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Cell division cycle 20 homologue (CDC20), a key regulator of mitosis, is frequently overexpressed in cancers and linked to tumor progression. However, its role in mantle cell lymphoma (MCL) remains unclear. This study explored the functional significance of CDC20 in MCL and its underlying mechanisms. CDC20 expression was analyzed in peripheral blood mononuclear cells (PBMCs), bone marrow mononuclear cells (BMNCs), clinical samples, and MCL cell lines (Z138, Mino, Rec1), followed by correlation with clinicopathological features. MCL cells were treated with the CDC20 inhibitor apcin or transduced with CDC20-knockdown lentivirus, and effects on proliferation, apoptosis, cell cycle, migration, and invasion were assessed. The anti-tumor effect of apcin was tested in the Z138-driven xenograft mouse model. RNA-seq was performed to identify signaling pathways altered upon CDC20 inhibition, and western blot (WB) analysis confirmed the dysregulation of key pathway components. Consequently, CDC20 was significantly upregulated in PBMCs, BMNCs, tumor tissues, and MCL cell lines compared to their respective controls. Apcin or CDC20 knockdown suppressed proliferation, migration, and invasion while inducing apoptosis and G2/M arrest in MCL cells. In vivo, apcin effectively and safely inhibited tumor growth. RNA-seq revealed differential genes were enriched in the PI3K/AKT signaling pathway. WB validated reduced PI3K/AKT phosphorylation levels after CDC20 inhibition, suggesting CDC20 promoted the malignant phenotype of MCL via PI3K/AKT signaling. Therefore, CDC20 plays a critical role in MCL pathogenesis. Targeting CDC20 and the PI3K/AKT pathway may offer a promising therapeutic strategy for MCL.

Mantle cell lymphoma (MCL) is an uncommon and aggressive type of B-cell non-Hodgkin lymphoma, wherein TP53 mutations play a critical role. This study analyzed the effect of different TP53 mutations on the clinical characteristics and prognosis of patients with MCL. TP53 sequencing data and clinical and prognostic information were collected from 215 patients with MCL treated at Peking University Third Hospital between August 2017 and December 2022. Furthermore, descriptive and Cox regression analyses were also performed. Our findings revealed the association between TP53 mutations and higher Ki67 levels ( p  = 0.008), elevated combined MCL International Prognostic Index (MIPI-c; p  = 0.032), blastoid/pleomorphic subtypes ( p  = 0.020) and ≥ 2 treatment lines ( p  = 0.026). Missense mutations (75.6%; G: C > A:T [48.31%]) were the predominant mutation type, occurring within the DNA-binding domain (DBD; 92.41%) and concentrated in exons 5–8 (82.05%). TP53 mutations significantly affected overall survival (OS; p  = 0.0091) and progression-free survival (PFS; p  = 0.029), and the extent of the impact on prognosis was dependent on the location of the mutations. Following MIPI-c adjustment, multivariate analysis revealed the detrimental effects of DBD (OS: hazard ratio [HR] = 3.06) and R273/G245 (OS: HR = 7.95) mutations ( p  = 0.012). G245 and R273 mutations lead to significantly reduced transactivation levels and impaired cell proliferation inhibition ( p  < 0.001), providing mechanistic evidence that supports their association with poorer prognosis in MCL patients.

Primary testicular lymphoma (PTL) is a rare lymphoma predominantly occurring in the elderly male population. It is characterized by a limited response to treatment and a heightened tendency towards relapse. Histologically, approximately 90% of PTL cases are classified as diffuse large B-cell lymphomas (DLBCL). Genetic features of PTL were delineated in a limited scope within several independent studies. Some of the articles which analyzed the genetic characterization of DLBCL have incorporated PTL samples, but these have been constrained by small sample sizes. In addition, there have been an absence of independent molecular typing studies of PTL. This report summarizes the common mutational features, copy number variations (CNVs) and molecular typing of PTL patients, based on whole-exome sequencing (WES) conducted on a cohort of 25 PTL patients. Among them, HLA, CDKN2A and MYD88 had a high mutation frequency. In addition, we found two core mutational characteristics in PTL including mutation in genes linked to genomic instability (TP53 and CDKN2A) and mutation in immune-related genes (HLA, MYD88, CD79B). We performed molecular typing of 25 PTL patients into C1 subtype with predominantly TP53 mutations and C2 subtype with predominantly HLA mutations. Notably, mutations in the TP53 gene predicted a poor outcome in most types of lymphomas. However, the C1 subtype, dominated by TP53 mutations, had a better prognosis compared to the C2 subtype in PTL. C2 subtype exhibited a worse prognosis, aligning with our finding that the mechanism of immune escape in PTL was primarily the deletions of HLA rather than PD-L1/PD-L2 alterations, a contrast to other DLBCLs. Moreover, we calculated the tumor mutation burden (TMB) and identified that TMB can predict prognosis and recurrence rate in PTL. Our study underscores the significance of molecular typing in PTL based on mutational characteristics, which plays a crucial role in prognostication and guiding therapeutic strategies for patients.

Classical Hodgkin lymphoma (cHL) has excellent survival outcomes, but real-world data from large-scale cohorts in China remain limited. This multicenter study characterized the clinical profile of a large Chinese cHL cohort to evaluate the efficacy of BV-containing regimens and investigate the prognostic value of clinical, nutritional, and biological markers, including peripheral monocyte percentage (M%). We retrospectively analyzed 547 patients with pathologically confirmed cHL from 10 centers between 2010 and 2023. Clinical characteristics and treatment outcomes were assessed. Propensity score matching (PSM) was employed to minimize selection bias when comparing progression-free survival (PFS) between treatment groups. Multivariate Cox regression models identified independent prognostic factors. The cohort featured a high prevalence of advanced-stage disease (55.0%) and the mixed cellularity subtype (34.4%), distinct from Western populations. While ABVD remained the dominant first-line regimen, the adoption of BV + AVD increased over time. In the PSM analysis, first-line BV + AVD demonstrated a numerically higher 3-year PFS compared with ABVD (95.2% vs. 88.9%), although this difference did not reach statistical significance (P = 0.359). Multivariate analysis identified decreased albumin and elevated M% as independent predictors of inferior PFS, while a focused biological model confirmed elevated M% and bone involvement as independent predictors of inferior overall survival. This study provides comprehensive real-world evidence delineating the clinical landscape of cHL in Chinese patients. While BV + AVD showed a favorable trend toward improved PFS, statistical superiority was not reached, warranting further investigation in larger cohorts. Furthermore, baseline nutritional status (albumin), tumor microenvironment surrogates (M%), and distinct extranodal infiltration (bone involvement) emerged as key prognostic markers, suggesting a need for risk-adapted strategies and potentially intensified therapies in high-risk subgroups.

Objective Interim 18 F-FDG PET/CT (iPET/CT) imaging demonstrates potential in assessing the early therapeutic response in lymphoma. Nevertheless, the prognostic significance of interim PET-CT in diffuse large B-cell lymphoma (DLBCL) remains controversial. This study aimed to evaluate whether semi-quantitative PET/CT metabolic parameters and other metrics could enhance the prognostic value of interim PET/CT in DLBCL patients exhibiting partial metabolic remission (PMR). Methods A retrospective analysis was performed from January 2018 to December 2023, focusing on patients with DLBCL who achieved PMR on interim PET-CT. Patient demographics, clinical characteristics, and semi-quantitative PET/CT metabolic parameters were extracted from the medical records. Multivariate analyses were conducted to identify the risk factors associated with failure to achieve complete metabolic remission (CMR) at the end of treatment (EOT). Receiver operating characteristic (ROC) curve analysis was employed to determine the optimal cut-off values for continuous predictive variables. Progression-free survival (PFS) and overall survival (OS) were estimated using Kaplan–Meier methods, and risk factors were evaluated using Cox regression models. Results In a cohort consisting of 80 newly diagnosed DLBCL cases that exhibited PMR on interim PET scans, 50 cases ultimately achieved CMR, while the remaining 30 cases still had positive PET findings at EOT. Analysis revealed that the interim lesion-to-liver maximum standardized uptake value ratio (RLL) and bone marrow involvement were independent prognostic factors for positive PET-CT outcomes at EOT. Notably, an interim RLL threshold greater than 1.66 emerged as a reliable predictor with a sensitivity of 73.3% and a specificity of 72.0%. Additionally, the International Prognostic Index (IPI) and interim RLL were identified as independent prognostic indicators for both progression-free survival (PFS) and overall survival (OS). Conclusion Our study revealed that within the cohort of DLBCL patients exhibiting PMR on interim PET scans, an interim RLL greater than 1.66 and bone marrow involvement emerged as independent risk factors for positive PET results at the end of treatment. Additionally, the IPI and interim RLL were identified as independent prognostic markers for both progression-free survival and overall survival. The integration of clinical characteristics with semi-quantitative PET/CT parameters has the potential to enhance the prognostic role of interim PET/CT exhibiting PMR in DLBCL cases.

The health of complex systems continues to decline as they operate over long periods of time, so it is important to assess the health state of complex systems. Belief rule base (BRB) is widely used in the field of health state assessment of complex systems as a semi-quantitative method that can address uncertainty effectively and with interpretability. In practical engineering, BRB still has problems: the incompleteness of expert knowledge and the inconsistency of the cognitive abilities of each expert have an effect on the construction of the model and interpretability. To address this problem, a complex system health state assessment method is proposed based on a joint multiexpert belief rule base (BRB-ME). Experts first build their own models, and a new multiexpert knowledge fusion algorithm is designed for the fusion of different expert models. The ER is used as the inference machine for the model. Next, a multi-population evolution whale optimization algorithm with multiexpert knowledge constraints (C-MEWOA) is used to optimize the BRB-ME model. Finally, the effectiveness of the BRB-ME model in health state assessment is verified through case studies of lithium-ion batteries and flywheels. Comparative studies have shown that the BRB-ME model can fuse multiexpert knowledge and has advantages in terms of the stability and accuracy of assessment results.

Autonomous underwater vehicles (AUVs) have been increasingly applied in marine environmental monitoring. Their outstanding capability of performing tasks without human intervention makes them a popular tool for environmental data collection, especially in unknown and remote regions. This paper addresses the path planning problem when AUVs are used to perform plume source tracing in an unknown environment. The goal of path planning is to locate the plume source efficiently. The path planning approach is developed using the Double Deep Q-Network (DDQN) algorithm in the deep reinforcement learning (DRL) framework. The AUV gains knowledge by interacting with the environment, and the optimal direction is extracted from the mapping obtained by a deep neural network. The proposed approach was tested by numerical simulation and on a real ground vehicle. In the numerical simulation, several initial sampling strategies were compared on the basis of survey efficiency. The results show that direct learning based on the interaction with the environment could be an appropriate survey strategy for plume source tracing problems. The comparison with the canonical lawnmower path used in practice showed that path planning using DRL algorithms could be potentially promising for large-scale environment exploration.