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The analysis of basketball strategies has traditionally relied on manual observation and limited data. As tracking technology progresses, there is potential for applying Artificial Intelligence specifically to strategy, delivering insights into defensive techniques to the teams. This research aims to develop a hybrid machine learning model combining Long-Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN) to classify and analyze defensive basketball strategies, specifically identifying switch and trap plays. The study uses large-scale tracking data to understand the team’s defensive behavior better. The proposed hybrid model integrates LSTM to identify temporal features of players’ motion and CNN to recognize spatial patterns across the court. The model was trained and evaluated on the National Basketball Association’s (NBA) SportVU tracking data, which includes over 32,000 possessions. Basic operations included standardizing the player’s position and reformatting half-court representations into grids. Automatic annotations were evaluated based on accuracy, precision, recall, and F1 score and compared with manual annotations. When implemented independently, the hybrid model decided switches and traps with an overall accuracy of 91.4%, higher than basic methods such as LSTM and CNN. The spatial density approach and temporal sequence showed the deformations in defensive structures, and the hybrid model had immense benefits in distinguishing the situations that called for switches and traps. The proposed hybrid model successfully categorizes and identifies defensive basketball moves and provides coaches and players with a strong tool to evaluate defensive tactics. This investigation has demonstrated the importance of using supervised machine learning models for real-time tactical analysis in sports, and future research in automated strategy evaluation and game planning has been laid out.

Myocardial ischemia-reperfusion (I/R) is characterized by myocardial cell death and exacerbated inflammatory responses that seriously affect cardiac function and patient prognosis. Limonin is a natural compound extracted from citrus fruits and has various biological activities, including anti-inflammatory and antioxidant activities. However, the role and mechanism of action of limonin in myocardial I/R injury remain unclear. This study aimed to explore the effects and underlying mechanisms of action of limonin on myocardial cell pyroptosis and inflammatory responses in mouse myocardial I/R injury. By analyzing the GSE225105 dataset in the Gene Expression Omnibus database, differentially expressed genes in I/R injury were screened and combined with the target genes of limonin in the Comparative Toxicogenomics Database. In the experiments, The oxygen-glucose deprivation/reoxygenation (OGD/R) model was used to simulate I/R injury in experiments. Limonin significantly inhibited OGD/R-induced pyroptosis and the release of inflammatory factors in AC16 myocardial cells, and these effects could be reversed by the caspase-3/gasdermin E (GSDME) pathway activator triclabendazole. Using experiments, we established a myocardial I/R model in C57BL/6 mice and found that limonin pretreatment improved cardiac function-related indicators, reduced myocardial tissue damage and inflammatory responses, inhibited apoptosis, and reduced myocardial fibrosis. This mechanism is closely related to the inhibition of caspase-3/GSDME pathway activation. This study revealed the protective effects of limonin in reducing myocardial I/R injury by inhibiting the caspase-3/GSDME pathway, thereby providing a theoretical basis for the development of limonin-based myocardial protection strategies.

The flexibility of the joint drive system of an industrial robot can cause vibration at the end part, which can lead to motion errors. A method to predict the vibration during the motion of the robot arm is proposed considering the robot joint flexibility. The method combines the internal transfer function of the drive system and the identification of parameters under external excitation. Firstly, the dynamics of the robot joint system are modeled by a double inertia elastic system. The joint system transfer function from the electromagnetic torque to the arm vibration is obtained according to the dynamics model. To solve the unknown parameters in the transfer function, a vibration dynamics model of the joint arm under the external forces on the arm is developed. According to this model, the equivalent stiffness, damping and load inertia of the joint can be obtained by the direct parametric method. Then, the vibration spectrum of the robot arm is derived from the motor electromagnetic torque and joint dynamics models were used to predict the vibration spectrum of the robot arm. The experiments were conducted on a single-joint robot testbed, and on an articulated industrial robot. In both experiments, the key parameters in the system were determined by impact experiments. Then, the vibration signal of the arm during the robot motion was obtained by electromagnetic torque prediction. The predicted vibration signals are analyzed in comparison with the actual vibration signals. The experimental results both show the validity of the vibration prediction.

Grassland degradation received considerable concern because of its adverse impact on agronomic productivity and its capacity to provide goods and service. Climate change and human activities are commonly recognized as the two broad underlying drivers that lead to grassland degradation. In this study, a comprehensive method based on net primary productivity (NPP) was introduced to assess quantitatively the relative roles of climate change and human perturbations on worldwide grassland degradation from 2000 to 2010. The results revealed that at a global scale, 49.25 % of grassland ecosystems experienced degradation. Nearly 5 % of these grasslands experienced strong to extreme significant degradation. Climate change was the dominant cause that resulted in 45.51 % of degradation compared with 32.53 % caused by human activities. On the contrary, 39.40 % of grassland restoration was induced by human interferences, and 30.6 % was driven by climate change. The largest area of degradation and restoration both occurred in Asia. NPP losses ranged between 1.40 Tg C year⁻¹ (in North America) and 13.61 Tg C year⁻¹ (in Oceania) because of grassland degradation. Maximum NPP increase caused by restoration was 17.57 Tg C year⁻¹ (in North America). Minimum NPP was estimated at 1.59 Tg C year⁻¹ (in Europe). The roles of climate change and human activities on degradation and restoration were not consistent at continental level. Grassland ecosystems in the southern hemisphere were more vulnerable and sensitive to climate change. Therefore, climate change issues should be gradually integrated into future policies and plans for domestic grassland management and administration.

Besides aroma and taste, the color of dry tea leaves, tea infusion, and infused tea leaves is also an important index for tea quality. Shading can significantly increase the chlorophyll content of tea leaves, leading to enhanced tea leaf coloration. However, the underlying regulatory mechanism remains unclear. In this study, we revealed that the expressions of chlorophyll synthesis genes were significantly induced by shading, specially, the gene encoding protochlorophyllide oxidoreductase ( CsPOR ). Indoor control experiment showed that decreased light intensity could significantly induce the expression of CsPOR , and thus cause the increase of chlorophyll content. Subsequently, we explored the light signaling pathway transcription factors regulating chlorophyll synthesis, including CsPIFs and CsHY5. Through expression level and subcellular localization analysis, we found that CsPIF3-2, CsPIF7-1, and CsHY5 may be candidate transcriptional regulators. Transcriptional activation experiments proved that CsHY5 inhibits CsPORL-2 transcription. In summary, we concluded that shading might promote the expression of CsPORL-2 by inhibiting the expression of CsHY5 , leading to high accumulation of chlorophyll in tea leaves. The results of this study provide insights into the mechanism regulating the improvements to tea plant quality caused by shading.

Amino acids contribute to the nutritional value and quality of black tea. Fermentation is the most important stage of the black tea manufacturing process. In this study, we investigated protein degradation and proteinaceous amino acid metabolism associated with enzymatic reactions during fermentation in the black tea manufacturing process. The results showed that the concentrations of both protein and free amino acids decreased during fermentation. We also confirmed that proteins were broken down into free amino acids by artificially synthesized dipeptide benzyloxycarbonyl glutamyl-tyrosine (Z-Glu-Tyr). Metabolites of the amino acid metabolic pathway increased significantly during fermentation. Furthermore, we confirmed that free amino acids were degraded to volatile compounds in a tracer experiment with the isotope precursor. These results provide information that will help black tea manufacturers improve the quality of black tea.

Pseudomonas aeruginosa (P. aeruginosa), one of the dangerous multidrug resistance pathogens, orchestrates virulence factors production through quorum sensing (QS). Since the exploration of QS inhibitors, targeting virulence to circumvent bacterial pathogenesis without causing significant growth inhibition is a promising approach to treat P. aeruginosa infections. The present study has evaluated the anti-QS and anti-infective activity of epigallocatechin-3-gallate (EGCG), a bioactive ingredient of the traditional green tea, against P. aeruginosa. EGCG showed significant inhibitory effects on the development of biofilm, protease, elastase activity, swimming, and swarming motility, which was positively related to the production of C4-AHL. The expression of QS-related and QS-regulated virulence factors genes was also evaluated. Quantitative PCR analysis showed that EGCG significantly reduced the expression of las, rhl, and PQS genes and was highly correlated with the alterations of C4-AHL production. In-vivo experiments demonstrated that EGCG treatment reduced P. aeruginosa pathogenicity in Caenorhabditis elegans (C. elegans). EGCG increased the survival of C. elegans by 23.25%, 30.04%, and 36.35% in a dose-dependent manner. The findings of this study strongly suggest that EGCG could be a potential candidate for QS inhibition as an anti-virulence compound against bacterial infection.

Organosulfates (OSs) have been widely detected in marine aerosols and have various potential formation pathways in the atmosphere. However, the key formation mechanism of OSs in the marine environment remains unclear. Here, by combining field measurements, laboratory experiments, and model calculations, we suggest that the surface spontaneous oxidation of sea spray aerosol (SSA) particles produces OSs rapidly and is the dominant formation pathway of OSs in the marine atmosphere. SSA microdroplets provide a large surface area for the spontaneous formation of OH radicals, inducing the oxidization of dimethyl sulfide into sulfate (SO 4 2– ), sulfuric acid, and organic acids, thereby acidifying the droplets. Subsequently, SO 4 2– reacts with dissolved alcohols under such acidic conditions to produce OSs. This process is fast enough to be a major source of detected OSs in the aerosol samples collected in the marine atmosphere. This pathway contributes to a global OS production of 13.96 ± 10.99 Tg yr –1 , comparable to global isoprene-derived OS production. This study reveals that rapid secondary processes are the main source of OSs in the marine atmosphere and highlights the important role of the droplet surface spontaneous oxidation process in atmospheric chemistry over the ocean. Organosulfates can rapidly form at the surfaces of sea spray droplets via the spontaneous oxidation of dimethyl sulfide and alcohols, providing a previously overlooked pathway in the marine sulfur cycle.

Glioblastoma multiform (GBM) is the most common malignant primary brain tumor in adults. Radiotherapy plus concomitant and adjuvant TMZ chemotherapy is the current standard of care for patients with GBM. Matrix metalloproteinases (MMPs), a family of zinc-dependent endopeptidases, are key modulators of tumor invasion and metastasis due to their ECM degradation capacity. The aim of the present study was to identify the most informative MMP member in terms of prognostic and predictive ability for patients with primary GBM. The mRNA expression profiles of all MMP genes were obtained from the Chinese Glioma Genome Atlas (CGGA), the Repository for Molecular Brain Neoplasia Data (REMBRANDT) and the GSE16011 dataset. MGMT methylation status was also examined by pyrosequencing. The correlation of MMP9 expression with tumor progression was explored in glioma specimens of all grades. Kaplan-Meier analysis and Cox proportional hazards regression models were used to investigate the association of MMP9 expression with survival and response to temozolomide. MMP9 was the only significant prognostic factor in three datasets for primary glioblastoma patients. Our results indicated that MMP9 expression is correlated with glioma grade (p<0.0001). Additionally, low expression of MMP9 was correlated with better survival outcome (OS: p = 0.0012 and PFS: p = 0.0066), and MMP9 was an independent prognostic factor in primary GBM (OS: p = 0.027 and PFS: p = 0.032). Additionally, the GBM patients with low MMP9 expression benefited from temozolomide (TMZ) chemotherapy regardless of the MGMT methylation status. Patients with primary GBMs with low MMP9 expression may have longer survival and may benefit from temozolomide chemotherapy.

Sea cucumbers are predominant deposit feeders in benthic ecosystems, providing protective benefits to coral reefs by reducing disease prevalence. However, how they receive sufficient nutrition from seabed sediments remains poorly understood. Here, we investigate Holothuria leucospilota , an ecologically significant tropical sea cucumber, to elucidate digestive mechanisms underlying marine deposit-feeding. Genomic analysis reveals intriguing evolutionary adaptation characterized by an expansion of digestive carbohydrase genes and a contraction of digestive protease genes, suggesting specialization in digesting microalgae. Developmentally, two pivotal dietary shifts, namely, from endogenous nutrition to planktonic feeding, and from planktonic feeding to deposit feeding, induce changes in digestive tract enzyme profiles, with adults mainly expressing carbohydrases and lipases. A nuanced symbiotic relationship exists between gut microbiota and the host, namely, specific resident bacteria supply crucial enzymes for food digestion, while other bacteria are digested and provide assimilable nutrients. Our study further identifies Holothuroidea lineage-specific lysozymes that are restrictedly expressed in the intestines to support bacterial digestion. Overall, this work advances our knowledge of the evolutionary innovations in the sea cucumber digestive system which enable them to efficiently utilize nutrients from seabed sediments and promote food recycling within marine ecosystems. Sea cucumbers are predominant deposit feeders in benthic ecosystems. This study elucidates the mechanisms within the sea cucumber digestive system and their symbiotic microbiome which enable them to efficiently utilize nutrients from seabed sediments.