Objective: To evaluate the incremental vaccine effectiveness (VE) of two dose of the mumps containing vaccine (MuCV) in chidren, so as to provide a basis for optimizing mumps immunization strategies. Methods: A 1∶2 frequency matched case-control study was conducted by using reported mumps cases in childcare centers or schools from Lu an, Hefei, Ma anshan and Huainan cities of Anhui Province from September 1, 2023 to June 30, 2024, as a case group(383 cases). And healthy children in the same classroom were selected as a control group(766 cases). The MuCV immunization histories of participants were collected to estimate the incremental VE of the second dose of MuCV against mumps. Group comparisons were performed using the Chi square test or t-test. For matched case-control pairs, the Cox regression model was employed to calculate the odds ratio (OR) with 95% confidence interval (CI) for two dose MuCV vaccination and to estimate the incremental vaccine effectiveness (VE). Results: There were no statistically significant differences between the case and control groups regarding gender, age, dosage of MuCV vaccination and the time interval since the last dose vaccination( χ 2/t=0.05, 0.20, 0.94, -0.02, P >0.05). The proportions of the case and control groups vaccinated with two doses of MuCV were 26.63% and 29.37%, respectively, and the overall incremental VE of the second dose of MuCV was 40.73% (95% CI=3.03%-63.77%, P <0.05). Subgroup analyses revealed that the incremental VE for children with a period of ≥1 year between the two doses of MuCV was 54.13% (95% CI=1.90%-78.56%, P <0.05), while for children with a period of <1 year, it was 30.63% (95% CI=-28.59%-62.58%, P >0.05). The incremental VE of the second dose of MuCV was 30.36% (95% CI=-25.95%-61.50%, P >0.05) in kindergarten children and 66.73% (95% CI=14.92%-86.99%, P <0.05) in elementary and secondary school students. The incremental VE was 28.78% (95% CI=-27.46%-60.21%, P >0.05) within five years of the last dose of MuCV vaccination and 66.07% (95% CI=-41.56%-91.87%, P >0.05) for vaccinations administered beyond five years. Conclusions The second dose of MuCV may offer additional protection for children; however, extending the interval between two dose of MuCV (<1 year) has shown limited incremental protective effects. Therefore, it is crucial to consider optimizing current immunization strategies for mumps.

Risk assessment models for periodontal disease provide dentists with a precise and consolidated evaluation of the prognosis of periodontitis, enabling the formulation of personalized treatment plans. Periodontal risk assessment systems have been widely applied in clinical practice and research. The application fields of periodontal risk assessment systems vary based on the distinctions between clinical periodontal parameters and risk factors. The assessment models listed below are commonly used in clinical practice, including the periodontal risk calculator (PRC), which is an individual-based periodontal risk assessment tool that collects both periodontal and systemic information for prediction; the periodontal assessment tool (PAT), which allows for quantitative differentiation of stages of periodontal disease; the periodontal risk assessment (PRA) and modified periodontal risk assessment (mPRA), which are easy to use; and the classification and regression trees (CART), which assess the periodontal prognosis based on a single affected tooth. Additionally, there are orthodontic-periodontal combined risk assessment systems and implant periapical risk assessment systems tailored for patients needing multidisciplinary treatment. This review focuses on the current application status of periodontal risk assessment systems.

OBJECTIVE To investigate the regulatory effect of autophagy on the resistance of human liver cancer cell Huh7 to lenvatinib. METHODS Using human liver cancer cell Huh7 as subject， the lenvatinib-resist cell model （Huh7-LR） was generated by the low-dose gradient method combined with long-term administration. The sensitivity of parental cell Huh7 and drug-resistant cell Huh7-LR to lenvatinib was detected by using CCK-8 assay and flow cytometry. Western blot assay and GFP-mCherry-LC3 plasmid transfection were performed to detect the expression levels of autophagic protein Beclin-1， autophagic adapter protein sequestosome 1 （p62）， microtubule-associated protein 1 light chain 3 （LC3） and autophagic level. Furthermore， an autophagy activation model was constructed by cell starvation， the protein expression of p62 and autophagy level were detected by using Western blot assay and GFP-mCherry-LC3 plasmid transfection， and the effect of autophagy activation on the sensitivity of Huh7-LR cells to lenvatinib was detected by flow cytometry. RESULTS Compared with parental cells， the drug resistance index of Huh7-LR cells was 6.2； protein expression of p62 was increased significantly， while apoptotic rate， protein expression of Beclin-1 and LC3Ⅱ/ LC3Ⅰ ratio were all reduced significantly （P＜0.05 or P＜0.01）； the level of autophagy was decreased to some extent. Autophagy activation could significantly increase the protein expression of p62 in Huh7-LR cells （P＜0.05） and autophagy level， and significantly increase its apoptotic rate （P＜0.05）. CONCLUSIONS Autophagy is involved in lenvatinib resistance， and activating autophagy can reverse the resistance of liver cancer cells to lenvatinib to some extent.

Objective:To analyze the specific immunoglobulin G (IgG) antibodies level in the population after the coronavirus disease 2019 (COVID-19) pandemic in Henan Province.Methods:A total of 5 178 peripheral venous blood samples were collected from 10 districts (counties) in Henan Province according to the national seroepidemiological survey program for COVID-19, and the method of cluster random sampling was adopted from March 6 to 15, 2023. Descriptive analysis was used for the basic data, history of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination, SARS-CoV-2 infection of the respondents. The specific IgG antibody of SARS-CoV-2 was detected using chemiluminescence method. Statistical analysis was performed by using rank sum test, Kruskal Wallis test, and Dunn′s test.Results:The overall positive rate of SARS-CoV-2-specific IgG antibody was 83.35%(4 316/5 178). There were statistically significant differences in the specific IgG antibodies against SARS-CoV-2 produced by people of different sexes, different ages, infected or not, vaccinated or not, and vaccinated with different doses of SARS-CoV-2 vaccine ( Z=3.60, H=195.32, Z=6.10, 18.08, H=382.70, respectively, all P<0.001). The specific IgG antibodies produced by unvaccinated+ uninfected group, unvaccinated+ infected group, vaccinated+ uninfected group, and vaccinated+ infected group were 3.54(0.98, 11.00), 60.65(2.33, 84.80), 133.00(59.80, 173.00), and 142.00(98.30, 176.00), respectively. And the difference was statistically significant( H=354.62, P<0.001). The specific IgG antibodies of uninfected people increased with the increase of inoculum times( H=287.00 and 98.48, both P<0.001). The specific IgG antibodies of people who were not infected with SARS-CoV-2 in the groups of whose interval from the last inoculation of SARS-CoV-2 vaccine to blood collection was less than three months, three to six months and more than six months were 171.86(156.04, 196.57), 71.71(17.08, 110.38) and 132.14(57.59, 172.25), respectively, and the difference was statistically significant ( H=19.93, P<0.001). Among them, the absolute difference between the less than three months group and the three to six months group was statistically significant ( Z=3.67, P<0.001), and the absolute difference between the less than three months group and the more than six months group was statistically significant ( Z=3.47, P<0.001). The specific IgG antibodies level in the less than three months group was the highest. Conclusions:There is a certain correlation between the number of SARS-CoV-2 vaccine doses and the specific IgG antibodies level in uninfected people. The specific IgG antibodies could maintain a high level for three months after immunization.

Objective:To investigate the effects of marathon exercise on knee cartilage volume and T2 relaxation time (T2 value) based on MRI.Methods:From December 2018 to December 2021, 25 healthy volunteers without long-distance running habits and 32 non-professional marathon runners with long-term long-distance running were recruited to undergo knee MRI 3D water-selective excitation (three dimensional water-selective excitation, 3D-WATS) and T2 mapping imaging were performed, and the cartilage volumes in 5 knee areas and T2 values in 42 subareas were extracted for analysis. To compare the cartilage volume and its ratio to body surface area of knee joint of healthy volunteers and non-professional marathon runners, the T2 value of cartilage in each subregion, and the correlation between marathon exercise intensity and the volume and T2 value of cartilage in different regions.Results:Compared with healthy volunteers, there was no significant difference in cartilage volume or the ratio of body surface area to body volume of non-professional marathon runners ( P>0.05). There were significant differences between healthy volunteers and non-professional marathon runners in cartilage T2 values of the median layer of medial condyle of femur (47.61±5.65 ms and 44.29±6.10 ms) and the deep layer of medial condyle of femur (36.82±9.05 ms and 31.67±7.59 ms), deep precondylar area of medial femur (38.37±4.68 ms and 34.09±4.19 ms), shallow area of medial condylar area of femur (52.17±11.11 ms and 45.51±7.76 ms), middle layer of medial condylar area of femur (49.09±5.08 ms and 45.63±5.04 ms), medial layer of anterior condylar region of lateral femur (45.69±4.68 ms and 42.57±5.77 ms), superficial layer of posterior condylar region of lateral femur (55.42±18.41 ms and 47.99±8.39 ms), deep layer of anterior tibial medial plateau (33.40±7.76 ms and 29.03±5.69 ms), deep layer of posterior tibial medial plateau (31.28±5.02 ms and 27.92±5.99 ms), deep layer of patellofemoral surface (35.65±6.99 ms and 32.30±5.28 ms), respectively ( P<0.05). In non-professional marathon runners, the medial tibial plateau cartilage volume was negatively correlated with step frequency ( r=-0.371, P=0.035), the lateral femoral condylar cartilage volume was negatively correlated with step frequency ( r=-0.365, P=0.043), and the lateral tibial plateau cartilage volume was negatively correlated with step frequency ( r=-0.550, P=0.001). The T2 value of the medial layer cartilage in the anterior tibial medial plateau region was negatively correlated with body weight ( r=-0.277, P=0.039) and body mass index ( r=-0.290, P=0.030). The T2 value of the superficial layer of patellofemoral surface was negatively correlated with the amount of running in 3 months ( r=-0.457, P=0.010). The superficial T2 value in the posterior lateral plateau of the tibia was negatively correlated with stride length ( r=-0.437, P=0.014), and the medial layer cartilage T2 value in the anterior condylar area of the lateral femur was negatively correlated with stride frequency ( r=-0.380, P=0.035). Conclusion:Marathon exercise had little effect on the knee cartilage volume, but had a certain effect on the cartilage T2 value, resulting in changes in cartilage structure. The higher the step frequency, the smaller the cartilage volume. The greater the body weight or body mass index, the greater the amount of running in 3 months, and the greater the stride length, the lower the cartilage T2 value.

Risk assessment models for periodontal disease provide dentists with a precise and consolidated evalua-tion of the prognosis of periodontitis,enabling the formulation of personalized treatment plans.Periodontal risk assess-ment systems have been widely applied in clinical practice and research.The application fields of periodontal risk assessment systems vary based on the distinctions between clinical periodontal parameters and risk factors.The assess-ment models listed below are commonly used in clinical practice,including the periodontal risk calculator(PRC),which is an individual-based periodontal risk assessment tool that collects both periodontal and systemic information for pre-diction;the periodontal assessment tool(PAT),which allows for quantitative differentiation of stages of periodontal dis-ease;the periodontal risk assessment(PRA)and modified periodontal risk assessment(mPRA),which are easy to use;and the classification and regression trees(CART),which assess the periodontal prognosis based on a single affected tooth.Additionally,there are orthodontic-periodontal combined risk assessment systems and implant periapical risk as-sessment systems tailored for patients needing multidisciplinary treatment.This review focuses on the current applica-tion status of periodontal risk assessment systems.

Risk assessment models for periodontal disease provide dentists with a precise and consolidated evalua-tion of the prognosis of periodontitis,enabling the formulation of personalized treatment plans.Periodontal risk assess-ment systems have been widely applied in clinical practice and research.The application fields of periodontal risk assessment systems vary based on the distinctions between clinical periodontal parameters and risk factors.The assess-ment models listed below are commonly used in clinical practice,including the periodontal risk calculator(PRC),which is an individual-based periodontal risk assessment tool that collects both periodontal and systemic information for pre-diction;the periodontal assessment tool(PAT),which allows for quantitative differentiation of stages of periodontal dis-ease;the periodontal risk assessment(PRA)and modified periodontal risk assessment(mPRA),which are easy to use;and the classification and regression trees(CART),which assess the periodontal prognosis based on a single affected tooth.Additionally,there are orthodontic-periodontal combined risk assessment systems and implant periapical risk as-sessment systems tailored for patients needing multidisciplinary treatment.This review focuses on the current applica-tion status of periodontal risk assessment systems.

Risk assessment models for periodontal disease provide dentists with a precise and consolidated evalua-tion of the prognosis of periodontitis,enabling the formulation of personalized treatment plans.Periodontal risk assess-ment systems have been widely applied in clinical practice and research.The application fields of periodontal risk assessment systems vary based on the distinctions between clinical periodontal parameters and risk factors.The assess-ment models listed below are commonly used in clinical practice,including the periodontal risk calculator(PRC),which is an individual-based periodontal risk assessment tool that collects both periodontal and systemic information for pre-diction;the periodontal assessment tool(PAT),which allows for quantitative differentiation of stages of periodontal dis-ease;the periodontal risk assessment(PRA)and modified periodontal risk assessment(mPRA),which are easy to use;and the classification and regression trees(CART),which assess the periodontal prognosis based on a single affected tooth.Additionally,there are orthodontic-periodontal combined risk assessment systems and implant periapical risk as-sessment systems tailored for patients needing multidisciplinary treatment.This review focuses on the current applica-tion status of periodontal risk assessment systems.

Risk assessment models for periodontal disease provide dentists with a precise and consolidated evalua-tion of the prognosis of periodontitis,enabling the formulation of personalized treatment plans.Periodontal risk assess-ment systems have been widely applied in clinical practice and research.The application fields of periodontal risk assessment systems vary based on the distinctions between clinical periodontal parameters and risk factors.The assess-ment models listed below are commonly used in clinical practice,including the periodontal risk calculator(PRC),which is an individual-based periodontal risk assessment tool that collects both periodontal and systemic information for pre-diction;the periodontal assessment tool(PAT),which allows for quantitative differentiation of stages of periodontal dis-ease;the periodontal risk assessment(PRA)and modified periodontal risk assessment(mPRA),which are easy to use;and the classification and regression trees(CART),which assess the periodontal prognosis based on a single affected tooth.Additionally,there are orthodontic-periodontal combined risk assessment systems and implant periapical risk as-sessment systems tailored for patients needing multidisciplinary treatment.This review focuses on the current applica-tion status of periodontal risk assessment systems.

Risk assessment models for periodontal disease provide dentists with a precise and consolidated evalua-tion of the prognosis of periodontitis,enabling the formulation of personalized treatment plans.Periodontal risk assess-ment systems have been widely applied in clinical practice and research.The application fields of periodontal risk assessment systems vary based on the distinctions between clinical periodontal parameters and risk factors.The assess-ment models listed below are commonly used in clinical practice,including the periodontal risk calculator(PRC),which is an individual-based periodontal risk assessment tool that collects both periodontal and systemic information for pre-diction;the periodontal assessment tool(PAT),which allows for quantitative differentiation of stages of periodontal dis-ease;the periodontal risk assessment(PRA)and modified periodontal risk assessment(mPRA),which are easy to use;and the classification and regression trees(CART),which assess the periodontal prognosis based on a single affected tooth.Additionally,there are orthodontic-periodontal combined risk assessment systems and implant periapical risk as-sessment systems tailored for patients needing multidisciplinary treatment.This review focuses on the current applica-tion status of periodontal risk assessment systems.