Objective: To reveal the therapeutic effect of acupuncture-moxibustion therapy for the treatment of post-stroke shoulder pain. Methods: Ninety patients with post-stroke acupuncture-moxibustion therapy (AM), acupuncture-moxibustion plus Chinese herbal decoction (AMCH), and Chinese herbal decoction (CH) respectively. Results: In the comparison of the therapeutic effects and blood viscosity, there was significant difference between the AM and CH group, as well as between the AMCH and CH group (P＜0.01); the difference was not significant between the AM and AMCH group. Conclusion:Acupuncture-moxibustion is an effective therapy in the treatment of the post-stroke shoulder pain, and it can also reduce the blood viscosity in short-term.

Objective To minimize variations in treatment outcomes of L5/S1 percutaneous intervertebral radiofrequency thermocoagulation(PIRFT)arising from physician proficiency and achieve precise quantitative risk assessment of the puncture paths.Methods We used a self-developed deep neural network DWT-UNet for automatic segmentation of the magnetic resonance(MR)images of the L5/S1 segments into 7 key structures:L5,S1,Ilium,Disc,N5,Dura mater,and Skin,based on which a needle insertion path planning environment was modeled.Six hard constraints and 6 soft constraints were proposed based on clinical criteria for needle insertion,and the physician's experience was quantified into weights using the analytic hierarchy process and incorporated into the risk function for needle insertion paths to enhance individual case adaptability.By leveraging the proposed skin entry point sampling sub-algorithm and Kambin's triangle projection area sub-algorithm in conjunction with the analytic hierarchy process,and employing various technologies such as ray tracing,CPU multi-threading,and GPU parallel computing,a puncture path was calculated that not only met clinical hard constraints but also optimized the overall soft constraints.Results A surgical team conducted a subjective evaluation of the 21 needle puncture paths planned by the algorithm,and all the paths met the clinical requirements,with 95.24%of them rated excellent or good.Compared with the physician's planning results,the plans generated by the algorithm showed inferior DIlium,DS1,and Depth(P<0.05)but much better DDura,DL5,DN5,and AKambin(P<0.05).In the 21 cases,the planning time of the algorithm averaged 7.97±3.73 s,much shorter than that by the physicians(typically beyond 10 min).Conclusion The multi-constraint optimal puncture path planning algorithm offers an efficient automated solution for PIRFT of the L5/S1 segments with great potentials for clinical application.

Objective To minimize variations in treatment outcomes of L5/S1 percutaneous intervertebral radiofrequency thermocoagulation(PIRFT)arising from physician proficiency and achieve precise quantitative risk assessment of the puncture paths.Methods We used a self-developed deep neural network DWT-UNet for automatic segmentation of the magnetic resonance(MR)images of the L5/S1 segments into 7 key structures:L5,S1,Ilium,Disc,N5,Dura mater,and Skin,based on which a needle insertion path planning environment was modeled.Six hard constraints and 6 soft constraints were proposed based on clinical criteria for needle insertion,and the physician's experience was quantified into weights using the analytic hierarchy process and incorporated into the risk function for needle insertion paths to enhance individual case adaptability.By leveraging the proposed skin entry point sampling sub-algorithm and Kambin's triangle projection area sub-algorithm in conjunction with the analytic hierarchy process,and employing various technologies such as ray tracing,CPU multi-threading,and GPU parallel computing,a puncture path was calculated that not only met clinical hard constraints but also optimized the overall soft constraints.Results A surgical team conducted a subjective evaluation of the 21 needle puncture paths planned by the algorithm,and all the paths met the clinical requirements,with 95.24%of them rated excellent or good.Compared with the physician's planning results,the plans generated by the algorithm showed inferior DIlium,DS1,and Depth(P<0.05)but much better DDura,DL5,DN5,and AKambin(P<0.05).In the 21 cases,the planning time of the algorithm averaged 7.97±3.73 s,much shorter than that by the physicians(typically beyond 10 min).Conclusion The multi-constraint optimal puncture path planning algorithm offers an efficient automated solution for PIRFT of the L5/S1 segments with great potentials for clinical application.

Radiotherapy is one of the most common treatments for oral cancer. However, in the clinic, recurrence and metastasis of oral cancer occur after radiotherapy, and the underlying mechanism remains unclear. Cancer stem cells (CSCs), considered the "seeds" of cancer, have been confirmed to be in a quiescent state in most established tumours, with their innate radioresistance helping them survive more easily when exposed to radiation than differentiated cancer cells. There is increasing evidence that CSCs play an important role in recurrence and metastasis post-radiotherapy in many cancers. However, little is known about how oral CSCs cause tumour recurrence and metastasis post-radiotherapy. In this review article, we will first summarise methods for the identification of oral CSCs and then focus on the characteristics of a CSC subpopulation induced by radiation, hereafter referred to as "awakened" CSCs, to highlight their response to radiotherapy and potential role in tumour recurrence and metastasis post-radiotherapy as well as potential therapeutics targeting CSCs. In addition, we explore potential therapeutic strategies targeting these "awakened" CSCs to solve the serious clinical challenges of recurrence and metastasis in oral cancer after radiotherapy.
Humans ; Mouth Neoplasms ; pathology ; radiotherapy ; Neoplasm Recurrence, Local ; radiotherapy ; Neoplastic Stem Cells ; pathology ; radiation effects ; Radiotherapy ; methods ; Recurrence

Objective: To investigate the risk factors affecting the occurrence of complications in patients with vaginal bleeding after in vitro fertilization/intracytoplasmic sperm injection embryo transfer(IVF/ICSI-ET) and the construction of nomogram prediction model. Methods: A total of 272 patients with threatened abortion after IVF/ICSI-ET were retrospectively analyzed in this study. They were divided into the live birth group and abortion group according to the final outcome of pregnancy. Patient characteristics were evaluated using the chi-square test, independent-samples Student's t-test or Wilcoxon rank sum test. A nomogram was created to predict the pregnancy outcome of women with threatened abortion who received IVF/ICSI using multivariate logistic regression coefficients. Results: There was no significant difference in the basic data, percentage of frozen embryos, treatment method, number of embryos transferred, high-quality embryo rate, and embryo implantation rate of the live birth group and abortion group(P>0.05). There were significant differences in body mass index, the onset of vaginal bleeding time after transplantation, serum levels of hCG and progesterone on 14 th day after embryo-transfer, and the number of gestational sacs between the two groups(P<0.05). After multivariate logistic regression analysis, the onset of vaginal bleeding time after transplantation and serum hCG levels on 14 th day after transfer were statistically significant(P<0.05). The nomogram was established based on the above indicators, with an area under the curve of 0.710 for the nomogram. The area under the ROC curve of our nomogram was better than the area under the ROC curve of a single risk factor(AUC of bleeding time after embryo-transfer: 0.644, AUC of serum hCG14:0.625). Conclusion The nomogram model established based on the onset of vaginal bleeding time after embryo-transfer and serum hCG value on 14 th day after embryo-transfer can better predict pregnancy outcome of patients with threatened abortion after IVF/ICSI-ET.