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Inter-organizational knowledge flow and agent collaborative decision-making constitute mutually interdependent processes critical for organizational performance in complex environments. This study proposes a novel deep neural network-based framework that explicitly models the bidirectional coupling mechanism between knowledge propagation dynamics and multi-agent coordination. The architecture integrates graph attention networks for knowledge transfer modeling with multi-agent reinforcement learning for decision coordination, establishing coupling interfaces that enable dynamic adaptation between these subsystems. The model incorporates temporal decay mechanisms, attention-based knowledge path optimization, and closed-loop feedback that propagates decision outcomes back to reshape knowledge transfer patterns. Experimental validation on synthetic and real-world datasets demonstrates substantial performance improvements of 8–24% over state-of-the-art baselines across knowledge transfer accuracy, decision success rates, and coordination efficiency metrics. Deployment in a supply chain coordination scenario achieved 18.5% cost reduction, 71% stockout frequency decrease, and 42.7% inventory turnover improvement. The coupling quality correlation coefficient reached 0.812, confirming strong interdependencies between knowledge evolution and decision outcomes. This work advances theoretical understanding of organizational knowledge systems while providing practical tools for enhancing inter-organizational collaboration.

The low efficiency and fast degradation of devices from ink-jet printing process hinders the application of quantum dot light emitting diodes on next generation displays. Passivating the trap states caused by both anion and cation under-coordinated sites on the quantum dot surface with proper ligands for ink-jet printing processing reminds a problem. Here we show, by adapting the idea of dual ionic passivation of quantum dots, ink-jet printed quantum dot light emitting diodes with an external quantum efficiency over 16% and half lifetime of more than 1,721,000 hours were reported for the first time. The liquid phase exchange of ligands fulfills the requirements of ink-jet printing processing for possible mass production. And the performance from ink-jet printed quantum dot light emitting diodes truly opens the gate of quantum dot light emitting diode application for industry. Designing efficient and scalable quantum dot LEDs meeting industrial requirements remains a challenge. Here, the authors, by leveraging the liquid phase exchange of d-MX 2 ligands, present printed quantum dot LEDs with external quantum efficiency over 16% and half lifetime of more than 1,721,000 hours.

Biomarkers are measurable changes associated with the disease. Urine can reflect the changes of the body while blood is under control of the homeostatic mechanisms; thus, urine is considered an important source for early and sensitive disease biomarker discovery. A comprehensive profile of the urinary proteome will provide a basic understanding of urinary proteins. In this paper, we present an in-depth analysis of the urinary proteome based on different separation strategies, including direct one dimensional liquid chromatography–tandem mass spectrometry (LC/MS/MS), two dimensional LC/MS/MS, and gel-eluted liquid fraction entrapment electrophoresis/liquid-phase isoelectric focusing followed by two dimensional LC/MS/MS. A total of 6085 proteins were identified in healthy urine, of which 2001 were not reported in previous studies and the concentrations of 2571 proteins were estimated (spanning a magnitude of 10 6 ) with an intensity-based absolute quantification algorithm. The urinary proteins were annotated by their tissue distribution. Detailed information can be accessed at the “Human Urine Proteome Database” (www.urimarker.com/urine).

Advanced prostate cancer (PCa) often develops bone metastasis, for which therapies are very limited and the underlying mechanisms are poorly understood. We report that bone-borne TGF-β induces the acetylation of transcription factor KLF5 in PCa bone metastases, and acetylated KLF5 (Ac-KLF5) causes osteoclastogenesis and bone metastatic lesions by activating CXCR4, which leads to IL-11 secretion, and stimulating SHH/IL-6 paracrine signaling. While essential for maintaining the mesenchymal phenotype and tumorigenicity, Ac-KLF5 also causes resistance to docetaxel in tumors and bone metastases, which is overcome by targeting CXCR4 with FDA-approved plerixafor. Establishing a mechanism for bone metastasis and chemoresistance in PCa, these findings provide a rationale for treating chemoresistant bone metastasis of PCa with inhibitors of Ac-KLF5/CXCR4 signaling. The therapies for bone metastatic prostate cancer are limited and the underlying mechanisms are unclear. Here, the authors show that bone derived TGF-β induces acetylation of KLF5 (Ac-KLF5), and Ac-KLF5 promotes prostate cancer bone metastasis and resistance to docetaxel by upregulating CXCR4.

This study investigates the relationship between personality types among second language (L2) learners through a bibliometric analysis. Personality traits, particularly the Big Five, are recognized as key predictors of L2 success. However, despite numerous empirical findings, the strength and nature of these correlations often show significant inconsistencies. Utilizing CitNetExplorer and VOSviewer, this study analyzes 161 research articles sourced from the Web of Science database. The analysis highlights major contributors, organizations, and countries in this field, emphasizing the impactful work of highly cited scholars, as well as leading research regions. The findings indicate that Openness, Conscientiousness, and possibly Agreeableness are significantly correlated with L2 achievement, while Neuroticism tends to show marginal or no correlation. These general trends are complicated by methodological inconsistencies in measures of L2 achievement and personality assessment tools. This study advocates standardized protocols for cross-cultural research and suggests further exploration using alternative personality measures. Additionally, personalizing teaching strategies based on learners’ personality types may enhance L2 outcomes.

Background Ovarian cancer (OC) ranks fifth as a cause of gynecological cancer-associated death globally. Until now, the molecular mechanisms underlying the tumorigenesis and prognosis of OC have not been fully understood. This study aims to identify hub genes and therapeutic drugs involved in OC. Methods Four gene expression profiles (GSE54388, GSE69428, GSE36668, and GSE40595) were downloaded from the Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) in OC tissues and normal tissues with an adjusted P-value  < 0.05 and a |log fold change (FC)| > 1.0 were first identified by GEO2R and FunRich software. Next, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) analyses were performed for functional enrichment analysis of these DEGs. Then, the hub genes were identified by the cytoHubba plugin and the other bioinformatics approaches including protein-protein interaction (PPI) network analysis, module analysis, survival analysis, and miRNA-hub gene network construction was also performed. Finally, the GEPIA2 and DGIdb databases were utilized to verify the expression levels of hub genes and to select the candidate drugs for OC, respectively. Results A total of 171 DEGs were identified, including 114 upregulated and 57 downregulated DEGs. The results of the GO analysis indicated that the upregulated DEGs were mainly involved in cell division, nucleus, and protein binding, whereas the biological functions showing enrichment in the downregulated DEGs were mainly negative regulation of transcription from RNA polymerase II promoter, protein complex and apicolateral plasma membrane, and glycosaminoglycan binding. As for the KEGG-pathway, the upregulated DEGs were mainly associated with metabolic pathways, biosynthesis of antibiotics, biosynthesis of amino acids, cell cycle, and HTLV-I infection. Additionally, 10 hub genes (KIF4A, CDC20, CCNB2, TOP2A, RRM2, TYMS, KIF11, BIRC5, BUB1B, and FOXM1) were identified and survival analysis of these hub genes showed that OC patients with the high-expression of CCNB2, TYMS, KIF11, KIF4A, BIRC5, BUB1B, FOXM1, and CDC20 were statistically more likely to have poorer progression free survival. Meanwhile, the expression levels of the hub genes based on GEPIA2 were in accordance with those based on GEO. Finally, DGIdb database was used to identify 62 small molecules as the potentially targeted drugs for OC treatment. Conclusions In summary, the data may produce new insights regarding OC pathogenesis and treatment. Hub genes and candidate drugs may improve individualized diagnosis and therapy for OC in future.

A recurring target-site mutation identified in various pests and disease vectors alters the voltage gated sodium channel ( vgsc ) gene (often referred to as knockdown resistance or kdr ) to confer resistance to commonly used insecticides, pyrethroids and DDT. The ubiquity of kdr mutations poses a major global threat to the continued use of insecticides as a means for vector control. In this study, we generate common kdr mutations in isogenic laboratory Drosophila strains using CRISPR/Cas9 editing. We identify differential sensitivities to permethrin and DDT versus deltamethrin among these mutants as well as contrasting physiological consequences of two different kdr mutations. Importantly, we apply a CRISPR-based allelic-drive to replace a resistant kdr mutation with a susceptible wild-type counterpart in population cages. This successful proof-of-principle opens-up numerous possibilities including targeted reversion of insecticide-resistant populations to a native susceptible state or replacement of malaria transmitting mosquitoes with those bearing naturally occurring parasite resistant alleles. Insecticide resistance (IR) poses a major global health challenge. Here, the authors generate common IR mutations in laboratory Drosophila strains and use a CRISPR-based allelic-drive to replace an IR allele with a susceptible wild-type counterpart, providing a potent new tool for vector control.

Graphene and its derivatives hold a great promise for widespread applications such as field‐effect transistors, photovoltaic devices, supercapacitors, and sensors due to excellent properties as well as its atomically thin, transparent, and flexible structure. In order to realize the practical applications, graphene needs to be synthesized in a low‐cost, scalable, and controllable manner. Plasma‐enhanced chemical vapor deposition (PECVD) is a low‐temperature, controllable, and catalyst‐free synthesis method suitable for graphene growth and has recently received more attentions. This review summarizes recent advances in the PECVD growth of graphene on different substrates, discusses the growth mechanism and its related applications. Furthermore, the challenges and future development in this field are also discussed. Plasma‐enhanced chemical vapor deposition (PECVD) is one of the promising methods for controllable synthesis of graphene with the advantages of low growth temperature and being catalyst‐free. This review summarizes recent advance in the PECVD growth of graphene on different substrates, and discusses the growth mechanism and its related applications in electrical devices, supercapacitors, sensors, and so on.

As an important ecological security barrier in northern China, the Inner Mongolia Autonomous Region (hereinafter referred to as Inner Mongolia) is seriously affected by drought. It is of great significance to characterize the spatial distribution of drought and identify the influencing factors of drought. Due to complex interactions among drought driving factors, it is difficult to quantify the contribution of each driving factor to drought using linear correlation analysis alone. In this study, we used the Standardized Precipitation Evapotranspiration Index (SPEI) as a quantitative indicator of drought to discuss the spatiotemporal variation of drought during growing seasons in the Inner Mongolia from 2000 to 2018. We quantitatively characterized mode, scope, and intensity of changes in SPEI caused by drought-influencing factors such as weather, water, topography, soil, and human activities using the Geodetector and Geographically Weighted Regression (GWR) models. We concluded that about 20.3% of the region showed a downward trend in SPEI, with the fastest rate of decline in the central and western Inner Mongolia. Air temperature, precipitation, elevation, and distance to rivers are the main controlling factors in drought change, and the factor interactions showed nonlinear enhancement. The drought driving effect was obvious in Alxa League, Wuhai City, Ulanqab City, and Baotou City. The results will help us to understand the effects of the driving factors on drought and eventually help policymakers with water-resource management.

Mitochondrial bioenergetic deficits and their resulting glucose hypometabolism are the key pathophysiological modulators that promote neurodegeneration. However, there are no specific potential molecules that have been identified to treat neurological diseases by regulating energy metabolism and repairing mitochondrial damage. Pyruvate dehydrogenase (PDH) complex (PDC), which can be phosphorylated by pyruvate dehydrogenase kinase (PDK), is the gate‐keeping enzyme for mitochondrial glucose oxidation. In this study, a small‐molecule scutellarin (SG) is discovered that can significantly alleviate the neuropathological changes in hippocampal CA1 of cerebral hypoperfusion model rats, rescued the morphological changes of abnormal mitochondria, and restored mitochondrial homeostasis. Mitochondrial proteomics, energy metabolism monitoring, and 13 C‐metabolic flux analysis targeted SG activity on PDK2, thus regulating PDK‐PDC‐mediated glycolytic metabolism to TCA cycle during mitochondrial OXPHOS damage. The knockdown of PDK2 in the SK‐N‐SH cells validated that SG could rescue mitochondrial damage via the PDK‐PDC axis, promote the MMP level and reduce the mitochondria‐dependent apoptosis. Collectively, this study explored the novel therapeutic approach: the PDK‐PDC axis for neurological injury and cognitive impairment and uncovered the effect of SG on mitochondrial protection via the PDK‐PDC axis and mitochondrial glucose oxidation. The findings indicate that active components ameliorating mitochondrial bioenergetic deficits could be of significant value for neurological disease therapy.