Multiple interactive memory representations underlie the induction of false memory.

Theoretical and computational models such as transfer-appropriate processing (TAP) and global matching models have emphasized the encoding-retrieval interaction of memory representations in generating false memories, but relevant neural mechanisms are still poorly understood. By manipulating the sensory modalities (visual and auditory) at different processing stages (learning and test) in the Deese-Roediger-McDermott task, we found that the auditory-learning visual-test (AV) group produced more false memories (59%) than the other three groups (42∼44%) [i.e., visual learning visual test (VV), auditory learning auditory test (AA), and visual learning auditory test (VA)]. Functional imaging results showed that the AV group's proneness to false memories was associated with (i) reduced representational match between the tested item and all studied items in the visual cortex, (ii) weakened prefrontal monitoring process due to the reliance on frontal memory signal for both targets and lures, and (iii) enhanced neural similarity for semantically related words in the temporal pole as a result of auditory learning. These results are consistent with the predictions based on the TAP and global matching models and highlight the complex interactions of representations during encoding and retrieval in distributed brain regions that contribute to false memories

The tumor suppressive role of CAMK2N1 in castration-resistant prostate cancer.

Prostate cancer at advanced stages including metastatic and castration-resistant cancer remains incurable due to the lack of effective therapies. The CAMK2N1 gene, cloned and characterized as an inhibitor of CaMKII (calcium/calmodulin-dependent protein kinase II), has been shown to affect tumorigenesis and tumor growth. However, it is still unknown whether CAMK2N1 plays a role in prostate cancer development. We first examined the protein and mRNA levels of CAMK2N1 and observed a significant decrease in human prostate cancers comparing to normal prostate tissues. Re-expression of CAMK2N1 in prostate cancer cells reduced cellular proliferation, arrested cells in G0/G1 phases, and induced apoptotic cell death accompanied by down-regulation of IGF-1, ErbB2, and VEGF downstream kinases PI3K/AKT, as well as the MEK/ERK-mediated signaling pathways. Conversely, knockdown of CAMK2N1 had a significant opposite effects on these phenotypes. Our analyses suggest that CAMK2N1 plays a tumor suppressive role in prostate cancer cells. Reduced CAMK2N1 expression correlates to human prostate cancer progression and predicts poor clinical outcome, indicating that CAMK2N1 may serve as a biomarker. The inhibition of tumor growth by expressing CAMK2N1 established a role of CAMK2N1 as a therapeutic target

Clinical features of De Novo acute myeloid leukemia with concurrent DNMT3A, FLT3 and NPM1 mutations

BACKGROUND: De novo acute myeloid leukemia (AML) with concurrent DNMT3A, FLT3 and NPM1 mutations (AML(DNMT3A/FLT3/NPM1)) has been suggested to represent a unique AML subset on the basis of integrative genomic analysis, but the clinical features of such patients have not been characterized systematically. METHODS: We assessed the features of patients (n = 178) harboring mutations in DNMT3A, FLT3 and/or NPM1, including an index group of AML(DNMT3A/FLT3/NPM1) patients. RESULTS: Patients with AML(DNMT3A/FLT3/NPM1) (n = 35) were significantly younger (median, 56.0 vs. 62.0 years; p = 0.025), mostly women (65.7% vs. 46.9%; p = 0.045), and presented with a higher percentage of bone marrow blasts (p < 0.001) and normal cytogenetics (p = 0.024) in comparison to patients within other mutation groups in this study. Among patients <60 years old, those with AML(DNMT3A/FLT3/NPM1) had a shorter event-free survival (EFS) (p = 0.047). DNMT3A mutations and not FLT3 or NPM1 mutations were independently associated with overall survival (OS) (p = 0.026). Within mutation subgroups, patients with AML(DNMT3A/NPM1) had a significantly shorter OS compared to those with AML(FLT3-ITD/NPM1) (p = 0.047) suggesting that the adverse impact of DNMT3A mutations is more pronounced than that of FLT3-ITD among patients with NPM1 mutation. CONCLUSIONS: DNMT3A has a significant dominant effect on the clinical features and outcomes of de novo AML patients with concurrent DNMT3A, FLT3 and NPM1 mutations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13045-014-0074-4) contains supplementary material, which is available to authorized users

Natural biomimetic nano-system for drug delivery in the treatment of rheumatoid arthritis: a literature review of the last 5 years

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized primarily by synovitis, leading to the destruction of articular cartilage and bone and ultimately resulting in joint deformity, loss of function, and a significant impact on patients’ quality of life. Currently, a combination of anti-rheumatic drugs, hormonal drugs, and biologics is used to mitigate disease progression. However, conventional drug therapy has limited bioavailability, and long-term use often leads to drug resistance and toxic side effects. Therefore, exploring new therapeutic approaches for RA is of great clinical importance. Nanodrug delivery systems offer promising solutions to overcome the limitations of conventional drugs. Among them, liposomes, the first nanodrug delivery system to be approved for clinical application and still widely studied, demonstrate the ability to enhance therapeutic efficacy with fewer adverse effects through passive or active targeting mechanisms. In this review, we provide a review of the research progress on the targeting mechanisms of various natural biomimetic nano-delivery systems in RA therapy. Additionally, we predict the development trends and application prospects of these systems, offering new directions for precision treatment of RA

CAMK2N1 inhibits prostate cancer progression through androgen receptor-dependent signaling.

Castration resistance is a major obstacle to hormonal therapy for prostate cancer patients. Although androgen independence of prostate cancer growth is a known contributing factor to endocrine resistance, the mechanism of androgen receptor deregulation in endocrine resistance is still poorly understood. Herein, the CAMK2N1 was shown to contribute to the human prostate cancer cell growth and survival through AR-dependent signaling. Reduced expression of CAMK2N1 was correlated to recurrence-free survival of prostate cancer patients with high levels of AR expression in their tumor. CAMK2N1 and AR signaling form an auto-regulatory negative feedback loop: CAMK2N1 expression was down-regulated by AR activation; while CAMK2N1 inhibited AR expression and transactivation through CAMKII and AKT pathways. Knockdown of CAMK2N1 in prostate cancer cells alleviated Casodex inhibition of cell growth, while re-expression of CAMK2N1 in castration-resistant cells sensitized the cells to Casodex treatment. Taken together, our findings suggest that CAMK2N1 plays a tumor suppressive role and serves as a crucial determinant of the resistance of prostate cancer to endocrine therapies

Antioxidant and Anti-tyrosinase Activities of Phenolic Extracts from Rape Bee Pollen and Inhibitory Melanogenesis by cAMP/MITF/TYR Pathway in B16 Mouse Melanoma Cells

Rape bee pollen possesses many nutritional and therapeutic properties because of its abundant nutrimental and bioactive components. In this study, free (FPE) and bound (BPE) phenolic extracts of rape bee pollen were obtained, phenolic and flavonoid contents were determined, and composition of phenolic acids was analyzed. In vitro antioxidant and anti-tyrosinase (TYR) activities of FPE and BPE were compared, and inhibitory melanogenesis of FPE was further evaluated. Results showed FPE and BPE contain total phenolic contents of 11.76 and 0.81 mg gallic acid equivalents/g dry weight (DW) and total flavonoid contents of 19.24 and 3.65 mg rutin equivalents/g DW, respectively. Phenolic profiling showed FPE and BPE fractions contained 12 and 9 phenolic acids, respectively. FPE contained the highest rutin content of 774.87 μg/g. FPE and BPE showed the high antioxidant properties in vitro and high inhibitory activities for mushroom TYR. Higher activities of FPE than those of BPE can be attributed to difference in their phenolic compositions. Inhibitory melanogenesis activities of FPE against B16 were further evaluated. Results showed suppressed intracellular TYR activity, reduced melanin content, and promoted glutathione synthesis (p &lt; 0.05) in FPE-treated cells. FPE reduced mRNA expression of TYR, TYR-related protein (TRP)-1 and TRP-2, and significantly suppressed cyclic adenosine monophosphate (cAMP) levels through down-regulation of melanocortin 1 receptor gene expression (p &lt; 0.05). FPE reduced mRNA expression of microphthalmia-associated transcription factor (MITF), significantly inhibiting intracellular melanin synthesis (p &lt; 0.05). Hence, FPE regulates melanogenesis of B16 cells involved in cAMP/MITF/TYR pathway. These results revealed that FPE can be used as pharmaceutical agents and cosmetics to protect cells from abnormal melanogenesis

Remaining useful life indirect prediction of lithium-ion batteries using CNN-BiGRU fusion model and TPE optimization

The performance of lithium-ion batteries declines rapidly over time, inducing anxiety in their usage. Ascertaining the capacity of these batteries is difficult to measure directly during online remaining useful life (RUL) prediction, and a single deep learning model falls short of accuracy and applicability in RUL predictive analysis. Hence, this study proposes a lithium-ion battery RUL indirect prediction model, fusing convolutional neural networks and bidirectional gated recurrent units (CNN-BiGRU). The analysis of characteristic parameters of battery life status reveals the selection of pressure discharge time, average discharge voltage and average temperature as health factors of lithium-ion batteries. Following this, a CNN-BiGRU model for lithium-ion battery RUL indirect prediction is established, and the Tree-structured Parzen Estimator (TPE) adaptive hyperparameter optimization method is used for CNN-BiGRU model hyperparameter optimization. Overall, comparison experiments on single-model and other fusion models demonstrate our proposed model's superiority in the prediction of RUL in terms of stability and accuracy

Lightweight high-performance pose recognition network: HR-LiteNet

To address the limited resources of mobile devices and embedded platforms, we propose a lightweight pose recognition network named HR-LiteNet. Built upon a high-resolution architecture, the network incorporates depthwise separable convolutions, Ghost modules, and the Convolutional Block Attention Module to construct L_block and L_basic modules, aiming to reduce network parameters and computational complexity while maintaining high accuracy. Experimental results demonstrate that on the MPII validation dataset, HR-LiteNet achieves an accuracy of 83.643% while reducing the parameter count by approximately 26.58 M and lowering computational complexity by 8.04 GFLOPs compared to the HRNet network. Moreover, HR-LiteNet outperforms other lightweight models in terms of parameter count and computational requirements while maintaining high accuracy. This design provides a novel solution for pose recognition in resource-constrained environments, striking a balance between accuracy and lightweight demands

A new perspective on hematological malignancies: m6A modification in immune microenvironment

Immunotherapy for hematological malignancies is a rapidly advancing field that has gained momentum in recent years, primarily encompassing chimeric antigen receptor T-cell (CAR-T) therapies, immune checkpoint inhibitors, and other modalities. However, its clinical efficacy remains limited, and drug resistance poses a significant challenge. Therefore, novel immunotherapeutic targets and agents need to be identified. Recently, N6-methyladenosine (m6A), the most prevalent RNA epitope modification, has emerged as a pivotal factor in various malignancies. Reportedly, m6A mutations influence the immunological microenvironment of hematological malignancies, leading to immune evasion and compromising the anti-tumor immune response in hematological malignancies. In this review, we comprehensively summarize the roles of the currently identified m6A modifications in various hematological malignancies, with a particular focus on their impact on the immune microenvironment. Additionally, we provide an overview of the research progress made in developing m6A-targeted drugs for hematological tumor therapy, to offer novel clinical insights