Objective To observe the clinical efficacy of withdrawal therapy based on regulating nutritive qi and defensive qi(shortened to Tiaohe Yingwei method)in treating sedative-hypnotic dependent insomnia of disharmony between nutritive qi and defensive qi type.Methods Ninety patients with sedative-hypnotic dependent insomnia of disharmony between nutritive qi and defensive qi type were randomly divided into the treatment group and the control group,with 45 patients in each group.The control group was given oral use of Estazolam by 25%of weekly dose-reduction,while the treatment group was treated with Chinese medicinal decoction of Tiaohe Yingwei Zhumian Prescription based on Tiaohe Yingwei method together with Estazolam.The treatment course for the two groups lasted for 4 weeks.The changes of Pittsburgh Sleep Quality Index(PSQI)scores,total TCM syndrome scores,and Drug-withdrawal Syndrome Scale(DWSS)scores in the two groups were observed before and after treatment.After treatment,the efficacy for improving sleep efficiency value(IUSEV)and clinical safety in the two groups were evaluated.Results(1)During the trial,2 cases fell off in the treatment group,and 43 cases included in the statistics;3 cases fell off in the control group,and 42 cases included in the statistics.(2)After 4 weeks of treatment,the total effective rate for improving IUSEV of the treatment group was 88.37%(38/43),and that of the control group was 61.90%(26/42).The intergroup comparison by non-parametric rank-sum test showed that the efficacy for improving IUSEV in the treatment group was significantly superior to that in the control group(P＜0.05).(3)After treatment,obvious reduction was shown in the overall PSQI scores and the scores of the items of sleep quality,time for falling asleep,sleep time,sleep efficiency,sleep disorder and daytime dysfunction in the two groups when compared with those before treatment(P＜0.05).The intergroup comparison showed that except for the items of sleep disorder and daytime dysfunction,the treatment group had stronger effect on decreasing the scores of the remaining items and the overall PSQI scores than the control group(P＜0.05).(4)After treatment,the total scores of TCM syndromes of both groups were significantly decreased compared with those before treatment(P＜0.05),and the decrease of the total scores of TCM syndrome in the treatment group was significantly superior to that in the control group(P＜0.05).(5)After treatment,the total DWSS scores of the two groups were significantly decreased compared with those before treatment(P＜0.05),and the effect on lowering the scores in the treatment group was significantly superior to that in the control group(P＜0.05).(6)During the course of treatment,no significant adverse reactions occurred in the two groups,or no abnormal changes were found in the safety indexes such as routine test of blood,urine and stool,liver and kidney function,and electrocardiogram of the patients.Conclusion Withdrawal therapy based on Tiaohe Yingwei method exerts certain effect for the treatment of sedative-hypnotic dependent insomnia of disharmony between nutritive qi and defensive qi type.The therapy is effective on improving the quality of sleep and reducing the incidence of drug-withdrawal syndrome,and has a high safety.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective To compare the efficacy of renal proximal renal artery denervation(pRDN)and full-length renal artery denervation(fRDN)for treatment of hypertension.Methods Fifty-six hypertensive patients were enrolled and randomly assigned to full-length renal artery denervation group(n=25)and proximal renal artery denervation group(n=31).After the procedure,24-hour ambulatory blood pressure monitoring(24 h-ABPM)at 6 months and office blood pressure at 12 months was recorded for statistical analysis.Results The blood pressure at follow-up reduced significantly in both groups,while there was no significant difference between groups.The baseline office blood pressure in fRDN group and pRDN group was(180±15)/(104±10)mmHg and(180±12)/(103±8)mmHg,respectively,which decreased to(142±9)/(82±7)mmHg and(143±10)/(83±6)mmHg at 12 months postoperatively(P＜0.001 within groups and P＞0.05 between groups).The baseline 24 h-ABPM in the two groups was(162±13)/(95±8)mmHg and(160±12)/(94±8)mmHg,respectively,which decreased to(142±11)/(83±7)mmHg and(141±8)/(81±7)mmHg at 6 months postoperatively(P＜0.001 within groups and P＞0.05 between groups).However,there was no significant difference in the reduction of office blood pressure and ambulatory blood pressure between the two groups.No treatment-related adverse events were observed.Conclusions pRDN has similar antihypertensive effect to fRDN.

This study investigated the characteristics of gut microbiota imbalance in patients with infectious diarrhea caused by various pathogenic infections,and the role of Bacteroides in maintaining homeostasis in the intestinal environment.The gut microbiota in patients with diarrhea caused by pathogenic infections,such as viral and bacterial infections,was determined through full-length 16S rRNA amplicon sequencing.Patients with diarrhea were grouped and analyzed according to the presence of single bacterial infection,single viral infection,mixed infection,or Clostridioides difficile infection.Bacteroides had the highest absolute number and relative abundance in the gut microbiota in healthy people,whereas patients with infectious diar-rhea showed lower relative abundance of Bacteroides at each phylum/order/family/genus taxonomic level.Alpha diversity anal-ysis indicated no significant differences among groups.NMDS and PCoA indicated formation of distinct clusters in the control group compared with the different infectious diarrhea groups.The diversity of the gut microbiota was higher in the control group than the infectious diarrhea groups.Patients with infec-tious diarrhea caused by different pathogens showed differing predominant gut microbiota.Bifidobacterium predominated in the single viral infection group,Streptococcus predominated in the single bacterial infection group,and Lachnoclostridium predominated in the mixed infection group.Escherichia and Klebsiella were the major gut microbiota in the C.difficile infection group.Meanwhile,the dominant gut microbiota in the healthy population was Bacteroides.COG function prediction revealed that the healthy control group formed a distinct cluster from the different infection groups.The functions of defense mechanisms,cell wall synthesis,protein modification,cellular differentiation,and replication and recombination were signifi-cantly diminished in all infectious diarrhea groups.In general,patients with infectious diarrhea caused by different pathogens showed dysbiosis,with diminished gut microbiota diversity and the emergence of related biomarkers.Our findings indicated that Bacteroides has a key role in maintaining the homeostasis of the human intestinal environment,thus providing new ideas for the subsequent treatment of infectious diarrhea and research in other fields.

Objective To investigate the neurodevelopmental characteristics of children with autism spectrum disorder(ASD),analyze the correlation between neurodevelopmental indicators and cerebral blood flow(CBF),and explore the potential mechanisms of neurodevelopment in ASD children.Methods A retrospective study was conducted on 145 children aged 2-6 years with newly-diagnosed ASD.Scores from the Gesell Developmental Diagnosis Scale and the Autism Behavior Checklist(ABC)and CBF results were collected to compare gender differences in the development of children with ASD and analyze the correlation between CBF and neurodevelopmental indicators.Results Fine motor and personal-social development quotient in boys with ASD were lower than those in girls with ASD(P<0.05).Gross motor development quotient in ASD children was negatively correlated with CBF in the left frontal lobe(r=-0.200,P=0.016),right frontal lobe(r=-0.279,P=0.001),left parietal lobe(r=-0.208,P=0.012),and right parietal lobe(r=-0.187,P=0.025).The total ABC score was positively correlated with CBF in the left amygdala(r=0.295,P<0.001).Conclusions Early intervention training should pay attention to gender and developmental structural characteristics for precise intervention in ASD children.CBF has the potential to become a biological marker for assessing the severity of ASD.

Objective To compare the oral cleansing effects of the microbubble toothbrush and the conventional pulsed oral irrigator to provide references for users.Methods Ninety identical 3D-printed resin tooth models were grouped and subjected to repeated experiments,which were divided randomly into five groups including a microbubble toothbrush high-speed gear(GN-H)group,a microbubble toothbrush medium-speed gear(GN-M)group,a microbubble low-speed gear(GN-L)group,a conventional pulsed oral irrigator high-speed gear(W-H)group and a conventional pulsed oral irrigator low-speed gear(W-L)group,with 18 teeth in each group.The cleansing effects of the microbubble toothbrush and the conventional pulsed oral irrigator were evaluated in terms of irrigating strength and abilities for eliminating plaque and debris.Results Both the two types of water flossers were provided with high irrigating strength and effectively reduced plaque and debris on tooth surfaces,and the GN-H,GN-M and GN-L groups behaved better significantly than the remained groups.The order of the five groups was GN-H group＞GN-M group＞W-H group＞GN-L group＞W-L group for irrigating strength,GN-H group＞GN-M group＞GN-L group＞W-H group＞W-L group for plaque removal,GN-H group＞GN-M group＞W-H group＞GN-L group＞W-L group for debris removal,with all the differences being statistically significant(P＜0.05).Conclusion Both the two types of water flossers remove plaque and debris effectively,while the microbubble toothbrush gains advantages over the conventional pulsed oral irrigator.[Chinese Medical Equipment Journal,2024,45(9):67-72]

Objective To investigate the influence of different delivery techniques,treatment sites and dose-volume algorithms on the results of three-dimensional dosimetric verification for intensity-modulated radiation therapy(IMRT)plans and the importance of individualized quality assurance(QA)evaluation standard for radiotherapy plans.Methods Totally 350 tumor patients receiving radiotherapy at some hospital from January 2017 to February 2022 had their three-dimensional dosimetric verification results of IMRT plans selected retrospectively and underwent data collection with COMPASS system,and then were grouped in terms of delivery technique(fixed-beam IMRT and volumetric modulated arc therapy),treatment site(neck,chest and abdomen)and dose-volume algorithm(anisotropic analytical algorithm and collapsed cone convolution algorithm).All the groups were compared based on the 3％/2 mm criterion with regard to the Gamma pass rate of 10％prescription dose area(GP10％),Gamma pass rate(GP50％)and mean Gamma index(μGI5o％)of 50％prescription dose area,dose of 95％target volume(D95％)and its mean dose(Dmean),parotid gland mean dose(Dmean),dose of 1％spinal cord volume(D1％),dose of 1％brain stem volume(D1％)of head and neck radiotherapy plan,heart and lung mean dose(Dmean)and dose of 1％spinal cord volume(D1％)of chest radiotherapy plan and bladder,rectum and femur mean dose of abdomen radiotherapy plan(Dmean).SPSS 26.0 software was used for statistical analysis.Results For different delivery techniques,significant differences were found in all the QA results except GP50％of abdomen radiotherapy plan(P＜0.05).For different treatment sites,the differences were statistically significant between the QA results of head and neck radiotherapy plan and abdomen plan and between those of chest radio-therapy plan and abdomen radiotherapy plan(P＜0.05),while were not significant between the QA results of head and neck radiotherapy plan and chest radiotherapy plan(P＞0.05).For different dose-volume algorithms,the QA results had significant differences except D5％of abdomen radiotherapy planning target volume and Dmean and D1％of chest radiotherapy PTV(P＜0.05).Conclusion Dosimetric verification results vary depending on the delivery technique,treatment site and dose-volume algorithm.Statistical process control recommended by AAPM TG-218 report may be involved in to establish individualized QA standard for radiotherapy plans in case universal action limits are not appropriate.[Chinese Medical Equipment Journal,2024,45(11):54-59]

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.