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Introduction: Comprehensive analysis is necessary to analyze the widespread use of bisphosphonate drugs in the treatment and prevention of various diseases of connective tissue structures. The relevance of the study depends on the impact they have on the patient’s somatic condition, given the number of early and late complications diagnosed by domestic and foreign clinicians. Materials and methods: The methodology used was developed on Stavropol Regional Clinical Hospital from 2010 to 2022. A randomized and observational study of the state of connective tissue structures was conducted in 186 patients who had a history of taking zoledronic acid and developed bisphosphonate osteonecrosis of the jawbone. At the diagnostic and treatment stages, patients were tested using laboratory methods to monitor amino acids in biological fluids (blood), as well as bone blocks extracted intraoperatively using highly effective gas-liquid chromatography on AAA 500. Results and discussion: Aminograms obtained in the pre-operative period indicate toxic effects of zoledronic acid on neuro, endocrine, and other human systems. The initiation and progression of aseptic inflammatory processes in tissue structures is correlated with the deteriorating general ocular status of patients when amino acids, such as alanine, serine, taurine, phenylalanine, tyrosine, proline, histidine, glycine, and valine, against a background of 90.4±2.1 mmol/L ammonia are reduced critically. Conclusion: Zoledronic acid initiates an aseptic chronic inflammatory process in the jaw bones, accompanied by toxic acidosis, which worsens osteoporotic symptoms.

Objective To investigate the incidence of COVID-19 in patients with tumor during the pandemic of Omicron variant strains. Methods From December 25, 2022 to January 25, 2023, through the questionnaire star platform in the form of electronic questionnaire, we collected information about COVID-19 vaccine, COVID-19 infection and clinical symptoms, and post-infection anti-tumor therapy of patients with malignant tumors (including patients who previously visited the oncology department of Peking Union Medical College Hospital and the oncology department of the local hospital where the trainee doctors of the oncology department of Peking Union Medical College Hospital are located) during the survey period (from December 9, 2022 to the time of questionnaire survey) and performed statistical analysis. Results A total of 270 questionnaires were sent out, of which 265 valid questionnaires were recovered (the effective questionnaire rate was 98.1%). Among the 265 patients with malignant tumors, 170(64.2%) patients received COVID-19 vaccine, 158(59.6%) patients were alive with tumor, and 216 patients (81.5%) were receiving antitumor therapy at the time of COVID-19 infection or during the investigation. In 210 cases (79.2%), patients were infected with COVID-19. Among them, 9 cases (4.3%) developed COVID-19 pneumonia and 3 cases (1.4%) were hospitalized due to COVID-19, and there were no severe or fatal cases. Among the infected patients, 205(97.6%) patients showed symptoms related to the COVID-19, among which fever was the most common (72.9%) symptom, and cough (64.8%) and sputum (50.5%) were the main respiratory symptoms. There were no significant differences in gender, age, tumor type, whether they had underlying diseases, whether they were vaccinated against COVID-19, and whether they were treated with anti-tumor therapy between COVID-19 infected and uninfected patients (all P > 0.05). Among the infected patients, the incidence of pneumonia in those who received ≥3 doses of vaccine was significantly lower than that in those who did not receive vaccine (1.1% vs. 9.9%, P=0.025). At the time of questionnaire survey, 88 patients started antitumor therapy after COVID-19 infection. Compared to infection before COVID-19, 12 patients(13.6%) had more serious adverse anti-tumor reactions after COVID-19 infection, 63 patients (72.7%) had similar symptoms, and 12 patients (13.6%) had milder symptoms. There was no significant correlation between the adverse reactions of anti-tumor therapy before and after infection and the timing of initiation of anti-tumor therapy after infection(P=0.938), but there was a certain correlation with anti-tumor therapy after infection(P=0.003). Conclusions During the pandemic period of Omicron variant, tumor patients were generally susceptible to COVID-19. Almost all infected patients showed related clinical symptoms, but very few patients developed pneumonia. Vaccination with≥3 doses of vaccine may be protective against pneumonia. The adverse reactions of anti-tumor therapy in most cancer patients after infection with COVID-19 were not significantly worse than those before infection.

ObjectiveThe root system is an important component of plant composition, and its growth and development are crucial for plants. Root image segmentation is an important method for obtaining root phenotype information and analyzing root growth patterns. Research on root image segmentation still faces difficulties, because of the noise and image quality limitations, the intricate and diverse soil environment, and the ineffectiveness of conventional techniques. This paper proposed a multi-scale feature extraction root segmentation algorithm that combined data augmentation and transfer learning to enhance the generalization and universality of the root image segmentation models in order to increase the speed, accuracy, and resilience of root image segmentation.MethodsFirstly, the experimental datasets were divided into a single dataset and a mixed dataset. The single dataset acquisition was obtained from the experimental station of Hebei Agricultural University in Baoding city. Additionally, a self-made RhizoPot device was used to collect images with a resolution pixels of 10,200×14,039, resulting in a total of 600 images. In this experiment, 100 sheets were randomly selected to be manually labeled using Adobe Photoshop CC2020 and segmented into resolution pixels of 768×768, and divided into training, validation, and test sets according to 7:2:1. To increase the number of experimental samples, an open source multi-crop mixed dataset was obtained in the network as a supplement, and it was reclassified into training, validation, and testing sets. The model was trained using the data augmentation strategy, which involved performing data augmentation operations at a set probability of 0.3 during the image reading phase, and each method did not affect the other. When the probability was less than 0.3, changes would be made to the image. Specific data augmentation methods included changing image attributes, randomly cropping, rotating, and flipping those images. The UNet structure was improved by designing eight different multi-scale image feature extraction modules. The module structure mainly included two aspects: Image convolution and feature fusion. The convolution improvement included convolutional block attention module (CBAM), depthwise separable convolution (DP Conv), and convolution (Conv). In terms of feature fusion methods, improvements could be divided into concatenation and addition. Subsequently, ablation tests were conducted based on a single dataset, data augmentation, and random loading of model weights, and the optimal multi-scale feature extraction module was selected and compared with the original UNet. Similarly, a single dataset, data augmentation, and random loading of model weights were used to compare and validate the advantages of the improved model with the PSPNet, SegNet, and DeeplabV3Plus algorithms. The improved model used pre-trained weights from a single dataset to load and train the model based on mixed datasets and data augmentation, further improving the model's generalization ability and root segmentation ability.Results and DiscussionsThe results of the ablation tests indicated that Conv_ 2+Add was the best improved algorithm. Compared to the original UNet, the mIoU, mRecall, and root F1 values of the model increased by 0.37%, 0.99%, and 0.56%, respectively. And, comparative experiments indicate Unet+Conv_2+Add model was superior to the PSPNet, SegNet, and DeeplabV3Plus models, with the best evaluation results. And the values of mIoU, mRecall, and the harmonic average of root F1 were 81.62%, 86.90%, and 77.97%, respectively. The actual segmented images obtained by the improved model were more finely processed at the root boundary compared to other models. However, for roots with deep color and low contrast with soil particles, the improved model could only achieve root recognition and the recognition was sparse, sacrificing a certain amount of information extraction ability. This study used the root phenotype evaluation software Rhizovision to analyze the root images of the Unet+Conv_2+Add improved model, PSPNet, SegNet, and DeeplabV3Plu, respectively, to obtain the values of the four root phenotypes (total root length, average diameter, surface area, and capacity), and the results showed that the average diameter and surface area indicator values of the improved model, Unet+Conv_2+Add had the smallest differences from the manually labeled indicator values and the SegNet indicator values for the two indicators. Total root length and volume were the closest to those of the manual labeling. The results of transfer learning experiments proved that compared with ordinary training, the transfer training of the improved model UNet+Conv_2+Add increased the IoU value of the root system by 1.25%. The Recall value of the root system was increased by 1.79%, and the harmonic average value of F1 was increased by 0.92%. Moreover, the overall convergence speed of the model was fast. Compared with regular training, the transfer training of the original UNet improved the root IoU by 0.29%, the root Recall by 0.83%, and the root F1 value by 0.21%, which indirectly confirmed the effectiveness of transfer learning.ConclusionsThe multi-scale feature extraction strategy proposed in this study can accurately and efficiently segment roots, and further improve the model's generalization ability using transfer learning methods, providing an important research foundation for crop root phenotype research.

SiC ceramics has been extensively used in heat exchangers because of their excellent mechanical properties, high thermal conductivity, and superior thermal shock, corrosion, and oxidation resistance. However, there is a wide variation in the thermal conductivity of SiC ceramics, depending on the raw materials, molding process, sintering process, and sintering additives. The thermal conductivity of SiC ceramics (≤ 270 W·m-1·K-1) is much lower than that of 6H-SiC single crystals (490 W·m-1·K-1) because of pores, grain boundaries, impurities, and defects in SiC ceramics. In this work, the important factors affecting the thermal conductivity of SiC ceramics were analyzed, including temperature, pore, crystal structure, and second phase. Further, the preparation processes of high conductivity SiC ceramics were systematically compared based on hot-pressed sintering, spark plasma sintering, pressureless sintering, recrystallization sintering, and reaction sintering. The improvement measures of thermal conductivity of SiC ceramics were summarized, including the optimization of the type and content of sintering aids, high-temperature annealing, and adding a high-thermal-conductivity second phase. Finally, the prospects and research directions of low-cost and high-thermal-conductivity SiC ceramics are proposed.

Tunable semiconductor lasers have many important applications such as wavelength division multiplexing, light detection and ranging, and gas detection. The increased interest in silicon photonics has led to the rapid development of miniaturized on-chip tunable semiconductor lasers. However, silicon has poor light-emitting properties. Therefore, realizing high-performance tunable semiconductor lasers requires the integration of light sources with silicon. In this study, we review silicon-based light source integration methods and the development of silicon-based integrated tunable semiconductor lasers. Considering that narrow-linewidth performance greatly expands the applications of tunable semiconductor lasers, methods for reducing the linewidth of tunable lasers are summarized. Finally, the development trends and prospects for silicon-based integrated light sources and silicon-based integrated tunable lasers are analyzed and discussed.

Cushion materials can effectively reduce the impact load acting on the rigid protective structures such as shed tunnel and improve the impact resistance of the structures. In order to investigate the variation of cushioning performance of recycled concrete aggregate (RCA) under successive impacts, drop weight impact tests and discrete element simulations are carried out. Test results show that compared with the quartz sand cushion, the transmitted load at the center of concrete shed for RCA under the first impact reduces by 83%, and it is distributed more uniformly. With the increase in the number of impacts, the cushioning performances of both the RCA and quartz sand deteriorate. For the sixth impact, the maximum transmitted loads at the center of concrete shed for RCA and quartz sand are 11.2 times and 1.4 times those of the first impact, respectively. Furthermore, the cushioning performance is strongly influenced by particle shape. The numerical simulation results show that when the proportion of strip particles increases from 0% to 100%, the rotation angle and translation distance of the particles decrease by 40% and 20%, respectively, and the maximum drop weight impact load increases by 37%. The inter-locking effect between particles increases with the irregularity of particle shape, which limits the rotation and translation of the particles, and increases the drop weight impact load and the transmitted load on the concrete slab. The research results may provide theoretical basis and engineering guidance for RCA as a new type of eco-friendly cushion.

In order to study the effect of igneous rock intrusion on coal oxidation, the electronic scanning mirror, specific surface area tester and pressure mercury meter are used to test the coal samples before and after the igneous rock intrusion, by comparing and analyzing the scanning electron microscope, specific surface area and pore volume of coal samples before and after igneous rock intrusion, the changes of microstructure and porosity of coal samples before and after igneous rock intrusion are studied. The results show that the pore structure of the coal sample changes after the igneous rock intrusion, the porosity increases, and the oxygen adsorption ability is enhanced; the change of coal molecular structure leads to the oxidation of metamorphic coal after igneous rock intrusion, and the greater the metamorphic degree, the easier the oxidation.

BackgroundCancer has become a leading cause of death for Chinese children, imposing a great economic burden on society and families. Therefore, it is extremely important to understand the epidemicsizes and trends of childhood malignancies.ObjectiveTo analyze the epidemiological characteristics of childhood cancer in China from 2005 to 2015, so as to provide evidence for the formulation of prevention and control strategies and rational allocation of health resources concerning childhood cancer in China.MethodsData regarding cancer incidence and mortality in Chinese 0-14 years old children during 2008 to 2018 were collected from the Chinese Cancer Registry Annual Report. Age-standardized incidence and mortality rates were computed by dividing the number of child deaths caused by cancer by the fifth national population census (2010) and multiplying by 100 000. Joinpoint Regression Program was used to compute the annual percentage change (APC) to analyze the temporal trends of annual child cancer incidence and mortality rates.Results(1) During the period of 2005 to 2015, the median crude incidence rate and median crude mortality rate of cancer in 0-14 years old were 9.35/100 000, and 3.91/100 000, respectively. The median crude incidence and median crude mortality rate of 0-4 years old group were higher than those of 5-9 years old group and 10-14 years old group (P

In order to deeply study the source law of high volume fraction CO in the two-lane broken rock zone of working face, scientifically formulate preventive measures to prevent fire in the two lanes, and investigate the CO change in the overlying goaf, the adjacent goaf and the working face with the mining. The results show that: with the working face mining, no high volume fraction CO was not found in the overlying goaf and adjacent goaf, while high volume fraction CO were found in the observation boreholes of this layer, which proved that the two roadways did not adopt full-face spraying during the mining process; under the condition of in-situ stress, the low temperature oxidation time of cracked coal in the broken rock zone is long, and the broken coal is caused by low temperature oxidation, and natural oxidation reaction is more likely to occur in the loosening circle of transport roadway than in the loosening circle of return air roadway.

Ti−6Al−3Nb−2Zr−1Mo alloys were prepared by forging and annealing at 980 ℃. The microstructure and mechanical properties of the annealed alloys on the different sections were studied by scanning electron microscopy (SEM) and electron back-scattered diffraction (EBSD). The results show that, compared with the forged alloys, the content of α phase in the annealed Ti−6Al−3Nb−2Zr−1Mo alloys decreases, and the content of the metastable β phase increases. During the cooling in the air, the metastable β phase is transformed into the secondary α phase and a small amount of β phase. After annealing at 980 ℃, α-Ti in Ti−6Al−3Nb−2Zr−1Mo alloys exhibits the texture types of RD//[\begin{document}$ \bar {1} $\end{document}2\begin{document}$ \bar {1} $\end{document}0] and FD//[0001], where RD is the forging compression direction (forging direction), and FD is the free extension direction of forging. The fracture morphology of Ti−6Al−3Nb−2Zr−1Mo alloys along the different tensile direction is mainly ductile fracture, and the fracture mode shows the micropore aggregation fracture. When the annealed alloys are stretched in RD direction, the size of the dimple is larger, and the corresponding elongation is superior to that in any other direction.

Objective To study the relationship between white matter fiber integrity and cognitive impairment after subcortical infarction, and to explore the possible mechanism with diffusion tensor imaging (DTI). Methods Total of 37 subcortical infarction patients with cognitive impairment were recruitded from March 2016 to December 2018. Montreal Cognitive Assessment (MoCA) was used to evaluate the cognitive function. DTI was performed to obtain the fractional anisotropy (FA) of white matter fiber in the whole brain. The correlation between FA values and MoCA scores was analyzed by Pearson correlation analysis and partial correlation analysis and then the multiple linear regression model was established. Results Correlation analysis showed that decreased FA values in the bilateral external capsule, cingulate gyrus, and superior longitudinal fasciculus (SLF), inferior fronto⁃occipital fasciculus (IFOF), fasciculus，anterior limb of internal capsule, anterior and superior corona radiata were significantly correlated with MoCA scores (P < 0.05, for all). Multiple linear regression analysis showed that MoCA scores affected the SLF (P=0.042) and IFOF (P=0.006). Conclusions Impaired white matter filber integrity of the ipsilesional SLF and IFOF can be imaging biomarkers for cognitive impairment after subcortical infarction.

Sample pretreatment is essential for metabonomic analysis. Lyophilization (freeze-drying) is widely used for sample pretreatment to remove solvent, especially water, prior to nuclear magnetic resonance (NMR) and/or mass spectrum (MS) analysis. However, the effects of lyophilization on metabonomic phenotypes remain to be fully investigated. In this study, NMR analysis was carried out to reveal the lyophilization-induced changes in metabonomic phenotypes of human urinary and serum samples. It was found that lyophilization resulted in large changes in the levels of some carboxylic acids and amino acids. Such effects were different between the urine and serum samples, perhaps indicating a biological matrix-dependent effect. The results of this study suggest that extra care and considerations should be taken when lyophilization is used for sample pretreatment and normalization in metabonomic analysis.

Runoff-generated debris flows are a common post-fire hazard in the western United States and a growing number of regions around the world. As wildfire continues to emerge across a broader range of geographic regions and plant communities, there is an increasing need for generalizable methods to predict post-fire debris-flow initiation. The prediction of post-fire debris flow during intense rainstorms has traditionally relied upon empirical rainfall thresholds. Rainfall intensity-duration thresholds are often developed based on rainfall data and the hydrologic response to those rainstorms. They are most applicable to the specific regions where data are collected. Here, we present a new predictive approach that utilises processes-based models with fundamental physics and machine learning methods to estimate discharge thresholds for runoff-generated debris-flow initiation in four recently burned areas in the western United States. We assess the performance of the objectively defined discharge threshold-based predictions for post-fire debris-flow initiation from our hybrid framework, which utilises debris-flow timing within rainstorms, physically based numerical simulations of runoff, and the support vector machines method. The proposed thresholds have a good balance between true and false predictions for debris flow and floods. Importantly, our method permits the direct estimation of rainfall intensity-duration thresholds for areas where post-fire debris flow observations are limited.

Solid-fluid interaction vitally influences the flow dynamics of particles in a geophysical flow. A coupled computational fluid dynamics and discrete element method (CFD-DEM) is used in this study to model multiphase geophysical flow as a mixture of fluid and solid phases. The two non-Newtonian fluids (i.e., Bingham and Hershcel-Bulkley fluids) and water mixed with particles are considered in the simulation, while dry granular flow with the same volume is simulated as a control test. Results revealed that the solid-fluid interaction heavily governs the particle dynamic behaviours. Specifically, compared to dry case, particles in three multiphase cases are characterized by larger flow mobility and greater shear rate while smaller basal normal force. In addition, a power-law distribution with a crossover to a generalized Pareto Distribution is recommended to fit the distribution of normalized interparticle contact force.

The first step in building an early warning system using seismic signals is to automatically identify events of interest. Here, the first digit distribution of seismic signals generated by debris flows and other surface processes was calculated to validate compliance with Benford's law (BL). A detector model for debris flow events was introduced based on amplitude range and goodness of fit of BL. We show that seismic signals generated by debris flows, landslides, and bedload transport follow the BL. These events release more energy and last longer than rockfalls, which do not follow BL. In the test dataset with 1224 samples, the accuracy of the detector model in identifying debris flow events was 0.75.

Objective To observe and evaluate the effect of different perfusion frequencies on the survival of human skin specimens in a quasi-static planar homogeneous flow field. Methods The foreskin skin grafts in size of 4 mm were placed a quasi-static planar homogeneous flow field, and randomly divided into experimental group (perfused with high frequency) and the control group (perfused with low frequency). After 12 days' culture, PAS staining and VG staining were used to observe the changes of basement membrane, cell morphology and dermal collagen fibers. Moreover, the number of total cells and the apoptotic cells in the 2 groups were separately determined by HE staining and TUNEL assay. The dissolved oxygen concentration in culture medium was measured by a dissolved oxygen meter. Results In the low frequency perfusion group, gross observation showed characteristic features of necrosis; PAS and VG staining results indicated that the epidermis was severely separated, basement membrane structure disappeared and collagen fibers accumulated. Significant differences were seen in total cell number (249.35±13.00 vs 37.50±9.18, P < 0.001) and apoptotic rate between the experimental group and the control group. The dissolved oxygen level was higher in the former group than the latter group. Conclusion In the quasi-static planar homogeneous flow field, high frequency perfusion is suitable for the culture of free skin grafts in vitro.

Ruellia simplex C.Wright is a perennial plant of the Acanthaceae, which has significant ornamental value. Because of its strong adaptability, it is widely planted in Chinese rural areas. Based on sequencing data from Illumina, the first complete chloroplast (cp) genome of Ruellia simplex C.Wright is reported in this paper. This cp genome was 143,016bp in length, including a large single-copy region (LSC) of 91,857bp, a small single-copy (SSC) of 17,591bp and two inverted repeat regions (IRs) of 16,784bp. It contained 128 genes, 35 transfer RNA genes, 8 ribosomal RNA genes, with an overall GC content of 38.41%. Additionally, the phylogenetic analysis showed that Ruellia simplex is closely related to Strobilanthes cusia (NC_037485), Strobilanthes bantonensis (MT576695) and Echinacanthus attenuatus (NC_039762). The results of this study provide valuable information for the continued study of its species evolution, genetic engineering and germplasm resource utilization.

BackgroundThe control rod guide tube (CRGT) is needed to facilitate the movement of the control rod in the molten salt reactor (MSR). Graphite material is resistant to neutron radiation, high temperature and molten salt corrosion, and has small neutron absorption cross section, hence it is an ideal CRGT material except for the comparatively low strength and toughness. It is believed that reinforcing the graphite CRGT with carbon fiber fabric (CFF) is a promising way to promote its application in molten salt reactor.PurposeThis study aims to optimize the preparation parameters of the CFF reinforcement for CRGT.MethodsFirst of all, the CFF was pre-impregnated with precursor solution in a vacuum environment, and wound on the graphite tube with a certain tension. Secondly, samples with different densification cycles and winding layers were prepared through multiple pressure impregnation, curing and carbonization cycles of the Precursor-Infiltration-Pyrolysis (PIP) process. Then, the mechanical properties of carbon fiber cloth reinforced graphite tube samples and the reference samples were tested. Finally, the microstructure and failure mode of the damaged samples were analyzed for further optimizing the preparation process to improve the material performance.Results & ConclusionsThe results show that the CFF winding and PIP method enhances the strength and toughness of the graphite tube, and the preparation parameters have been optimized that make the reinforced graphite CRGT with carbon fiber fabric (CFF) possible to be applied to MSR.

Objective To investigate the effects of type Ⅱa histone deacetylase inhibitor LMK-235 during early osteoblast/odontoblast differentiation in hPDLCs.Methods hPDLCs were obtained by the collagenase digestion method. hPDLCs at the 3 rd passage were treated with medium containing 10% fetal bovine serum mixed with different concentrations of LMK-235 (0, 50, 100, 250, 500 nmol/L), respectively. Proliferative capability of hPDLCs was tested by MTT and qRT-PCR was used to detect mRNA expression levels of Runx2, ALP and DMP-1 3 d later. Results MTT assay showed that cell proliferation in hPDLCs treated with 100 nmol/L LMK-235 was increased significantly compared with the control group (P

Based on the theory of random vibration,the dynamic response on tower crane under random seismic excitation was investigated. The input of earthquake ground motion is indicated by Duxiuli-Chenhouqun power spectral. The random seismic responses of structural ’s force and displacement were researched under five different earthquake model input with uniform earthquake excitations method. The analysis reveals that the force of tower crane increase significantly under vertical seismic excitation than X-direction,Z-direction excitation have the greatest influence in tower body bending moment; the primary reason of tower arm fracture is vertical seismic action,too large seismic wave cause tower body capsized easily.

Lightweight design on bridge crane exist the following problems by ANSYS: Mostly using static indicators as a design criterion,ignoring the dynamic performance; the whole process takes a long time; and the parameters optimized often should be rounded,weaken the effect. In this paper,taking the bridge crane with 20t- 22. 5m as an example,utilization of ANSYS and multidisciplinary design optimization software Isight,based on the theory of Latin hypercube design,BP neural network,Hooke-Jeeves algorithm,presenting a better and faster optimization method for main girder of bridge crane. By this method,optimization time shortened,and a decrease in mass of girder of bridge crane by 14. 84%.

To describe the angular distribution for a group-to-group neutron scattering event, the coefficients of a truncated Legendre polynomial are usually used in the multigroup cross section. However, the truncated expansion can caused negative values of a probability density function (PDF) in some scattering angles. In this study, the PDF of scattering angles is calculated using the maximum entropy method to avoid the negative probabilities of some scattering angles and the multigroup cross section library in ACE format is generated. The multigroup cross section library is verified by the computation of RBEC-M benchmark using RMC. The differences between two methods generating scattering data, the maximum entropy method and discrete angle method, are also discussed. The calculation results using multigroup cross section library in ACE format are well good agreement with the results of benchmark report. It shows that multigroup cross section library including the scattering angle data computed by the maximum entropy method is corrected and can be used for Monte Carlo calculation.

Background: Previous study revealed that the link between dental caries and obesity has been controversial. The purpose of this research is to investigate the association between dental caries and obesity among primary school children in Wannan area, China. Methods: A cross-sectional study was designed to collect the routine health screening data for primary school children aged 5-14 years inWannan area,China, Overweight and obesity status were determined using the International Obesity Task Force standard (IOTF) BMI cut-off points. Caries status was recorded based on WHO recommendations. Results: Our results revealed that the overall caries prevalence of the subjects was 44.9%, Maximum number of caries affected children belonged to underweight and normal group, followed by overweight, and the least number was obesity. These differences were statistically significant (chi-square test, P < 0.001). Children with obesity were 1.908 times (OR =1.908; CI95%=1.750, 2.079) more likely have caries than children with underweight or health weight. Overweight children were 1.547 times (OR = 1.547; CI95% = 1.479, 1.618) more likely to have caries than children with underweight or health weight. After adjusted the gender and age, a statistically significant association was also observed between body mass index categories and caries. Conclusions: Obesity may have a significant effect on caries prevalence of primary school children in Wannan area, China. The importance of obesity should not only be emphasized with respect to general diseases but also with regard to carious lesions.