MACC1 enhances an oncogenic RNA splicing of IRAK1 through interacting with HNRNPH1 in lung adenocarcinoma.

Dysregulation of alternative pre-mRNA splicing plays a critical role in the progression of cancers, yet the underlying molecular mechanisms remain largely unknown. It is reported that metastasis-associated in colon cancer 1 (MACC1) is a novel prognostic and predictive marker in many types of cancers, including lung adenocarcinoma. Here, we reveal that the oncogene MACC1 specifically drives the progression of lung adenocarcinoma through its control over cancer-related splicing events. MACC1 depletion inhibits lung adenocarcinoma progression through triggering IRAK1 from its long isoform, IRAK1-L, to the shorter isoform, IRAK1-S. Mechanistically, MACC1 interacts with splicing factor HNRNPH1 to prevent the production of the short isoform of IRAK1 mRNA. Specifically, the interaction between MACC1 and HNRNPH1 relies on the involvement of MACC1's SH3 domain and HNRNPH1's GYR domain. Further, HNRNPH1 can interact with the pre-mRNA segment (comprising exon 11) of IRAK1, thereby bridging MACC1's regulation of IRAK1 splicing. Our research not only sheds light on the abnormal splicing regulation in cancer but also uncovers a hitherto unknown function of MACC1 in tumor progression, thereby presenting a novel potential therapeutic target for clinical treatment.

[Heart rate extraction algorithm based on adaptive heart rate search model].

Photoplethysmography (PPG) is a non-invasive technique to measure heart rate at a lower cost, and it has been recently widely used in smart wearable devices. However, as PPG is easily affected by noises under high-intensity movement, the measured heart rate in sports has low precision. To tackle the problem, this paper proposed a heart rate extraction algorithm based on self-adaptive heart rate separation model. The algorithm firstly preprocessed acceleration and PPG signals, from which cadence and heart rate history were extracted respectively. A self-adaptive model was made based on the connection between the extracted information and current heart rate, and to output possible domain of the heart rate accordingly. The algorithm proposed in this article removed the interference from strong noises by narrowing the domain of real heart rate. From experimental results on the PPG dataset used in 2015 IEEE Signal Processing Cup, the average absolute error on 12 training sets was 1.12 beat per minute (bpm) (Pearson correlation coefficient: 0.996; consistency error: -0.184 bpm). The average absolute error on 10 testing sets was 3.19 bpm (Pearson correlation coefficient: 0.990; consistency error: 1.327 bpm). From experimental results, the algorithm proposed in this paper can effectively extract heart rate information under noises and has the potential to be put in usage in smart wearable devices.

Transcriptional activation of NANOG by YBX1 promotes lung cancer stem-like properties and metastasis.

Aberrant overexpression of the transcription/translation factor Y-box-binding protein-1 (YBX1) is associated with non-small cell lung cancer (NSCLC) aggressiveness. Cancer stem cells (CSCs) contribute to the tumorigenesis and metastasis of NSCLC. Hitherto, the mechanism by which YBX1 regulates CSCs and metastasis in NSCLC remains unclear. Here, we demonstrated that YBX1 levels were elevated in NSCLC tissues and cell lines. Enforced expression of YBX1 promoted NSCLC cells invasion, sphere forming ability and ALDH1+ population. Conversely, reduced YBX1 impaired CSC properties of NSCLC cells in vitro and tumor-initiating frequencies, as well as metastasis in vivo. Importantly, we described a mechanism whereby YBX1 directly promoted NANOG, a transcription factor, transcriptional activation. Depletion of NANOG abolished the enhanced ability of invasion and sphere formation in YBX1 elevated-A549 cells. Collectively, these findings demonstrate a novel role of YBX1 in maintaining the stemness of CSCs and metastasis, unveiling YBX1 as promising therapeutic target for NSCLC treatments.

Application of spiral enhanced whale optimization algorithm in solving optimization problems.

The Whale Optimization Algorithm (WOA) is regarded as a classic metaheuristic algorithm, yet it suffers from limited population diversity, imbalance between exploitation and exploration, and low solution accuracy. In this paper, we propose the Spiral-Enhanced Whale Optimization Algorithm (SEWOA), which incorporates a nonlinear time-varying self-adaptive perturbation strategy and an Archimedean spiral structure into the original WOA. The Archimedean spiral structure enhances the diversity of the solution space, aiding the algorithm in escaping local optima. The nonlinear time-varying self-adaptive optimization dynamic perturbation strategy improves the algorithm's local search capability and enhances solution accuracy. The effectiveness of the proposed algorithm is validated from multiple perspectives using CEC2014 test functions, CEC2017 test functions, and 23 benchmark test functions. The experimental results demonstrate that the enhanced Whale Optimization Algorithm significantly improves population diversity, balances global and local search, and enhances solution accuracy. Additionally, SEWOA exhibits excellent performance in solving three engineering design problems, showcasing its value and wide range of potential applications.

A multi-view multi-label fast model for Auricularia cornea phenotype identification and classification.

The identification and classification of various phenotypic features of Auricularia cornea fruit bodies are crucial for quality grading and breeding efforts. The phenotypic features of Auricularia cornea fruit bodies encompass size, number, shape, color, pigmentation, and damage. These phenotypic features are distributed across various views of the fruit bodies, making the task of achieving both rapid and accurate identification and classification challenging. This paper proposes a novel multi-view multi-label fast network that integrates two different views of the Auricularia cornea fruiting body, enabling rapid and precise identification and classification of six phenotypic features simultaneously. Initially, a multi-view feature extraction model based on partial convolution was constructed. This model incorporates channel attention mechanisms to achieve rapid phenotypic feature extraction of the Auricularia cornea fruiting body. Subsequently, an efficient multi-task classifier was designed, based on class-specific residual attention, to ensure accurate classification of phenotypic features. Finally, task weights were dynamically adjusted based on heteroscedastic uncertainty, reducing the training complexity of the multi-task classification. The proposed network achieved a classification accuracy of 94.66% and an inference speed of 11.9 ms on an image dataset of dried Auricularia cornea fruiting bodies with three views and six labels. The results demonstrate that the proposed network can efficiently and accurately identify and classify all phenotypic features of Auricularia cornea.

Wheat Spike Detection and Counting in the Field Based on SpikeRetinaNet.

The number of wheat spikes per unit area is one of the most important agronomic traits associated with wheat yield. However, quick and accurate detection for the counting of wheat spikes faces persistent challenges due to the complexity of wheat field conditions. This work has trained a RetinaNet (SpikeRetinaNet) based on several optimizations to detect and count wheat spikes efficiently. This RetinaNet consists of several improvements. First, a weighted bidirectional feature pyramid network (BiFPN) was introduced into the feature pyramid network (FPN) of RetinaNet, which could fuse multiscale features to recognize wheat spikes in different varieties and complicated environments. Then, to detect objects more efficiently, focal loss and attention modules were added. Finally, soft non-maximum suppression (Soft-NMS) was used to solve the occlusion problem. Based on these improvements, the new network detector was created and tested on the Global Wheat Head Detection (GWHD) dataset supplemented with wheat-wheatgrass spike detection (WSD) images. The WSD images were supplemented with new varieties of wheat, which makes the mixed dataset richer in species. The method of this study achieved 0.9262 for mAP50, which improved by 5.59, 49.06, 2.79, 1.35, and 7.26% compared to the state-of-the-art RetinaNet, single-shot multiBox detector (SSD), You Only Look Once version3 (Yolov3), You Only Look Once version4 (Yolov4), and faster region-based convolutional neural network (Faster-RCNN), respectively. In addition, the counting accuracy reached 0.9288, which was improved from other methods as well. Our implementation code and partial validation data are available at https://github.com/wujians122/The-Wheat-Spikes-Detecting-and-Counting.

VLDLR disturbs quiescence of breast cancer stem cells in a ligand-independent function.

Breast cancer stem cells are responsible for cancer initiation, progression, and drug resistance. However, effective targeting strategies against the cell subpopulation are still limited. Here, we unveil two splice variants of very-low-density lipoprotein receptor, VLDLR-I and -II, which are highly expressed in breast cancer stem cells. In breast cancer cells, VLDLR silencing suppresses sphere formation abilities in vitro and tumor growth in vivo. We find that VLDLR knockdown induces transition from self-renewal to quiescence. Surprisingly, ligand-binding activity is not involved in the cancer-promoting functions of VLDLR-I and -II. Proteomic analysis reveals that citrate cycle and ribosome biogenesis-related proteins are upregulated in VLDLR-I and -II overexpressed cells, suggesting that VLDLR dysregulation is associated with metabolic and anabolic regulation. Moreover, high expression of VLDLR in breast cancer tissues correlates with poor prognosis of patients. Collectively, these findings indicate that VLDLR may be an important therapeutic target for breast cancer treatment.

YBX1 Enhances Metastasis and Stemness by Transcriptionally Regulating MUC1 in Lung Adenocarcinoma.

Abnormal expression of the transcription factor Y-box-binding protein-1 (YBX1) is associated with the proliferation, migration, aggressiveness, and stem-like properties of various cancers. These characteristics contribute to the tumorigenesis and metastasis of cancer. We found that the expression levels of Mucin-1 (MUC1) and YBX1 were positively correlated in lung adenocarcinoma cells and lung adenocarcinoma tissue. Our retrospective cohort study of 176 lung adenocarcinoma patients after surgery showed that low expression of both YBX1 and MUC1 was an independent predictor of the prognosis and recurrence of lung adenocarcinoma. In lung adenocarcinoma cells, the silencing/overexpression of YBX1 caused a simultaneous change in MUC1, and MUC1 overexpression partially reversed the decreased tumor cell migration, aggressiveness, and stemness caused by YBX1 silencing. Moreover, chromatin immunoprecipitation (ChIP) and dual-luciferase reporter assays proved that MUC1 was the downstream target of YBX1 and that YBX1 bound to the -1480~-1476 position in the promoter region of MUC1 to regulate its transcription. Furthermore, in mouse xenograft models and a lung cancer metastasis model, MUC1, which is downstream of YBX1, partially reversed the decreased number and size of tumors caused by YBX1 silencing. In conclusion, our findings indicated a novel mechanism by which YBX1 promotes the stemness and metastasis of lung adenocarcinoma by targeting MUC1 and provided a combination approach for diagnosis different from traditional single tumor biomarkers to predict patient prognosis and provide clinical treatment targets.

GalNAc-T3 and MUC1, a combined predictor of prognosis and recurrence in solitary pulmonary adenocarcinoma initially diagnosed as malignant solitary pulmonary nodule (≤ 3 cm).

The significance of the polypeptide N-acetyl-galactosaminyl transferase-3 (GalNAc-T3) and mucin 1 (MUC1) in solitary pulmonary adenocarcinoma (SPA) initially diagnosed as malignant solitary pulmonary nodule (≤ 3 cm), especially as a combined predictor of prognosis and recurrence, was explored in this study. A retrospective analysis of 83 patients with SPA (≤ 3 cm), which revealed postoperative pathological diagnosis was lung adenocarcinoma after complete resection. Immunohistochemical staining was used to detect the expression of GalNAc-T3 and MUC1 in primary tumor specimens. The relationship between expression and various clinicopathological factors was analyzed, as well as the effects of patients' overall survival (OS) and disease-free survival (DFS). In all patients, GalNAc-T3 was highly expressed in 53 (63.9%) cases; MUC1 was highly expressed in 31 (37.3%) cases. The GalNAc-T3 expression was correlated with differentiation, pathological risk group, N stage, and TNM stage. The group with high GalNAc-T3 expression and low MUC1 expression (GalNAc-T3Hig/MUC1Low) is correlated to pathological differentiation and has a trend related to the TNM stage. The patients with better differentiation, lower pathological risk group, lower N stage, and GalNAc-T3 high expression had better overall survival, especially the GalNAc-T3Hig/MUC1Low group. Moreover, the moderate differentiation, N3 stage, and GalNAc-T3Hig/MUC1Low group were independent predictive factors for OS. Besides, patients with lower N stage, lower TNM stage, higher GalNAc-T3 expression got better disease-free survival (DFS), especially the GalNAc-T3Hig/MUC1Low group. The GalNAc-T3Hig/MUC1Low group was an independent predictive factor for DFS. In conclusion, GalNAc-T3 and MUC1 were combined predictors of prognosis and recurrence in SPA (≤ 3 cm).

YBX1 mediates autophagy by targeting p110ß and decreasing the sensitivity to cisplatin in NSCLC.

Y-box binding protein 1 (YBX1) is involved in the development of multiple types of tumors. However, the relationship between YBX1 and autophagy in non-small cell lung cancer (NSCLC) remains unclear. In this study, we analyzed the expression and clinical significance of YBX1 and markers of autophagy (LC3I/II) in NSCLC and examined their roles in regulating sensitivity to cisplatin in NSCLC. The retrospective analysis of patients with NSCLC indicated that YBX1 was positively correlated with autophagy. Increased levels of YBX1 or autophagy also observed in NSCLC cells compared with those in 16HBE cells. Compared to the controls, the knockdown of YBX1 expression suppressed autophagy, increased drug sensitivity and promoted apoptosis in response to cisplatin in NSCLC cells by targeting the p110ß promoter and inhibiting p110ß/Vps34/beclin1 signaling pathways. We also demonstrated in an in vivo study that the overexpressed YBX1 effectively increased NSCLC growth and progression and decreased the sensitivity to cisplatin by inducing autophagy in a xenograft tumor model, and these effects were concomitant with the increasing of p110ß and beclin1 expression. Collectively, these results show that YBX1 plays an essential role in autophagy in NSCLC.

MicroRNA-30e inhibits proliferation and invasion of non-small cell lung cancer via targeting SOX9.

Previous studies have reported that microRNA-30e (miR-30e) is dysregulated in multiple human cancers. However, the expression, functions and molecular mechanism of miR-30e in NSCLC remain unknown. In this study, we found that miR-30e was expressed at a low level in NSCLC tissues and cell lines. In NSCLC cell lines, enforced expression of miR-30e could inhibit cell proliferation and invasion in vitro. In addition, miR-30e negatively regulated SOX9 expression through directly binding to the 3'UTR of SOX9, and an inverse correlation was found between miR-30e and SOX9 mRNA expression in NSCLC tissues. Moreover, knockdown of SOX9 led to decreased proliferation and invasion of NSCLC cells. Taken together, miR-30e acts as a tumor suppressor in NSCLC, and inhibits cell proliferation and invasion possibly by directly targeting SOX9. These findings might provide novel therapeutic targets for NSCLC.

MACC1 overexpression in carcinoma­associated fibroblasts induces the invasion of lung adenocarcinoma cells via paracrine signaling.

Carcinoma­associated fibroblasts (CAFs) are essential for initiating lung cancer cell invasion and metastasis. An elevated MACC1 expression has been implicated in the progression of lung adenocarcinoma. Hitherto, the role of MACC1 in lung adenocarcinoma­derived CAFs remains unclear. In this study, CAFs isolated from the tissues of patients with lung adenocarcinoma expressed typical CAF markers (shown by immunohistochemical and immunofluorescence analysis) and exhibited enhanced migration and invasion abilities when co­cultured with A549 cells in a microfluidic model. MACC1­overexpressing CAFs not only demonstrated an increased invasion, but also exerted a promoting effect on the invasion of tumor cells. The reduced expression of MACC1 impaired the invasive ability of the CAFs. Western blot analysis and RT­qPCR analysis demonstrated that multiple paracrine pathways were activated in the MACC1­overexpressing CAFs. Overall, this study presents a novel role of MACC1 in CAF­induced lung adenocarcinoma cell invasion, which possibly occurs via paracrine signaling. Furthermore, MACC1 was indicated to be a potential therapeutic target for lung adenocarcinoma.

Neural-Network-Based Adaptive Backstepping Control With Application to Spacecraft Attitude Regulation.

This paper investigates the neural-network-based adaptive control problem for a class of continuous-time nonlinear systems with actuator faults and external disturbances. The model uncertainties in the system are not required to satisfy the norm-bounded assumption, and the exact information for components faults and external disturbance is totally unknown, which represents more general cases in practical systems. An indirect adaptive backstepping control strategy is proposed to cope with the stabilization problem, where the unknown nonlinearity is approximated by the adaptive neural-network scheme, and the loss of effectiveness of actuators faults and the norm bounds of exogenous disturbances are estimated via designed online adaptive updating laws. The developed adaptive backstepping control law can ensure the asymptotic stability of the fault closed-loop system despite of unknown nonlinear function, actuator faults, and disturbances. Finally, an application example based on spacecraft attitude regulation is provided to demonstrate the effectiveness and the potential of the developed new neural adaptive control approach.

Elevated MACC1 expression predicts poor prognosis in small invasive lung adenocarcinoma.

BACKGROUND: Patients with small (⩽ 2 cm) invasive lung adenocarcinoma are at high risk of poor prognosis and disease recurrence after complete surgical resection. Therefore, identification of high-risk individuals from these patients emerges as an urgent problem. Elevated MACC1 expression predicts a poor prognosis in multiple types of cancer that are independent of TNM staging. This study investigated the prognostic value of MACC1 expression in patients with small invasive lung adenocarcinoma. OBJECTIVE: The current study aimed to evaluate the relationship between MACC1 expression in patients' tumor tissue and prognosis in small invasive lung adenocarcinoma. METHODS: The records of 131 patients with small invasive lung adenocarcinoma who underwent complete surgical resection were reviewed. The MACC1 expression was detected by immunohistochemical staining in all specimens. Meanwhile, western blot and real-time quantitative PCR were used to examine the expression level of MACC1 in human lung adenocarcinoma cell lines. The effect of clinicopathological risk factors on patients' survival was analyzed using the Kaplan-Meier approach and multivariable Cox models. RESULTS: Elevated MACC1 expression was observed in 53 (40.5%) specimens, and in A549, H358, H460 and H322 lung adenocarcinoma cell lines. MACC1 overexpression was associated with differentiation (P= 0.005) and blood vessel invasion (P= 0.001). Compared with low MACC1 expression, elevated MACC1 expression was associated with significantly shorter overall survival (odds ratio = 6.515; 95% confidence interval: 1.382-30.721; P= 0.018) and disease-free survival (odds ratio = 3.270; 95% confidence interval: 1.117-9.569; P= 0.031). Multivariate analyses demonstrated high MACC1 expression is an independent risk factor of worse overall survival (odds ratio = 5.684; 95% confidence interval: 1.145-28.210; P= 0.034) and disease-free survival (odds ratio = 4.667; 95% confidence interval: 1.372-15.877; P= 0.014). CONCLUSION: MACC1 is an independent prognostic marker in patients with small invasive lung adenocarcinoma after complete surgical resection. Differential outcomes are associated with MACC1 expression level.

YB-1 regulates tumor growth by promoting MACC1/c-Met pathway in human lung adenocarcinoma.

Aberrant overexpression of the transcription/translation factor Y-box-binding protein (YB-1) is associated with poor prognosis of lung adenocarcinoma, however the underlying mechanism by which YB-1 acts has not been fully elucidated. Here, we reported that inhibition of YB-1 diminished proliferation, migration and invasion of lung adenocarcinoma cells. Interestingly, we identified metastasis associated in colon cancer-1 (MACC1) as a target of YB-1. Depletion of YB-1 markedly decreased MACC1 promoter activity and suppressed the MACC1/c-Met signaling pathway in lung adenocarcinoma cells. Additionally, chromatin immunoprecipitation (ChIP) assay demonstrated that YB-1 bound to the MACC1 promoter. Moreover, YB-1 was positively correlated with MACC1, and both proteins were over-expressed in lung adenocarcinoma tissues. The Cox-regression analysis indicated that high YB-1 expression was an independent risk factor for prognosis in enrolled patients. Furthermore, depletion of YB-1 attenuated tumorigenesis in a xenograft mouse model and reduced MACC1 expression in tumor tissues. Collectively, our data suggested that targeting YB-1 suppressed lung adenocarcinoma progression through the MACC1/c-Met pathway and that the high expression of YB-1/MACC1 is a potential prognostic marker in lung adenocarcinoma.