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Background Periodontitis has increasingly been recognized for its impact on systemic health. Mendelian Randomization (MR), an emerging causal inference method, effectively overcomes confounding biases in observational studies. To systematically evaluate the causal relationship between periodontitis and various systemic diseases through a meta-analysis of mendelian randomization studies. Methods The China National Knowledge Infrastructure, WanFang data, PubMed, Web of Science and Science Direct were searched for mendelian randomization studies on periodontitis in relation to systemic disorders. Meta-analysis was performed on data gathered using the inverse-variance weighted and mendelian randomization-Egger methods. Results A total of 610 records was screened. The systematic review included 78 mendelian randomization experiments, while the meta-analysis included 34. There was strong evidence linking periodontitis to an increased risk of cardioembolic stroke and depression. However, the data showed that periodontitis had no substantial causal association with Alzheimer’s disease, Parkinson’s disease, coronary atherosclerosis, rheumatoid arthritis, hypothyroidism, hyperthyroidism, gastric cancer, psoriasis, Sjögren’s syndrome, or inflammatory bowel disease. Conclusions The evidence from mendelian randomization studies suggests that periodontitis plays a causal role in in cardioembolic stroke and depression. However, the rest of the findings differ from those of earlier observational research. As a result, future research should focus on resolving these constraints using bigger, more diverse populations and investigating the molecular mechanisms behind the observed relationships. Trial registration The PROSPERO database lists this meta-analysis under the registration number CRD42024581585.

Objectives Peri-implantitis was an inflammatory progress on the tissue around the implant. The Osteoprotegerin G1181C (rs2073618) polymorphism was reported to be related to the increased risk of the peri-implantitis, whereas another found no relationship. The present study was conducted to research the relationship between Osteoprotegerin rs2073618 polymorphism and peri-implantitis susceptibility. Materials and methods The meta-analysis was performed according to the Preferred Reporting Items for Systematic reviews. Electronic databases including PubMed, Web of science, Springer Link and Embase (updated to April 15, 2022) were retrieved. The cohort study, case-control study or cross-sectional study focusing on the Osteoprotegerin rs2073618 polymorphism and peri-implantitis were retrieved. The data included basic information of each study and the genotype and allele frequencies of the cases and controls. Results Three studies were finally included, including 160 cases and 271 controls. Allelic model, homozygote model, recessive model, dominant model, and heterozygous model were established to assess the relationship between OPG rs2073618 polymorphism and peri-implantitis susceptibility. The Osteoprotegerin rs2073618 polymorphism was significantly associated with peri-implantitis in Recessive model and Homozygote model. Conclusion OPG rs2073618 polymorphism in Recessive model and Homozygote model was highly likely related to the risk of peri-implantitis. PROSPERO registration number : CRD42022320812

Background 2019 Coronavirus disease (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The COVID-19 pandemic has already had a serious influence on human existence, causing a huge public health concern for countries all around the world. Because SARS-CoV-2 infection can be spread by contact with the oral cavity, the link between oral illness and COVID-19 is gaining traction. Through bioinformatics approaches, we explored the possible molecular mechanisms linking the COVID-19 and periodontitis to provide the basis and direction for future research. Methods Transcriptomic data from blood samples of patients with COVID-19 and periodontitis was downloaded from the Gene Expression Omnibus database. The shared differentially expressed genes were identified. The analysis of Gene Ontology, Kyoto Encyclopedia of Genesand Genomes pathway, and protein–protein interaction network was conducted for the shared differentially expressed genes. Top 5 hub genes were selected through Maximal Clique Centrality algorithm. Then mRNA-miRNA network of the hub genes was established based on miRDB database, miRTarbase database and Targetscan database. The Least absolute shrinkage and selection operator regression analysis was used to discover possible biomarkers, which were then investigated in relation to immune-related genes. Results Fifty-six shared genes were identified through differential expression analysis in COVID-19 and periodontitis. The function of these genes was enriched in regulation of hormone secretion, regulation of secretion by cell. Myozenin 2 was identified through Least absolute shrinkage and selection operator regression Analysis, which was down-regulated in both COVID-19 and periodontitis. There was a positive correlation between Myozenin 2 and the biomarker of activated B cell, memory B cell, effector memory CD4 T cell, Type 17 helper cell, T follicular helper cell and Type 2 helper cell. Conclusion By bioinformatics analysis, Myozenin 2 is predicted to correlate to the pathogenesis and immune infiltrating of COVID-19 and periodontitis. However, more clinical and experimental researches are needed to validate the function of Myozenin 2.

IntroductionPeriodontal regeneration surgery has been widely used to deal with intrabony defects. Modified minimally invasive surgical technique (M-MIST) is designed to deal with isolated interdental intrabony defects, and has achieved satisfactory periodontal regenerative effect. Bio-Oss Collagen, as a bioactive material, has been applied for periodontal regeneration. It is similar to human cancellous bone, with the ability to promote bone formation; furthermore, it has exceptional plasticity and spatial stability. The combination of different materials and techniques has become a research hotspot in recent years. By combining the superiority of regeneration technology and materials, better regenerative effect can be achieved. This study will search for differences between M-MIST combined with Bio-Oss Collagen, and M-MIST alone in regeneration therapy for intrabony defects.Methods and analysisThe present research is designed as a two-group parallel randomised controlled trial. The total number of patients is 40. The patients will be randomly assigned to two groups, with 20 participants in each group, for further periodontal regenerative surgery. Test group: M-MIST plus Bio-Oss Collagen. Control group: M-MIST. After 12 months, the measurement indices will be recorded; these will include clinical attachment gain and radiographical intrabony defect depth change as the primary results, and secondary outcomes of full-mouth plaque scores, probing depth, full-mouth bleeding scores, gingival recession, mobility, gingival papilla height and Visual Analogue Scale. The paired samples t-test will be applied to detect any difference between baseline and 1-year registrations. A general linear model will be performed to study the relationship between the secondary and the primary outcome.Ethics and disseminationThe present research has received approval from the Ethics Committee of Peking University School and Hospital of Stomatology (PKUSSIRB-202053002). Data of the present research will be registered with the International Clinical Trials Registry Platform. Additionally, we will disseminate the results through scientific dental journals.Trial registration numberChiCTR-2000030851.Protocol versionProtocol Version 4, 14 July 2020.

Background This retrospective study evaluated the long-term patency of transjugular intrahepatic portosystemic shunt (TIPS) placement and identified predictors of shunt dysfunction in patients with portal and superior mesenteric vein thrombosis (PSVT). Methods From January 2018 to January 2024, patients with symptomatic PSVT who underwent TIPS were enrolled. Clinical variables, imaging features, adverse events, and clinical outcomes were recorded. The cumulative rate of TIPS patency rates were calculated using the Kaplan-Meier method, with subgroup comparisons performed by the log-rank test. Independent predictors of shunt dysfunction were identified via Cox regression analysis. Results Forty-nine patients (mean age 47.8 ± 12.5 years; 79.6% male) were successfully treated with TIPS. Among them, 69.4% had cirrhosis and 49.0% had hepatitis B virus infection, with cirrhosis-related portal hypertension being the most common etiology of thrombosis. The 6-, 12-, and 24-month primary patency rates were 70.8% (95% CI: 59.0–85.0%), 66.4% (95% CI: 54.3–81.3%), and 56.5% (95% CI: 43.7–73.1%), respectively. Multivariate analysis identified sufficient inflow (patency of the splenic vein or an inflow vein diameter > 8 mm) and the use of covered stents in the main portal vein as independent predictors of TIPS patency. Conclusions TIPS can be safely performed in patients with PSVT. Adequate inflow and the use of covered stents in the main portal vein are important factors for long-term TIPS patency.

Using Chinese manufacturing data between 1998 and 2007, this paper investigates the impact of agglomeration on firm’s export behavior. It is found that the agglomeration of manufacturing industries in China over this period increases firm’s export probability as well as its export volume, and the impact is larger for more efficient firms. However, the impact on firm’s export volume depends on the degree of agglomeration. When the degree of agglomeration is low, an increase in agglomeration would expand firm’s export volume but the impact will be diminishing and even turns negative if the degree of agglomeration is already very high.

Using the Annual Survey of Chinese Industrial Firm over the period 1998-2007, we have investigated the impact of the public subsidy on the firm survival rate of new exporting firms by the survival analysis techniques. We find that the median survival time of Chinese exporting is short, just 2 years and the mean duration is 2.5-2.6 years , which is consistent with the present survival literatures. Conditioning on the firm-specific variables , the public subsidy has negative effect on the survival rate and the ownership of enterprise matters. It also documents that the longer firms stay in the exporting market , the lower the hazard rate and the firms productivity, export intensity, the amount of the foreign capital have significantly positive effect on the survival probability.

The prototypical antiferroelectric perovskite \\( PbZrO_3\\) (PZO) has garnered considerable attentions in recent years due to its significance in technological applications and fundamental research. Many unresolved issues in PZO are associated with large length- and time-scales, as well as finite temperatures, presenting significant challenges for first-principles density functional theory studies. Here, we introduce a deep learning interatomic potential of PZO, enabling investigation of finite-temperature properties through large-scale atomistic simulations. Trained using an elaborately designed dataset, the model successfully reproduces a large number of phases, in particular, the recently discovered 80-atom antiferroelectric \\(Pnam\\) phase and ferrielectric \\(Ima2\\) phase, providing precise predictions for their structural and dynamical properties. Using this model, we investigated phase transitions of multiple phases, including \\(Pbam\\)/\\(Pnam\\), \\(Ima2\\) and \\(R3c\\), which show high similarity to the experimental observation. Our simulation results also highlight the crucial role of free-energy in determining the low-temperature phase of PZO, reconciling the apparent contradiction: \\(Pbam\\) is the most commonly observed phase in experiments, while theoretical calculations predict other phases exhibiting even lower energy. Furthermore, in the temperature range where the \\(Pbam\\) phase is thermodynamically stable, typical double polarization hysteresis loops for antiferroelectrics were obtained, along with a detailed elucidation of the structural evolution during the electric-field induced transitions between the non-polar \\(Pbam\\) and polar \\(R3c\\) phases.

The prototypical antiferroelectric perovskite \\( PbZrO_3\\) (PZO) has garnered considerable attentions in recent years due to its significance in technological applications and fundamental research. Many unresolved issues in PZO are associated with large length- and time-scales, as well as finite temperatures, presenting significant challenges for first-principles density functional theory studies. Here, we introduce a deep learning interatomic potential of PZO, enabling investigation of finite-temperature properties through large-scale atomistic simulations. Trained using an elaborately designed dataset, the model successfully reproduces a large number of phases, in particular, the recently discovered 80-atom antiferroelectric \\(Pnam\\) phase and ferrielectric \\(Ima2\\) phase, providing precise predictions for their structural and dynamical properties. Using this model, we investigated phase transitions of multiple phases, including \\(Pbam\\)/\\(Pnam\\), \\(Ima2\\) and \\(R3c\\), which show high similarity to the experimental observation. Our simulation results also highlight the crucial role of free-energy in determining the low-temperature phase of PZO, reconciling the apparent contradiction: \\(Pbam\\) is the most commonly observed phase in experiments, while theoretical calculations predict other phases exhibiting even lower energy. Furthermore, in the temperature range where the \\(Pbam\\) phase is thermodynamically stable, typical double polarization hysteresis loops for antiferroelectrics were obtained, along with a detailed elucidation of the structural evolution during the electric-field induced transitions between the non-polar \\(Pbam\\) and polar \\(R3c\\) phases.

We show in the Chinese Annual Survey of Industrial Firms that size distributions of non-exporters and exporters have different shapes, which can only be explained by assuming that their productivity distributions have different shapes. Empirical estimations verify this assumption. This paper also analyzes the relationship between firms' size and productivity distributions and shows that: 1) productivity and size distributions change accordingly, and 2) productivity is deterministic for size distribution.