Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Objective To create a self-optimization pharmaceutical care(PC)model for breast cancer patients after modified radical mastectomy based on the concept of"CMT"and evaluate the value of reference.Methods A total of 846 breast cancer patients after modified radical mastectomy in the HIS system of First Affiliated Hospital of Hebei North University from June 2019 to June 2023 were selected.The model included four levels:quality of life(QOL)score,research,QOL score classification and association rule analysis.The QOL scores of the patients were counted.The PC features of the patients were col-lected through research.The QOL scores were classified by using automatic binning analysis.The effective strong association rules between PC feature of patients with interest QOL scores were analyzed by using association rule analysis.logistic regression analy-sis was performed on the date of all the patients to analyze the independent risk factors leading to the interest type QOL score.The reference value of the model was evaluated based on the statistical results and PC optimization measures were proposed.Results The QOL scores of the patients were divided into four categories,with the lowest score being the interest category.Six effective strong association rules were obtained."CCI＞4","Clarifying long-term medication goals:No","Timely detection and reporting of adverse reactions:No","Explaining medication prognosis:No","Answering patient questions:No","Drug selection",and"Insufficient training"were all the reasons for the lowest QOL score.The results of the model were basically consistent with that of Logistic regression analysis.Based on the feedback results of the model,targeted optimization measures were proposed to reme-dy PC defects.Conclusion The application of PC self-optimization model for breast cancer patients after modified radical mastectomy has certain feasibility and can provide some reference for improving the quality of PC.

Adenoid cystic carcinoma (ACC) is the second most common pathological subtype of malignant tumors of salivary glands. The incidence of recurrence and metastasis is high after initial treatment. The optimal treatment for these patients is still controversial. In recent years, multiple attempts have been made to treat recurrent and / or metastatic ACC, such as radiation therapy, targeted therapy and immunotherapy. In this article, the treatment options for recurrent and / or metastatic ACC was reviewed and the effect and prospect of each treatment were summarized.

In order to improve the efficiency of protein spots detection, a fast detection method based on CUDA was proposed. Firstly, the parallel algorithms of the three most time-consuming parts in the protein spots detection algorithm: image preprocessing, coarse protein point detection and overlapping point segmentation were studied. Then, according to single instruction multiple threads executive model of CUDA to adopted data space strategy of separating two-dimensional (2D) images into blocks, various optimizing measures such as shared memory and 2D texture memory are adopted in this study. The results show that the operative efficiency of this method is obviously improved compared to CPU calculation. As the image size increased, this method makes more improvement in efficiency, such as for the image with the size of 2,048 x 2,048, the method of CPU needs 52,641 ms, but the GPU needs only 4,384 ms.
Algorithms ; Image Processing, Computer-Assisted ; Proteomics ; methods ; Software

Objective To establish a Chinese hamster model of babesia infection, to find the changing pattern of organs and biochemical parameters in Chinese hamster infected with Babesia, and to promote the detection and treatment of babesiosis.Methods Healthy 5-week old Chinese hamsters were infected by intraperitoneal injection of blood containing Babesia.Blood samples were collected at 0, 2, 4, 6, 8, 10, 12, 14, 16, 23, 30, and 37 days after infection from 5 hamsters at each time point.Blood smears were prepared to detect the parasites using Giemsa staining.ELISA assay was employed to test the IL-2 concentration.The blood biochemical indexes were detected using an automatic biochemical analyzer.DNA was extracted from the whole blood and REAL-TIME RCR was performed to determine the reproduction of Babesia.Aftert the animals were sacrificed, the heart, lung, spleen, liver, and kidney were taken to analyze the changes of organ coefficients.Results The highest level of Babesia in the hamsters occurred on day 4 after the Babesia injection, and then showing a decreasing tendency.However, there was a transient increase on the 12th day after infection.The liver and spleen displayed most extensive response to the infection showing hepatomegaly and splenomegaly, but the variation of heart and kidneys coefficients was within the norm.There were prominent changes of blood cells, especially leucocytes, with two peaks at day 10 and 23 after the Babesia infection.The peak changes of blood biochemical indexes occurred at day 12 after infection.The concentration of serum IL-2 reached a peak on the 10th day after infection.Conclusions The Chinese hamsters display typical characteristics of tick-borne diseases such as hepatomegaly and splenomegaly.The immunological system is activated along with the infection and reaches a highest stage in the second week.Afterwards the Babesia can live in the hamster body for a long period of time.The results of this study provide useful information supporting further studies on the detection, treatment and prevention of Babesiosis.

There are no intuitive and unified standards for selecting features in existing protein gel image point matching method, for which an analysis method based on similarity map is proposed. Firstly, the definition and generation methods of similarity map were presented. Secondly, trait and merits of features such as coordinate similarity, shape-context similarity and morphology similarity were analyzed using similarity map method. Finally, comprehensive utilization of multi-features named product-method which has a better effect than mean-method was proposed based on the results. Many experiments using different 2-DE gel images were carried out to prove the validity of similarity map and product-method. The results showed that similarity map could be used for intuitional, effective analysis of matching performance and to guide the selection and comprehensive utilization of multi-features.