With the scientific and modernization of acupuncture,various kinds of acupuncture medical equipment continue to innovate,especially with the emergence of intelligent acupuncture diagnosis and treatment units,automatic detection of acupuncture needles in the"needle retention"stage of acupuncture clinical practice has become a hot demand.Aiming at the problems that the input image size is too large,the acupuncture needles are slender,and the acupuncture needles are densely distributed,the Acupuncture Needle Object Detection Model(ANODM),an improved YOLOv5 model for acupuncture needles,is proposed in this paper.① In the preprocessing stage,the image is divided into multiple patches for prediction,respectively.② At the model structure level,a new small object detection layer is added to the original three detection layers to improve the recognition ability of small objects.The ordinary convolution of the backbone network is replaced by the dialated convolution to increase the sensitivity field.Features of different stages are fused.③ In the post-processing stage,Soft-NMS is used to reduce the miss rate of positive samples,and cosine similarity match is used to reduce the error rate of negative samples.The experimental results show that,compared with the original YOLOv5,the detection accuracy of the improved YOLOv5 in this paper is improved by 4.2%on the acupuncture needle small object dataset,which can better complete the acupuncture needle small target detection task.

With the scientific and modernization of acupuncture,various kinds of acupuncture medical equipment continue to innovate,especially with the emergence of intelligent acupuncture diagnosis and treatment units,automatic detection of acupuncture needles in the"needle retention"stage of acupuncture clinical practice has become a hot demand.Aiming at the problems that the input image size is too large,the acupuncture needles are slender,and the acupuncture needles are densely distributed,the Acupuncture Needle Object Detection Model(ANODM),an improved YOLOv5 model for acupuncture needles,is proposed in this paper.① In the preprocessing stage,the image is divided into multiple patches for prediction,respectively.② At the model structure level,a new small object detection layer is added to the original three detection layers to improve the recognition ability of small objects.The ordinary convolution of the backbone network is replaced by the dialated convolution to increase the sensitivity field.Features of different stages are fused.③ In the post-processing stage,Soft-NMS is used to reduce the miss rate of positive samples,and cosine similarity match is used to reduce the error rate of negative samples.The experimental results show that,compared with the original YOLOv5,the detection accuracy of the improved YOLOv5 in this paper is improved by 4.2%on the acupuncture needle small object dataset,which can better complete the acupuncture needle small target detection task.

Objective To investigate the pharmacokinetic characteristics of asparaginase-loaded sulfobutyl ether-β-cyclodextrin supramolecule lipidic nanoparticles (ASLN) in rats and its inhibitory effect on the proliferation of small cell lung cancer cells. Methods ASLN were prepared by a reverse phase evaporation method,and their physicochemical properties,including morphology,particle size,zeta potential,and drug entrapment efficiency,were characterized. Twelve male Sprague-Dawley rats were randomly divided into 2 groups,with 6 rats in each group. After intravenous injection of ASLN and free asparaginase (Aase) 2 kU/kg,the activity of Aase in plasma samples was measured at different time points in 48 h,and the activity-time curve was drawn. The pharmacokinetic parameters were calculated by software DAS 2.1.1. The cytotoxicity of ASLN on H446 cells was explored by the MTT method. Results ASLN showed a spherical shape with a mean particle size of (321.27±1.42) nm,zeta potential of (-9.31±0.42) mV,and entrapment efficiency of (66.46±1.57)％. Pharmacokinetic parameters of ASLN and Aase were as follows:the area under curve (AUC(0-48 h)) (199.48±2.18) U·mL-1·h,(57.63±3.89) U·mL-1·h;the mean residence time (MRT(0-48 h)) (4.40±0.05) h,(2.09±0.07) h;and the peak concentration (Cmax) (35.49±1.11) U/mL,(27.58±1.28) U/mL. The relative bioavailability of ASLN to Aase was 325.96％. The cytotoxicity results indicated that ASLN had a proliferation inhibitory effect on H446 cells,and there was a positive correlation between the inhibition rate and the dose. Conclusion ASLN can improve the pharmacokinetics of Aase,enhance the bioavailability of Aase,and inhibit the proliferation of small cell lung cancer cells.

OBJECTIVE: To study the safety and feasibility after functional Endoscopic surgery(FESS), without no nasal packing in 74 patients,compare these patients with 20 packing patients, and discuss the possibility and indication of avoiding packing. METHOD: No nasal packing after FESS in 74 patients, the measures had been taken to reduce postoperative bleeding including appropriate case-chosen, medical administration before and after operation, alleviation of trauma in operation, and meticulous sinus clearance to prevent synechia. RESULT: The postoperative blood loss were less than 50 ml. No bleeding complication happened out of the 74 no-packing patients, the blood exudation ceased timely after FESS. CONCLUSION The nasal packing could be avoided in the majority of FESS through proper management. This choice will reduce the discomfort and the cost of the patients who have to receive FESS procedure, and increase their compliance.
Adolescent ; Adult ; Chronic Disease ; Endoscopy ; methods ; Feasibility Studies ; Female ; Hemostatic Techniques ; Humans ; Male ; Middle Aged ; Otorhinolaryngologic Surgical Procedures ; methods ; Postoperative Hemorrhage ; prevention & control ; Postoperative Period ; Sinusitis ; surgery ; Tampons, Surgical ; Treatment Outcome ; Young Adult