BACKGROUND:We have designed and manufactured a novel artificial cervical vertebra and intervertebral complex (ACVC) which combines the cervical titanium cage with the artificial cervical disc, and also developed the ACVC with a hydroxyapatite biocoating (ACVC-HA). OBJECTIVE:To evaluate biomechanical properties of the joint system, and the role of HA coating in promoting osseointegration and long-term stability. METHODS:Twenty-four goats were randomly divided into three groups and underwent the anterior C2/3 and C3/4 discectomy, and C3 subtotal corpectomy, fol owed by ACVC implantation (group 1) and ACVC-HA implantation (group 2), and given no intervention (black control group), respectively. group. At 12 weeks after surgery, C1-5 samples were col ected to undergo biomechanical tests and histological staining. RESULTS AND CONCLUSION:Prior to the fatigue test, compared with the blank control group, the range of motion and neural zone of groups 1 and 2 in the directions of flexion-extension and lateral bending showed no significant differences, but the above indicators were significantly increased in the direction of rotation (P<0.05). Additional y, the stiffness in al three directions was significantly lower than that in the blank control group (P<0.05). There were no significant differences in the range of motion and neural zone in al directions between groups 1 and 2. Similar results were found after the fatigue test. The histological staining showed that both two implants had good biocompatibility and abradability, but more new bone formed on the ACVC-HA. These results suggest that ACVC can effectively reconstruct the motor function of the cervical spine after decompression. Furthermore, HA coating can markedly improve bone-implant interface to promote osseointegration.

Objective:To explore the effect and mechanism of interleukin-35 gene modified mesenchyma stem cells(MSC)on ameliorating cardiac allograft rejection and prolonging graft survival of transplanted heart in mice.Methods:In this study, IL-35-MSC secreting IL-35 continuously and steadily were successfully constructed in vitro. Abdominal heterotopic heart transplantation model was established successfully. And they were randomly divided into syngeneic control group; saline control group, MSC treatment group and IL-35-MSC experimental group(n=12 each). Six mice were randomly selected for sacrificing at Day 5 post-operation for detecting the related indicators in each group: Hematoxylin eosin staining was used for pathological examination. Enzyme-linked immunosorbent assay(ELISA)was employed for detecting the concentration of IL-35 in peripheral blood and the proportion of T lymphocyte subsets in spleen was analyzed by flow cytometry(FCM). Then the remaining mice were used for recording the graft survival.Results:The model of abdominal heterotopic heart transplantation in mice was successfully constructed. As compared with saline control group(6.50±0.55 d)and MSC treatment group(12.00±0.89 days), IL-35-MSC significantly alleviated rejection after transplantation and effectively prolonged the survival time of graft(18.50±1.64 days)(n=6, P<0.01). As compared with other groups, percentage of Th17 cells and Th1/Th2 ratio in spleen decreased significantly while the proportion of CD4 + Foxp3 + Treg increased significantly in IL-35-MSC experimental group at Day 5 post-transplantation(n=6, P<0.01). Conclusions:IL-35-MSC may alleviate cardiac allograft rejection and prolong graft survival. And cellular immunotherapy based upon IL-35-MSC may provide a new approach for inducing immune tolerance.

This paper introduced the legislative development of community benefits system of nonprofit hospitals at federal level in the United States,as well as state legislatures in this regard. Based on America's experiences, an analysis was made on the "community benefits and health promotion model", which refers to community health needs assessment, health promotion programs, program implementation, supervision and appraisal. Thus the authors put forward inspirations for the social responsibility system development of public hospitals in China as follows. This refers to the establishment of hospitals' social responsibility system; development of community health promotion planning based on health needs;and establishment of social responsibility information disclosure system for fulfillment of their social responsibilities.

Objective:To construct a traditional Chinese medicine syndrome differentiation model for tinnitus using automatic machine learning technology, and to explore the key factors that affect the results of tinnitus syndrome differentiation.Methods:The clinical characteristics of 594 patients with subjective tinnitus in seven medical units in Shanghai from January 2021 to January 2022 were retrospectively analyzed. The Auto-sklearn automatic machine learning method was used to compare 15 algorithms, and the model with the best classification effect was selected to analyze the key factors affecting tinnitus.Results:The results showed that the optimal algorithm for classification results was the random forest, its accuracy, precision, sensitivity, specificity, F1-score, AUC and kappa coefficient were 87.37%, 88.34%, 89.06%, 96.63%, 88.38%, 97.50%, and 83.37%, respectively. It is concluded that the key factors affecting the classification of the pattern of kidney yin deficiency and fire effulgence, the pattern of liver fire disturbing upward, the pattern of stagnation and binding of phlegm and fire, the pattern of spleen and stomach deficiency, the pattern of wind and heat attacking the external are smooth pulse, string pulse, smooth pulse, weak tongue, and floating pulse respectively.Conclusions:Random forest can provide a good classification prediction function for structured clinical data, suggesting that machine learning technology has clinical application value in assisting the diagnosis of subjective tinnitus.

The present study retrospectively analyzed the clinical data of 137 patients who underwent prostate in North Jiangsu People's Hospital from June 2020 to May 2021. All patients underwent peripheral prostatic nerve block anesthesia (PPNB). The observation group received 1% ropivacaine 32 ml local, and the control group received the same dose of lidocaine. There was no significant difference in general data before puncture between the two groups ( P>0.05). All 137 cases were performed by the same surgeon. The number of puncture needles in the observation group and the control group was (20.2±2.8) and (20.2±2.9), respectively, and the difference was not statistically significant ( P>0.05). The visual analogue scores (VAS-1) of pain during puncture in the observation group and the control group were (2.62±0.74) and (2.48±0.79) points, respectively. The visual numeric score (VNS-1) was (3.03±0.88) points and (3.15±0.80) points, respectively, and there was no significant difference ( P>0.05). 30 min after puncture, VAS-2 was (0.48±0.53) points and (0.30±0.47) points, VNS-2 was (3.31±0.48) points and (3.55±0.71) points, respectively.The differences were statistically significant ( P<0.05). There was no significant difference in overall complication rate between the two groups ( P=0.661).

BACKGROUND:MRI is important for the diagnosis of early knee osteoarthritis.MRI image recognition and intelligent segmentation of knee osteoarthritis using deep learning method is a hot topic in image diagnosis of artificial intelligence. OBJECTIVE:Through deep learning of MRI images of knee osteoarthritis,the segmentation of femur,tibia,patella,cartilage,meniscus,ligaments,muscles and effusion of knee can be automatically divided,and then volume of knee fluid and muscle content were measured. METHODS:100 normal knee joints and 100 knee osteoarthritis patients were selected and randomly divided into training dataset(n=160),validation dataset(n=20),and test dataset(n=20)according to the ratio of 8:1:1.The Coarse-to-Fine sequential training method was used to train the 3D-UNET network deep learning model.A Coarse MRI segmentation model of the knee sagittal plane was trained first,and the rough segmentation results were used as a mask,and then the fine segmentation model was trained.The T1WI and T2WI images of the sagittal surface of the knee joint and the marking files of each structure were input,and DeepLab v3 was used to segment bone,cartilage,ligament,meniscus,muscle,and effusion of knee,and 3D reconstruction was finally displayed and automatic measurement results(muscle content and volume of knee fluid)were displayed to complete the deep learning application program.The MRI data of 26 normal subjects and 38 patients with knee osteoarthritis were screened for validation. RESULTS AND CONCLUSION:(1)The 26 normal subjects were selected,including 13 females and 13 males,with a mean age of(34.88±11.75)years old.The mean muscle content of the knee joint was(1 051 322.94±2 007 249.00)mL,the mean median was 631 165.21 mL,and the mean volume of effusion was(291.85±559.59)mL.The mean median was 0 mL.(2)There were 38 patients with knee osteoarthritis,including 30 females and 8 males.The mean age was(68.53±9.87)years old.The mean muscle content was(782 409.18±331 392.56)mL,the mean median was 689 105.66 mL,and the mean volume of effusion was(1 625.23±5 014.03)mL.The mean median was 178.72 mL.(3)There was no significant difference in muscle content between normal people and knee osteoarthritis patients.The volume of effusion in patients with knee osteoarthritis was higher than that in normal subjects,and the difference was significant(P<0.05).(4)It is indicated that the intelligent segmentation of MRI images by deep learning can discard the defects of manual segmentation in the past.The more accuracy evaluation of knee osteoarthritis was necessary,and the image segmentation was processed more precisely in the future to improve the accuracy of the results.

【Objective】 To report the early clinical effects and surgical complications of endoscopic spinal fusion technology （Endo-LIF） in the treatment of degenerative lumbar disease. 【Methods】 The clinical data of 31 patients with degenerative lumbar spine disease treated with Endo-LIF from June 2019 to May 2021 were retrospectively analyzed. All the 31 patients underwent endoscopic spinal fusion therapy. We recorded the operation time， hospital stay duration， postoperative complications， visual analogue scale for pain （VAS）， oswestry dysfunction Index （ODI） and low back pain in the Chinese Orthopaedic Association Spine Group Surgery scoring standards before operation， immediately after operation， and the last follow-up to evaluate clinical efficacy. 【Results】 The operation time of the 31 patients was （134.80±34.98） min， the intraoperative blood loss was （100.13±18.49） mL， the hospital stay was （6.65±0.17） days， and the follow-up time was 6 to 18 （14±2.3） months. One patient had hematoma compression after surgery； he had incision made immediately to clear the hematoma and healed after bed rest. Two patients developed spinal hypertension and healed after bed rest. All the patients had no symptoms of nerve injury after operation， and the clinical symptoms were significantly relieved. We compared the perioperative VAS score and ODI index of all the patients， which were lower immediately after operation and at the last follow-up than those before the operation （P<0.05）， and the difference was statistically significant. 【Conclusion】 Endo-LIF technology has good short-term clinical effects and the advantages of milder trauma， less blood loss， and quick recovery after surgery. It is a safe and minimally invasive lumbar fusion surgery.

Humans ; SARS-CoV-2 ; COVID-19 ; Antibodies ; Antibodies, Viral/therapeutic use* ; Antibodies, Neutralizing/therapeutic use*