Cancer Immunotherapy and Medical Imaging Research Trends from 2003 to 2023: A Bibliometric Analysis.

Purpose: With the rapid development of immunotherapy, cancer treatment has entered a new phase. Medical imaging, as a primary diagnostic method, is closely related to cancer immunotherapy. However, until now, there has been no systematic bibliometric analysis of the state of this field. Therefore, the main purpose of this article is to clarify the past research trajectory, summarize current research hotspots, reveal dynamic scientific developments, and explore future research directions. Patients and Methods: A comprehensive search was conducted on the Web of Science Core Collection (WoSCC) database to identify publications related to immunotherapy specifically for the medical imaging of carcinoma. The search spanned the period from the year 2003 to 2023. Several analytical tools were employed. These included CiteSpace (6.2.4), and the Microsoft Office Excel (2016). Results: By searching the database, a total of 704 English articles published between 2003 and 2023 were obtained. We have observed a rapid increase in the number of publications since 2018. The two most active countries are the United States (n=265) and China (n=170). Pittock, Sean J and Abu-sbeih, Hamzah are very concerned about the relationship between cancer immunotherapy and medical images and have published more academic papers (n = 5; n = 4). Among the top 10 co-cited authors, Topalian Sl (n=43) cited ranked first, followed by Graus F (n=40) cited. According to clustering, timeline, and burst word analysis, the results show that the current research focus is on "MRI", "deep learning", "tumor microenvironment" and so on. Conclusion: Medical imaging and cancer immunotherapy are hot topics. The United States is the country with the most publications and the greatest influence in this field, followed by China. "MRI", "PET/PET-CT", "deep learning", "immune-related adverse events" and "tumor microenvironment" are currently hot research topics and potential targets.

Predicting postoperative prognosis of pancreatic cancer using a computed tomography-based radio-clinical model: exploring biologic functions.

Computed tomography (CT) imaging has the potential to assist in predicting the prognosis and treatment strategies for pancreatic cancer (PC). This study aimed to develop and validate a radio-clinical model based on preoperative multiphase CT assessments to predict the overall survival (OS) of PC and identify differentially expressed genes associated with OS. METHODS: Patients with PC who had undergone radical pancreatectomy (R0 resection) were divided into development and external validation sets. Independent predictors of OS were identified using Cox regression analyses and included in the nomogram, which was externally validated. The area under the curve was used to measure the model's accuracy in estimating OS probability. RNA sequencing data from The Cancer Genome Atlas were used for gene expression analysis. RESULTS: In the development and external validation sets, survival was estimated respectively for 132 and 27 patients. Multivariate Cox regression analysis identified 5 independent OS predictors: age (P = .049), sex (P = .001), bilirubin level (P = .005), tumor size (P = .020), and venous invasion (P = .041). These variables were incorporated into the nomogram. Patients were divided into high- and low-risk groups for OS and survival curves showed that all patients in the low-risk group had better OS than that of those in the high-risk group (P < .001). Differentially expressed genes in patients with a poor prognosis were involved in neuroactive ligand-receptor interaction. CONCLUSION: The radio-clinical model may be clinically useful for successfully predicting PC prognosis.

Three-dimensional morphology scoring of hepatocellular carcinoma stratifies prognosis and immune infiltration.

BACKGROUND: The morphological attributes could serve as pivotal indicators precipitating early recurrence and dismal overall survival in hepatocellular carcinoma (HCC), and quantifying morphological features may better stratify the prognosis of HCC. OBJECTIVE: To develop a radiomics approach based on 3D tumor morphology features for predicting the prognosis of HCC and identifying differentially expressed genes related to morphology to guide HCC treatment. MATERIALS AND METHODS: Retrospective study of 357 HCC patients. Radiomic features were extracted from MRI tumor regions; 14 morphology-related features predicted early HCC recurrence and patient stratification via LASSO-Cox modeling. Overall survival (OS) and recurrence-free survival (RFS) were analyzed. RNA sequencing from the Cancer Imaging Archive (TCIA) examined drug sensitivity and stratified HCC using morphological immunity genes, validating recurrence and prognosis. RESULTS: Patients were split into training (n = 225), test (n = 132), and 50 TCIA dataset cohorts. Two features (Maximum2DdiameterColumn, Sphericity) in Cox regression stratified patients into high/low-risk Morphological Radiological Score (Morph-RS) groups. Significant OS and RFS were seen across all sets. Differentially expressed genes focused on T cell receptor signaling; low-risk group had higher T cells (P = 0.039), B cells (P = 0.041), NK cells (P = 0.018). SN-38, GSK2126458 might treat high-risk morphology. Morphology-immune genes stratified HCC, showing significant RFS/OS differences. CONCLUSION: Tumor Morph-RS effectively stratifies HCC patients' recurrence and prognosis. Limited immune infiltration seen in Morph-RS high-risk groups signifies the potential of employing tumor morphology as a potent visual biomarker for diagnosing and managing HCC.

Tree parameter extraction in Fokienia hodginsii plantation based on airborne LiDAR data.

Accurate and efficient extraction of tree parameters from plantations lay foundation for estimating individual wood volume and stand stocking. In this study, we proposed a method of extracting high-precision tree parameters based on airborne LiDAR data. The main process included data pre-processing, ground filtering, individual tree segmentation, and parameter extraction. We collected high-density airborne point cloud data from the large-diameter timber of Fokienia hodginsii plantation in Guanzhuang State Forestry Farm, Shaxian County, Fujian Province, and pre-processed the point cloud data by denoising, resampling and normalization. The vegetation point clouds and ground point clouds were separated by the Cloth Simulation Filter (CSF). The former data were interpolated using the Delaunay triangulation mesh method to generate a digital surface model (DSM), while the latter data were interpolated using the Inverse Distance Weighted to generate a digital elevation model (DEM). After that, we obtained the canopy height model (CHM) through the difference operation between the two, and analyzed the CHM with varying resolutions by the watershed algorithm on the accuracy of individual tree segmentation and parameter extraction. We used the point cloud distance clustering algorithm to segment the normalized vegetation point cloud into individual trees, and analyzed the effects of different distance thresholds on the accuracy of indivi-dual tree segmentation and parameter extraction. The results showed that the watershed algorithm for extracting tree height of 0.3 m resolution CHM had highest comprehensive evaluation index of 91.1% for individual tree segmentation and superior accuracy with R2 of 0.967 and RMSE of 0.890 m. When the spacing threshold of the point cloud segmentation algorithm was the average crown diameter, the highest comprehensive evaluation index of 91.3% for individual tree segmentation, the extraction accuracy of the crown diameter was superior, with R2 of 0.937 and RMSE of 0.418 m. Tree height, crown diameter, tree density, and spatial distribution of trees were estimated. There were 5994 F. hodginsii, with an average tree height of 16.63 m and crown diameter of 3.98 m. Trees with height of 15-20 m were the most numerous (a total of 2661), followed by those between 10-15 m. This method of forest parameter extraction was useful for monitoring and managing plantations.

ParTRE: A relational triple extraction model of complicated entities and imbalanced relations in Parkinson's disease.

The relational triple extraction of unstructured medical texts about Parkinson's disease is critical for the construction of a medical knowledge graph. However, the triple entities in Parkinson's disease are usually complicated and overlapped, which impedes the accuracy of triple extraction, especially in the case of rarely available corpus. Therefore, this study first builds a corpus about Parkinson's disease. Then, a tagging-based three-stage relational triple extraction model is proposed, named ParTRE. To enhance the contextual representation of sentences, the proposed model employs BiLSTM modules to capture fine-grained semantic information. Additionally, a conditional normalization layer is used so that entity pairs can be extracted accurately from two complementary directions. As for the imbalanced relationship categories, an adaptive loss function strategy based on focal loss is derived by assigning different weights to relationship categories and reducing the loss of easy-to-classify samples. The model performance is evaluated on the Parkinson's corpus and public datasets. The results indicate that the proposed model achieves an overall F1-score of 93.3 % on the Parkinson's corpus and comparable performance on public datasets compared with the state-of-the-art methods. Moreover, a satisfactory result is achieved by the proposed model on conquering the overlapped entities and imbalanced relationship categories. Owing to demonstrated availability and validity, the proposed method can be integrated with medical knowledge graphs and therefore benefits medical intelligence.

Overcoming the permeability-selectivity challenge in water purification using two-dimensional cobalt-functionalized vermiculite membrane.

Clean water and sanitation are major global challenges highlighted by the UN Sustainable Development Goals. Water treatment using energy-efficient membrane technologies is one of the most promising solutions. Despite decades of research, the membrane permeability-selectivity trade-off remains the major challenge for synthetic membranes. To overcome this challenge, here we develop a two-dimensional cobalt-functionalized vermiculite membrane (Co@VMT), which innovatively combines the properties of membrane filtration and nanoconfinement catalysis. The Co@VMT membrane demonstrates a high water permeance of 122.4 L·m-2·h-1·bar-1, which is two orders of magnitude higher than that of the VMT membrane (1.1 L·m-2·h-1·bar-1). Moreover, the Co@VMT membrane is applied as a nanofluidic advanced oxidation process platform to activate peroxymonosulfate (PMS) for degradation of several organic pollutants (dyes, pharmaceuticals, and phenols) and shows excellent degradation performance (~100%) and stability (for over 107 h) even in real-world water matrices. Importantly, safe and non-toxic effluent water quality is ensured by the Co@VMT membrane/PMS system without brine, which is totally different from the molecular sieving-based VMT membrane with the concentrated pollutants remaining in the brine. This work can serve as a generic design blueprint for the development of diverse nanofluidic catalytic membranes to overcome the persistent membrane permeability-selectivity issue in water purification.

Continuously Producing Highly Concentrated and Pure Acetic Acid Aqueous Solution via Direct Electroreduction of CO2.

It is crucial to achieve continuous production of highly concentrated and pure C2 chemicals through the electrochemical CO2 reduction reaction (eCO2RR) for artificial carbon cycling, yet it has remained unattainable until now. Despite one-pot tandem catalysis (dividing the eCO2RR to C2 into two catalytical reactions of CO2 to CO and CO to C2) offering the potential for significantly enhancing reaction efficiency, its mechanism remains unclear and its performance is unsatisfactory. Herein, we selected different CO2-to-CO catalysts and CO-to-acetate catalysts to construct several tandem catalytic systems for the eCO2RR to acetic acid. Among them, a tandem catalytic system comprising a covalent organic framework (PcNi-DMTP) and a metal-organic framework (MAF-2) as CO2-to-CO and CO-to-acetate catalysts, respectively, exhibited a faradaic efficiency of 51.2% with a current density of 410 mA cm-2 and an ultrahigh acetate yield rate of 2.72 mmol m-2 s-1 under neutral conditions. After electrolysis for 200 h, 1 cm-2 working electrode can continuously produce 20 mM acetic acid aqueous solution with a relative purity of 95+%. Comprehensive studies revealed that the performance of tandem catalysts is influenced not only by the CO supply-demand relationship and electron competition between the two catalytic processes in the one-pot tandem system but also by the performance of the CO-to-C2 catalyst under diluted CO conditions.

The Therapeutic Effect of Swallow Training with a Xanthan Gum-Based Thickener in Addition to Classical Dysphagia Therapy in Chinese Patients with Post-Stroke Oropharyngeal Dysphagia: A Randomized Controlled Study.

Objective: In patients with post-stroke oropharyngeal dysphagia (PSOD), classical dysphagia therapy (CDT) continues to provide unsatisfactory outcomes and makes it challenging for them to remove the nasal feeding tube. Increasing bolus viscosity helps prevent aspiration in PSOD. However, conventional starch thickeners enhance post-digestion residue. This study aims to evaluate the efficacy of swallow training with xanthan gum-based thickener (XGT) (Softia G, NUTRI Co., Ltd., Yokkaichi, Japan) additional to CDT in Chinese PSOD patients with a nasogastric tube when compared to CDT alone. Methods: Patients with PSOD who had a nasogastric tube were randomly assigned to either the experimental group (E-group) or the control group (C-group) in this randomized controlled, single-blind, parallel-group study. Both groups received CDT for 4 weeks. The E-group cases received additional swallow training with a Softia G-prepared hydrogel training material. The Functional Oral Intake Scale (FOIS) and modified volume-viscosity swallow test (M-VVST) for swallowing safety and efficacy according to adjusted Chinese dietary habits were administered before and after treatment. Post-training, both groups' nasogastric tube removal rates were calculated. Results: One hundred sixty-seven participants (E-group: 82 and C-group: 85) completed the study. The E-group's median score of FOIS improved significantly than the C-group after training (median = 5 vs. 3, P < 0.001). The incidence of coughing, voice changes, oxygen desaturation of 3% or more, pharyngeal residue and piecemeal deglutition in the E-group was significantly lower than that in the C-group (P < 0.05). The E-group had 100% nasogastric tube removal, while the C-group had 28.24% (P < 0.001). Conclusion: Swallow training with XGT Softia G in addition to CDT can promote swallowing safety and efficacy in Chinese patients with PSOD more effectively than CDT alone.

Establishment and Validation of the LI-RADS Morphologic Type II Hepatocellular Carcinoma Early Recurrence Risk Scoring System.

BACKGROUND: Tumor morphology links to early recurrence of hepatocellular carcinoma. Controversy exists regarding the recurrence risk of Liver Imaging Reporting and Data System morphologic Type II hepatocellular carcinoma. This study aims to explore risk factors for early recurrence of Type II hepatocellular carcinoma. METHODS: Retrospective analysis of hepatocellular carcinoma patients who underwent curative resection and preoperative contrast-enhanced MRI from June 2016 to June 2020. Our patients formed the development set, and hepatocellular carcinoma patients from the TCIA database served as validation. Univariable and multivariable Cox regression identified independent risk factors for early recurrence. A risk scoring system was established for risk stratification, and an early recurrence prediction model was developed and validated. RESULTS: 95 Type II hepatocellular carcinoma patients were in the development set, and 29 cases were in the validation set. Early recurrence rates were 33.7% and 37.9%, respectively. Multivariate analysis revealed age, histological grade, AFP, and intratumoral hemorrhage as independent risk factors for early recurrence. The model's diagnostic performance for early recurrence was AUC = 0.817 in the development set. A scoring system classified patients into low-risk (scores ≤ 3) and high-risk (scores > 3) groups. The high-risk group had significantly lower recurrence-free survival (40.0% vs 73.2%, P = 0.001), consistent with the validation set (25.0% vs 73.3%, P = 0.028). CONCLUSIONS: The risk scoring system demonstrated excellent discrimination and predictive ability, aiding clinicians in assessing early recurrence risk and identifying high-risk individuals effectively.

A novel integrated time-resolved array avalanche photodiode detection system for nuclear resonant scattering measurements.

The nuclear resonant scattering (NRS) experiment requires photon-counting detectors with high time resolution, short dead time, large dynamic range, low noise, and large detection area. An 8-channel avalanche photodiode (APD) array detector system with high integrity, flexibility, and reliability has been developed to adapt to the demands of NRS experiments. The detector system mainly consists of four key parts: (i) an array-APD sensor, (ii) 8-channel integrated fast preamplifiers, (iii) the time-to-digital converter readout electronics, and (iv) a data acquisition system and EPICS support software. Remarkably, the system exhibits a time resolution of better than 500 ps and has a sufficiently low noise level, allowing for the lowest detection energy threshold of 4 keV. The performance of the new array-APD system as well as its real application in nuclear forward scattering (NFS) and nuclear resonant inelastic x-ray scattering (NRIXS) experiments was tested in two synchrotron facilities. With the new system, the NFS signal very close to the prompt electronic scattering signal can be extracted. Thanks to the customized EPICS-areaDetector-based control software, NRIXS spectra can be readily measured with time and energy information of the NRIXS signal stored in the raw data, which is promising for developing NRIXS data analysis in the time domain. The array-APD detector can be deployed for nuclear resonant scattering experiments at various synchrotron radiation facilities.

Unveiling the Electrolyte Cations Dependent Kinetics on CoOOH-Catalyzed Oxygen Evolution Reaction.

The electrolyte cations-dependent kinetics have been widely observed in many fields of electrocatalysis, however, the exact mechanism of the influence on catalytic performance is still a controversial topic of considerable discussion. Herein, combined with operando X-ray diffraction (XRD) and high-resolution transmission electron microscopy (HRTEM), we verify that the electrolyte cations could intercalate into the layer of pristine CoOOH catalyst during the oxygen evolution reaction (OER) process, while the bigger cations lead to enlarged interlayer spacing and increased OER activity, following the order Cs+ >K+ >Na+ >Li+ . X-ray absorption spectroscopy (XAS), in situ Raman, in situ Ultraviolet-visible (UV/Vis) spectroscopy, in situ XAS spectroscopy, cyclic voltammetry (CV), and theoretical calculations reveal that the intercalation of electrolyte cations efficiently modify the oxidation states of Co by enlarging the Co-O bonds, which in turn enhance the d-band center of Co, optimize the adsorption strength of oxygen intermediates, facilitate the formation of OER active Co(IV) species, and reduce the energy barrier of the rate-determing step (RDS), thereby enhancing the OER activity. This work not only provides an informative picture to understand the complicated dependence of OER kinetics on electrolyte cations, but also sheds light on understanding the mechanism of other electrolyte cation-targeted electrocatalysis.

Dicopper(I) Sites Confined in a Single Metal-Organic Layer Boosting the Electroreduction of CO2 to CH4 in a Neutral Electrolyte.

It is challenging and important to achieve high performance for an electrochemical CO2 reduction reaction (eCO2RR) to yield CH4 under neutral conditions. So far, most of the reported active sites for eCO2RR to yield CH4 are single metal sites; the performances are far below the commercial requirements. Herein, we reported a nanosheet metal-organic layer in single-layer, namely, [Cu2(obpy)2] (Cuobpy-SL, Hobpy = 1H-[2,2']bipyridinyl-6-one), possessing dicopper(I) sites for eCO2RR to yield CH4 in a neutral aqueous solution. Detailed examination of Cuobpy-SL revealed high performance for CH4 production with a faradic efficiency of 82(1)% and a current density of ∼90 mA cm-2 at -1.4 V vs. reversible hydrogen electrode (RHE). No obvious degradation was observed over 100 h of continuous operation, representing a remarkable performance to date. Mechanism studies showed that compared with the conventional single-copper sites and completely exposed dicopper(I) sites, the dicopper(I) sites in the confined space formed by the molecular stacking have a strong affinity to key C1 intermediates such as *CO, *CHO, and *CH2O to facilitate the CH4 production, yet inhibiting C-C coupling.

Functional copper complexes with benzofurans tridentate ligand: Synthesis, crystal structure, DNA binding and anticancer studies.

Metal complexes, particularly copper(II) complexes, are often used as anticancer drugs due to their ability to generate reactive oxygen species (ROS) in cells. Four copper(II) complexes have been designed based on ligands for triplet pyridine derivatives (complexes 1-4), and their structures have been determined using X-ray single crystal analysis. The interactions of these complexes with calf thymus DNA (CT-DNA) have been investigated using various techniques, including UV-vis absorption, viscosity measurements, and circular dichroism spectroscopy. The results indicate that complexes 1-4 strongly interact with DNA through partial intercalations. Further investigation using agarose gel electrophoresis shows that all four complexes can cleave pBR322 DNA in the presence of ascorbic acid as a reducing agent, and the DNA cleavage mechanism is through the generation of singlet oxygen (1O2). In vitro anticancer activities of these complexes have been evaluated using A549, MDA-MB-231, HeLa, and HepG2 cells. The calculated IC50 values indicate significant efficacy against cancer cells. Additionally, AO/EB staining assays reveal that these complexes induce cell apoptosis in HeLa cell line.

Mitochondrial supercomplex assembly regulates metabolic features and glutamine dependency in mammalian cells.

Rationale: Mitochondria generate ATP via the oxidative phosphorylation system, which mainly comprises five respiratory complexes found in the inner mitochondrial membrane. A high-order assembly of respiratory complexes is called a supercomplex. COX7A2L is a supercomplex assembly factor that has been well-investigated for studying supercomplex function and assembly. To date, the effects of mitochondrial supercomplexes on cell metabolism have not been elucidated. Methods: We depleted COX7A2L or Cox7a2l in human and mouse cells to generate cell models lacking mitochondrial supercomplexes as well as in DBA/2J mice as animal models. We tested the effect of impaired supercomplex assembly on cell proliferation with different nutrient supply. We profiled the metabolic features in COX7A2L-/- cells and Cox7a2l-/- mice via the combined use of targeted and untargeted metabolic profiling and metabolic flux analysis. We further tested the role of mitochondrial supercomplexes in pancreatic ductal adenocarcinoma (PDAC) through PDAC cell lines and a nude mouse model. Results: Impairing mitochondrial supercomplex assembly by depleting COX7A2L in human cells reprogrammed metabolic pathways toward anabolism and increased glutamine metabolism, cell proliferation and antioxidative defense. Similarly, knockout of Cox7a2l in DBA/2J mice promoted the use of proteins/amino acids as oxidative carbon sources. Mechanistically, impaired supercomplex assembly increased electron flux from CII to CIII/CIV and promoted CII-dependent respiration in COX7A2L-/- cells which further upregulated glutaminolysis and glutamine oxidation to accelerate the reactions of the tricarboxylic acid cycle. Moreover, the proliferation of PDAC cells lacking COX7A2L was inhibited by glutamine deprivation. Conclusion: Our results reveal the regulatory role of mitochondrial supercomplexes in glutaminolysis which may fine-tune the fate of cells with different nutrient availability.

Dynamic space-time dark level correction approach for lunar radiometric calibration of the Lunar Observation Imaging Spectrometer.

Lunar radiometric calibration is used to solve the problem of consistent radiometric calibration for multiple satellite platforms and remote sensors. However, the dark level fluctuates when observing the Moon with a short-wave infrared spectrometer, which seriously affects the accuracy of lunar radiation data. In this work, we propose a dynamic space-time dark level correction approach to address the fluctuation of the dark level. This method employs cold space signals in space and time dimensions to estimate the dark level for each frame individually and to reduce errors due to environmental variations. Experiments on lunar observations at multiple phase angles were conducted, and the dark level correction results demonstrate that our proposed method is effective even in the short-wave infrared, and is also superior to currently existing techniques. For a single-band (1700 nm) image of the full Moon, the mean background proportion of the proposed method is 1.00%, which is better than that of the static dark correction method (2.25%) and linear dark correction method (5.93%).

Top-down manufacturing of efficient CO2 reduction catalysts from the gasification residue carbon.

Gram scale preparation of carbon-supported single-atom catalysts was achieved via a top-down approach starting from metallic and metalloid constituent-enriched gasification residual carbon, exhibiting superior electrocatalytic performance for CO2-to-CO conversion in both H-type and membrane electrode assembly electrolyzers.

Splicing abnormalities caused by a novel mutation in the PHKA2 gene in children with glycogen storage disease type IX / 中华肝脏病杂志

Objective: Glycogen storage disease type IX (GSD-IX) is a rare primary glucose metabolism abnormality caused by phosphorylase kinase deficiency and a series of pathogenic gene mutations. The clinical characteristics, gene analysis, and functional verification of a mutation in a child with hepatomegaly are summarized here to clarify the pathogenic cause of the disease. Methods: The clinical data of a child with GSD-IX was collected. Peripheral blood from the child and his parents was collected for genomic DNA extraction. The patient's gene diagnosis was performed by second-generation sequencing. The suspected mutations were verified by Sanger sequencing and bioinformatics analysis. The suspected splicing mutations were verified in vivo by RT-PCR and first-generation sequencing. Results: Hepatomegaly, transaminitis, and hypertriglyceridemia were present in children. Liver biopsy pathological examination results indicated glycogen storage disease. Gene sequencing revealed that the child had a c.285 + 2_285 + 5delTAGG hemizygous mutation in the PHKA2 gene. Sanger sequencing verification showed that the mother of the child was heterozygous and the father of the child was of the wild type. Software such as HSF3.1 and ESEfinder predicted that the gene mutation affected splicing. RT-PCR of peripheral blood from children and his mother confirmed that the mutation had caused the skipping of exon 3 during the constitutive splicing of the PHKA2 gene. Conclusion: The hemizygous mutation in the PHKA2 gene (c.285 + 2_285 + 5delTAGG) is the pathogenic cause of the patient's disease. The detection of the novel mutation site enriches the mutation spectrum of the PHKA2 gene and serves as a basis for the family's genetic counseling.

Early memory impairment is accompanied by changes in GluA1/p-GluA1 in APP/PS1 mice.

AIMS: Exploring the neurobiological mechanisms of early AD damage Background: The early diagnosis of Alzheimer's disease (AD) has a very important impact on the prognosis of AD. However, the early symptoms of AD are not obvious and difficult to diagnose. Existing studies have rarely explored the mechanism of early AD. AMPARs are early important learning memory-related receptors. However, it is not clear how the expression levels of AMPARs change in early AD. OBJECTIVE: We explored learning memory abilities and AMPAR expression changes in APP/PS1 mice at 4 months, 8 months, and 12 months. METHOD: We used the classic Morris water maze to explore the learning and memory impairment of APP/PS1 mice and used western blotting to explore the changes in AMPARs in APP/PS1 mice. RESULT: We found that memory impairment occurred in APP/PS1 mice as early as 4 months of age, and the impairment of learning and memory gradually became serious with age. The changes in GluA1 and p-GluA1 were most pronounced in the early stages of AD in APP/PS1 mice. CONCLUSION: Our study found that memory impairment in APP/PS1 mice could be detected as early as 4 months of age, and this early injury may be related to GluA1.

Inhibition of ANXA2 regulated by SRF attenuates the development of severe acute pancreatitis by inhibiting the NF-κB signaling pathway.

BACKGROUND: Acute pancreatitis (AP) is an inflammatory process of the pancreas resulting from biliary obstruction or alcohol consumption. Approximately, 10-20% of AP can evolve into severe AP (SAP). In this study, we sought to explore the physiological roles of the transcription factor serum response factor (SRF), annexin A2 (ANXA2), and nuclear factor-kappaB (NF-κB) in SAP. METHODS: C57BL/6 mice and rat pancreatic acinar cells (AR42J) were used to establish an AP model in vivo and in vitro by cerulein with or without lipopolysaccharide (LPS). Production of pro-inflammatory cytokines (IL-1ß and TNF-α) were examined by ELISA and immunoblotting analysis. Hematoxylin and eosin (HE) staining and TUNEL staining were performed to evaluate pathological changes in the course of AP. Apoptosis was examined by flow cytometric and immunoblotting analysis. Molecular interactions were tested by dual luciferase reporter, ChIP, and Co-IP assays. RESULTS: ANXA2 was overexpressed in AP and correlated to the severity of AP. ANXA2 knockdown rescued pancreatic acinar cells against inflammation and apoptosis induced by cerulein with or without LPS. Mechanistic investigations revealed that SRF bound with the ANXA2 promoter region and repressed its expression. ANXA2 could activate the NF-κB signaling pathway by inducing the nuclear translocation of p50. SRF-mediated transcriptional repression of ANXA2-protected pancreatic acinar cells against AP-like injury through repressing the NF-κB signaling pathway. CONCLUSION: Our study highlighted a regulatory network consisting of SRF, ANXA2, and NF-κB that was involved in AP progression, possibly providing some novel targets for treating SAP.