures evaluating the feasibility and preliminary effectiveness of NeuroACT compared with TAU for autistic adults. The pilot study design allowed for the inclusion of several outcome measures to cover different aspects of potential treatment benefits and to follow a broad spectrum of symptoms, correlates, and consequences of autism. Assessments were conducted at pre-treatment (T1), post-treatment (T2), and 6 months after treatment completion (T3). Power calculation was based on an open-trial pilot study on ACT for autistic adults  using thRandomization was conducted block-wise  and perfThe trial was approved by the regional ethics committee of Stockholm, Sweden (2015-1005-31) and followed the Declaration of Helsinki . All parDiagnostic and Statistical Manual of Mental Disorders  Asperger’s syndrome . The ACT group consisted of 20 participants , and the TAU group contained 19 participants .Participants were recruited at the Neuropsychiatric Unit Karolinska, Psychiatry Northwest, Stockholm City Council, Sweden, a clinic specialized in assessing and treating neurodevelopmental disorders in adults. Individuals who met the diagnostic criteria of ASD were invited to participate. Inclusion criteria were as follows: (a) a diagnosis of The diagnostic assessment followed local clinical guidelines and was based on multiple sources of information. First, a clinical interview was performed by a psychiatrist, followed by neuropsychological testing by a psychologist , or Wechsler Adult Intelligence Scale–Third Edition (WAIS-III)) , 1997, fhttp://www.brainproof.se or by contacting the corresponding author. The treatment program consists of training in ACT processes, psychoeducation on stress, emotions, and perception, and support for executive difficulties. Primary treatment objectives were to (1) facilitate participants’ motivation to behavior change and (2) train participants’ skills to cope with daily hassles and stressful situations to reduce behavioral avoidance. The treatment consisted of 14 weekly 150-min group sessions with 8–10 participants, led by two clinical psychologists with experience in ACT and autism (the first and fourth authors of this article). After each session, 30 min were added for questions or assistance with homework assignments. Each session had a similar format with a short mindfulness or acceptance exercise, followed by a review of homework assignments, an introduction to the theme of the particular session, and a review of new homework assignments and session evaluation. In-session activities and homework assignments consisted of pencil-and-paper exercises using adapted worksheets . In addition, mindfulness and acceptance were practiced at home five times per week using prerecorded adapted audio exercises. Before each exercise, a rationale for why to practice mindfulness or acceptance was provided. The central components and processes of each treatment session were explained using didactic presentations. In addition, psychoeducational information sheets were provided, such as about stress, emotions, or perception. Compared to the protocol used by The manualized treatment  was a modified version of the protocol evaluated in autistic adults within a psychiatric outpatient setting . The neuThe TAU group received ordinary care, such as communication training, psychoeducational programs, or psychotherapy, as part of their standard disability service or outpatient psychiatric care and obtained the NeuroACT treatment with a 1-year delay.r = 0.90), and WAIS’ full-scale IQ correlates highly with the Stanford–Binet IV test (r = 0.88)  was assessed using the WAIS-R  or the W = 0.88) .International Classification of Disease (ICD) psychiatric disorders. MINI has shown moderate concurrent validity with mood and anxiety disorders  , a strucisorders  with AUCisorders .Overall feasibility was calculated as a percentage of (1) treatment completion; (2) measurement fulfillment at T1, T2, and T3; (3) dropout rates between the NeuroACT group and the TAU group post randomization; (4) treatment credibility; and (5) any adverse events as reported in participants’ medical records, according to the CONSORT statement for randomized trials of nonpharmacological treatments .Treatment credibility was assessed using an ASD-adapted version of the Treatment Credibility Scale (TCS) . TCS connever to 4 = very often), with higher scores indicating more stress. A total score is calculated after reversing positive items’ scores and then summing up all scores. The PSS has shown good criterion validity with anxiety (r = 0.68), depression (r = 0.57), and mental or physical exhaustion (r = 0.71), and good internal consistency in a Swedish sample (Cronbach’s α = 0.84) (Perceived stress was assessed using the PSS 14 items (PSS-14) , a 14-it = 0.84) . The PSSr = 0.39)   and good = 0.39) . The QOL = 0.39) . In addir = 0.72) (Perceived depressive symptoms were assessed using the Beck Depression Inventory–II (BDI-II) , a 21-it = 0.72)  and inte = 0.72) . The BDIr = 0.84) have been reported (Perceived anxiety symptoms were assessed using the Beck Anxiety Inventory (BAI) , a 21-itreported . The BAIPerceived sleep problems were assessed using the Karolinska Sleep Questionnaire (KSQ) , a 6-poiPerceived functional impairment  was assessed using the Sheehan Disability Scale (SDS) , a threer = 0.80)  , a seven = 0.80) . In addir = −0.78) in a clinical sample (Perceived cognitive fusion was assessed using the Cognitive Fusion Questionnaire (CFQ-7) , a 7-itel sample . In addil sample  and in tPerceived cognitive and behavioral avoidance was assessed using the Cognitive–Behavioral Avoidance Scale (CBAS) , a 31-itTo assess the participants’ subjective perception of their autistic core challenges, we used the Social Responsiveness Scale (SRS) , a 65-itPerceived executive difficulties were assessed using the Dysexecutive Questionnaire (DEX-S), a 20-item 5-point Likert-type scale, with a higher score indicating more executive problems . The DEXt-tests for continuous variables and chi-square tests for categorical variables. An exploratory analysis was performed to assess the normal distribution and potential outliers, indicating normality for all measures except the BDI, the BAI, the KSQ—Breathing Index, and the KSQ—Fatigue Index. Outcome measures were analyzed using two-tailed mixed-design repeated-measures analyses of variance (rmANOVA). Group (NeuroACT/TAU) was the between-subjects factor and time  was the within-subjects factor. Calculations of the outcome measures were performed on treatment completers. Contrast analyses were performed from pre (T1)- to post (T2)-intervention and from post- to six-month follow-up (T3). Kruskal–Wallis and Wilcoxon Signed-rank tests were used for non-normal distributed samples. The interpretations of Cronbach’s alpha were α ⩾ 0.70 = satisfactory, α ⩾ 0.80 = good, and α ⩾ 0.90 = satisfactory, where a too low or high alpha value may indicate insufficient reliability     and the D = 6.9)  along wiSD = 13.5). The NeuroACT group had an IQ score of 107.0 (SD = 13.8), and the TAU group’s IQ score was 109.6 (SD = 13.9). The distribution of participant characteristics  is shown in A slight majority of participants were male (54%). Most had comorbid disorders , depression, or dysthymia) and used pharmacological treatment . The mean overall IQ score was 108.5  were considered candidates and invited to the study. All 39 invited participants chose to participate. However, 17 of 20 participants (85%) completed the treatment. Meanwhile, 34 of 39 (87%) completed all assessments at T1, T2, and T3. Dropout rates were slightly higher in the NeuroACT group (20%) compared with the TAU group (5%) post randomization, and no adverse events were reported. Two participants were included who had a lower score  on the PSS than the inclusion cut-off (PSS > 24) but instead met the inclusion criteria on QOLI. Five participants were included who had a higher score (1.9–2.9) in the QOLI than the inclusion cut-off (QOLI < 1.84) but instead met inclusion criteria on PSS.M = 7.3, SD = 2.5) using the TCS (SD = 2.5) on Item 1 (how apprehensible the treatment seemed to the participants); 6.3 (SD = 3.2) on Item 2  on Item 3 (how confident they would be in recommending this kind of group to a friend with ASD); 8.0 (SD = 2.7) on Item 4 (how successful the participants thought that the treatment would be for other diagnoses); and 6.4 (SD = 3.1) on Item 5 (how much improvement they expected to become with this treatment).Treatment credibility (max score = 10) was rated as high ( the TCS . The meaAs presented in detail in As shown in As shown in As shown in As shown in d = 1.02–1.24). Significant improvements occurred from T1 to T2, except in AM, where changes were observed from T2 to T3, and quality of life, where changes were equally distributed between T1 and T2 compared with T2 and T3. Improvements from T1 to T2 were maintained or further ameliorated to T3. The results suggest that NeuroACT is a promising treatment for autistic adults with co-existing stress and reduced quality of life and that more extensive evaluations are warranted.The current randomized controlled pilot study evaluated the feasibility and preliminary effectiveness of an adapted NeuroACT for autistic adults in a psychiatric outpatient setting. Results indicated overall good treatment feasibility, where most participants completed the treatment alongside high treatment credibility ratings and satisfactory measurement fulfillment. Analyses of effects showed statistically significantly improved primary outcomes of perceived stress and quality of life, with moderate to large effect sizes, in the NeuroACT group compared with the TAU group. In the secondary outcomes, reduced psychological inflexibility, cognitive fusion, cognitive and behavioral avoidance, and AM were statistically significant, with moderate to large effect sizes, in the NeuroACT group compared with the TAU group. Moreover, clinically significant changes in perceived stress and quality of life were observed in favor of the NeuroACT group compared with the TAU group. However, no statistically significant differences were observed between the two groups in depressive symptoms, anxiety, sleep problems, the second quality of life measure, functional impairment, social aspects of autism, or executive difficulties. Furthermore, dropout rates were slightly higher in the NeuroACT group compared with the TAU group. Where significant changes were found, the largest effect sizes were noticed in perceived stress, cognitive and behavioral avoidance, and cognitive fusion (Cohen’s To our knowledge, this is the first RCT to indicate that autistic adults with high perceived stress and reduced quality of life could benefit from ACT. The improvements in several outcomes are in line with research on CBT and mindfulness practice for autistic adults, suggesting that psychological treatments could positively influence mental health and improve quality of life . ACT forThe overall significant interaction effect of the SWLS but not the QOLI, both measuring quality of life, may be associated with the more durable sub-areas of the QOLI, such as economic status, neighborhood well-being, and family-related concerns. The SWLS measures subjective quality of life and overall well-being, potentially reflecting a more general sense of meaning and purpose than the QOLI. Replication studies and prolonged follow-up might further evaluate the eventual effects of using these instruments in autistic adults.While no statistically significant changes were observed in social aspects of autism, such as social cognition, social awareness, or communication, significant improvements were found in AM, related to cognitive and behavioral inflexibility. The finding is in line with research on modified CBT for autistic individuals, which has observed changes in the SRS subscales of social motivation and AM but not overall social functioning . Also, tMoreover, in ACT for autistic individuals, the goal is not to “treat autism,” but to alleviate some core challenges that are thought to be exacerbated by mental health problems. ACT aims to change how the individual perceives his or her autistic functioning. By doing this, the individual may be able to act more flexibly in the presence of autism. Consequently, the observed changes in one subscale of the self-rated version of the SRS, as a result of the intervention, may reflect an altered perception but not necessarily an actual change in autistic core difficulties. Future studies may further evaluate these two treatment approaches in autistic individuals; social skills training, developing skills to handle thoughts and emotions, or a combination of both.Although promising, the current study has limitations. First, a small sample size reduces statistical power and increases the risk of type 2 error. Second, there might be a risk of type 1 error regarding the statistically significant efficacy measures due to the vast number of measures included, increasing the risk of a multiple testing effect. However, several outcome measures’ changes align with previous research, suggesting that the results do not depend just on chance. Third, the outcome measures relied on participant’s self-report, and no objective or independent criteria were used, increasing the risk of over- or underestimating individual progress. Fourth, the study was conducted within a psychiatric outpatient clinic, so the generalizability outside this setting may be limited. Fifth, the study design did not control for group effects. Therefore, changes observed may not be entirely due to ACT but an effect of the intervention’s group setting. Sixth, the participants included in the study all had average or above-average intellectual capacity, so generalization of the results to autistic adults with lower intellectual capacity cannot be made.Overall, this study results indicate that the NeuroACT program may be a feasible and beneficial treatment for autistic adults with comorbid stress and reduced quality of life. However, for future research, to increase the integrity of the results, large-scale studies with blinded assessments, control of treatment adherence, and group aspects of the intervention, alongside qualitative feedback from participants, are needed to explore the potential benefits of NeuroACT in autistic adults further. In addition, evaluating the effect of potential mediators and moderators of change, such as sex, cognitive profile, psychological inflexibility, behavioral avoidance, or adherence to homework assignments, is warranted.


Resilience can be viewed as trajectory of stable good mental health or the quick recovery of mental health during or after stressor exposure. Resilience factors (RFs) are psychological resources that buffer the potentially negative effects of stress on mental health. A problem of resilience research is the large number of conceptually overlapping RFs complicating their understanding. The current study sheds light on the interrelations of RFs in the face of the COVID-19 pandemic as a use case for major disruptions. The non-preregistered prospective study assessed a sample of 1275 German-speaking people from February 2020 to March 2021 at seven timepoints. We measured coping, hardiness, control beliefs, optimism, self-efficacy, sense of coherence (SOC), sense of mastery, social support and dispositional resilience as RFs in February 2020, and mental health  at all timepoints. Analyses used partial correlation network models and latent growth mixture modeling (LGMM). Pre-pandemic RFs were strongly interrelated, with SOC being the most central node. The strongest associations emerged between coping using emotional support and social support, SOC and sense of mastery, and dispositional resilience and self-efficacy. SOC and active coping were negatively linked. When we examined RFs as predictors of mental health trajectories, SOC was the strongest predictor of psychopathological symptoms and rumination, while trajectories of stress-related growth were predicted by optimism. Subsequent network analyses, including individual intercepts and slopes from LGMM, showed that RFs had small to moderate associations with intercepts but were unrelated to slopes. Our findings provide evidence for SOC playing an important role in mental distress and suggest further examining SOC’s incremental validity. However, our results also propose that RFs might be more important for stable levels of mental health than for adaptation processes over time. The differential associations for negative and positive outcomes support the use of multidimensional outcomes in resilience research. Resilience can be viewed as stable good mental health or fast recovery of mental health during or after stressor exposure , 2. AccoFor instance, control beliefs  are closResearch on the overlap and incremental validity of single RFs is not new , and manHere we set out to use network analyses to shed light on overlapping and most likely interrelated RFs . NetworkBeing the hitherto largest and most disruptive global stressor of the 21st century, the COVID-19 pandemic is an important use case for resilience research . Stress To our knowledge, only a small number of studies employed a network model approach to RFs in the context of the COVID-19 pandemic –33. HoweUsing the COVID-19 pandemic as a use case, the current study aimed at: (1) examining the network of pre-pandemic RFs; 2) studying those RFs as predictors of mental responses to the pandemic , emotional support , and positive reframing . These subscales showed acceptable to good internal consistencies .The Brief COPE Inventory  was usedHardiness was assessed using a German translation of the Dispositional Resilience Scale , 51. TheInternal and external locus of control were assessed using the Brief Scale for the Assessment of Internal and External Control Beliefs . The insDispositional optimism was assessed using the Scale for Optimism-Pessimism 2 . The 2-iGeneralized self-efficacy was assessed using the General Self-Efficacy Short Scale . The 3-iSOC was assessed using the 9-item German short version  of the OSense of mastery was assessed using a German version of the Pearlin Mastery Scale . The 4-iPerceived social support was assessed using the Brief Form of the Perceived Social Support Questionnaire . The 6-iThe Resilience Scale 13  was usedAll analyses were performed using R version 4.4.2  and MpluRbtest package [The  package  was used package .For the study of mental responses to the pandemic, we employed the most common approach used in resilience research, that is, latent growth mixture modeling , 66  , that isbootnet [qgraph [mgm [For the network analyses, we used the R packages bootnet , qgraph  [qgraph , and mgmaph [mgm . We calcstrength as centrality index that describes how well a node directly connects to other nodes .The mgm estimation employs a penalty approach for false-positive findings . The LAFirst, we estimated pre-pandemic RF network models to examine between-RF interrelations at baseline and investigated the moderator effects of age, gender, and educational level on edge weights . Second,Mage = 50.06, SD = 13.49, range: 20–95 years, 51.5% women). Three respondents had no school degree (0.2%), 13.1% reported to have 9 years of school, 32.1% had 10 years of school, 19.8% had an A-level exam, 31.8% held a university degree, and 3.1% completed a doctoral degree. The sample comprised a comparable proportion of women, but was significantly older than the German general population and more educated. Psychopathological symptoms were comparable to the pre-pandemic German general population (details can be found in a previous publication [Our sample comprised 1275 respondents (lication ).t(2005) = 8.00, p < 0.001, d = 0.37, and more likely to be women, χ2(1) = 2.11, p < 0.001, Cramer’s V = 0.11, but were equally educated, t(2005) = 1.63, p = 0.103, d = 0.08. Moreover, they reported lower psychopathological symptom levels in February 2020, t(2004) = 2.07, p = 0.039, d = 0.10, lower levels of dispositional resilience, t(2004) = −4.23, p < 0.001, d = −0.20, and SOC, t(2004) = −3.21, p = 0.001, d = −0.15, while there were no differences in other RFs, p ≥ 0.079. A comparison of complete cases versus non-complete cases can be found in Supplementary Material SMRespondents included in our study were significantly older than those who dropped out after the baseline assessment, t200 = 8.00, Data on RFs was complete, while data on mental health outcomes was partly missing. For psychopathological symptoms, the proportion of missing data ranged between 0.1% (February 2020) and 24.1% (November 2020), all respondents had at least three timepoints available, and 99.5% had at least four timepoints available. Missing data for COVID-19-related rumination ranged between 3.5% (March 2020) and 25% (November 2020) per assessment wave. Nine respondents (0.7%) had only two timepoints available. For stress-related growth, missing data ranged between 10.4% (April 2020) and 25.3% (November 2020). For 143 respondents (11.2%), data was only available for two timepoints. For 620 respondents (48.6%), data was complete across all timepoints and outcomes. Regression-based tests indicated that missing data was missing completely at random for 83.3% of the variables, while data for 16.7% of the variables was missing at random. Missing data was only relevant to LGMM and handled using FIML.r = 0.37), (2) SOC and sense of mastery (r = 0.35), and (3) dispositional resilience and self-efficacy (r = 0.34). SOC and active coping had the only negative interrelation (r = −0.07).The network model of pre-pandemic RFs is presented in Fig. r = 0.75) allowed for a valid interpretation of centrality . Thus, we opted for the more parsimonious 4-class solution. Two classes showed resilient responses with initially decreasing and later stable no-to-low rumination . Another 37.7% also showed initial decreases in rumination that stabilized at a moderate level. Chronically high levels of rumination were shown by 34.9% of the respondents. In contrast to other trajectories, those respondents showed an increase in rumination during the second COVID-19 wave captured by our study.We examined 1–5-class solutions for stress-related growth, with studies including additional quadratic slopes showing better model fit. Decreases in AIC, SSBIC and BLRT suggested the final solution comprising two classes: most individuals (82.3%) showed relatively stable levels of stress-related growth, while a sub-population (17.7%) demonstrated a less stable pattern with initial decreases and later increases in stress-related growth.p = 0.313) and rumination (p = 0.462).For each model, individual-level intercepts and slopes were saved for later network analyses. This approach was further supported by significant or close-to-significant variances of intercepts and slopes in all models, except for the variance of slopes for moderate-stable trajectories of psychopathological symptoms  as well as between SOC and sense of mastery (r = 0.34), while the strongest negative link was found between SOC and individual intercepts (r = −0.29), that is, a higher SOC was associated with less severe symptoms and vice versa.Figure cs = 0.75, see Supplementary Material SMThe correlation stability coefficient , and between SOC and sense of mastery (r = 0.35). Individual intercepts of COVID-19-related rumination showed only a small negative association with SOC (r = −0.06), with a stronger SOC being associated with lower levels of rumination and vice versa.The network model of pre-pandemic RFs and individual intercepts derived from the LGMM on rumination are depicted in Fig. cs = 0.75) allowed for a valid interpretation of centrality indicators. While SOC was the most central node, individual intercepts for rumination had the smallest impact on the network.The correlation stability coefficient  as well as between SOC and sense of mastery (r = 0.35), while links to individual intercepts of stress-related growth were positive but small (rs ≤0.11). Higher levels of stress-related growth were associated with more positive reframing (r = 0.11), an internal locus of control (r = 0.06), higher levels of hardiness (r = 0.06), more coping using emotional support (r = 0.05), and stronger optimism (r = 0.04).Figure cs = 0.75), centrality indicators can be interpreted validly. Again, SOC was the most central node, while individual intercepts for stress-related growth were least central.Based on a high correlation stability coefficient  changed our results and whether associations between RFs and individual intercepts and slopes were amplified by age, gender, and educational level. All analyses left our results unchanged and provided support for the robustness of our findings.This 1-year prospective study examined pre-stressor resilience factors (RFs) and their association with mental health during one year of stressor exposure. Like other studies on RF networks , 25, we manageability and meaningfulness may overlap with the control and commitment components of hardiness [manageability and control referring to the feeling of being able to handle life challenges and meaningfulness and commitment representing the belief that these challenges are a potential source of purpose and growth [manageability component may also overlap with sense of mastery as the belief to be in control in different life domains [competence dimension of dispositional resilience [manageability. While active coping stresses the use of own resources to handle stress, the manageability component of SOC explicitly includes the reliance on external resources [To our knowledge, this study was among the first to examine the interrelations of a broad range of RFs in an adult general population sample. In the pre-pandemic network of RFs, SOC was the most central node with unique positive partial correlations with hardiness, sense of mastery, dispositional resilience, optimism, and self-efficacy, and one small negative association with active coping. On a conceptual level, the SOC components ardiness , with mad growth . Parts o domains , the comsilience   unique relationships between intercepts of stress-related growth and a larger number of RFs, that is, optimism, positive reframing, internal locus of control, hardiness, and coping using emotional support. These associations are in line with a previous meta-analysis finding posttraumatic growth to be associated with higher levels of optimism and reappraisal  and may benefits , which wbenefits . The assbenefits . Moreove meaning . SurprisThe results of the current study also point to a sizable problem of resilience research by showing that—after regularization—a set of 11 RFs accounts for only 22.6% of the variance in intercepts of psychopathological symptoms, and RFs explained 2.6% in the variance of rumination intercepts, and 11.4% of the differences in intercepts for stress-related growth. Moreover, for none of the mental health outcomes, we found significant associations with individual dynamics over time. These findings are in line with the so-called ‘resilience paradox’ , describInterestingly, in combined models , we found evidence for, at first sight, paradox associations. For example, active coping and coping using emotional support were associated with a higher probability of chronic compared to resilience trajectories for psychopathological symptoms. In line with a similar study , for rumIt is important to consider the limitations of the current study. First, this study was not preregistered. This has not been done as the study evolved into a larger longitudinal project with the unforeseen start of the COVID-19 pandemic in March 2020. As the pandemic had also major implications for our work as researchers, we developed this project as a fast response but deviated from our standard procedure of preregistrations. This may have biased our results, however, our aim of examining the interrelations of RFs and their predictive value for mental health outcomes has been consistently reported at all stages of this project , 43. HowThe current study enhances our understanding of RFs in the face of a major global stressor. We found 11 RFs to be highly interrelated, with SOC being the strongest component of a network of pre-pandemic RFs and the strongest predictor and correlate of resilient responses. Consistent with previous studies, SOC demonstrated incremental validity beyond other RFs. Patterns of associations for stress-related growth were different, pointing to the need for multidimensional outcomes in resilience research. In combined models, we found partially inverse associations for some RFs , which were linked to less favorable responses. This may support the idea that the fit between RFs, coping strategies and situational demands may be key to successful adaptation. Thus, future studies need to shed light on mediating resilience mechanisms that may allow for a deeper understanding of resilience.Supplemental Material 3