Background. Psychological distress is a progressive health problem that has been linked to decreased quality of life among university students. This meta-analysis reviews existing randomized controlled trials (RCTs) that have examined the effects of mindfulness-based stress reduction (MBSR) on the relief of psychosomatic stress-related outcomes and quality of life among university students. Methods. The PubMed, EMBASE, Web of Science, PsycINFO (formerly PsychLit), Ovid MEDLINE, ERIC, Scopus, Google Scholar, ProQuest, and Cochrane Library databases were searched in November 2023 to identify the RCTs for analysis. Data on pathology (anxiety, depression, and perceived stress), physical capacity (sleep quality and physical health), and well-being (mindfulness, self-kindness, social function, and subjective well-being) were analyzed. Results. Of the 276 articles retrieved, 29 met the inclusion criteria. Compared with control therapies, the pooled results suggested that MBSR had significant effects, reducing anxiety (SMD=0.29; 95 CI: 0.49 to 0.09), depression (SMD=0.32; 95 CI: 0.62 to 0.02), and perceived stress (SMD=0.41; 95 CI: 0.60 to 0.29) and improving mindfulness (SMD=0.34; 95 CI: 0.08 to 0.59), self-kindness (SMD=0.57; 95 CI: 0.30 to 1.12), and physical health (SMD=0.59; 95 CI: 1.14 to 0.04). No significant differences were observed in sleep quality (SMD=0.20; 95 CI: 0.06 to 0.20), social function (SMD=0.71; 95 CI: 2.40 to 0.97), or subjective well-being (SMD=0.07; 95 CI: 0.18 to 0.32). The quality of the evidence regarding sleep quality and physical health outcomes was low. Conclusions. MBSR therapy appears to be potentially useful in relieving functional emotional disorders. However, additional evidence-based large-sample trials are required to definitively determine the forms of mindfulness-based therapy that may be effective in this context and ensure that the benefits obtained are ongoing. Future studies should investigate more personalized approaches involving interventions that are tailored to various barriers and students clinical characteristics. To optimize the effects of such interventions, they should be developed and evaluated using various designs such as the multiphase optimization strategy, which allows for the identification and tailoring of the most valuable intervention components.

Diploid cells undergoing senescence and mitotic slippage have been reported in the literature. However, the mechanisms triggering senescence in long-term G2-arrested cells are currently unclear. Previously, we reported that the cell cycle of the human uveal melanoma cell line, 92-1, is suspended for up to 6 d upon exposure to 10 Gy ionizing radiation (IR), followed by senescence. In the current study, we initially distinguished senescence in long-term blocked 92-1 cells from mitotic slippage by confirming the blockage of cells in the G2 phase. We subsequently showed that the genes essential for G2-M transition are prematurely downregulated at both the transcriptional and translational levels. Furthermore, levels of the G1-specific markers, Cyclin D1 and Caveolin-1, were distinctly increased, while S/G2-specific markers, Cyclin B1 and Aurora A, were significantly downregulated. These findings collectively imply that long-term G2-arrested cells undergo senescence via G2 slippage. To our knowledge, this is the first study to report that the cellular process of G2 slippage is the mechanism responsible for senescence of cells under long-term G2 arrest.

To drive high-quality omics translational research using The Cancer Genome Atlas (TCGA) data, a TCGA Pan-Cancer Clinical Data Resource was proposed. However, there is an out-of-step issue between clinical outcomes and the omics data of TCGA for skin cutaneous melanoma (SKCM), due to the majority of metastatic samples. In clinical cases, the survival time started from the initial SKCM diagnosis, while the omics data were characterized at TCGA sampling. This study aimed to address this issue by proposing an observed survival interval (OBS), which was defined as the time interval from TCGA sampling to patient death or last follow-up. We compared the OBS with the usual recommended overall survival (OS) by associating them with both clinical data and microRNA sequencing data of TCGA-SKCM. We found that the OS of primary SKCM was significantly shorter than that of metastatic SKCM, while the opposite happened if OBS was compared. OS was associated with the pathological stage of both primary and metastatic SKCM, while OBS was associated with the pathological stage of primary SKCM but not that of metastatic SKCM. Five previously cross-validated survival-associated microRNAs were found to be associated with the OBS rather than OS in metastatic SKCM. Thus, the OBS was more appropriate for associating microRNA-omics data of TCGA-SKCM than OS, and it is a timely supplement to TCGA Pan-Cancer Clinical Data Resource.

Chinese traditional herbal medicine Fuzhengkangai (FZKA) formulation combination with gefitinib can overcome drug resistance and improve the prognosis of lung adenocarcinoma patients. However, the pharmacological and molecular mechanisms underlying the active ingredients, potential targets, and overcome drug resistance of the drug are still unclear. Therefore, it is necessary to explore the molecular mechanism of FZKA. A systems pharmacology and bioinformatics-based approach was employed to investigate the molecular pathogenesis of EGFR-TKI resistance with clinically effective herb formula. The differential gene expressions between EGFR-TKI sensitive and resistance cell lines were calculated and used to find overlap from targets as core targets. The prognosis of core targets was validated from the cancer genome atlas (TCGA) database by Cox regression. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment is applied to analysis core targets for revealing mechanism in biology. The results showed that 35 active compounds of FZKA can interact with eight core targets proteins (ADRB2, BCL2, CDKN1A, HTR2C, KCNMA1, PLA2G4A, PRKCA and LYZ). The risk score of them were associated with overall survival and relapse free time (HR = 6.604, 95% CI: 2.314–18.850; HR = 5.132, 95% CI: 1.531–17.220). The pathway enrichment suggested that they involved in EGFR-TKI resistance and non-small cell lung cancer pathways, which directly affect EGFR-TKI resistance. The molecular docking showed that licochalcone a and beta-sitosterol can closely bind two targets (BCL2 and PRKCA) that involved in EGFR-TKI resistance pathway. This study provided a workflow for understanding mechanism of CHM for against drug resistance.

In the development of targeted drugs, anticancer peptides (ACPs) have attracted great attention because of their high selectivity, low toxicity and minimal non-specificity. In this work, we report a framework of ACPs generation, which combines Wasserstein autoencoder (WAE) generative model and Particle Swarm Optimization (PSO) forward search algorithm guided by attribute predictive model to generate ACPs with desired properties. It is well known that generative models based on Variational AutoEncoder (VAE) and Generative Adversarial Networks (GAN) are difficult to be used for de novo design due to the problems of posterior collapse and difficult convergence of training. Our WAE-based generative model trains more successfully (lower perplexity and reconstruction loss) than both VAE and GAN-based generative models, and the semantic connections in the latent space of WAE accelerate the process of forward controlled generation of PSO, while VAE fails to capture this feature. Finally, we validated our pipeline on breast cancer targets (HIF-1) and lung cancer targets (VEGR, ErbB2), respectively. By peptide-protein docking, we found candidate compounds with the same binding sites as the peptides carried in the crystal structure but with higher binding affinity and novel structures, which may be potent antagonists that interfere with these target-mediated signaling.

Previous studies have indicated that radiation resistance of glioma is one of the leading causes of radiotherapy failure. Mounting evidence suggests that long non‐coding RNA (lncRNA) plays an important role in regulating radiosensitivity of cancer cells via implicating in various cell processes. However, the underlying mechanisms remain unclear and need further study, especially at the molecular level. We found that the expression level of lncRNA H19 was elevated by radiation, and then, the modulation of H19 affected the resistant of glioma cells to X‐rays. Dual‐luciferase reporter analyses showed that H19 was transcriptionally activated by CREB1 in glioma cells after irradiation. In addition, both flow cytometry and 5‐ethynyl‐2 ^′‐deoxyuridine (EdU) assay suggested that H19 was involved in the cell cycle arrest, apoptosis, and DNA synthesis to modulate the radiation response of glioma cells and influenced their radioresistance. Therefore, H19 might play a crucial role in enhancing the radioresistance of glioma.