BACKGROUND:Studies have found that probiotics have a certain preventive and therapeutic effect on peri-implantitis,and there are further explorations in the mechanism against peri-implantitis.OBJECTIVE:To review the mechanism and clinical application of probiotics in the treatment of peri-implantitis.METHODS:Relevant literature was searched on PubMed,Web of Science,CNKI,and WanFang Data,using the search terms of"probiotics,peri-implantitis,flora imbalance,immunoregulation,inflammatory reaction,mechanism of action"in Chinese and English.A total of 90 articles were finally included.RESULTS AND CONCLUSION:Probiotics have the following mechanisms.They can activate the anti-inflammatory mechanism by inhibiting the secretion of inflammatory factors and promoting the production of anti-inflammatory factors.They can destroy the cell wall of pathogenic bacteria by secreting microbial complexes and bacteriocins,reduce the pH value of biofilms,improve the composition of microorganisms in microecology,induce the change of bacterial community structure,and restore the balance of microbial population around implants.They have immunomodulatory effects and can enhance the resistance of the host oral mucosa to pathogenic bacteria in the surrounding area of the implant.In addition,probiotics can produce antibacterial compounds,offset the adhesion of pathogenic microorganisms,and regulate immune function.Through the above mechanisms,probiotics have certain potential in the adjuvant treatment of peri-implantitis,which can improve the clinical parameters of peri-implantitis and affect the microbiota.Probiotic therapy provides a new treatment option,but more long-term prospective studies are needed to further verify its effect.

BACKGROUND:Studies have found that probiotics have a certain preventive and therapeutic effect on peri-implantitis,and there are further explorations in the mechanism against peri-implantitis.OBJECTIVE:To review the mechanism and clinical application of probiotics in the treatment of peri-implantitis.METHODS:Relevant literature was searched on PubMed,Web of Science,CNKI,and WanFang Data,using the search terms of"probiotics,peri-implantitis,flora imbalance,immunoregulation,inflammatory reaction,mechanism of action"in Chinese and English.A total of 90 articles were finally included.RESULTS AND CONCLUSION:Probiotics have the following mechanisms.They can activate the anti-inflammatory mechanism by inhibiting the secretion of inflammatory factors and promoting the production of anti-inflammatory factors.They can destroy the cell wall of pathogenic bacteria by secreting microbial complexes and bacteriocins,reduce the pH value of biofilms,improve the composition of microorganisms in microecology,induce the change of bacterial community structure,and restore the balance of microbial population around implants.They have immunomodulatory effects and can enhance the resistance of the host oral mucosa to pathogenic bacteria in the surrounding area of the implant.In addition,probiotics can produce antibacterial compounds,offset the adhesion of pathogenic microorganisms,and regulate immune function.Through the above mechanisms,probiotics have certain potential in the adjuvant treatment of peri-implantitis,which can improve the clinical parameters of peri-implantitis and affect the microbiota.Probiotic therapy provides a new treatment option,but more long-term prospective studies are needed to further verify its effect.

Objective:Using resting-state functional magnetic resonance imaging (rs-fMRI), we explored the changes in dynamic functional network connections (dFNC) in the brains of patients with first-episode schizophrenia (SZ) and evaluated the potential clinical value of dFNC changes in combination with a machine learning model.Methods:Clinical data of 50 patients with schizophrenia (schizophrenia group), 29 males and 21 females, aged 18-47 (28.3±7.2) years, who attended the psychiatric department of the Second Affiliated Hospital of Xinxiang Medical College from January 2022 to August 2023, were retrospectively included. In the same period, 50 healthy controls matched for age and education (healthy control group) were recruited, of which 24 were male and 26 were female, aged 18-48 (28.0±6.9) years. The rs-fMRI imaging data were acquired for each subject. The dFNC cluster analysis was performed based on independent component analysis, and the differences between groups with different state FNC matrices were statistically analyzed. The dataset samples were divided into a training set (35 SZ patients and 35 healthy controls) and a validation set (15 SZ patients and 15 healthy controls) in a 7∶3 ratio. A machine learning classification model was constructed based on the dFNC matri. The performance of the model for distinguishing between schizophrenia and healthy controls was assessed by five-fold cross-validation using accuracy (ACC), recall (REC), F1 score, and area under curve (AUC) metrics of the working characteristics of the subjects.Results:Five network functional connectivity states were obtained by dFNC cluster analysis. Patients with first SZ showed a wide range of high connectivity and low connectivity changes on the neural dynamic functional networks, as shown by increased dynamic connectivity within the visual network (VIS) in state 1 (weak connectivity); The dynamic connectivity between executive control network (ECN) and VIS, frontal parietal network (FPN) and VIS decreases at state 3 (strong connectivity); The dynamic connectivity between default mode network (DMN) and FPN, DMN and ventral attention network (VAN) decreases at state 4 (weak connectivity). The machine learning results show that the classification model constructed by the dFNC matrix combined with SVM in state 3 (strongly connected) in the validation set obtains the best classification results (ACC=0.938; REC=0.938; F1=0.937; AUC=0.984), and the overall average classification ACC of the five states reaches 0.751, and AUC reaches 0.784.Conclusion:Patients with first-episode SZ have some brain functional network connectivity abnormalities, and a machine learning model based on dFNC features has high classification performance in distinguishing first-episode SZ from HC.

Objective:Using resting-state functional magnetic resonance imaging (rs-fMRI), we explored the changes in dynamic functional network connections (dFNC) in the brains of patients with first-episode schizophrenia (SZ) and evaluated the potential clinical value of dFNC changes in combination with a machine learning model.Methods:Clinical data of 50 patients with schizophrenia (schizophrenia group), 29 males and 21 females, aged 18-47 (28.3±7.2) years, who attended the psychiatric department of the Second Affiliated Hospital of Xinxiang Medical College from January 2022 to August 2023, were retrospectively included. In the same period, 50 healthy controls matched for age and education (healthy control group) were recruited, of which 24 were male and 26 were female, aged 18-48 (28.0±6.9) years. The rs-fMRI imaging data were acquired for each subject. The dFNC cluster analysis was performed based on independent component analysis, and the differences between groups with different state FNC matrices were statistically analyzed. The dataset samples were divided into a training set (35 SZ patients and 35 healthy controls) and a validation set (15 SZ patients and 15 healthy controls) in a 7∶3 ratio. A machine learning classification model was constructed based on the dFNC matri. The performance of the model for distinguishing between schizophrenia and healthy controls was assessed by five-fold cross-validation using accuracy (ACC), recall (REC), F1 score, and area under curve (AUC) metrics of the working characteristics of the subjects.Results:Five network functional connectivity states were obtained by dFNC cluster analysis. Patients with first SZ showed a wide range of high connectivity and low connectivity changes on the neural dynamic functional networks, as shown by increased dynamic connectivity within the visual network (VIS) in state 1 (weak connectivity); The dynamic connectivity between executive control network (ECN) and VIS, frontal parietal network (FPN) and VIS decreases at state 3 (strong connectivity); The dynamic connectivity between default mode network (DMN) and FPN, DMN and ventral attention network (VAN) decreases at state 4 (weak connectivity). The machine learning results show that the classification model constructed by the dFNC matrix combined with SVM in state 3 (strongly connected) in the validation set obtains the best classification results (ACC=0.938; REC=0.938; F1=0.937; AUC=0.984), and the overall average classification ACC of the five states reaches 0.751, and AUC reaches 0.784.Conclusion:Patients with first-episode SZ have some brain functional network connectivity abnormalities, and a machine learning model based on dFNC features has high classification performance in distinguishing first-episode SZ from HC.

Background::Dual-energy computed tomography (DECT) is purported to accurately distinguish uric acid stones from non-uric acid stones. However, whether DECT can accurately discriminate ammonium urate stones from uric acid stones remains unknown. Therefore, we aimed to explore whether they can be accurately identified by DECT and to develop a radiomics model to assist in distinguishing them.Methods::This research included two steps. For the first purpose to evaluate the accuracy of DECT in the diagnosis of uric acid stones, 178 urolithiasis patients who underwent preoperative DECT between September 2016 and December 2019 were enrolled. For model construction, 93, 40, and 109 eligible urolithiasis patients treated between February 2013 and October 2022 were assigned to the training, internal validation, and external validation sets, respectively. Radiomics features were extracted from non-contrast CT images, and the least absolute shrinkage and selection operator (LASSO) algorithm was used to develop a radiomics signature. Then, a radiomics model incorporating the radiomics signature and clinical predictors was constructed. The performance of the model (discrimination, calibration, and clinical usefulness) was evaluated.Results::When patients with ammonium urate stones were included in the analysis, the accuracy of DECT in the diagnosis of uric acid stones was significantly decreased. Sixty-two percent of ammonium urate stones were mistakenly diagnosed as uric acid stones by DECT. A radiomics model incorporating the radiomics signature, urine pH value, and urine white blood cell count was constructed. The model achieved good calibration and discrimination {area under the receiver operating characteristic curve (AUC; 95% confidence interval [CI]), 0.944 (0.899–0.989)}, which was internally and externally validated with AUCs of 0.895 (95% CI, 0.796–0.995) and 0.870 (95% CI, 0.769–0.972), respectively. Decision curve analysis revealed the clinical usefulness of the model.Conclusions::DECT cannot accurately differentiate ammonium urate stones from uric acid stones. Our proposed radiomics model can serve as a complementary diagnostic tool for distinguishing them in vivo.

OBJECTIVE To investigate the effects and mechanism of Glycyrrhiza inflata polysaccharides （GiP） and GiP-B1 on the maturation and anti-tumor effect of dendritic cell （DC）. METHODS The immature DC （imDC） of hepatocellular carcinoma cell H22 tumor-bearing mice cultured in vitro were divided into control group， tumor necrosis factor-α （TNF-α） group， GiP group， and GiP-B1 group. The viability， positive expressions of surface markers （CD11c， CD80， CD86， MHC-Ⅱ）， the levels of interleukin-12p70 （IL-12p70） and IL-4 in mature DC （mDC） of tumor-bearing mice were detected. mDC and CD4+T lymphocytes were co-cultured to generate CD4-cytotoxic T cell （CD4-CTL）； stimulation index， the levels of IL-12p70， interferon-γ （IFN-γ）， IL-4 and IL-10， the killing activity of CD4-CTL to H22 cell were detected. mRNA expressions of IL-12， IL-12 receptor （IL-12R）， signal transducer and activator of transcription-4 （STAT-4）， as well as the protein expression of IL-12 receptor β2 （IL-12Rβ2）， phosphorylation levels of nuclear factor-kappa B （NF- κB） p65 and STAT-4 proteins in mDC were detected after co-culture. RESULTS Compared with the control group， the viability of mDC， the positive expressions of MHC-Ⅱ， and the levels of IL-12p70 and IL-4 were increased significantly in GiP group and GiP-B1 group （P＜0.05）. The positive expressions of CD11c， CD80 and CD86 showed an increasing trend， but the differences were not statistically significant （P＞0.05）. After co-culturing， the stimulation index， the levels of IL-12p70 and IFN-γ were significantly increased （P＜0.05）， while the levels of IL-4 and IL-10 （except for the GiP group） were significantly decreased （P＜0.05）； the cytotoxicity against H22 cells was significantly enhanced （P＜0.05）. mRNA expressions of IL-12 and IL-12R （except for GiP group） and STAT-4， protein expression of IL-12Rβ2 as well as phosphorylation levels of NF-κB p65 and STAT-4 protein were increased significantly in mDC （P＜0.05）. CONCLUSIONS GiP and GiP-B1 have a good promoting effect on the maturation of DC in tumor-bearing mice， effectively stimulate CD4+T cell proliferation， enhance the anti-tumor activity of CD4-CTL，and its mechanism may be related to activating IL-12/NF-κB/ STAT-4 signaling pathway.

ObjectiveTo explore the relationship between smoking behavior and related factors among the adult residents in Fengxian District,so as to provide an evidence for carrying out tobacco control and other health promotion work. MethodsA multi-stage stratified cluster random sampling method was used to select 2 272 community residents aged between 15 and 69 yeas to carry out the questionnaire survey. ResultsIn 2020, the smoking rate of adult residents in Fengxian District was 23.50%. Smoking behavior was statistically correlated with age, gender, household registration, chronic disease, occupation and educational level. Smoking behavior was inversely correlated with educational level. Smoking rate of male residents was significantly higher than that of female residents, smoking rate of residents with chronic diseases was significantly higher than that of those without suffering from chronic diseases, and smoking rate of permanent registered residents was significantly higher than that of those non-locals. The highest smoking prevalence was among retired and freelancers, followed by staff of government agencies and public institutes, while the lowest was among students, followed by intellectuals. Multivariate logistic regression analysis showed that gender, age and education level were the main factors affecting the smoking prevalence level. ConclusionThe general　smoking rate of adult residents in Fengxian District was higher than the average level in Shanghai but lower than the national level. Male residents aged ≥25 years and with lower education level are the key invention targets for tobacco control.

Objective To investigate the biological safety of commercially available natural rubber latex and synthetic polyurethane condoms.Methods Natural rubber latex condom brands of A1 and A2 and polyurethane condom brands of B1 and B2 were purchased from large chain pharmacies in Chengdu,with three packages randomly selected for each brand.The study assessed the toxic effects of condom extracts on L-929 mouse fibroblasts according to GB/T standards.Gross observation and histopathological evaluation were conducted to assess the irritation reactions of condoms on the vagina and penis of rabbits(3 rabbits were used for each brand),as well as their sensitization effects on guinea pig skin.Additionally,the impact of continuous perfusion of condom extracts of the vaginas of SD rats for 30 days on their reproductive systems was evaluated,following GB/T standards(5 rats were used for each brand).Results Extracts from natural rubber latex condom brands A1 and A2,at concentrations of 100%and 50%,exhibited significant cytotoxicity,with optical density(OD)values being significantly lower than those of the blank control group and the polyurethane condom brands B1 and B2(P＜0.01).There was no significant difference in cell morphology and OD values between the extracts of B1 and B2 and the blank control group(P＞0.05).Vaginal congestion was found in 3 rabbits from A1 group and 1 rabbit from the A2 group,while no obvious congestion was noted in rabbits from the B1 and the B2 groups.Histopathological examination showed scattered inflammatory cell infiltration in the vaginal tissue of 3 rabbits from the A1 group and 2 rabbits from the A2 group,and slight congestion in the blood vessels of the lamina propria.No obvious pathological changes were observed in the vaginal tissue of polyurethane brand rabbits.Two rabbits from the A1 group and 1 rabbit from the A2 group showed transient and mild erythema on the penis during the experiment.Histopathological examination showed that 1 rabbit from A1 group had small foci of pericapillary lymphocytes in the dermis of the penis,while no significant pathological changes were observed in the penile tissue of A2,B1,and B2 groups.After 30 days of continuous vaginal perfusion with condom extract,3 rats in A1 group and 2 rats in the A2 group had uterine congestion,with the degree of congestion being lower in the A2 group.No significant congestion or pathological changes were observed in the vaginal and penile tissues of rabbits,or in the uterine tissues of rats from the polyurethane groups.None of the 4 groups of guinea pigs showed significant skin allergic reactions to the condom extracts.Conclusion Significant differences in biosafety exist among condoms of various materials and brands.To ensure product safety,it is crucial to strengthen quality control and regulatory oversight after condoms become commercially available.

Objective:To compare the dose and image quality of selected photon shield (SPS) technique, organ-based tube current modulation (OBTCM) technique and the combination of these two techniques for reducing the organ dose in head CT examination for infants.Methods:Two anthropomorphic head phantoms (CIRS 1-yr-old and 5-yr-old) were scanned by using Reference mode, Reference + OBTCM mode, SPS mode and SPS + OBTCM mode, respectively. Radiation doses to the lens of the eye, the anterior of the brain, the posterior of the brain, noise level and CNR of orbit and brain in different phantoms were measured and compared by using different scanning modes.Results:Compared with Reference mode, the doses to the lens of the eye in 1-yr-old and 5-yr-old phantom decreased by (21.89 ± 0.01)% and (28.33 ± 0.34)%, respectively. In SPS mode, the reduction in doses to the lens of the eye in 1-yr-old and 5-yr-old phantom were (71.38 ± 1.30)% and (53.72 ± 2.42)%, respectively. In SPS + OBTCM mode, the reduction was (71.12 ± 2.54)% and (55.73 ± 1.90)%, respectively. There was significant difference in the noise level of orbit and brain in different phantoms under various scanning modes ( F=5.67-85.47, P< 0.05). The noise level in OBTCM mode compared with reference mode increased slightly (<1.45 HU) in various phantoms. SPS and SPS + OBTCM mode resulted in a small noise increase (<2.58 HU). There was no significant difference in CNR of different phantoms under various scanning modes ( P>0.05). Conclusions:SPS and SPS + OBTCM mode can significantly reduce the radiation dose of lens and the whole image plane in the head CT scan for infants, with maintaining the image quality.

【Objective】 To confirm the role of Wnt signaling pathway in the occurrence and development of gastric cancer （GC）， establish a prognostic model composed of Wnt pathway related genes， and then evaluate the predictive value of the model. 【Methods】 We downloaded the gene expression data and survival data of GC in TCGA database， and used GSEA enrichment analysis to verify the enrichment of Wnt pathway in GC and para-cancer samples. In this study， univariable COX regression analysis and survival curve analysis were used to select the prognosis-related genes of GC. Then the multivariate COX proportional hazard regression model was used to obtain the prognostic model of Wnt signaling pathway related genes. Then， receiver operating characteristic （ROC） curve and forest plot were used to verify the clinical predictive value of the model. The model was then validated in GEO external database. Finally， by utilizing quantitative real-time PCR （qPCR）， we detected the expressions of Wnt signaling pathway related genes in 8 pairs of clinical GC and para-cancer samples. 【Results】 We downloaded 32 samples of normal para-cancer samples and 375 cancer samples and their corresponding clinical data. GSEA enrichment showed that compared with normal samples， Wnt pathway was significantly enriched in GC samples （P<0.05）. The results of univariate COX analysis showed that 13 Wnt pathway genes were closely related to the prognosis of GC patients. Multivariate COX determined that the model was multiplied and accumulated by ETV2， SERPINE1， CPZ， VPS35 and IGFBP1 and their corresponding coefficient β. The survival curve and ROC curve showed that the model could accurately predict the prognosis of GC patients， and the 1-year， 3-year， and 5-year areas under the curve （AUC） were 68.0%， 69.4% and 78.5%， respectively. Clinical univariate and multivariate COX analyses showed that the model could become an independent prognostic factor other than TNM system of GC. The external data set （GSE84437） validation results of GC showed that the model could better predict the prognosis of GC patients. qPCR results indicated that ETV2， SERPINE1， CPZ， VPS35 and IGFBP1 expressions were upregulated in GC samples compared with para-cancer samples. 【Conclusion】 This study further confirmed that Wnt pathway plays an important role in the progress of GC from the perspective of bioinformatics， and we have established a prognosis-related risk model， providing a new perspective for clinical genetic testing， targeted therapy and individualized therapy.