Porphyromonas gingivalis induces exacerbated periodontal disease during pregnancy.

Although pregnant women are prone to gingival inflammation, its mechanism remains unclear. Animal models are ideal for investigating immunological mechanisms in the periodontal disease. A murine model for ligature-induced periodontal disease has been modified and utilized to determine the susceptibility to periodontal inflammation and tissue damage in pregnant mice. Expression of different inflammatory mediators in the gingivae was determined by quantitative real-time PCR (qPCR). Inflammatory bone loss was determined by measuring the distance from the cementoenamel junction to the alveolar bone crest (CEJ-ABC). Oral bacterial number was determined by the CFU (Colony Forming Units) count from anaerobic culture of oral swabs. In our experiments, ligation itself did not cause higher gingival inflammation and bone loss in pregnant mice than non-pregnant mice, while ligation combined with P. gingivalis infection led to increased gingival inflammation and periodontal bone loss, accompanied by lower gingival expression of anti-inflammatory cytokines in pregnant mice. Our results indicated that P. gingivalis infection was important in inducing more severe periodontal diseases during pregnancy, which might be attributed to the down-regulated anti-inflammatory mechanisms, but not be associated with higher oral bacterial burden.

Automatic segmentation of spine x-ray images based on multiscale feature enhancement network.

BACKGROUND: Automatic segmentation of vertebrae in spinal x-ray images is crucial for clinical diagnosis, case analysis, and surgical planning of spinal lesions. PURPOSE: However, due to the inherent characteristics of x-ray images, including low contrast, high noise, and uneven grey scale, it remains a critical and challenging problem in computer-aided spine image analysis and disease diagnosis applications. METHODS: In this paper, a Multiscale Feature Enhancement Network (MFENet), is proposed for segmenting whole spinal x-ray images, to aid doctors in diagnosing spinal-related diseases. To enhance feature extraction, the network incorporates a Dual-branch Feature Extraction Module (DFEM) and a Semantic Aggregation Module (SAM). The DFEM has a parallel dual-branch structure. The upper branch utilizes multiscale convolutional kernels to extract features from images. Employing convolutional kernels of different sizes helps capture details and structural information at different scales. The lower branch incorporates attention mechanisms to further optimize feature representation. By modeling the feature maps spatially and across channels, the network becomes more focused on key feature regions and suppresses task-irrelevant information. The SAM leverages contextual semantic information to compensate for details lost during pooling and convolution operations. It integrates high-level feature information from different scales to reduce segmentation result discontinuity. In addition, a hybrid loss function is employed to enhance the network's feature extraction capability. RESULTS: In this study, we conducted a multitude of experiments utilizing dataset provided by the Spine Surgery Department of Henan Provincial People's Hospital. The experimental results indicate that our proposed MFENet demonstrates superior segmentation performance in spinal segmentation on x-ray images compared to other advanced methods, achieving 92.61 ± 0.431 for MIoU, 92.42 ± 0.329 for DSC, and 99.51 ± 0.037 for Global_accuracy. CONCLUSIONS: Our model is able to more effectively learn and extract global contextual semantic information, significantly improving spinal segmentation performance, further aiding doctors in analyzing patient conditions.

Iron­calcium dual crosslinked graphene oxide/alginate aerogel microspheres for extraordinary elimination of tetracycline in complex wastewater: Performance, mechanism, and applications.

Antibiotics have been considered as a group of emerging contaminants for their stable chemical structure, significant pseudo-persistence, and biological toxicity. Tetracycline (TC), as one of the typical antibiotics frequently detected in environmental media, can cause the dissemination and accumulation of antibiotic resistance gene (ARG), ultimately threatening human health and environmental safety. Herein, a novel iron­calcium di-crosslinked graphene oxide/alginate (GO/SA-Fe3+-Ca2+) aerogel was facilely synthesized for TC uptake. It was found that the introduction of GO nanosheets and Fe3+ sites into composite enormously enhanced TC removal. Specifically, TC can be stably and efficiently eliminated over the wide pH range of 5-8. The fitted maximum qe with Liu isotherm model at 308 K reached 1664.05 mg/g, surpassing almost all reported sorbents. The pseudo-second-order kinetic model with chemical sorption characteristics better fitted TC adsorption process, which was endothermic and spontaneous in nature. Multifarious adsorptive sites of GO/SA-Fe3+-Ca2+ synergically participated in TC uptake through multi-mechanisms (e.g., π-π EDA, cation-π bonding, H-bonding, Fe3+-coordination, and electrostatic attraction, etc.). The as-prepared composite showed satisfactory TC removal in several runs of adsorption-desorption operations, high salinity, and model aquaculture wastewater. Moreover, the packed-column could continuously run for >200 h until adsorption saturation was achieved with a dynamic adsorption capacity of 216.69 mg/g, manifesting its scale-up engineering applications. All above merits make as-constructed composite an alternative sorbent for eliminating TC from complex wastewater.

Brain-machine interface-based training for improving upper extremity function after stroke: A meta-analysis of randomized controlled trials.

Background: Upper extremity dysfunction after stroke is an urgent clinical problem that greatly affects patients' daily life and reduces their quality of life. As an emerging rehabilitation method, brain-machine interface (BMI)-based training can extract brain signals and provide feedback to form a closed-loop rehabilitation, which is currently being studied for functional restoration after stroke. However, there is no reliable medical evidence to support the effect of BMI-based training on upper extremity function after stroke. This review aimed to evaluate the efficacy and safety of BMI-based training for improving upper extremity function after stroke, as well as potential differences in efficacy of different external devices. Methods: English-language literature published before April 1, 2022, was searched in five electronic databases using search terms including "brain-computer/machine interface", "stroke" and "upper extremity." The identified articles were screened, data were extracted, and the methodological quality of the included trials was assessed. Meta-analysis was performed using RevMan 5.4.1 software. The GRADE method was used to assess the quality of the evidence. Results: A total of 17 studies with 410 post-stroke patients were included. Meta-analysis showed that BMI-based training significantly improved upper extremity motor function [standardized mean difference (SMD) = 0.62; 95% confidence interval (CI) (0.34, 0.90); I 2 = 38%; p < 0.0001; n = 385; random-effects model; moderate-quality evidence]. Subgroup meta-analysis indicated that BMI-based training significantly improves upper extremity motor function in both chronic [SMD = 0.68; 95% CI (0.32, 1.03), I 2 = 46%; p = 0.0002, random-effects model] and subacute [SMD = 1.11; 95%CI (0.22, 1.99); I 2 = 76%; p = 0.01; random-effects model] stroke patients compared with control interventions, and using functional electrical stimulation (FES) [SMD = 1.11; 95% CI (0.67, 1.54); I 2 = 11%; p < 0.00001; random-effects model]or visual feedback [SMD = 0.66; 95% CI (0.2, 1.12); I 2 = 4%; p = 0.005; random-effects model;] as the feedback devices in BMI training was more effective than using robot. In addition, BMI-based training was more effective in improving patients' activities of daily living (ADL) than control interventions [SMD = 1.12; 95% CI (0.65, 1.60); I 2 = 0%; p < 0.00001; n = 80; random-effects model]. There was no statistical difference in the dropout rate and adverse effects between the BMI-based training group and the control group. Conclusion: BMI-based training improved upper limb motor function and ADL in post-stroke patients. BMI combined with FES or visual feedback may be a better combination for functional recovery than robot. BMI-based trainings are well-tolerated and associated with mild adverse effects.

Down-regulated Treg cells in exacerbated periodontal disease during pregnancy.

Pregnancy is a special period marked with complicated changes in various immune responses. Although pregnant women are prone to developing gingival inflammation, its immunological mechanism remains to be clarified. In a modified ligature-induced periodontal disease murine model, pregnant mice developed more severe alveolar bone loss. Using this model, we investigated the Treg responses during exacerbated periodontal disease in pregnant mice. We tested Treg-associated molecules in gingival tissues by quantitative real-time PCR and found decreased gingival expression of Foxp3, TGFß, CTLA-4, and CD28 in pregnant mice after periodontal disease induction. We further confirmed that lower number of Treg cells were present in the cervical lymph nodes of pregnant periodontitis mice. Treg cells from the cervical lymph nodes of ligated pregnant mice and non-pregnant mice were tested for their suppressive function in vitro. We manifested that Treg suppressive function was also down-regulated in the pregnant mice. Additionally, we demonstrated that more inflammatory Th17 cells were present in the cervical lymph nodes of ligated pregnant mice. Therefore, impaired Treg development and function, together with upregulated Th17 response, may contribute to the exacerbated periodontal disease during pregnancy.

MicroRNA-21 down-regulates inflammation and inhibits periodontitis.

Periodontitis is one of the most prevalent inflammatory diseases, characterized by gingival inflammation and alveolar bone loss. MicroRNAs (MiRNAs) are important regulators of inflammation and involved in periodontitis pathogenesis. In this work, we studied the roles of microRNA-21 (miR-21) in periodontitis. MiR-21 is up-regulated in both periodontitis patients and the mice that induced with periodontitis. We tested the roles of miR-21 in the macrophages challenged by periodontitis pathogen Porphyromonas gingivalis (P. gingivalis) lipopolysaccharide (LPS). MiR-21 expression is up-regulated in P. gingivalis LPS-stimulated macrophages. MiR-21 mimic inhibits the pro-inflammatory cytokine production by macrophages, while miR-21 deficiency elevates the production of pro-inflammatory cytokines. Moreover, absence of miR-21 promotes activation of nuclear factor-κB (NF-κB) in P. gingivalis LPS- stimulated cells. In a murine periodontitis model, ligation induced exacerbated gingival inflammation and alveolar bone loss in miR-21 deficient mice than their wild-type littermates. These results demonstrated the anti-inflammatory function of miR-21 in vitro and in vivo, indicating miR-21 could be an interventional target for the control of periodontitis.

Comparing cone-beam computed tomography with periapical radiography for assessing root canal obturation in vivo using microsurgical findings as validation.

OBJECTIVES: The aim of this study was to verify whether there is a difference in the in vivo performance characteristics of CBCT and periapical radiography (PR) in assessing the apical extension of root canal obturation (RCO) and to evaluate the ability of CBCT in void detection using microsurgical findings as validation. METHODS: This study included 323 tooth roots that required surgical treatment and for which pre-existing periapical radiographs and CBCT images were available. Three calibrated observers individually analyzed the periapical radiographs, CBCT images and photomicrographs of each root. Performance characteristics of CBCT and PR were compared in terms of their evaluation of the apical extension of the RCOs. The ability of CBCT to detect voids in the RCOs was evaluated using microsurgical findings as validation. Kappa values were used for intraobserver/interobserver agreement. RESULTS: Perfect intraobserver/interobserver agreement (1.0) was achieved when using photomicrography. The two agreements of PR were superior to those of CBCT when CBCT was used to detect voids (p < 0.05). The sensitivity of CBCT [0.86, 95% confidence interval (CI) 0.76-0.93] was superior to that of PR (0.66, 95% CI 0.54-0.76) in detecting overextension (p < 0.005). CBCT showed a poor sensitivity (0.24, 95% CI 0.19-0.30) and specificity (0.67, 95% CI 0.54-0.78) in void detection. CONCLUSIONS: CBCT was better than PR for evaluating the apical extension of RCOs. CBCT, with its poor sensitivity and specificity, might both overestimate and underestimate the proportion of voids in RCOs. CBCT was not suitable for evaluating the quality of RCOs.

[Assessment of referral cases for root canal therapy].

OBJECTIVE: To assess referral cases for root canal therapy to provide clinical evidence with establishment of referral system. METHODS: A questionnaire was designed to collect 312 cases (355 teeth) referred to Department of Conservative Dentistry and Endodontics, West China School of Stomatology, Sichuan University for root canal therapy from April to June in 2011. The questionnaire consisted of questions such as age, gender, occupation, general disease and medical histories of patients, sources. Difficulty of treatment before therapy and reasons for referral were evaluated. RESULTS: In 355 referral teeth, the most were mandibular first molars (17%), the greatest percentage of reasons were calcified root canals (30%), the second was root canal retreatment (24%). 72% of teeth belong to the complicated difficulty (Class III), while 7% were listed as the uncomplicated difficulty (Class I). No significantly difference from different sources was found (P = 0.9). CONCLUSION: Establishment of referral system needs cooperation with every dentist. Difficulty of cases for root canal therapy before treatment should be first evaluated to treat or to refer. Referral cases for root canal therapy should be treated by endodontist of corresponding level according to the difficulty.

Associations between maxillary sinus mucosal thickening and apical periodontitis using cone-beam computed tomography scanning: a retrospective study.

INTRODUCTION: This study evaluated the pathologic and spatial associations between apical periodontitis of the maxillary premolars/molars and the maxillary sinus mucosal thickening using cone-beam computed tomography (CBCT) scanning. METHODS: CBCT images of 372 patients with 508 exposed maxillary sinuses were inspected retrospectively. Clinical features such as sex and age of the patients and pathologic findings of the maxillary sinus and adjacent teeth were recorded, graded, and analyzed. RESULTS: Maxillary sinus mucosal thickening was found in 180 (48.4%) patients and 235 (46.2%) sinuses. The prevalence of maxillary sinus mucosal thickening increased dramatically as the severity of apical periodontitis increased (from 41.5% in those without periodontal disease to 100%). However, the nature of the spatial relationship between the maxillary sinus floor and the infected root tips or between the sinus floor and periapical lesions did not appear to have an effect on the prevalence of maxillary sinus mucosal thickening. Patients over 60 years of age had the highest prevalence of maxillary sinus mucosal thickening. CONCLUSIONS: A retrospective inspection of CBCT images revealed that the prevalence and severity of maxillary sinus mucosal thickening were positively associated with the degree of apical periodontitis. CBCT imaging is applicable for the evaluation of the maxillary sinuses and adjacent teeth.

[The antibacterial efficacy of KaVo KEY laser on Enterococcus faecalis within infected root canals and roots surface in vitro].

OBJECTIVE: To evaluate the antibacterial efficacy of KaVo KEY laser on Enterococcus faecalis (E. faecalis) within infected root canals and roots surface in vitro. METHODS: Fifty single-rooted teeth were selected, and infected root canals and roots surface vitro models were prepared. Then, these specimens were divided into three groups. First group were untreated as blank control. The other two groups were the laser groups: Irradiated 15 s and 30 s respectively with 80 mJ and 140 mJ in root canals and on roots surface. Microbiological samples were collected from root canals and roots surface at two time points (before irrigation and immediately after irrigation). The dentin chips from three different zone of part of root canals in each group were immediately collected and were cultured for 24 h in brain heart infusion (BHI). RESULTS: The number of E. faecalis in root canal and root surface in each of the groups were effectively reduced (P < 0.05), and there was no significant difference between each two groups (P > 0.05). Compared with the blank control, the bacterial number in 100 microm of dental tubules decreased after specimens treated with 80 mJ, and the experimental group irradiated 15 s was a significant decease (P < 0.05). The other groups were no changed in different zone of dental tubules. CONCLUSION: KaVo KEY laser is effective on sterilizing infected root canals and roots surface. It has also significant effect on bacterial in superficial dental tubules with low energy and short time.