Objective To investigate the changes in eosinophil counts and the activation of microglial cells in the brain tissues of mice at different stages of Angiostrongylus cantonensis infection, and to examine the role of microglia in regulating the progression of angiostrongyliasis and unravel the possible molecular mechanisms. Methods Fifty BALB/c mice were randomly divided into the control group and the 7-d, 14-d, 21-day and 25-d infection groups, of 10 mice in each group. All mice in infection groups were infected with 30 stage III A. cantonensis larvae by gavage, and animals in the control group was given an equal amount of physiological saline. Five mice were collected from each of infection groups on days 7, 14, 21 d and 25 d post-infection, and 5 mice were collected from the control group on the day of oral gavage. The general and focal functional impairment was scored using the Clark scoring method to assess the degree of mouse neurological impairment. Five mice from each of infection groups were sacrificed on days 7, 14, 21 d and 25 d post-infection, and 5 mice from the control group were sacrificed on the day of oral gavage. Mouse brain tissues were sampled, and the pathological changes of brain tissues were dynamically observed using hematoxylin and eosin (HE) staining. Immunofluorescence staining with eosinophilic cationic protein (ECP) and ionized calcium binding adaptor molecule 1 (Iba1) was used to assess the degree of eosinophil infiltration and the counts of microglial cells in mouse brain tissues in each group, and the morphological parameters of microglial cells (skeleton analysis and fractal analysis) were quantified by using Image J software to determine the morphological changes of microglial cells. In addition, the expression of M1 microglia markers Fcγ receptor III (Fcgr3), Fcγ receptor IIb (Fcgr2b) and CD86 antigen (Cd86), M2 microglia markers Arginase 1 (Arg1), macrophage mannose receptor C-type 1 (Mrc1), chitinase-like 3 (Chil3), and phagocytosis genes myeloid cell triggering receptor expressed on myeloid cells 2 (Trem2), CD68 antigen (Cd68), and apolipoprotein E (Apoe) was quantified using real-time quantitative reverse transcription PCR (RT-qPCR) assay in the mouse cerebral cortex of mice post-infection. Results A large number of A. cantonensis larvae were seen on the mouse meninges surface post-infection, and many neuronal nuclei were crumpled and deeply stained, with a large number of bleeding points in the meninges. The median Clark scores of mouse general functional impairment were 0 (interquartile range, 0), 0 (interquartile range, 0.5), 6 (interquartile range, 1.0), 14 (interquartile range, 8.5) points and 20 (interquartile range, 9.0) points in the control group and the 7-d, 14-d, 21-d and 25-d groups, respectively (H = 22.45, P < 0.01), and the median Clark scores of mouse focal functional impairment were 0 (interquartile range, 0), 2 (interquartile range, 2.5), 7 (interquartile range, 3.0), 18 (interquartile range, 5.0) points and 25 (interquartile range, 6.5) points in the control group and the 7-d, 14-d, 21-d and 25-d groups, respectively (H = 22.72, P < 0.01). The mean scores of mice general and focal functional impairment were all higher in the infection groups than in the control group (all P values < 0.05). Immunofluorescence staining showed a significant difference in the eosinophil counts in mouse brain tissues among the five groups (F = 40.05, P < 0.000 1), and the eosinophil counts were significantly higher in mouse brain tissues in the 14-d (3.08 ± 0.78) and 21-d infection groups (5.97 ± 1.37) than in the control group (1.00 ± 0.28) (both P values < 0.05). Semi-quantitative analysis of microglia immunofluorescence showed a significant difference in the counts of microglial cells among the five groups (F = 17.66, P < 0.000 1), and higher Iba1 levels were detected in mouse brain tissues in 14-d (5.75 ± 1.28), 21-d (6.23 ± 1.89) and 25-d infection groups (3.70 ± 1.30) than in the control group (1.00 ± 0.30) (all P values < 0.05). Skeleton and fractal analyses showed that the branch length [(162.04 ± 34.10) μm vs. (395.37 ± 64.11) μm; t = 5.566, P < 0.05] and fractal dimension of microglial cells (1.30 ± 0.01 vs. 1.41 ± 0.03; t = 5.266, P < 0.05) were reduced in mouse brain tissues in the 21-d infection group relative to the control group. In addition, there were significant differences among the 5 groups in terms of M1 and M2 microglia markers Fcgr3 (F = 48.34, P < 0.05), Fcgr2b (F = 55.46, P < 0.05), Cd86 (F = 24.44, P < 0.05), Arg1 (F = 31.18, P < 0.05), Mrc1 (F = 15.42, P < 0.05) and Chil3 (F = 24.41, P < 0.05), as well as phagocytosis markers Trem2 (F = 21.19, P < 0.05), Cd68 (F = 43.95, P < 0.05) and Apoe (F = 7.12, P < 0.05) in mice brain tissues. Conclusions A. cantonensis infections may induce severe pathological injuries in mouse brain tissues that are characterized by massive eosinophil infiltration and persistent activation of microglia cells, thereby resulting in progressive deterioration of neurological functions.

OBJECTIVE: To quantitatively evaluate the accuracy of data obtained from liquid-interference surfaces using an intraoral 3D scanner (IOS) integrated with a compressed airflow system, so as to provide clinical proof of accuracy for the application of the compressed airflow system-based scanning head in improving data quality on liquid-interference surfaces. METHODS: The study selected a standard model as the scanning object, adhering to the "YY/T 1818-2022 Dental Science Intraoral Digital Impression Scanner" guidelines, a standard that defined parameters for intraoral scanning. To establish a baseline for accuracy, the ATOS Q 12M scanner, known for its high precision, was used to generate true reference values. These true values served as the benchmark for evaluating the IOS performance. Building on the design of an existing scanner, a new scanning head was developed to integrate with a compressed airflow system. This new design aimed to help the IOS capture high-precision data on surfaces where liquid-interference, such as saliva, might otherwise degrade scanning accuracy. The traditional scanning method, without airflow assistance, was employed as a control group for comparison. The study included five groups in total, one control group and four experimental groups, to investigate the effects of scanning lens obstruction, airflow presence, liquid media, and the use of the new scanning head on scanning process and accuracy. Each group underwent 15 scans, generating ample data for a robust statistical comparison. By evaluating trueness and precision in each group, the study assessed the impact of the compressed airflow system on the accuracy of IOS data collected from liquid-interference surfaces. Additionally, we selected Elite and Primescan scanners as references for numerical accuracy values. RESULTS: The scanning accuracy on liquid-interference surfaces was significantly reduced in terms of both trueness and precision [Trueness: 18.5 (6.5) vs. 38.0 (6.7), P < 0.05; Precision: 19.1 (8.5) vs. 31.7 (15.0), P < 0.05]. The use of the new scanning head assisted by the compressed airflow system significantly improved the scanning accuracy [Trueness: 22.3(7.6) vs. 38.0 (6.7), P < 0.05; Precision: 25.8 (9.6) vs. 31.7 (15.0), P < 0.05]. CONCLUSION The scanning head based on the compressed airflow system can assist in improving the accuracy of data obtained from liquid-interference surfaces by the IOS.
Imaging, Three-Dimensional/methods* ; Humans ; Dental Impression Technique/instrumentation*

In recent years, gut microbiota has been increasingly recognized as a key player in ethanol metabolism and the development of related diseases. On one hand, ethanol intake directly affects the gut, leading to significant alterations in microbial diversity and composition. On the other hand, gut microbiota influences ethanol-induced damage to various organs, especially the liver, through multiple metabolic byproducts (such as short-chain fatty acids like butyrate, propionate, and acetate), modulation of immune responses, alteration of intestinal barrier function, and regulation of ethanol-metabolizing enzymes. Given the close association between gut microbiota and ethanol metabolism, the gut microbiome presents a promising therapeutic target for alcohol-related liver diseases. This review summarizes recent advances in understanding how gut microbiota affects ethanol metabolism, aiming to elucidate its role in the onset and progression of ethanol-related diseases and to provide a theoretical basis and novel targets for microbiota-based interventions.
Gastrointestinal Microbiome/physiology* ; Ethanol/metabolism* ; Humans ; Fatty Acids, Volatile/metabolism* ; Liver Diseases, Alcoholic/metabolism* ; Animals ; Alcohol Drinking/metabolism*

Nonalcoholic fatty liver disease （NAFLD） has become the most common chronic liver disease in the world， and it is also one of the main causes of liver cirrhosis and hepatocellular carcinoma， so it is particularly important to curb the development and progression of NAFLD in a timely manner. However， due to its complex pathogeneses， there are currently no effective methods for radical treatment. As a new generation of probiotics， Akkermansia muciniphila （Akk bacteria） can improve metabolic disorders of the body， and more and more studies have shown that Akk bacteria have a potential therapeutic effect on metabolic diseases， especially NAFLD. Therefore， this article briefly reviews the mechanism of action of Akk bacteria in NAFLD， in order to provide new ideas for improving the treatment of NAFLD and creating new therapies.

Objective To investigate the capillarization of liver sinusoidal endothelial cells (LSECs) and its association with hepatic fibrosis during the development of alveolar echinococcosis, so as to provide the basis for unraveling the mechanisms underlying the role of LSEC in the development and prognosis of hepatic injuries and hepatic fibrosis caused by alveolar echinococcosis. Methods Forty C57BL/6 mice at ages of 6 to 8 weeks were randomly divided into a control group and 1-, 2- and 4-week infection groups, of 10 mice in each group. Each mouse in the infection groups was intraperitoneally injected with 2 000 Echinococcus multilocularis protoscoleces, while each mouse in the control group was given an equal volume of phosphate-buffered saline using the same method. All mice were sacrificed 1, 2 and 4 weeks post-infection and mouse livers were collected. The pathological changes of livers were observed using hematoxylin-eosin (HE) staining, and hepatic fibrosis was evaluated through semi-quantitative analysis of Masson’s trichrome staining-positive areas. The activation of hepatic stellate cells (HSCs) and extracellular matrix (ECM) deposition were examined using immunohistochemical staining of α-smooth muscle actin (α-SMA) and collagen type I alpha 1 (COL1A1), and the fenestrations on the surface of LSECs were observed using scanning electron microscopy. Primary LSECs were isolated from mouse livers, and the mRNA expression of LSEC marker genes Stabilin-1, Stabilin-2, Ehd3, CD209b, GATA4 and Maf was quantified using real-time fluorescence quantitative PCR (qPCR) assay. Results Destruction of local liver lobular structure was observed in mice 2 weeks post-infection with E. multilocularis protoscoleces, and hydatid cysts, which were surrounded by granulomatous tissues, were found in mouse livers 4 weeks post-infection. Semi-quantitative analysis of Masson’s trichrome staining showed a significant difference in the proportion of collagen fiber contents in mouse livers among the four groups (F = 26.060, P < 0.001), and a higher proportion of collagen fiber contents was detected in mouse livers in the 4-week infection group [(11.29 ± 2.58)%] than in the control group (P < 0.001). Immunohistochemical staining revealed activation of a few HSCs and ECM deposition in mouse livers 1 and 2 weeks post-infection, and abundant brown-yellow stained α-SMA and COL1A1 were deposited in the lesion areas in mouse livers 4 weeks post-infection, which spread to surrounding tissues. Semi-quantitative analysis revealed significant differences in α-SMA (F = 7.667, P < 0.05) and COL1A1 expression (F = 6.530, P < 0.05) in mouse levers among the four groups, with higher α-SMA [(7.13 ± 3.68)%] and COL1A1 expression [(13.18 ± 7.20)%] quantified in mouse livers in the 4-week infection group than in the control group (both P values < 0.05). Scanning electron microscopy revealed significant differences in the fenestration frequency (F = 37.730, P < 0.001) and porosity (F = 16.010, P < 0.001) on the surface of mouse LSECs among the four groups, and reduced fenestration frequency and porosity were observed in the 1-[(1.22 ± 0.48)/μm² and [(3.05 ± 0.91)%] and 2-week infection groups [(3.47 ± 0.10)/μm² and (7.57 ± 0.23)%] groups than in the control group (all P values < 0.001). There was a significant difference in the average fenestration diameter on the surface of mouse LSECs among the four groups (F = 15.330, P < 0.001), and larger average fenestration diameters were measured in the 1-[(180.80 ± 16.42) nm] and 2-week infection groups [(161.70 ± 3.85) nm] than in the control group (both P values < 0.05). In addition, there were significant differences among the four groups in terms of Stabilin-1 (F = 153.100, P < 0.001), Stabilin-2 (F = 57.010, P < 0.001), Ehd3 (F = 31.700, P < 0.001), CD209b (F = 177.400, P < 0.001), GATA4 (F = 17.740, P < 0.001), and Maf mRNA expression (F = 72.710, P < 0.001), and reduced mRNA expression of Stabilin-1, Stabilin-2, Ehd3, CD209b, GATA4 and Maf genes was quantified in three infection groups than in the control group (all P values < 0.001). Conclusions E. multilocularis infections may induce capillarization of LSECs in mice, and result in a reduction in the expression of functional and phenotypic marker genes of LSECs, and capillarization of LSECs occurs earlier than activation of HSC and development of hepatic fibrosis.

Objective To explore the correlation between thyroid antibody levels and early renal injury in patients with type 2 diabetes mellitus(T2DM)combined with Hashimoto's thyroiditis(HT).Methods A total of 375 T2DM patients hospitalized in The Affiliated Hospital of Xuzhou Medical University from January 2018 to December 2022 were selectedas the study subjects,and 197 healthy people were selected as the control subjects.The patients with T2DM were divided into simple T2DM group(n=191)and T2DM combined with HT group(HT,n=184).According to the urinary albumin/creatinine ratio(UACR)level,T2DM patients with HT were divided into microalbuminuria subgroup(MUAlb,30≤UACR≤300 mg/g,n=70)and normal albuminuria subgroup(NUAlb,UACR<30 mg/g,n=114).According to whether the thyroid antibody was positive,they were divided into thyroid peroxides antibody[TPOAb(+)]subgroup(n=56),thyroglobulin antibody[TGAb(+)]subgroup(n=40)and TGAb and TPOAb double antibody positive subgroup(n=88).Results Compared with the NC group,the smoking,drinking,urinary creatinine,alpha 1-microglobulin,UACR,FPG,HbA1c,LDL-C,TC,and TG in the HT and T2DM groups increased(P<0.05),while HDL-C decreased(P<0.05).Compared with the NUAlb subgroup,the MUAlb subgroup showed age,DM duration,FPG,HbA1c,TGAb,TPOAb,thyroid stimulating hormone(TSH)increased(P<0.05),while FT3 and eGFR decreased(P<0.05).Spearman correlation analysis showed that UACR was positively correlated with age,HbA1c,TPOAb,TGAb,TSH(P<0.01),and negatively correlated with FT3(P<0.01).The UACR of the TGAb(+)+TPOAb(+)subgroup was higher than that of the TGAb(+)and TPOAb(+)subgroups(P<0.05).Logistic regression analysis showed that TSH,TGAb,TPOAb,and HbA1c were risk factors for MUAlb,while FT3 was a protective factor for MUAlb.Conclusions In T2DM with HT patients with normal thyroid function,TPOAb and TGAb are closely related to the occurrence of early renal injury.

Objective To explore the clinical features,treatment and prognosis of glioblastomas(GBM)in adults.Methods A retrospective cohort study was performed on 176 adult GBM patients admitted to our department from January 2015 to December 2021.Chi-square test was used to investigate the clinical differences between isocitrate dehydrogenase(IDH)mutant and wild-type GBM.Kaplan-Meier and Log-Rank tests were employed to plot survival curve and compute the survival analysis.Multivariate Cox regression model was applied to identify the independent prognostic factors.Results IDH wild-type GBM account for 89.2％and had significantly differences from the IDH-mutant GBM in terms of age of onset,Karnofsky(KPS)score at admission,symptoms of neurological deficit,and methylation status of O6-methylguanine-DNA-methyltransferase(MGMT)promoter(P＜0.05).For the IDH wild-type GBM patients receiving conventional therapy,univariate Cox hazard analysis showed gross total resection,methylation of MGMT promoter,initiation of radiation within the 5th to 6th week after surgery,and adjuvant temozolomide(TMZ)chemotherapy ≥6 cycles were favorable prognostic factors for overall survival(OS);GBMs in the left hemisphere,involvement of single lobe,methylation of MGMT promoter,and initiation of radiation within the 5th to 6th week after surgery were favorable prognostic factors for progression free survival(PFS)(all P＜0.05).Moreover,multivariate Cox hazard regression analysis indicated that methylation of MGMT promoter,and initiation of radiation within the 5th to 6th week after surgery,and adjuvant TMZ chemotherapy ≥6 cycles were independent protective factors for OS,and GBMs in the left hemisphere,involvement of single lobe and methylation of MGMT promoter were independent protective factors for PFS in the GBM patients(all P＜0.05).Conclusion The clinical and prognostic features are totally different between IDH mutant and wild-type GBM,and molecular detections are needed for the further pathological classification.Methylation of MGMT promoter is a primary marker of favorite prognosis for IDH wild-type GBM,and slightly delay in radiotherapy(the 5th to 6th week after surgery)can effectively improve the survival prognosis of IDH wild-type GBM.

In fixed prosthodontics, clear exposure of the preparation margin is the prerequisite for obtaining accurate digital impressions and improving the marginal fit of restorations. To resolve the issues associated with the cord retraction technique, such as pain, acute injury, and prolonged procedural time, this study proposes a new technology for intraoral digital impression taking with pneumatic gingival retraction. The new scanning head blows a high-speed airflow that instantaneously separates the free gingiva, locally exposing the subgingival preparation margin. Combined with the farthest point preservation stitching algorithm based on the distance from the normal vector and high-speed laser scanning photography, it achieves global preparation edge data and gingival reconstruction, realizing painless, non-invasive, and efficient precise acquisition of the preparation margin. Using this new technique, a patient with a full porcelain crown restoration on a posterior tooth was treated. The digital impression revealed a clear margin of the preparation, and the crown made from this data has a good marginal fit.

OBJECTIVES: The magnesium depletion score (MDS) is considered more reliable than traditional approaches for predicting magnesium deficiency in humans. We explored the associations of MDS and dietary magnesium intake with diabetes. METHODS: We obtained data from 18,853 participants in the National Health and Nutrition Examination Survey 2011-2018. Using multivariate regression and stratified analysis, we investigated the relationships of both MDS and magnesium intake with diabetes. To compute prevalence ratios (PRs), we employed modified Poisson or log-binomial regression. We characterized the non-linear association between magnesium intake and diabetes using restricted cubic spline analysis. RESULTS: Participants with MDS ≥2 exhibited a PR of 1.26 (95% confidence interval [CI], 1.19 to 1.34) for diabetes. Per-standard deviation (SD) increase in dietary magnesium intake was associated with a lower prevalence of diabetes (PR, 0.91; 95% CI, 0.87 to 0.96). Subgroup analyses revealed a positive association between MDS ≥2 and diabetes across all levels of dietary magnesium intake, including the lowest (PR, 1.35; 95% CI, 1.18 to 1.55), middle (PR, 1.23; 95% CI, 1.12 to 1.35), and highest tertiles (PR, 1.25; 95% CI, 1.13 to 1.37; pinteraction<0.001). Per-SD increase in magnesium intake was associated with lower diabetes prevalence in participants with MDS <2 (PR, 0.92; 95% CI, 0.87 to 0.98) and those with MDS ≥2 (PR, 0.91; 95% CI, 0.84 to 0.98; pinteraction=0.030). CONCLUSIONS MDS is associated with diabetes, particularly among individuals with low magnesium intake. Adequate dietary magnesium intake may reduce diabetes risk, especially in those with high MDS.

Bone substitute material implantation has become an important treatment strategy for the repair of oral and maxillofacial bone defects. Recent studies have shown that appropriate inflammatory and immune cells are essential factors in the process of osteoinduction of bone substitute materials. Previous studies have mainly focused on innate immune cells such as macrophages. In our previous work, we found that T lymphocytes, as adaptive immune cells, are also essential in the osteoinduction procedure. As the most important antigen-presenting cell, whether dendritic cells (DCs) can recognize non-antigen biomaterials and participate in osteoinduction was still unclear. In this study, we found that surgical trauma associated with materials implantation induces necrocytosis, and this causes the release of high mobility group protein-1 (HMGB1), which is adsorbed on the surface of bone substitute materials. Subsequently, HMGB1-adsorbed materials were recognized by the TLR4-MYD88-NFκB signal axis of dendritic cells, and the inflammatory response was activated. Finally, activated DCs release regeneration-related chemokines, recruit mesenchymal stem cells, and initiate the osteoinduction process. This study sheds light on the immune-regeneration process after bone substitute materials implantation, points out a potential direction for the development of bone substitute materials, and provides guidance for the development of clinical surgical methods.
Biocompatible Materials/metabolism* ; HMGB1 Protein/metabolism* ; Myeloid Differentiation Factor 88/metabolism* ; Bone Substitutes/metabolism* ; Dendritic Cells/metabolism*