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In the current study, N-doped apple tree branch-based biochar-supported Co/CoO catalyst (Co/CoO@NBCs) was prepared using an impregnation-pyrolysis synergistic strategy, which addressed the issues of easy aggregation, poor stability, and low specific surface area of the Co/CoO catalyst. The characterization results show that Co/CoO@NBCs has a large specific surface area (1871.02 m2/g), a developed pore structure (0.99 cm3/g), and Co exists in the form of Co atoms and CoO. Under conditions of 0.25 mM peroxymonosulfate (PMS), 10 mg of catalyst, and room temperature, the degradation rate of norfloxacin (NOR, 30 mg/L) reached equilibrium within 70 min, with a removal rate of 99.06%. Besides the strong alkali condition (pH = 11) and the presence of HCO3-, the removal rate of NOR by Co/CoO@NBCs in other pH ranges and in anionic environments can still exceed 73%. Furthermore, analysis of the degradation mechanism shows that the active sites of Co0 and Co2+ can activate PMS to produce reactive oxygen species, with O2-• and 1O2 serving as the main active substances involved in NOR degradation. Additionally, tests with real water systems and cycling experiments further demonstrate that Co/CoO@NBCs have practical application potential. This work offers new insights into designing heterogeneous catalysts with multiple active sites for wastewater treatment.

The existing literature on whether subchondral bone injections in knee osteoarthritis is advisable for relieving patient pain is minimal and the level of evidence is low. A recent case series (2023) analyzed 30 individuals with knee OA (Kellgren-Lawrence 2-3). It showed that combined intraarticular and subchondral BMAC (bone marrow aspirate concentrate injections) provided clinical and imaging benefits up to 24 months for the treatment of symptomatic knee OA, with a low failure rate, and a significant reduction of bone marrow edema. Besides, VAS (visual analog scale) pain worsened at the final follow-up, although remained lower compared to the baseline value. Although some studies mention that subchondral bone injections can relieve pain in mild/moderate knee OA, it does not seem reasonable to advise it until better-designed research can confirm the preliminary studies discussed in this article.

Toll-like receptor 8 (TLR8) is crucial for detecting viral and bacterial ssRNA in mammals. However, its functional characteristics in early vertebrates remain largely unclear. Here, we employed the economically important fish Ctenopharyngodon idella, which harbors two TLR8 homologs (CiTLR8a/b), as a representative model. CiTLR8a/b are trafficked to early endosomes and lysosomes by UNC93B1, where they dynamically form homodimers and heterodimer, and bind ssRNA and dsRNA. Upon ligand binding, they first recruit MyD88, then TIRAP as adaptors. Unexpectedly, CiTLR8a enhances viral replication by suppressing downstream IFN, NF-κB, and AP-1 pathways in vitro and in vivo. In contrast, CiTLR8b is signaling-defective despite ligand binding and adaptor recruitment. Most strikingly, heterodimerization with signaling-inert CiTLR8b switches CiTLR8a into an antiviral sensor by remodeling intracellular TIR-domain conformation through extracellular LRR-ligand interaction. Further, structural and mutagenesis analyses identify critical functional determinants: specific residues (CiTLR8a-V116/S164; CiTLR8b-S43/N790) required for dsRNA binding, and key N-glycosylation sites (N138/N189) and cysteines (C3/C4/C6/C7) in CiTLR8a responsible for its proviral functions, with Cys6/Cys7 being critical for CiTLR8a/b proper localization. TLR8 evolution follows a stepwise pattern: absent in cyclostomes, it emerges in jawed vertebrates and expands via lineage-specific duplications (whole-genome in teleosts; tandem in amphibians/reptiles), is lost in avians, and persists as a single copy in mammals. Notably, Cyprinid TLR8 can bind dsRNA besides ssRNA. Collectively, our findings elucidate the functions, adaptive mechanisms, and evolutionary trajectory of TLR8 in lower vertebrates, uncovering a unique regulatory system involving its two homologs. These results offer a new perspective on how TLR evolution shapes vertebrate immune system.

Diabetic kidney disease (DKD) is a serious condition associated with diabetes, and the role of uric acid (UA) in its development remains debated. This study used a Mendelian randomization (MR) analysis, epidemiological validation, transcriptome data mining and animal study to assess the causal relationship between high serum uric acid (HUA) and DKD. Meanwhile, differential expression analysis of lactate-related genes were conducted. Besides, the suggested lactylation associated genes was verified in vivo and vitro. MR shows that gene-predicted serum uric acid level was positively correlated with the risk of DKD (OR = 1.25, 95% CI: 1.01-1.54, P = 0.0396). The finding was further supported by US National Health and Nutrition Survey data. Lactylation associated transcriptome analysis identified associated genes, HMOX1, OGDH, and SPP1. In type 1 and type 2 diabetes HUA mouse model, the expression of HMOX1, OGDH, and SPP1 was significantly enhanced and HUA treatment significantly aggravated renal injury. In podocyte cell line, inhibition of the expression of HMOX1, OGDH, and SPP1 significantly improve the podocyte function. This study provides evidence that high serum uric acid is associated with DKD, and indicates HMOX1, OGDH, and SPP1 as possible important molecules linked to disease progression. These findings offer new biomarkers and potential therapeutic targets for early diagnosis and intervention of DKD.

Numerous studies identified the positive effects of GenAI tools in the formal language learning settings, but further efforts are still recommended to explore the use of GenAI tools in the Informal Digital Learning of English (GenAI-IDLE). To address the research gap, this study intends to figure out how GenAI-IDLE alleviate the second language (L2) demotivation through autonomous learning behavior and academic buoyancy based on the Basic Psychological Needs Theory and the Organismic Integration Theory. The approach of structural equation modelling was adopted to analyze the questionnaire data among first-year college students. Confirmatory factor analysis and serial mediation analysis were conducted through Mplus 8.3. The findings revealed positive effects of GenAI-IDLE on autonomous learning behavior and academic buoyancy, along with a negative correlation between GenAI-IDLE and L2 demotivation. Besides, the chain mediation of autonomous learning behavior and academic buoyancy was identified to mitigate the L2 demotivation through GenAI-IDLE activities. Informed by these results, the present study offers both theoretical and practical implications. It not only draws on the Basic Psychological Needs Theory and the Organismic Integration Theory to explain the role of GenAI-IDLE practice, but also sheds light on optimising the design of GenAI-IDLE activities to address the demotivation issue from both behavioral and psychological perspectives.

Plants face significant threats from pathogens while chemical pesticides remain the primary method for disease control. However, excessive use of chemical pesticides has led to increased pathogen resistance and environmental hazards, highlighting the urgent need for sustainable alternatives such as plant immune priming agents. Among these, levan have shown great potential compared to commercial priming agents, but their high degree of polymerization (DP) results in low solubility. To address this, we synthesized levan-derived oligosaccharides (LOS) with reduced DP. However, if LOS could induce plant immunity and what's the priming mechanism remain unclear. This study evaluated the effects in foliar applications on melon (Cucumis melo L.) and watermelon (Citrullus lanatus Thunb.), focusing on two pathogens, Botrytis cinerea (B. cinerea) and Phytophthora capsica (P. capsica). While LOS did not significantly reduce lesion area caused by B. cinerea in either crop, it reduced the lesion area caused by P. capsica by more than 65% in melons and watermelons. LOS also decreased disease severity by increasing the proportion of mild lesions (grades 1-2) and reducing the proportion of severe lesions (grades 3-4). Compared to CK, foliar application of LOS to single-leaf melons and watermelons did not significantly alter lesion area of untreated leaves, but it did significantly reduce the proportion of severe disease symptoms. Besides, LOS showed efficacy across multiple melon and watermelon cultivars while also demonstrated better immune effects compared to commercially available elicitors. Although LOS did not significantly improve melon quality compared to CK, it significantly increased the soluble solids content in watermelon fruit by 16%. LOS spraying promoted reactive oxygen species production, with H₂O₂ levels increasing 4.8-fold in melons and 44.5% in watermelons at 72 h. Physiological analysis revealed significant enhancement in the activity of antioxidant enzymes, such as catalase, peroxidase, and polyphenol oxidase in both crops. Besides, lignin content remained elevated in both melon types compared to CK, enhancing the plant's physical defense capabilities. Furthermore, gene expression analysis showed upregulation of several immunity-related genes (RBOHD, PR1, PAL, NPR1), indicating activation of the salicylic acid and jasmonic acid signaling pathways. These results suggest that LOS, as a broad-spectrum priming agent, enhances disease resistance in watermelons and melons, making it a promising sustainable solution for plant disease management.

Sulfur(VI) fluorides based on sulfur(VI) fluoride exchange (SuFEx) chemistry have demonstrated their unique versatility and high efficiency in the field of medicinal chemistry. Acting as both covalent and hydrogen bond donors, the novel N-CF2H sulfamoyl fluoride will enhance the binding strength between drugs and receptors in organism, thereby injecting new vitality into the research of targeted drugs. Herein, we report the two-step synthesis of N-CF2H sulfamoyl fluorides from primary amines via successive fluorosulfonylation and insertion of difluorocarbene. This method shows broad scope, provides a platform for rapidly generating N-CF2H sulfamoyl fluorides by virtue of the diversity and availability of amines. The stability of N-CF2H sulfamoyl fluorides was tested in aqueous environment at different pH, showing that most compounds remained >95% intact for 72 h. As a novel SuFEx building block, N-CF2H sulfamoyl fluoride shows chemoselectivity toward phenol and does not react with amines and alcohols. Besides, N-CF2H sulfamoyl fluorides were subjected to debenzylation and amide-bond-formation reactions to generate peptides, Sitagliptin derivative and bioactive alkylamine. Finally, N-CF2H sulfamoyl fluoride underwent successful F-18 labeling. With the reported syntheses, we believe that N-CF2H sulfamoyl fluoride will soon be practically applied in drugs, covalent targeted radioligand, F-18 PET tracers, electrolyte in general.

BackgroundIntervertebral disc degeneration (IVDD) is a prevalent musculoskeletal condition that affects the spine, particularly in the lumbar region and induces low back pain. Tuina therapy has been widely utilized to alleviate low back pain for a long time. However, the specific mechanism underlying this effect of Tuina therapy on IVDD remains unclear.MethodsThe rat IVDD model was established by puncturing caudal vertebrae. Magnetic resonance imaging, Hematoxylin and eosin staining, and Safranin O staining were operated to assess histological changes. RT-qPCR and Western blot were carried out to measure mRNA and protein levels, respectively. Prussian Blue Staining and an iron assay kit were utilized to measure iron content in NP tissues.ResultsThe chaotic fibrous tissues, loss of NP tissues and cartilaginous components were observed in IVDD rats, and these pathological changes were alleviated by Tuina therapy. Besides, the mRNA and protein levels of inflammatory factors (TNF-alpha, IL-1beta, and IL-6) were significantly upregulated in IVDD group compared to sham group, and Tuina therapy reduced the release of these inflammatory factors. Moreover, the increased content of iron ion in IVDD rats was also reduced by Tuina therapy. Furthermore, the upregulation of ACSL4 protein, the downregulation of GPX and FTH proteins in IVDD groups were reversed by Tuina therapy.ConclusionsTuina therapy prevented IVDD aggravation by suppressing inflammatory response and ferroptosis in rat model.

Aquaculture is a rapidly growing sector in the global food production chain as a recognized fundamental source of high-quality proteins. One of the crucial tasks in aquaculture is phenotype prediction. While machine learning research has mainly focused on classification tasks on Big Data, in many bioinformatics applications, including aquaculture, the real challenge behind prediction problems is dealing with small sample and high-dimensional data. In such contexts, it is in fact common that the number of genetic features (such as SNPs) far exceeds the sample size. As a test case, this study focuses on the prediction of resistance to Viral Nervous Necrosis(VNN) from a population of European sea bass. We explore a range of machine learning techniques, from established methods such as Support Vector Machines and Gradient Boosting, to increasingly popular Deep Learning Approaches, also including a variant of image-based classification based on Chaos Game Representation. Besides standard training-test partitioning, we also considered a more challenging partition of the dataset that maximize the genomic distance among training and testing set to better reflect the kind of generalization problem encountered in breeding practice due to data scarcity typical of non-model species. Although all the animals belong to the same population, this approach offered the most appropriate way to ensure the procedure was sufficiently challenging given the available data. We assessed the performance of learning approaches in different scenarios, reducing the data dimensionality by selecting SNPs on the basis of functional information. Our experiments confirmed the difficult nature of this association task. However, each tested tool showed promising results in at least one scenario. While predicting disease susceptibility remains a challenging task for breeding programs, within the boundaries of the tested scenarios, our results show that machine learning approaches, combined with a controlled amount of additional functional information, can help mitigate the issues arising from high dimensional, low sample size datasets typical in the study of non-model species.

Type II L-asparaginases are important therapeutic agents for treating childhood leukemia, but numerous side effects of these enzymes, besides neutralization by antibodies due to repeated injection, prompt extensive research to identify alternatives in other classes of this enzyme. Among the six asparaginase-producing strains, the best-producing isolate was identified as Glutamicibacter. The asparaginase and glutaminase activities in culture supernatant were 15 U/ml and 1.5 U/ml, respectively. The full-length asparaginase gene was sequenced, and the phylogenetic tree revealed strong clustering with recently identified class 3 asparaginases from Rhizobium etli. The presence of key residues from Class 3 ReAV and ReAIV further confirms this similarity. The AlphaFold 3 server confidently predicted the enzyme's 3D structure. Molecular docking of L-asparagine and L-glutamine using Rosetta revealed binding energies of -9.99 REU for both substrates that were higher than those of the Type IV and V enzymes. Molecular dynamics results indicated that enzyme-Asn was more stable than enzyme-Gln with average RMSD values of 0.33 nm and 0.44 nm, respectively. Enzyme-Asn reached a relatively stable plateau after 0.05 ns, whereas enzyme-Gln showed a sudden jump after 0.75 ns, indicating the separation of glutamine from the protein. A comparison of the antigenic determinants of GlAVI with those of ReAIV, ReAV, EcAII, and ErAII revealed that GlAVI exhibited lower immunogenicity than the other enzymes. Allergenic epitopes were predicted using bioinformatics, demonstrating that nonallergenic epitopes cover a significant portion of the enzyme. The newly isolated Glutamicibacter L-asparaginase appears to be a new type of class 3 asparaginases with high potential for novel therapeutic drug development because of its less and dissimilar immunological properties.

The Shono oxidation stands as a premier electrochemical method for the α-C-H functionalization of amines. While glycine esters serve as ideal substrates with immense synthetic potential, their electrochemical derivatization has historically been restricted primarily to C-C and C-P bond formation. Herein, we report the first electrochemical strategy for the direct N-heteroarylation of α-C-H bonds in Gly-containing natural products, drug molecules, and peptides via a controllable anodic oxidation pathway under transition-metal-free conditions. At the same time, modified target product 3x exhibited good inhibitory activities toward the SKOV3 and MDA-MB-231 cell lines, with IC50 values of 9.94 ± 1.46 and 17.11 ± 3.67, respectively, far superior to the antitumor activities of unmodified substrate 1a (IC50 > 50). Therefore, besides synthetic applications, this method also provides new possibilities for discovering potentially bioactive molecules.

Lactate is implicated in several brain diseases; however, its precise role in depression remains to be further elucidated. The current study looks into the role of lactate-associated genes in depression, along with their diagnostic and therapeutic potential. Genes related to lactate were obtained from the Harmonizome database. Depression-related datasets were acquired from the GEO database, and differentially expressed genes (DEGs) were identified using the limma package. The overlapping genes from the DEGs and lactate-related genes were subjected to enrichment analyses using enrichR. The correlation analysis confirmed the validation of screened core genes via the random forest algorithm. Cytoscape was used for the construction of transcription factors and miRNA-based gene regulatory networks. Receiver operating characteristics (ROC) analysis was used to evaluate diagnostic performance. Molecular docking was performed to predict drug interactions. The lactate-related DEGs were seen to be implicated in processes like negative regulation of the apoptotic process and NOD-like receptor signaling pathways. TLR4 and RB1 were identified as core genes, showing elevated expression and strong diagnostic potential in depression. In addition to the positive correlation, TLR4 was shown to be the target of multiple miRNAs, while RB1 was unveiled to be the target of several transcription factors. Besides, the binding of RB1 (protein: 6C2R) to topotecan and dexamethasone was confirmed, while TLR4 (protein: 4R7N) could bind with Tlr4-IN-C34 and resatorvid. This study successfully identified TLR4 and RB1 as core lactate-related genes in depression, providing a new perspective on elucidating the role of lactate in the pathogenesis of depression.

Activating mutations in NOTCH1 are frequent in T-cell acute lymphoblastic leukemia (T-ALL) and, in the absence of alterations in RAS or PTEN, are associated with favorable prognosis. Besides classical heterodimerization and PEST domain mutations, juxtamembrane internal tandem duplications (JME-ITDs) represent a third class of activating variants. Their intermediate size and sequence composition can challenge short-read next-generation sequencing and variant calling algorithms, leading to underdetection in routine diagnostics. An index case of newly diagnosed T-ALL harboring a NOTCH1 juxtamembrane insertion that was discordantly detected by variant callers during routine targeted NGS (Hematology OncoKitDx v2) prompted further analysis. The variant was evaluated using VarDict and VarScan2, followed by manual inspection with IGV and orthogonal confirmation by Sanger sequencing. To further assess variability in the detection of JME-ITDs, six additional BAM files from patients with previously confirmed variants were reanalyzed using VarDict, VarScan2, Mutect2, and Pindel. In the index case, VarDict detected a 51-bp NOTCH1 JME-ITD (c.5168-2_5216dup) that was missed by VarScan2 and confirmed by Sanger sequencing. Reanalysis of the seven cases showed that Mutect2 and VarDict detected all JME-ITDs (100%), VarScan2 identified only three (42.8%), and Pindel detected six mutations (85.7%). These results reflect differences in algorithmic strategies where haplotype-based callers incorporate soft-clipped and split reads, whereas pileup-based discard them. Detection of NOTCH1 JME-ITDs depends strongly on variant-calling strategy. Combining haplotype-based callers with split-read structural variant tools may reduce false negatives and improve detection of clinically relevant insertions in diagnostic NGS pipelines.

This work was dedicated to the synthesis and characterization of Fe2O3:ZnO/MWCNTs (multiwalled carbon nanotubes) nanocomposite as a high-performance humidity sensor. The Fe2O3:ZnO composite was prepared by a simple and inexpensive solid-phase synthesis method by using thermal annealing. The sensor fabrication involved the deposition of the Fe2O3:ZnO thin film and MWCNTs onto the sensor substrates using radio frequency (RF) magnetron and e-beam deposition methods, respectively. Various characterization techniques, including scanning electron microscopy, profilometry, energy-dispersive X-ray spectroscopy (EDX), transmission electron microscopy, and X-ray photoelectron spectroscopy, were employed to investigate the material properties of the Fe2O3:ZnO/MWCNTs nanocomposites. The sensor responses were measured toward a relative humidity range of 2.2%-98%, where their values changed from 1.5 to 5, respectively. The high selectivity and temporal stability of the sensor were confirmed by the experimental results. Besides, the Nyquist curves of the Fe2O3:ZnO/MWCNTs material were extracted using the impedance investigation, and an equivalent electrical circuit was proposed. Thus, this work will contribute to the implementation of highly efficient and viable sensors in humidity detection systems.

Atherosclerosis, a chronic inflammatory disease of the arterial wall, is a leading cause of cardiovascular diseases worldwide. The complex pathogenesis of atherosclerosis involves genetic predisposition, environmental factors, and immune responses. N-Methyl-d-aspartate receptors (NMDARs), a subclass of glutamate receptors, are critical for synaptic plasticity, learning, and memory in the central nervous system (CNS). Non-neuronal NMDARs are poorly understood compared to neuronal receptors, but there is a developing consensus that they have distinct structural and functional properties when activated by glutamate and NMDARs co-agonists. Emerging evidence indicates that non-neuronal NMDARs may participate in an array of physiological and pathophysiological processes, including but not limited to driving macrophage polarization, lipid dysregulation in macrophages, inflammation response, vascular smooth muscle cells phenotype switching and endothelial dysfunction, thereby fueling atherogenesis. This review discusses the association between NMDARs genes and atherosclerosis risk, molecular mechanisms underlying NMDARs-mediated regulation of atherosclerosis-related cells, and potential therapeutic implications. Besides, we introduce some pharmacological tools that can be used for studying NMDARs outside the CNS, which reflect modern subunit-selective agents to provide more precise insight into NMDARs mediate the various effects. Overall, the study of NMDARs may provide insights into the pathogenesis of atherosclerosis and lead to the development of more effective therapeutic strategies.

Urbanization, faulty waste disposal, and improper management contribute to soil pollution in many Indian cities, while excessive fertilizer use contaminates the cropland and plantation soils. This study on soil pollution was conducted in the Jalpaiguri district of West Bengal, located in the eastern Terai region of India. This region features diverse land uses, including urban peri-urban areas (UPA), extensive croplands, tea gardens, and several forests. The aim was to understand how different land uses influence soil pollution, considering the bioavailable forms of heavy metals, NO3- nitrogen, available phosphorus (P2O5), and microplastics as pollutants. Results showed a significant presence (above critical limit) of bioavailable (DTPA-extractable) heavy metals such as Zn, Cu, Fe, Mn, Cd, and Cr, along with high microplastic contamination in UPA soils. Besides, the soils of UPA and tea gardens showed elevated levels of NO3- nitrogen and available phosphorus. Using empirical pollution indices such as the Average Pollution Index, Nemerow Pollution Index, Pollution Load Index, and Vector Modulus of Pollution Index, combined with their spatial mapping, revealed that forest, cropland, and tea garden soils were not polluted, whereas UPA soils were contaminated with heavy metals. This study also proposed a novel weighted soil pollution index, which considered heavy metals and other pollutants. This index also distinctly indicated considerable soil pollution in UPA areas, while the soils of other land uses appeared clean. Urban pollution affects human health through direct exposure to contaminants, while soil pollution in peri-urban areas poses risks due to potential food-chain contamination from agricultural activities. Further, the UPA soil pollution may spread to neighboring ecosystems. This study recommended soil pollution monitoring at the district or state level and implementation of regulatory measures based on that.

Nicotine is a highly bioactive and addictive alkaloid that exerts prevalent cardiovascular and metabolic toxicity independent of other combustion-derived chemicals. Its rapid absorption and interaction with nicotinic acetylcholine receptors initiate a cascade of oxidative, inflammatory, and neuropharmacological responses that interrupt vascular, renal, and metabolic homeostasis. Nicotine triggers NADPH oxidase, mitochondrial dysfunction, and acid sphingomyelinase-ceramide signaling, resulting in reduced nitric oxide bioavailability, endothelial dysfunction, and lipid raft aggregation that promotes NLRP3 inflammasome activation. These mechanisms contribute to hypertension, atherosclerosis, arrhythmias, and heart failure through augmented oxidative stress, impaired vasodilation, sympathetic activation, and structural cardiac remodeling. Besides the cardiovascular system, nicotine disrupts lipid and glucose metabolism, induces podocyte injury, accelerates chronic kidney disease and promotes insulin resistance via inflammatory and redox-sensitive pathways. Understanding the molecular mechanisms driving nicotine toxicity is essential for developing targeted interventions. Emerging therapeutic strategies include pharmacotherapies for dependence, antihypertensive and lipid-lowering agents, metabolic modulators, antioxidants, and inhibitors of inflammasome or ceramide signaling. Overall, this review synthesizes current mechanistic and pharmacological evidence to clarify how nicotine contributes to cardiovascular and systemic disease and highlights the therapeutic opportunities to mitigate its increasing public health burden.

Although it seems impossible to make reliable predictions about climate changes in the near future, an attempt will be made to answer the question posed in the title of this contribution. To this end, a few basic concepts which influence the climate on Earth will be discussed. The principal difficulty is the fact that in the long history of the Earth it is the first time that natural variations of the climate are influenced by human activities as well. And here, the problem arises that besides scientific issues of how these activities (e.g. fossil fuel burning) influence the climate, economic and political considerations are also drawn into the discussion. And this clearly has consequences on how to react to some of the observed changes (e.g. global warming). But emerging technologies to trace radionuclides in the environment at large may still help to get a better understanding of the climate on Earth.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by β-amyloid (Aβ) deposition, neuroinflammation, and cognitive decline. Microglia, the brain's primary immune cells, play a central role in AD pathogenesis by driving neuroinflammatory responses. Deubiquitinating enzymes (DUBs) regulate microglial activation, but the role of the ovarian tumor domain-containing DUB OTUD6A in AD remains unclear. In this study, we demonstrate that OTUD6A is upregulated in microglia across multiple AD models, including Aβ-infused mice, 3 ×Tg mice, and APP/PS1 mice. Otud6a KO or microglia-specific knockdown Otud6a ameliorated cognitive deficits and reduced neuroinflammation in AD mice. Besides, OTUD6A binds to C/EBPβ by removing K48-linked ubiquitin chains at lysine 253 (K253), thereby leading to C/EBPβ accumulation and enhancing NF-κB signaling and proinflammatory cytokine production. Moreover, mutation of OTUD6A catalytic residue (C157A) abolished its deubiquitination activity, confirming its role in C/EBPβ stabilization. Furthermore, C/EBPβ knockdown reversed OTUD6A-mediated neuroinflammation, validating the microglial OTUD6A-C/EBPβ-NF-κB axis as a critical pathway in AD pathogenesis. Therefore, our findings highlight OTUD6A as a novel regulator of microglial activation and suggest that targeting this DUB could provide a therapeutic strategy to mitigate neuroinflammation in AD.