Machine vision image processing technology is extensively employed in the medical realm, particularly in dynamic navigation and robotic systems for oral implantology. It plays a pivotal role in assisting clinicians with precise implant placements, enhancing the predictability of implant restorations. The fundamental principles of machine vision image processing technology utilized in dynamic navigation and robotic systems for oral implantology primarily encompass spatial positioning and registration. However, due to variations in technical principles among different systems, their workflows and technical nuances exhibit distinctive characteristics. Therefore, commencing from the principles of spatial positioning and registration in machine vision image processing technology. This article delves into the current application landscape of machine vision in dynamic navigation and robotics for oral implantology. Its objective is to furnish valuable insights for the clinical implementation of machine vision-assisted implant technology.

Objective This study aimed to explore the spatial heterogeneity and risk factors for dental caries in 12-year-old children in Shanxi province,China. Methods The data encompassed 3,721 participants from the two most recent oral health surveys conducted across 16 districts in Shanxi Province in 2015 and 2018.Eighteen specific variables were analyzed to examine the interplay between socioeconomic factors,medical resources and environmental conditions.The Geo-detector model was employed to assess the impacts and interactions of these ecological factors. Results Socioeconomic factors(Q=0.30,P<0.05)exhibited a more substantial impact compared to environmental(Q=0.19,P<0.05)and medical resource factors(Q=0.25,P<0.05).Notably,the urban population percentage(UPP)demonstrated the most significant explanatory power for the spatial heterogeneity in caries prevalence,as denoted by its highest q-value(q=0.51,P<0.05).Additionally,the spatial distribution's heterogeneity of caries was significantly affected by SO2 concentration(q=0.39,P<0.05)and water fluoride levels(q=0.27,P<0.05)among environmental factors. Conclusion The prevalence of caries exhibited spatial heterogeneity,escalating from North to South in Shanxi Province,China,influenced by socioeconomic factors,medical resources,and environmental conditions to varying extents.

Objective·To assess the accuracy and time of the two-in-one registration technique by comparing it with the U-shaped tube registration in dynamic navigation implantation.Methods·Thirty standardized 3D-printed models with mandibular posterior sites missing a single tooth were randomly divided into three groups:two-in-one registration group,U-shaped tube registration group and free-hand implantation group,and the implant surgical plan was designed by the"YIZHIMEI"DCARER oral implant surgery navigation system.Cone beam CT before and after operation was taken.The implant platform deviation,implant apex deviation and angular deviation of the actual implant positions and the designed implant positions were measured.The operating time for using two-in-one registration technique and the U-shaped tube registration technique was recorded to evaluate the complexity of the two registration techniques.The one-way ANOVA and SNK(Student-Newman-Keuls)test were used to analyze the implant platform deviation,implant apex deviation and angular deviation of each group.Results·There were no statistically significant differences in implant platform deviation,implant apex deviation and angular deviation between the two-in-one registration group and the U-shaped tube registration group(P>0.05).However,the implant platform deviation,implant apex deviation and angular deviation of the two-in-one registration group and the U-shaped tube group were lower than those in the free-hand implantation group,and the differences were statistically significant(P<0.001).The operating time required for the two-in-one registration was shorter than that for the U-shaped tube registration process,and the difference was statistically significant(P<0.001).Conclusion·The accuracy of the two-in-one dynamic navigation registration technique used in implanting on a model of mandibular posterior sites missing a single tooth is similar to that of the U-shaped tube dynamic navigation registration technique.But the two-in-one registration takes less time for registration procedure than the U-shaped tube registration,and is easier to operate.

Objective:To investigate the predictive value of differential distribution of peripheral lymphocyte subsets before and after the first 131I treatment on the therapeutic response to 131I treatment in patients with papillary thyroid cancer (PTC). Methods:A retrospective study was conducted on 46 PTC patients (16 males, 30 females, age 20-77 years) who underwent total thyroidectomy and received 131I treatment between January 2021 and August 2021 in First Hospital of Shanxi Medical University. Peripheral blood lymphocyte subsets (T, B, CD4 + T, CD8 + T, natural killer (NK), helper T (Th)1, Th2, Th17, and regulatory T (Treg) cells) were measured 1-2 d before and 30 d after 131I treatment. Based on serological and imaging evidence, therapeutic response at 6-12 months post- 131I therapy was categorized as either excellent response (ER) or non-excellent response (NER). Differences of preablative stimulated thyroglobulin (psTg) and clinical baseline characteristics between two groups were assessed by using independent-sample t test, paired t test, or Mann-Whitney U test. Predictive value of lymphocyte subsets before and after 131I treatment for therapeutic response was assessed through logistic regression analysis, ROC curve analysis, and decision curve analysis (DCA). Results:In ER group ( n=33) and NER group ( n=13), most lymphocyte subsets showed different degrees of reduction 30 d after 131I treatment compared to before 131I treatment, such as T, B, CD4 + T and Th1 cells in ER group, as well as T, B, CD4 + T, Th1, Th2, Th17, and Treg cells in NER group ( t values: 2.41-9.57, all P<0.05). Before 131I treatment, NER group had significantly higher levels of psTg, Th2, Th17, and Treg cells compared to the ER group ( t values: from -3.32 to -2.48, U=29.00, all P<0.05). After 131I treatment, most of lymphocyte subsets in NER group (T, B, CD4 + T, CD8 + T, Th1 and Treg cells) showed higher trend than those in ER group but without statistical significances ( t values: from -1.12 to -0.06, all P>0.05). Th2 cells before 131I treatment (odds ratio ( OR)=25.00, 95% CI: 1.36-459.10, P=0.030) was identified as a risk factor for NER. ROC curve analysis indicated that AUCs of psTg and Th2 cells for predicting therapeutic response were 0.932 and 0.790, respectively, which was 0.958 for the combined psTg and Th2 cells. DCA showed that within the threshold probability range of 10%-60%, the curves for psTg, Th2 cells, and the combined psTg and Th2 cells were all higher than the extreme curve, suggesting good effect. Conclusions:Most lymphocyte subsets decrease to varying degrees, and NER group shows a significant decrease 30 d after 131I treatment. Th2 cells may be a risk factor for poor response to 131I treatment, providing a certain value in predicting the therapeutic response to 131I treatment.

Objective: This study examined the gut bacterial communities of dogs from different breeds, all kept under identical domestication conditions. Methods: Noninvasive sampling and 16S rRNA high-throughput sequencing were used to compare the composition and function of the gut microbiota of three dog breeds: the Chinese Kunming dog (CKD), German Shepherd dog (GSD), and Belgian Malinois dog (BMD). Results: The gut microbiota of the three dog breeds consisted of 257 species across 146 genera, 60 families, 35 orders, 15 classes, and 10 phyla. The dominant bacterial phyla across the three breeds were Firmicutes (57.44%), Fusobacteriota (28.86%), and Bacteroidota (7.63%), while the dominant bacterial genera across the three breeds were Peptostreptococcus (21.08%), Fusobacterium (18.50%), Lactobacillus (12.37%), and Cetobacter (10.29%). Further analysis revealed significant differences in the intestinal flora of the three breeds at the phylum and genus levels. The intestinal flora of BMD was significantly richer than that of CKD and GSD. The functional prediction and Kyoto Encyclopedia of Genes and Genomes analysis showed that the primary functions of the gut microbiota in these breeds were similar, with significant enrichment in various metabolic pathways, including carbohydrate and amino acid metabolism, secondary metabolite biosynthesis, and microbial metabolism in different environments. The intestinal flora of these breeds also played a crucial role in genetic information processing, including transcription, translation, replication, and material transport. Conclusions and Relevance: These results provide novel insights into the intestinal flora of intervention dogs and suggest novel methods to improve their health status, which help increase microbial diversity and normalize metabolite production in diseased dogs.

Objective: This study examined the gut bacterial communities of dogs from different breeds, all kept under identical domestication conditions. Methods: Noninvasive sampling and 16S rRNA high-throughput sequencing were used to compare the composition and function of the gut microbiota of three dog breeds: the Chinese Kunming dog (CKD), German Shepherd dog (GSD), and Belgian Malinois dog (BMD). Results: The gut microbiota of the three dog breeds consisted of 257 species across 146 genera, 60 families, 35 orders, 15 classes, and 10 phyla. The dominant bacterial phyla across the three breeds were Firmicutes (57.44%), Fusobacteriota (28.86%), and Bacteroidota (7.63%), while the dominant bacterial genera across the three breeds were Peptostreptococcus (21.08%), Fusobacterium (18.50%), Lactobacillus (12.37%), and Cetobacter (10.29%). Further analysis revealed significant differences in the intestinal flora of the three breeds at the phylum and genus levels. The intestinal flora of BMD was significantly richer than that of CKD and GSD. The functional prediction and Kyoto Encyclopedia of Genes and Genomes analysis showed that the primary functions of the gut microbiota in these breeds were similar, with significant enrichment in various metabolic pathways, including carbohydrate and amino acid metabolism, secondary metabolite biosynthesis, and microbial metabolism in different environments. The intestinal flora of these breeds also played a crucial role in genetic information processing, including transcription, translation, replication, and material transport. Conclusions and Relevance: These results provide novel insights into the intestinal flora of intervention dogs and suggest novel methods to improve their health status, which help increase microbial diversity and normalize metabolite production in diseased dogs.

Objective: This study examined the gut bacterial communities of dogs from different breeds, all kept under identical domestication conditions. Methods: Noninvasive sampling and 16S rRNA high-throughput sequencing were used to compare the composition and function of the gut microbiota of three dog breeds: the Chinese Kunming dog (CKD), German Shepherd dog (GSD), and Belgian Malinois dog (BMD). Results: The gut microbiota of the three dog breeds consisted of 257 species across 146 genera, 60 families, 35 orders, 15 classes, and 10 phyla. The dominant bacterial phyla across the three breeds were Firmicutes (57.44%), Fusobacteriota (28.86%), and Bacteroidota (7.63%), while the dominant bacterial genera across the three breeds were Peptostreptococcus (21.08%), Fusobacterium (18.50%), Lactobacillus (12.37%), and Cetobacter (10.29%). Further analysis revealed significant differences in the intestinal flora of the three breeds at the phylum and genus levels. The intestinal flora of BMD was significantly richer than that of CKD and GSD. The functional prediction and Kyoto Encyclopedia of Genes and Genomes analysis showed that the primary functions of the gut microbiota in these breeds were similar, with significant enrichment in various metabolic pathways, including carbohydrate and amino acid metabolism, secondary metabolite biosynthesis, and microbial metabolism in different environments. The intestinal flora of these breeds also played a crucial role in genetic information processing, including transcription, translation, replication, and material transport. Conclusions and Relevance: These results provide novel insights into the intestinal flora of intervention dogs and suggest novel methods to improve their health status, which help increase microbial diversity and normalize metabolite production in diseased dogs.

Objective: This study examined the gut bacterial communities of dogs from different breeds, all kept under identical domestication conditions. Methods: Noninvasive sampling and 16S rRNA high-throughput sequencing were used to compare the composition and function of the gut microbiota of three dog breeds: the Chinese Kunming dog (CKD), German Shepherd dog (GSD), and Belgian Malinois dog (BMD). Results: The gut microbiota of the three dog breeds consisted of 257 species across 146 genera, 60 families, 35 orders, 15 classes, and 10 phyla. The dominant bacterial phyla across the three breeds were Firmicutes (57.44%), Fusobacteriota (28.86%), and Bacteroidota (7.63%), while the dominant bacterial genera across the three breeds were Peptostreptococcus (21.08%), Fusobacterium (18.50%), Lactobacillus (12.37%), and Cetobacter (10.29%). Further analysis revealed significant differences in the intestinal flora of the three breeds at the phylum and genus levels. The intestinal flora of BMD was significantly richer than that of CKD and GSD. The functional prediction and Kyoto Encyclopedia of Genes and Genomes analysis showed that the primary functions of the gut microbiota in these breeds were similar, with significant enrichment in various metabolic pathways, including carbohydrate and amino acid metabolism, secondary metabolite biosynthesis, and microbial metabolism in different environments. The intestinal flora of these breeds also played a crucial role in genetic information processing, including transcription, translation, replication, and material transport. Conclusions and Relevance: These results provide novel insights into the intestinal flora of intervention dogs and suggest novel methods to improve their health status, which help increase microbial diversity and normalize metabolite production in diseased dogs.

Selection and measurement of clinical outcome are key components of clinical research in implant dentistry. Shanghai Ninth People′s Hospital, Shanghai Jiao Tong University School of Medicine took the lead and collaborated with multiple internationally renowned colleges of stomatology to develop an international consensus on the core outcome set and measurement in implant dentistry, which took two years and was published in May, 2023 in Journal of Clinical Periodontology and Clinical Oral Implants Research simultaneously. The consensus, aiming at identifying the full spectrum of benefits and harms of interventions, provides a comprehensive, agreed, and standardized set of outcomes that should be measured and reported as a minimum in clinical trials relating with implant dentistry, bone augmentation, and soft tissue augmentation. The present review describes the methodology and key elements of the consensus to help Chinese clinical researchers fully understand and appropriately apply the core outcome set and improve the overall quality of Chinese clinical research in implant dentistry.

Schizophrenia is a serious mental disease. The diagnosis of schizophrenia so far relies heavily on subjective evidence, including self-reported experiences by patients, manifestations described by relatives, and abnormal behaviors assessed by psychiatrists. The diagnosis, monitoring of the disease progression and therapy efficacy assessment are challenging due to the lack of established laboratory biomarkers. Based on the current literature, clinical consensus, guidelines, and expert recommendations, this review highlighted evidence-based potential laboratory biomarkers for the diagnosis of schizophrenia, including genetic biomarkers, neurotransmitters, neurodevelopmental-related proteins, and intestinal flora, and discussed the potential future directions for the application of these biomarkers in this field, aiming to provide an objective basis for the use of these biomarkers in the early and accurate diagnosis, treatment, and prognosis and rehabilitation assessment of schizophrenia.