[Retracted] MicroRNA­17­5p contributes to osteoarthritis progression by binding p62/SQSTM1.

[This retracts the article DOI: 10.3892/etm.2017.5622.].

Assessing the current situation and the influencing factors affecting perceived stigma among older patients after leukemia diagnosis.

BACKGROUND: Psychological problems are becoming increasingly prominent among older patients with leukemia, with patients potentially facing stigmatization after diagnosis. However, there is limited research on the stigma experienced by these patients and the factors that may contribute to it. AIM: To investigate the stigma faced by older patients after being diagnosed with leukemia and to analyze the potential influencing factors. METHODS: A retrospective analysis was conducted using clinical data obtained from questionnaire surveys, interviews, and the medical records of older patients with leukemia admitted to the Hengyang Medical School from June 2020 to June 2023. The data obtained included participants' basic demographic information, medical history, leukemia type, family history of leukemia, average monthly family income, pension, and tendency to conceal illness. The Chinese versions of the Social Impact Scale (SIS), Perceived Social Support Scale (PSSS), Self-Rating Anxiety Scale (SAS), and Self-Rating Depression Scale (SDS) were used to assess indicators related to stigma, social support, and mental health status. We used Pearson's correlation coefficient to analyze the strength and direction of the relationship between the scores of each scale, and regression analysis to explore the factors related to the stigma of older patients with leukemia after diagnosis. RESULTS: Data from 120 patients with leukemia aged 65-80 years were analyzed. The total score on the SIS and PSSS was 43.60 ± 4.07 and 37.06 ± 2.87, respectively. The SAS score was 58.35 ± 8.32 and the SDS score was 60.58 ± 5.97. The stigma experienced by older leukemia patients was negatively correlated with social support (r = -0.691, P < 0.05) and positively correlated with anxiety and depression (r = 0.506, 0.382, P < 0.05). Age, education level, smoking status, average monthly family income, pension, and tendency to conceal illness were significantly associated with the participants' level of stigma (P < 0.05). Age, smoking status, social support, anxiety, and depression were predictive factors of stigmatization among older leukemia patients after diagnosis (all P < 0.05), with a coefficient of determination (R2) of 0.644 and an adjusted R2 of 0.607. CONCLUSION: Older patients commonly experience stigmatization after being diagnosed with leukemia. Factors such as age, smoking status, social support, and psychological well-being may influence older patients' reported experience of stigma.

Identification of plant microRNAs using convolutional neural network.

MicroRNAs (miRNAs) are of significance in tuning and buffering gene expression. Despite abundant analysis tools that have been developed in the last two decades, plant miRNA identification from next-generation sequencing (NGS) data remains challenging. Here, we show that we can train a convolutional neural network to accurately identify plant miRNAs from NGS data. Based on our methods, we also present a user-friendly pure Java-based software package called Small RNA-related Intelligent and Convenient Analysis Tools (SRICATs). SRICATs encompasses all the necessary steps for plant miRNA analysis. Our results indicate that SRICATs outperforms currently popular software tools on the test data from five plant species. For non-commercial users, SRICATs is freely available at https://sourceforge.net/projects/sricats.

Identification of the ferroptosis-related prognostic gene signature in mesothelioma.

Mesothelioma, an uncommon yet highly aggressive malignant neoplasm, presents challenges in the effectiveness of current therapeutic approaches. Ferroptosis, a non-apoptotic mechanism of cellular demise, exhibits a substantial association with the progression of diverse cancer forms. It is important to acknowledge that there exists a significant association between ferroptosis and the advancement of various forms of cancer. Nevertheless, the precise role of ferroptosis regulatory factors within the context of mesothelioma remains enigmatic. In our investigation, we initially scrutinized the prognostic significance of 24 ferroptosis regulatory factors in the realm of mesothelioma. Our observations unveiled that heightened expression levels of CARS1, CDKN1A, TFRC, FANCD2, FDFT1, HSPB1, SLC1A5, SLC7A11, coupled with reduced DPP4 expression, were indicative of an unfavorable prognosis. Built upon the nine previously discussed prognostic genes, the ferroptosis prognostic model offers a reliable means to forecast mesothelioma patients' survival with a substantial degree of precision. Furthermore, a notable correlation emerged between these prognostic ferroptosis regulators and parameters such as immune cell infiltration, tumor mutation burden, microsatellite instability, and PD-L1 expression in the context of mesothelioma. Within this cadre of nine ferroptosis regulatory factors with prognostic relevance, FANCD2 exhibited the most pronounced prognostic influence, as elucidated by our analyses. Subsequently, we executed a validation process employing clinical specimens sourced from our institution, thus confirming that heightened FANCD2 expression is a discernible harbinger of an adverse prognosis in the context of mesothelioma. In vitro experiments revealed that knocking down FANCD2 markedly suppressed the proliferation, migration, and ability of mesothelioma cells to attract immune cells. Furthermore, our findings also showed that reducing FANCD2 levels heightened the vulnerability of mesothelioma cells to inducers of ferroptosis. Furthermore, an extensive pan-cancer analysis uncovered a robust association between FANCD2 and the gene expression linked to immune checkpoints, thereby signifying an adverse prognosis across a broad spectrum of cancer types. Additional research is warranted to validate these findings.