Explore the vast range of titles available.

This article adopts a literature analysis method, taking the popular phenomenon of MBTI（Myers Briggs Type Indicator） in the current era of new media as the background, aiming to study the emergence and development process of MBTI from the perspective of audience psychology. The author conducts analytical research on communication psychology-related theories such as usage and satisfaction, selective contact hypothesis, and interest groups, deeply explores the application of MBTI in audience psychology research, analyzes its value in understanding audience behavior and psychological characteristics, and explores its challenges and prospects in practical applications. While MBTI has become popular, it has also brought some negative orientations due to its labeling, such as stereotypes and group anxiety. The fanaticism and initiative exhibited by individuals in the congenial group trigger group effects through communication. In the era of new media, with the rapid development of various media matrices, how to rationally view the emotional interactions of individuals and even groups constructed by MBTI, how to use the power of new media to correctly meet audience needs, and how to make the emergence and dissemination of MBTI conform to the benign trend of social development are all issues worthy of in-depth research.

Ferroptosis is an iron- and lipotoxicity-dependent form of regulated cell death (RCD). It is morphologically and biochemically distinct from characteristics of other cell death. This modality has been intensively investigated in recent years due to its involvement in a wide array of pathologies, including cancer, neurodegenerative diseases, and acute kidney injury. Dysregulation of ferroptosis has also been linked to various liver diseases and its modification may provide a hopeful and attractive therapeutic concept. Indeed, targeting ferroptosis may prevent the pathophysiological progression of several liver diseases, such as hemochromatosis, nonalcoholic steatohepatitis, and ethanol-induced liver injury. On the contrary, enhancing ferroptosis may promote sorafenib-induced ferroptosis and pave the way for combination therapy in hepatocellular carcinoma. Glutathione peroxidase 4 (GPx4) and system x c − have been identified as key players to mediate ferroptosis pathway. More recently diverse signaling pathways have also been observed. The connection between ferroptosis and other forms of RCD is intricate and compelling, where discoveries in this field advance our understanding of cell survival and fate. In this review, we summarize the central molecular machinery of ferroptosis, describe the role of ferroptosis in non-cancer hepatic disease conditions and discuss the potential to manipulate ferroptosis as a therapeutic strategy.

Tunnel-structured Na0.44MnO2 (NMO) has been extensively studied as a potential cathode for sodium-ion batteries (SIBs) due to its favorable cycling endurance, cost-effectiveness, environmental benignity, and notable air-moisture stability. However, limitations, such as sluggish ion diffusion kinetics, an insufficient Na+ storage capacity, and an unsatisfactory Jahn–Teller effect, impede its widespread application. To address these problems, this study proposes a co-doping strategy that involves the simultaneous introduction of a cation and an anion. The optimized cathode Na0.44Mn0.99Ni0.01O1.985F0.015 demonstrates remarkable rate capabilities with average discharge capacities of 136.2, 133.0, 129.6, 124.0, 115.9, and 95.8 mAh g−1 under current rates ranging from 0.1 to 5 C. Furthermore, it also exhibits exceptional long-term cyclability, retaining 86.5% and 89.4% capacity retention at 1 and 5 C after 200 and 400 cycles, respectively, accompanied by nearly 100% Coulombic efficiency. A comprehensive structural characterization and experimental analysis reveal that the synergistic incorporation of Ni and F can effectively adjust the lattice parameters and alleviate the Jahn–Teller distortion of the NMO cathode, thereby resulting in enhanced structural integrity, rapid ion transfer dynamics, and excellent sodium storage performance. Consequently, this investigation establishes a significant approach for optimizing tunnel-phase Mn-based cathodes through the synergistic effect of cation and anion co-doping, which promotes the practical implementation of advanced SIBs.

Potato early blight and late blight are devastating diseases that affect potato planting and production. Thus, precise diagnosis of the diseases is critical in treatment application and management of potato farm. However, traditional computer vision technology and pattern recognition methods have certain limitations in the detection of crop diseases. In recent years, the development of deep learning technology and convolutional neural networks has provided new solutions for the rapid and accurate detection of crop diseases. In this study, an integrated framework that combines instance segmentation model, classification model, and semantic segmentation model was devised to realize the segmentation and detection of potato foliage diseases in complex backgrounds. In the first stage, Mask R-CNN was adopted to segment potato leaves in complex backgrounds. In the second stage, VGG16, ResNet50, and InceptionV3 classification models were employed to classify potato leaves. In the third stage, UNet, PSPNet, and DeepLabV3+ semantic segmentation models were applied to divide potato leaves. Finally, the three-stage models were combined to segment and detect the potato leaf diseases. According to the experimental results, the average precision (AP) obtained by the Mask R-CNN network in the first stage was 81.87%, and the precision was 97.13%. At the same time, the accuracy of the classification model in the second stage was 95.33%. The mean intersection over union (MIoU) of the semantic segmentation model in the third stage was 89.91%, and the mean pixel accuracy (MPA) was 94.24%. In short, it not only provides a new model framework for the identification and detection of potato foliage diseases in natural environment, but also lays a theoretical basis for potato disease assessment and classification.

Corn seed materials of different quality were imaged, and a method for defect detection was developed based on a watershed algorithm combined with a two-pathway convolutional neural network (CNN) model. In this study, RGB and near-infrared (NIR) images were acquired with a multispectral camera to train the model, which was proved to be effective in identifying defective seeds and defect-free seeds, with an averaged accuracy of 95.63%, an averaged recall rate of 95.29%, and an F1 (harmonic average evaluation) of 95.46%. Our proposed method was superior to the traditional method that employs a one-pathway CNN with 3-channel RGB images. At the same time, the influence of different parameter settings on the model training was studied. Finally, the application of the object detection method in corn seed defect detection, which may provide an effective tool for high-throughput quality control of corn seeds, was discussed.

Hepatocellular death is a sensitive parameter for detecting acute liver injury (ALI) of toxic, viral, metabolic, and autoimmune origin. Ferroptosis has recently been implicated in carbon tetrachloride (CCl 4 )-induced ALI. However, the underpinning mechanism and mechanistic basis remain elusive. In this study, bicyclol, a proprietary hepatoprotectant in China, and ferroptosis-specific inhibitor ferrostatin-1 (Fer-1) were administered in CCl 4 -injured mice. A panel of ferroptosis-related markers, including mitochondria morphology, reactive oxygen species production, protein adducts in response to lipid peroxidation, and key modulators of ferroptotic process, was determined in vivo. Erastin-treated L-O2 hepatocytes were transfected with glutathione peroxidase 4 (GPx4) or nuclear factor erythroid 2-related factor 2 (Nrf2) siRNA to delineate the pathway of bicyclol against ferroptosis in vitro. As a result, CCl 4 led to iron accumulation, excessive reactive oxygen species production, enhanced lipid peroxidation, and characteristic morphological changes in mitochondria, along with a decrease in GPx4 and xCT protein levels in ALI mice liver, all of which were generally observed in ferroptosis. The use of Fer-1 further corroborated that ferroptosis is responsible for liver damage. Bicyclol exerted its hepatoprotection by preventing the aforesaid ferroptotic process. Furthermore, bicyclol alleviated erastin-induced cellular inviability, destruction, and lipid peroxidation in vitro. Knockdown of GPx4 diminished these protective activities against perturbations associated with ferroptosis in L-O2 hepatocytes. Additionally, Nrf2 silencing drastically reduced GPx4 levels, and further impeded the medicinal effects of bicyclol. In summary, positively regulating Nrf2-GPx4 axis by bicyclol can prevent ferroptosis in CCl 4 -induced ALI in mice.

IntroductionIn the process of rice production and storage, there are many defects in the traditional detection methods of rice appearance quality, but using modern high-precision instruments to detect the appearance quality of rice has gradually developed into a new research trend at home and abroad with the development of agricultural artificial intelligence.MethodsIn this study, we independently designed a fast automatic rice appearance quality detection system based on machine vision technology by introducing convolutional neural network and image processing technology. In this study, NIR and RGB images were generated into five-channel image data by superposition function, and image are preprocessed by combining the Watershed algorithm with the Otus adaptive threshold function. Different grains in the samples were labeled and put in the convolutional neural network for training. The rice grains were classified and the phenotype data were analyzed by selecting the optimal training model to realize the detection of rice appearance quality.Results and discussionThe experimental results showed that the resolution of the system could reach 92.3%. In the detection process, the system designed with this method not only reduces the subjectivity problems caused by different detection environments, visual fatigue caused large sample size and the inspector’s personal factors, but also significantly improves the detection time and accuracy, which further enhances the detection efficiency of rice appearance quality, and has positive significance for the development of the rice industry.

Background and Aims Digestive diseases, including gastrointestinal and liver disorders, are prevalent and contribute significantly to morbidity, healthcare costs, and reduced quality of life, particularly among middle‐aged adults. Frailty, characterized by reduced physiological reserve, and depression, a common psychological disorder, have both been linked to an increased risk of these conditions. However, the combined impact of frailty and depression on digestive diseases remains poorly understood. This study aimed to examine the combined effects and joint trajectories of frailty and depression on the risk of digestive diseases in middle‐aged adults and explore potential mechanisms of their interaction. Methods We conducted a prospective cohort study using data from the China Health and Retirement Longitudinal Study, involving 7876 participants aged 45 and above. Participants were classified into three frailty categories (robust, pre‐frail, frail) and assessed for depression. The incidence of digestive, gastrointestinal, and liver diseases was monitored over a median follow‐up of 9 years. We utilized Cox regression models to evaluate the individual and joint effects of frailty and depression on disease risk. Results During follow‐up, 2076 participants developed new digestive system diseases (26.36% incidence). Frailty and depression were independently associated with increased risks of digestive (hazard ratio [HR] for frail = 2.00, HR for depression = 1.61), gastrointestinal (HR for frail = 2.08, HR for depression = 1.67), and liver diseases (HR for frail = 2.14, HR for depression = 1.31). No significant multiplicative or additive interactions between the two were observed. Mediation analysis indicated that depression mediated 17.4% of the relationship between frailty and digestive diseases, whereas frailty mediated 18.8% of the relationship between depression and digestive diseases. The combined frailty and depression index improved predictive accuracy for all disease outcomes. In the joint trajectory analysis, the group with consistently higher depression scores and faster increases in the frailty index had the highest risk for all diseases. Conclusions Integrated assessment of frailty and depression should be prioritized in residual risk stratification and primary prevention strategies for digestive diseases. This study identifies the compounded impact of frailty and depression on the risk of digestive diseases, revealing that worsening frailty and depression significantly elevate the risk for gastrointestinal and liver disorders. Integrated assessments of frailty and depression may enhance early identification and intervention strategies for digestive health.

To address the challenges of low pesticide utilization, insufficient automation, and health risks in orchard plant protection, we developed an autonomous spraying vehicle using ArduPilot firmware and a robot operating system (ROS). The system tackles orchard navigation hurdles, including global navigation satellite system (GNSS) signal obstruction, light detection and ranging (LIDAR) simultaneous localization and mapping (SLAM) error accumulation, and lighting-limited visual positioning. A key innovation is the integration of an extended Kalman filter (EKF) to dynamically fuse T265 visual odometry, inertial measurement unit (IMU), and GPS data, overcoming single-sensor limitations and enhancing positioning robustness in complex environments. Additionally, the study optimizes PID controller derivative parameters for tracked chassis, improving acceleration/deceleration control smoothness. The system, composed of Pixhawk 4, Raspberry Pi 4B, Silan S2L LIDAR, T265 visual odometry, and a Quectel EC200A 4G module, enables autonomous path planning, real-time obstacle avoidance, and multi-mission navigation. Indoor/outdoor tests and field experiments in Sun Village Orchard validated its autonomous cruising and obstacle avoidance capabilities under real-world orchard conditions, demonstrating feasibility for intelligent plant protection.

Background Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, with limited treatment options in advanced stages. Liensinine, a natural alkaloid derived from Nelumbo nucifera , has shown promise as an anticancer agent. However, its underlying mechanisms, particularly in modulating tumor metabolism and immune responses, remain poorly understood. This study aimed to investigate the antitumor effects of Liensinine in HCC, focusing on its ability to modulate metabolic pathways, immune responses, and the tumor microenvironment. Methods HCC cell lines (HUH7 and Hep1-6) were treated with Liensinine in vitro to assess cell viability, migration, proliferation, and apoptosis. Metabolic reprogramming was analyzed through RNA sequencing, Seahorse metabolic assays, and glucose/lactate measurements. The effects on immune cells were studied by treating THP-1 macrophages and peripheral blood mononuclear cells (PBMCs) with conditioned media from Liensinine-treated cells. In vivo, subcutaneous xenograft and orthotopic liver cancer models were used to evaluate the therapeutic efficacy of Liensinine combination with radiotherapy and immunotherapy. Results Liensinine inhibited HCC cell viability, migration, and proliferation, promoting apoptosis and shifting metabolism from glycolysis to oxidative phosphorylation. This metabolic reprogramming was linked to the activation of the AMPK-HIF-1α axis and increased ROS production. Furthermore, Liensinine induced Endoplasmic reticulum (ER) stress, as evidenced by elevated levels of CHOP and ATF4, which contributed to AMPK activation and suppression of HIF-1α. Liensinine reduced PD-L1 expression, enhanced M1 macrophage polarization, and promoted CD8 + T cell infiltration into tumors. In vivo, Liensinine significantly suppressed tumor growth, reduced vascular density, and reshaped the immune microenvironment by promoting M1 macrophage polarization. Combination therapy with Liensinine, radiotherapy, and immunotherapy resulted in synergistic effects, including enhanced tumor cell apoptosis, increased immune cell infiltration, and improved therapeutic efficacy. Conclusion Liensinine exerts potent antitumor effects in HCC by reprogramming tumor metabolism, inducing ER stress, enhancing immune responses, and modulating the TME. The combination of Liensinine with immunotherapy and radiotherapy significantly improves therapeutic efficacy, suggesting its potential as a novel treatment strategy for HCC. Graphical abstract