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Malignant pleural effusion (MPE) is a serious complication of advanced tumor, with relatively high morbidity and mortality rates, and can severely affect the quality of life and survival of patients. The mechanisms of MPE development are not well defined, but much research has been conducted to gain a deeper understanding of this process. In recent decades, although great progress has been made in the management of MPE, the diagnosis and treatment of MPE are still major challenges for clinicians. In this article, we provide a review of the research advances in the mechanisms of MPE development, diagnosis and treatment approaches. We aim to offer clinicians an overview of the latest evidence on the management of MPE, which should be individualized to provide comprehensive interventions for patients in accordance with their wishes, health status, prognosis and other factors.

Abstract Background Cancer stem cells (CSCs) play an important role in cancer initiation, relapse and metastasis. To date, no specific medicine has been found to target CSCs as they are resistant to most conventional therapies and proliferate indefinitely. Compound Kushen Injection (CKI) has been widely used for cancer patients with remarkable therapeutic effects in Chinese clinical settings for many years. This study focused on whether CKI could inhibit MCF-7 SP cells in vitro and in vivo. Methods The analysis of CKI on SP population and the main genes of Wnt signaling pathway were studied first. Then we studied the tumorigenicity of SP cells and the effects of CKI on SP cells in vivo. The mice inoculated with 10,000 SP cells were randomly divided into three groups (6 in each group) and treated with CKI, cisplatin and saline (as a control) respectively for 7 weeks. The tumor formation rates of each group were compared. The main genes and proteins of the Wnt signaling pathway were analyzed by RT-PCR and western blot. Results CKI suppressed the size of SP population (approximately 90%), and down-regulated the main genes of Wnt signaling pathway. We also determined that MCF-7 SP cells were more tumorigenic than non-SP and unsorted cells. The Wnt signaling pathway was up-regulated in tumors derived from SP cells compared with that in tumors from non-SP cells. The tumor formation rate of the CKI Group was 33% (2/6, P < 0.05), and that of Cisplatin Group was 50%(3/6, P < 0.05), whereas that of the Control Group was 100% (6/6).The RT-PCR and western blot results indicated that CKI suppressed tumor growth by down-regulating the Wnt/β-catenin pathway, while cisplatin activated the Wnt/β-catenin pathway and might spare SP cells. Conclusions It suggested that CKI may serve as a novel drug targeting cancer stem-like cells, though further studies are recommended.

This paper presents a feedforward control algorithm that combines the benefits of optimal iterative learning control (OILC) and model‐based feedforward control (MFC) using iterative feedforward tuning and input shaping filter (IFT‐ISF) for industrial motion systems. OILC effectively compensates for tracking errors in repeating tasks under actuator constraints. However, its performance deteriorates when the trajectory changes. In contrast, MFC can achieve high performance for varying trajectory tracking tasks, but its performance may degrade for constrained systems if the control force exceeds the actuator saturation boundary. The proposed algorithm aims to overcome these limitations to achieve optimal trajectory tracking performance for varying trajectories under actuator constraints. Simulation and experimental results demonstrate that the proposed algorithm achieves optimal tracking performance while complying with the actuator constraints. The algorithm provides a data‐driven approach without requiring the tedious process of model identification. By combining the benefits of OILC and IFT‐ISF, the proposed algorithm can achieve high‐performance trajectory tracking for both repeating and varying tasks under actuator constraints, making it suitable for industrial motion systems. [ABSTRACT FROM AUTHOR]

Emerging evidence suggests a tentative association between cathepsins and uterine leiomyoma (UL). Previous investigations have predominantly focused on the role of cathepsins in the metastasis and colonization of gynecological malignancies. Still, observational studies may lead to confounding and biases. We employed a bidirectional Mendelian randomization (MR) analysis to elucidate the causative links between various cathepsins and UL. Instrumental variables (IVs) of cathepsins and UL within the European cohort were from extant genome-wide association study datasets. Sensitivity assessments was executed, and the heterogeneity of the findings was meticulously dissected to affirm the solidity of the outcomes. Our findings reveal the association between cathepsin B (CTSB) and an elevated risk of developing UL (all cancers excluded) [Inverse Variance Weighted (IVW) method]: OR = 1.06, 95%CI [1.02, 1.11], P = 0.008895711. Although the association does not persist after multiple testing or Steiger filtering, this finding adds to our understanding of the causal relationship between CTSB of various cathepsins and UL (all cancers excluded) and may herald new therapeutic avenues for individuals affected by this condition. [ABSTRACT FROM AUTHOR]

Thermocells with high thermopower have received much attention in recent years owing to their capability of converting heat to electricity. In particular, endowing these thermocells with promising self-healability and stretchability after self-healing are of fundamental importance to self-powered wearable electronics. However, there is still a lack of such effective thermocells due to the contradictory characteristics of good self-healing properties and good thermopower enhancement. Herein, by employing a zwitterionic polymer (poly[2-(methacryloyloxy)-ethyl]dimethyl-(3-sulfo-propyl) ammonium hydroxide) P(SBMA), we have successfully fabricated a hydrogel thermocell with high self-healability (90%), stretchability after self-healing (325%) and enhanced thermopower (3.5 mV K−1). In detail, we have not only proposed and verified that the zwitterion-boosted thermopower is due to the selective interactions between the cation in SBMA and Fe(CN)64−, but we have also realized self-healing and stretchability after self-healing in a hydrogel thermocell. In addition, the thermocell is still self-healable at a low temperature of −10 °C upon the addition of LiCl. The applicability of the hydrogel thermocell as a self-powered wearable energy converter is demonstrated by stably lighting an LED lamp and by the thermovoltage output under extreme conditions, including self-healing and stretching after self-healing. This work provides an effective strategy to develop promising thermocells for self-powered wearable electronics. [ABSTRACT FROM AUTHOR]

The acquisition of vegetation coverage information is crucial for crop field management, and utilizing visible light spectrum vegetation indices to extract vegetation coverage information is a commonly used method. However, most visible light spectrum vegetation indices do not fully consider the relationships between the red, green, and blue bands during their construction, making it difficult to ensure the accurate extraction of coverage information throughout the crop's entire growth cycle. To rapidly and accurately obtain potato vegetation coverage information, drones were used in this study to obtain high-resolution digital orthoimages of potato growth stages. Based on the differences in the grayscale values of potato plants, soil, shadows, and drip irrigation belts, this study presents a combination index of blue and green bands (BGCI) and a combination index of red and green bands (RGCI). The vegetation index intersection method was used with 10 vegetation information indices to extract vegetation coverage, and the differences in extraction accuracy were compared with those of the maximum entropy method and bimodal histogram method. Based on the high-precision fraction vegetation coverage (FVC) extraction results, the Pearson correlation coefficient method and random forest feature selection were used to screen 10 vegetation and 24 texture features, and the top six vegetation indices most strongly correlated with the FVC were selected for potato growth stage FVC estimation and accuracy verification. A high-precision potato vegetation coverage estimation model was successfully established. This study revealed that during the potato tuber formation and expansion stages, the BGCI combined with the vegetation index intersection method achieved the highest vegetation coverage extraction accuracy, with overall accuracies of 99.61% and 98.84%, respectively. The RGCI combined with the vegetation index intersection method achieved the highest accuracy, 98.63%, during the maturation stage. For the potato vegetation coverage estimation models, the model based on the BGCI achieved the highest estimation accuracy (R2 = 0.9116, RMSE = 5.7903), and the RGCI also achieved good accuracy in terms of vegetation coverage estimation (R2 = 0.8987, RMSE = 5.8633). In the generality verification of the models, the R2 values of the FVC estimation models based on the BGCI and RGCI were both greater than 0.94. A potato vegetation coverage estimation model was constructed based on two new vegetation information indices, demonstrating good accuracy and universality. [ABSTRACT FROM AUTHOR]