Repetitive traumatic brain injury-induced complement C1-related inflammation impairs long-term hippocampal neurogenesis.

JOURNAL/nrgr/04.03/01300535-202503000-00027/figure1/v/2024-06-17T092413Z/r/image-tiff Repetitive traumatic brain injury impacts adult neurogenesis in the hippocampal dentate gyrus, leading to long-term cognitive impairment. However, the mechanism underlying this neurogenesis impairment remains unknown. In this study, we established a male mouse model of repetitive traumatic brain injury and performed long-term evaluation of neurogenesis of the hippocampal dentate gyrus after repetitive traumatic brain injury. Our results showed that repetitive traumatic brain injury inhibited neural stem cell proliferation and development, delayed neuronal maturation, and reduced the complexity of neuronal dendrites and spines. Mice with repetitive traumatic brain injuryalso showed deficits in spatial memory retrieval. Moreover, following repetitive traumatic brain injury, neuroinflammation was enhanced in the neurogenesis microenvironment where C1q levels were increased, C1q binding protein levels were decreased, and canonical Wnt/ß-catenin signaling was downregulated. An inhibitor of C1 reversed the long-term impairment of neurogenesis induced by repetitive traumatic brain injury and improved neurological function. These findings suggest that repetitive traumatic brain injury-induced C1-related inflammation impairs long-term neurogenesis in the dentate gyrus and contributes to spatial memory retrieval dysfunction.

Hypertriglyceridemia, Hypercholesterolemia, Body Mass Index, and the Risk of Acute Pancreatitis.

OBJECTIVE: The purpose of this work was to check the connection between parameters of lipid profile and body mass index (BMI) in relation to the occurrence of acute pancreatitis within a sample of adults from northern China. METHODOLOGY: A total of 123,214 participants from the Kailuan Group were incorporated into this prospective study. The subjects were categorized into quartiles on the basis of their initial levels of triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). On the basis of BMI classification, the individuals in the study were divided into three distinct groups: normal weight, overweight, and obese. The data were analyzed to explore the correlation between lipid profile and BMI with acute pancreatitis. RESULTS: Over a period of 12.59 ± 0.98 years, during the median follow-up duration, a total of 410 new patients with acute pancreatitis were recorded. The occurrence rate and total occurrence of acute pancreatitis demonstrated an upward trend in correlation with elevated levels of TG, TC, and BMI. Following adjustment for multiple variables, it was observed that individuals in the fourth quartile of TG and TC levels demonstrated the highest likelihood of developing acute pancreatitis. Furthermore, our analysis revealed that a proportion of 19.29% of the correlation between BMI and the likelihood of experiencing acute pancreatitis can be attributed to the influence of elevated TG levels, whereas 12.69% of the association was mediated by higher TC. CONCLUSIONS: We found that hypertriglyceridemia, hypercholesterolemia, and obesity were risk factors for acute pancreatitis, especially in young and middle-aged men.TG and TC were the mediating factors between BMI and the risk of acute pancreatitis.

Review of tracer kinetic models in evaluation of gliomas using dynamic contrast-enhanced imaging.

Glioma is the most common type of primary malignant tumor of the central nervous system (CNS), and is characterized by high malignancy, high recurrence rate and poor survival. Conventional imaging techniques only provide information regarding the anatomical location, morphological characteristics, and enhancement patterns. In contrast, advanced imaging techniques such as dynamic contrast-enhanced (DCE) MRI or DCE CT can reflect tissue microcirculation, including tumor vascular hyperplasia and vessel permeability. Although several studies have used DCE imaging to evaluate gliomas, the results of data analysis using conventional tracer kinetic models (TKMs) such as Tofts or extended-Tofts model (ETM) have been ambiguous. More advanced models such as Brix's conventional two-compartment model (Brix), tissue homogeneity model (TH) and distributed parameter (DP) model have been developed, but their application in clinical trials has been limited. This review attempts to appraise issues on glioma studies using conventional TKMs, such as Tofts or ETM model, highlight advancement of DCE imaging techniques and provides insights on the clinical value of glioma management using more advanced TKMs.

Finite element analysis of a three-dimensional cervical spine model with muscles based on CT scan data.

BACKGROUND: The incidence of cervical spondylosis is increasing, gradually affecting people's normal lives. Establishing a finite element model of the cervical spine is one of the methods for studying cervical spondylosis. MRI (Magnetic Resonance Imaging) still has certain difficulties in transitioning from human imaging to establishing muscle models suitable for finite element analysis. Medical software provides specific morphologies and can generate muscle finite element models. Additionally, there is little research on the static analysis of cervical spine finite element models with solid muscle. PURPOSE: A new method is proposed for establishing a finite element model of the cervical spine based on CT (Computed Tomography) data and medical software, and the model's effectiveness is validated. Human movement characteristics based on the force distribution in various parts are analyzed and predicted. METHODS: The muscle model is reconstructed in medical software and a three-dimensional finite element model of the entire cervical spine (C0-C7) is established by combining muscle models with CT vertebral data models. 1.5 Nm of load is applied to the finite element model to simulate the cervical spine movement. RESULTS: The finite element model was successfully established, and effectiveness was verified. Stress variations in various parts under six movements were obtained. The effectiveness of the model was basically verified. CONCLUSION: The finite element model of the cervical spine for mechanical analysis can be successfully established by using medical software and CT data. In daily life, the C2-3, C3-4, C4-C5 intervertebral discs, rectus capitis posterior major, longus colli, and obliquus capitis inferior are more prone to injury.

Potent synergy and sustained bactericidal activity of polymyxins combined with Gram-positive only class of antibiotics versus four Gram-negative bacteria.

BACKGROUND: Gram-negative bacteria (GNB) are becoming increasingly resistant to a wide variety of antibiotics. There are currently limited treatments for GNB, and the combination of antibiotics with complementary mechanisms has been reported to be a feasible strategy for treating GNB infection. The inability to cross the GNB outer membrane (OM) is an important reason that a broad spectrum of Gram-positive only class of antibiotics (GPOAs) is lacking. Polymyxins may help GPOAs to permeate by disrupting OM of GNB. OBJECTIVE: To identify what kind of GPOAs can be aided to broaden their anti-GNB spectrum by polymyxins, we systematically investigated the synergy of eight GPOAs in combination with colistin (COL) and polymyxin B (PMB) against GNB in vitro. METHODS: The synergistic effect of COL or PMB and GPOAs combinations against GNB reference strains and clinical isolates were determined by checkerboard tests. The killing kinetics of the combinations were assessed using time-kill assays. RESULTS: In the checkerboard tests, polymyxins-GPOAs combinations exert synergistic effects characterized by species and strain specificity. The synergistic interactions on P. aeruginosa strains are significantly lower than those on strains of A. baumannii, K. pneumoniae and E. coli. Among all the combinations, COL has shown the best synergistic effect in combination with dalbavancin (DAL) or oritavancin (ORI) versus almost all of the strains tested, with FICIs from 0.16 to 0.50 and 0.13 to < 0.28, respectively. In addition, the time-kill assays demonstrated that COL/DAL and COL/ORI had sustained bactericidal activity. CONCLUSIONS: Our results indicated that polymyxins could help GPOAs to permeate the OM of specific GNB, thus showed synergistic effects and bactericidal effects in the in vitro assays. In vivo combination studies should be further conducted to validate the results of this study.

Characterization of the covalent binding of cyanidin-3-glucoside to bovine serum albumin and its inhibition mechanism for advanced nonenzymatic glycosylation reactions.

Nonenzymatic glycosylation of proteins can generate advanced glycosylation end products, which are closely associated with the pathogenesis of certain chronic physiological diseases and aging. In this study, we characterized the covalent binding of cyanidin-3-glucoside (C3G) to bovine serum albumin (BSA) and investigated the mechanism by which this covalent binding inhibits the nonenzymatic glycosylation of BSA. The results indicated that the covalent interaction between C3G and BSA stabilized the protein's secondary structure. Through liquid chromatography-electrospray ionization tandem mass spectrometry analysis, we identified the covalent binding sites of C3G on BSA as lysine, arginine, asparagine, glutamine, and cysteine residues. This covalent interaction significantly suppressed the nonenzymatic glycosylation of BSA, consequently reducing the formation of nonenzymatic glycosylation products. C3G competitively binds to nonenzymatic glycosylation sites (e.g., lysine and arginine) on BSA, thereby impeding the glycosylation process and preventing the misfolding and structural alterations of BSA induced by fructose. Furthermore, the covalent attachment of C3G to BSA preserves the secondary structure of BSA and hinders subsequent nonenzymatic glycosylation events.

Characterization of Sesquiterpene Dimers from the Flowers of Inula japonica and the Structural Revisions of Related Compounds.

Sesquiterpene dimers are mainly found in the Asteraceae family. However, conflicting reports on the structures of these compounds can be found in the literature. Herein, we describe ten sesquiterpene dimers isolated from the flowers of Inula japonica, including configurational revisions of japonicone H (1-1), japonicone D (2-1), inulanolide A (4-1), japonicone X (5-1), and inulanolide F (5-2) to compounds 1, 2, 4, and 5, respectively. Five new related metabolites (3 and 6-9) are also described. Application of GIAO NMR/DP4+ analyses and ECD/OR calculations enabled us to revise the absolute configurations of an additional 13 sesquiterpene dimers isolated from plants of the genus Inula. Compounds 1, 2, 4, and 6 exhibited inhibition of nitric oxide production in lipopolysaccharide activated RAW264.7 macrophages with IC50 values of 4.07-10.00 µM.

Dissecting the Superior Drivers for the Simultaneous Improvement of Fiber Quality and Yield Under Drought Stress Via Genome-Wide Artificial Introgressions of Gossypium barbadense into Gossypium hirsutum.

Global water scarcity and extreme weather intensify drought stress, significantly reducing cotton yield and quality worldwide. Drought treatments are conducted using a population of chromosome segment substitution lines generated from E22 (G. hirsutum) and 3-79 (G. barbadense) as parental lines either show superior yields or fiber quality under both control and drought conditions. Fourteen datasets, covering 4 yields and 4 quality traits, are compiled and assessed for drought resistance using the drought resistance coefficient (DRC) and membership function value of drought resistance (MFVD). Genome-wide association studies, linkage analysis, and bulked segregant analysis are combined to analyze the DR-related QTL. A total of 121 significant QTL are identified by DRC and MFVD of the 8 traits. CRISPR/Cas9 and virus-induced gene silencing techniques verified DRR1 and DRT1 as pivotal genes in regulating drought resistant of cotton, with hap3-79 exhibiting greater drought resistance than hapE22 concerning DRR1 and DRT1. Moreover, 14 markers with superior yield and fiber quality are selected for drought treatment. This study offers valuable insights into yield and fiber quality variations between G. hirsutum and G. barbadense amid drought, providing crucial theoretical and technological backing for developing cotton varieties resilient to drought, with high yield and superior fiber quality.

New cembranoid with potent anti-inflammatory effect isolated from Boswellia sacra by inactivating the NF-κB signaling pathway.

Boswellia sacra has the properties of activating blood circulation, fixing pain, subduing swelling and promoting muscle growth. However, the anti-inflammatory active ingredients and molecular mechanisms of Boswellia sacra are still not clearly explored. Boswellia sacra was grounded and extracted using 95% ethanol, the extracts were separated by column chromatography preparation to give compounds. Spectral analysis and quantum calculations confirmed the structures of compounds and identified compound 1 as a new compound. Compounds 1-3 showed potent inhibitory activities and their effects on inflammatory mediator NO and inflammatory cytokines were examined by ELISA assay. Furthermore, their modulatory mechanism on inflammatory signal pathways was explored.

Investigation of Babesia spp. and Theileria spp. in ticks from Western China and identification of a novel genotype of Babesia caballi.

Babesia spp. and Theileria spp. are tick-borne protozoan parasites with veterinary importance. In China, epidemiological and genetic investigations on many Babesia and Theileria species were still absent in many areas and many tick species. From Aug 2021 to May 2023, 645 ticks were collected from the body surface of domestic animals (camels, goats, sheep, and cattle) using tweezers in seven counties in three provinces including Xinjiang (Qitai, Mulei, Hutubi, and Shihezi counties), Chongqing (Youyang and Yunyang counties), and Qinghai (Huangzhong county). Three tick species were morphologically and molecularly identified (334 Hyalomma asiaticum from Xinjiang, 245 Rhipicephalus microplus from Chongqing, and 66 Haemaphysalis qinghaiensis from Qinghai). A total of three Babesia species and two Theileria species were detected targeting the 18S gene. The COI and cytb sequences were also recovered from Babesia strains for further identification. In R. microplus from Chongqing, Babesia bigemina, the agent of bovine babesiosis, was detected. Notably, in H. asiaticum ticks from Xinjiang, a putative novel genotype of Babesia caballi was identified (0.90%, 3/334), whose COI and cytb genes have as low as 85.82% and 90.64-90.91% nucleotide identities to currently available sequences. It is noteworthy whether the sequence differences of its cytb contribute to the drug resistance of this variant due to the involvement of cytb in the drug resistance of Babesia. In addition, Theileria orientalis and Theileria annulata were detected in R. microplus from Chongqing (12.20%, 31/245) and H. asiaticum from Xinjiang (1.50%, 5/334), respectively. These results suggest that these protozoan parasites may be circulating in domestic animals in these areas. The pathogenicity of the novel genotype of B. caballi also warrants further investigation.

Alcoholic Liver Disease in China: A Disease Influenced by Complex Social Factors That Should Not Be Neglected.

Alcoholic liver disease (ALD) encompasses liver damage caused by chronic, excessive alcohol consumption. It manifests initially as marked hepatocellular steatosis and can progress to steatohepatitis, liver fibrosis, and cirrhosis. With China's rapid economic growth, coupled with a complex social background and the influence of a deleterious wine culture, the number of patients with ALD in China has increased significantly; the disease has become a social and health problem that cannot be ignored. In this review, we briefly described the social factors affecting ALD in China and elaborated on differences between alcoholic and other liver diseases in terms of complications (e.g., cirrhosis, upper gastrointestinal bleeding, hepatic encephalopathy, hepatocellular carcinoma, addiction, and other extrahepatic diseases). We also emphasized that ALD was more dangerous and difficult to treat than other liver diseases due to its complications, and that precise and effective treatment measures were lacking. In addition, we considered new ideas and treatment methods that may be generated in the future.

Poly[[{µ2-5-[(di-methyl-amino)(thioxo)meth-oxy]benzene-1,3-di-carboxyl-ato-κ4 O 1,O 1':O 3,O 3'}(µ2-4,4'-di-pyridyl-amine-κ2 N 4:N 4')cobalt(II)] di-methyl-formamide hemisolvate monohydrate].

In the crystal structure of the title compound, {[Co(C11H9NSO5)(C10H9N3)]0.5C3H7NO·H2O} n or {[Co(dmtb)(dpa)]·0.5DMF·H2O} n (dmtb2- = 5-[(di-meth-yl-amino)-thioxometh-oxy]-1,3-benzene-dicarboxyl-ate and dpa = 4,4'-di-pyridyl-amine), an assembly of periodic [Co(C11H9NSO5)(C10H9N3)] n layers extending parallel to the bc plane is present. Each layer is constituted by distorted [CoO4N2] octa-hedra, which are connected through the µ 2-coordination modes of both dmtb2- and dpa ligands. Occupationally disordered water and di-meth-yl-formamide (DMF) solvent mol-ecules are located in the voids of the network to which they are connected through hydrogen-bonding inter-actions.

Hybrid ant colony-based inter-cluster routing protocol for FANET.

This study addresses the challenges in large-scale unmanned aerial vehicle (UAV) clusters, specifically the scalability issues and limitations of using reactive routing protocols for inter-cluster routing. These traditional methods place an excessive burden on cluster heads and struggle to adapt to frequently changing topologies, leading to decreased network performance. To solve these problems, we propose an innovative inter-cluster routing protocol (ICRP), which is based on a hybrid ant colony algorithm. During the route establishment phase, ICRP uses this algorithm to identify the optimal relay node. This approach is inspired by the foraging behavior of Physarum polycephalum, combining factors such as the number of hops from the source node, the load condition of the node, and its weight in the pheromone calculation. In the route maintenance phase, ICRP uses a predictive repair and contraction mechanism to dynamically maintain routes, accommodating the high mobility of UAVs. Comparative simulations in OMNeT + + showed that this protocol surpasses ad-hoc on-demand distance vector (AODV), fuzzy-logic-assisted-AODV, and Enhanced-Ant-AODV routing protocols in packet delivery rate and end-to-end transmission delay. Furthermore, it showed superior adaptation to network environments with high-speed node mobility.

Chinese herbal medicine Shufeng Jiedu capsule for mild to moderate COVID-19: a multicenter, randomized, double-blind, placebo-controlled phase II trial.

Background: The COVID-19 pandemic has had a profound global impact, although the majority of recently infected cases have presented with mild to moderate symptoms. Previous clinical studies have demonstrated that Shufeng Jiedu (SFJD) capsule, a Chinese herbal patent medicine, effectively alleviates symptoms associated with the common cold, H1N1 influenza, and COVID-19. This study aimed to assess the efficacy and safety of SFJD capsules in managing symptoms of mild to moderate COVID-19 infection. Methods: A randomized, double-blind, placebo-controlled trial was conducted from May to December 2022 at two hospitals in China. Mild and moderate COVID-19-infected patients presenting respiratory symptoms within 3 days from onset were randomly assigned to either the SFJD or placebo groups in a 1:1 ratio. Individuals received SFJD capsules or a placebo three times daily for five consecutive days. Participants were followed up for more than 14 days after their RT-PCR nucleoid acid test for SARS-CoV-2 turned negative. The primary outcome measure was time to alleviate COVID-19 symptoms from baseline until the end of follow-up. Results: A total of 478 participants were screened; ultimately, 407 completed the trial after randomization (SFJD, n = 203; placebo, n = 204). No statistically significant difference in baseline parameters was observed between the two groups. The median time to alleviate all symptoms was 7 days in the SFJD group compared to 8 days in the placebo group (p = 0.037). Notably, the SFJD group significantly attenuated fever/chills (p = 0.04) and headache (p = 0.016) compared to the placebo group. Furthermore, the median time taken to reach normal body temperature within 24 h was reduced by 7 hours in the SFJD group compared to the placebo group (p = 0.033). No deaths or instances of serious or critical conditions occurred during this trial period; moreover, no serious adverse events were reported. Conclusion: The trial was conducted in a unique controlled hospital setting, and the 5-day treatment with SFJD capsules resulted in a 1-day reduction in overall symptoms, particularly headache and fever/chills, among COVID-19-infected participants with mild or moderate symptoms. Compared to placebo, SFJD capsules were found to be safe with fewer side effects. SFJD capsules could potentially serve as an effective treatment for alleviating mild to moderate symptoms of COVID-19. Clinical Trial Registration: https://www.isrctn.com/, identifier ISRCTN14236594.

Enhanced performance and mechanism of adsorption pretreatment for alleviating membrane fouling in AGMBR: Impact of structural variations in carbon adsorbents.

The structural variances of adsorbents play a crucial role in determining the number of effective adsorption sites and pretreatment performance. However, there is still a gap in comprehending the impact of different carbon structural adsorbents on membrane fouling. Therefore, this study aimed to compare the efficacy of granular activated carbon (GAC), powdered activated carbon (PAC), and activated carbon fiber (ACF) in mitigating membrane fouling during municipal sewage reclamation using an aerobic granular sludge membrane bioreactor (AGMBR). The results demonstrated that the utilization of PAC significantly enhanced the normalized flux and reduced fouling resistance in comparison to GAC and ACF systems. PAC effectively adsorbed low and medium-molecular-weight pollutants present in raw sewage, resulting in an increase in average particle size and a decrease in foulant content on the membrane surface. The Hermia model indicated that adsorption pretreatment minimized standard blocking while promoting the formation of a sparse and porous cake layer. Moreover, according to the extended Derjaguin-Landau-Verwey-Overbeek theory, PAC has been demonstrated as the optimal antifouling system owing to its enhanced repulsion between membrane-foulant and foulant-foulant interactions. Correlation analysis revealed that the exceptional antifouling performance of the PAC system was due to its high removal rates of chemical oxygen demand (~78 %) and suspended solids (~97 %). This research offers valuable insights into the mitigation of membrane fouling through the utilization of adsorbents featuring diverse carbon structures.

Proteomics Meets Dose-Response: A New Paradigm for Deciphering Drug Effects.

In a groundbreaking study, Eckert and colleagues introduce DecryptE, an innovative approach to dose-resolved proteomics that significantly advances our understanding of drug effects at the proteomic level. This method integrates cutting-edge sample preparation and mass spectrometry technologies, establishing a robust platform for high-throughput proteome analysis. DecryptE enables the quantification of over 7,000 proteins per hour and was employed to study 144 clinical drugs and research compounds, generating over 1 million dose-response curves using Jurkat acute T cell leukemia cells as a model system. The platform demonstrates outstanding reproducibility, ensuring reliable and consistent results across multiple experiments. By providing detailed information on drug potency and efficacy, DecryptE allows the identification of subtle changes in protein expression and facilitates the clustering of drugs based on their proteomic profiles. This study not only reveals novel drug mechanisms but also creates a comprehensive resource that can be utilized by the broader research community. Furthermore, it highlights the potential of integrating proteomics-and potentially other omics modalities in the future-with dose-response analysis to advance pharmacological research and improve therapeutic strategies.

ATP Hydrolases Superfamily Protein 1 (ASP1) Maintains Root Stem Cell Niche Identity through Regulating Reactive Oxygen Species Signaling in Arabidopsis.

The maintenance of the root stem cell niche identity in Arabidopsis relies on the delicate balance of reactive oxygen species (ROS) levels in root tips; however, the intricate molecular mechanisms governing ROS homeostasis within the root stem cell niche remain unclear. In this study, we unveil the role of ATP hydrolase superfamily protein 1 (ASP1) in orchestrating root stem cell niche maintenance through its interaction with the redox regulator cystathionine ß-synthase domain-containing protein 3 (CBSX3). ASP1 is exclusively expressed in the quiescent center (QC) cells and governs the integrity of the root stem cell niche. Loss of ASP1 function leads to enhanced QC cell division and distal stem cell differentiation, attributable to reduced ROS levels and diminished expression of SCARECROW and SHORT ROOT in root tips. Our findings illuminate the pivotal role of ASP1 in regulating ROS signaling to maintain root stem cell niche homeostasis, achieved through direct interaction with CBSX3.

Automated detection and classification of coronary atherosclerotic plaques on coronary CT angiography using deep learning algorithm.

Background: Coronary artery disease (CAD) is the leading cause of mortality worldwide. Recent advances in deep learning technology promise better diagnosis of CAD and improve assessment of CAD plaque buildup. The purpose of this study is to assess the performance of a deep learning algorithm in detecting and classifying coronary atherosclerotic plaques in coronary computed tomographic angiography (CCTA) images. Methods: Between January 2019 and September 2020, CCTA images of 669 consecutive patients with suspected CAD from Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine were included in this study. There were 106 patients included in the retrospective plaque detection analysis, which was evaluated by a deep learning algorithm and four independent physicians with varying clinical experience. Additionally, 563 patients were included in the analysis for plaque classification using the deep learning algorithm, and their results were compared with those of expert radiologists. Plaques were categorized as absent, calcified, non-calcified, or mixed. Results: The deep learning algorithm exhibited higher sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy {92% [95% confidence interval (CI): 89.5-94.1%], 87% (95% CI: 84.2-88.5%), 79% (95% CI: 76.1-82.4%), 95% (95% CI: 93.4-96.3%), and 89% (95% CI: 86.9-90.0%)} compared to physicians with ≤5 years of clinical experience in CAD diagnosis for the detection of coronary plaques. The algorithm's overall sensitivity, specificity, PPV, NPV, accuracy, and Cohen's kappa for plaque classification were 94% (95% CI: 92.3-94.7%), 90% (95% CI: 88.8-90.3%), 70% (95% CI: 68.3-72.1%), 98% (95% CI: 97.8-98.5%), 90% (95% CI: 89.8-91.1%) and 0.74 (95% CI: 0.70-0.78), indicating strong performance. Conclusions: The deep learning algorithm has demonstrated reliable and accurate detection and classification of coronary atherosclerotic plaques in CCTA images. It holds the potential to enhance the diagnostic capabilities of junior radiologists and junior intervention cardiologists in the CAD diagnosis, as well as to streamline the triage of patients with acute coronary symptoms.

Learning Disentangled Priors for Hyperspectral Anomaly Detection: A Coupling Model-Driven and Data-Driven Paradigm.

Accurately distinguishing between background and anomalous objects within hyperspectral images poses a significant challenge. The primary obstacle lies in the inadequate modeling of prior knowledge, leading to a performance bottleneck in hyperspectral anomaly detection (HAD). In response to this challenge, we put forth a groundbreaking coupling paradigm that combines model-driven low-rank representation (LRR) methods with data-driven deep learning techniques by learning disentangled priors (LDP). LDP seeks to capture complete priors for effectively modeling the background, thereby extracting anomalies from hyperspectral images more accurately. LDP follows a model-driven deep unfolding architecture, where the prior knowledge is separated into the explicit low-rank prior formulated by expert knowledge and implicit learnable priors by means of deep networks. The internal relationships between explicit and implicit priors within LDP are elegantly modeled through a skip residual connection. Furthermore, we provide a mathematical proof of the convergence of our proposed model. Our experiments, conducted on multiple widely recognized datasets, demonstrate that LDP surpasses most of the current advanced HAD techniques, exceling in both detection performance and generalization capability.