This study explores the basic characteristics and potential functions of the terpene synthase(TPS) gene family members in Lonicera japonica. The L. japonica TPS(LjTPS) gene family was identified and functionally analyzed using bioinformatics methods. The results showed that a total of 70 members of the LjTPS gene family were identified in L. japonica, with protein lengths ranging from 130 to 1 437 amino acids. Most of these proteins were hydrophilic, and they were unevenly distributed across nine chromosomes. Phylogenetic analysis showed that the LjTPS gene family members were divided into six subfamilies, mainly consisting of members from the TPS-a, TPS-b, and TPS-e subfamilies. Promoter cis-acting element analysis showed that LjTPS members contained a large number of stress-responsive cis-acting elements. Aphid inoculation experiments showed that key enzyme genes in the MVA pathway for terpenoid backbone synthesis in L. japonica, such as HMGS, HMGR, MK, MPD, and the key enzyme gene in the DXP pathway, DXS, exhibited an initial increase followed by a decrease under aphid stress. The qRT-PCR analysis showed that the expression levels of the α-farnesene synthase genes LjTPS34 and LjTPS39 were down-regulated, while the expression levels of(E)-β-caryophyllene synthase genes LjTPS15 and LjTPS17 were up-regulated 12 h before aphid feeding, then began to decline. Farnesyl pyrophosphate synthase(FPS), which interacted with these genes, also displayed a pattern of increasing followed by decreasing expression. The expression of linalool synthase genes LjTPS12 and LjTPS33 was significantly up-regulated after 72 h of aphid feeding(P<0.000 1), reaching 24.39 and 22.64 times the initial expression, respectively. This pattern was in close alignment with the trend of linalool content in L. japonica. This study provides a theoretical foundation for future research on the interaction between L. japonica and pests, as well as on the functional roles of the LjTPS gene family.
Animals ; Aphids/physiology* ; Alkyl and Aryl Transferases/chemistry* ; Lonicera/parasitology* ; Phylogeny ; Plant Proteins/chemistry* ; Gene Expression Regulation, Plant ; Multigene Family ; Terpenes/metabolism*

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 develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To evaluate the clinical outcomes of robot-assisted percutaneous vertebroplasty(PVP)versus manual PVP in treating osteoporotic vertebral compression fractures(OVCF),and explore the advantages of robotic assistance for clinical decision-making.Methods Patients who underwent single-level PVP for OVCF at the Department of Joint Surgery and Bone Tumor,Beijing Shijitan Hospital,Capital Medical University,between April 2021 and April 2025 were enrolled.The robot group(n=29)and manual PVP group(control,n=88)were followed-up for 1 month.Parameters compared included:total hospital stay,operative time,cement volume,cement leakage rate,nerve injury rate,intraoperative fluoroscopy number,first-attempt success rate of puncture,postoperative versus preoperative anterior vertebral height difference,Visual Analogue Scale(VAS)and Oswestry Disability Index(ODI)scores preoperatively,at 1-day and 1-month postoperatively.Results No statistically significant differences existed in baseline characteristics(gender,age,fracture-to-surgery interval,and fracture distribution)between groups(P>0.05).The number of intraoperative fluoroscopy times and the ODI index on the first day after surgery in the robot group were significantly lower than those in the control group(P<0.05),and the first-attempt success rate of puncture was significantly higher than that in the control group(P<0.05).There were no statistically significant differences in the other parameters between the two groups(P>0.05).Conclusion Both robot-assisted PVP and manual PVP have good clinical efficacy in the treatment of OVCF.Robot-assisted PVP can reduce the number of intraoperative fluoroscopy times and may have more advantages in improving the first-attempt success rate of puncture and early postoperative lumbar function.However,its reliability needs to be further verified through large-sample randomized controlled studies with multivariate analysis.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Objective:To investigate the effects of surgical timing on incidence of perioperative complications and postoperative 30-day mortality in elderly patients with hip fracture.Methods:The data were retrospectively analyzed of the 450 elderly patients with hip fracture who had been admitted to Department of Joint Surgery, Beijing Shijitan Hospital, Capital Medical University from January 2016 to December 2021. The patients were divided into 2 groups according to the time from admission to surgery. In the early surgery group of 143 cases [41 males and 102 females with an age of 82(75, 86) years], the time from admission to surgery was ≤ 48 hours. In the delayed surgery group of 307 cases [88 males and 219 females with an age of 83(77, 87) years], the time from admission to surgery was over 48 hours. The 2 groups were compared in terms of comorbidities, perioperative complications, death events within postoperative 30 days, ICU transfer rate and total length of hospital stay.Results:There was no significant difference in the preoperative general data like age and gender between the 2 groups, indicating comparability ( P>0.05). The proportions of patients with coronary atherosclerotic heart disease [30.0%(92/307)], a stroke history [19.9%(61/307)], abnormal heart function [55.4%(170/307)] and abnormal kidney function [24.4%(75/307)] in the delayed surgery group were significantly higher than those in the early surgery group [18.2%(26/143), 10.5% (15/143), 39.2%(56/143), and 12.6%(18/143)] ( P<0.05). The proportions of perioperative pulmonary infection [22.5% (69/307)] and urinary infection [21.2%(65/307)] in the delayed operation group were significantly higher than those in the early operation group [11.9%(17/143) and 11.2%(16/143)] ( P<0.05). The total hospital stay in the delayed operation group [18(14, 22) d] was significantly longer than that in the early operation group [14(10, 17) d] ( P<0.05). There was no significant difference in ICU transfer rate or postoperative 30-day mortality between the 2 groups ( P>0.05). Conclusion:For elderly patients with hip fracture, delayed surgery may increase the incidence of pulmonary infection and urinary infection, and extend their total hospital stay, but have no effect on the postoperative 30-day mortality.

Objective To evaluate the clinical outcomes of robot-assisted percutaneous vertebroplasty(PVP)versus manual PVP in treating osteoporotic vertebral compression fractures(OVCF),and explore the advantages of robotic assistance for clinical decision-making.Methods Patients who underwent single-level PVP for OVCF at the Department of Joint Surgery and Bone Tumor,Beijing Shijitan Hospital,Capital Medical University,between April 2021 and April 2025 were enrolled.The robot group(n=29)and manual PVP group(control,n=88)were followed-up for 1 month.Parameters compared included:total hospital stay,operative time,cement volume,cement leakage rate,nerve injury rate,intraoperative fluoroscopy number,first-attempt success rate of puncture,postoperative versus preoperative anterior vertebral height difference,Visual Analogue Scale(VAS)and Oswestry Disability Index(ODI)scores preoperatively,at 1-day and 1-month postoperatively.Results No statistically significant differences existed in baseline characteristics(gender,age,fracture-to-surgery interval,and fracture distribution)between groups(P>0.05).The number of intraoperative fluoroscopy times and the ODI index on the first day after surgery in the robot group were significantly lower than those in the control group(P<0.05),and the first-attempt success rate of puncture was significantly higher than that in the control group(P<0.05).There were no statistically significant differences in the other parameters between the two groups(P>0.05).Conclusion Both robot-assisted PVP and manual PVP have good clinical efficacy in the treatment of OVCF.Robot-assisted PVP can reduce the number of intraoperative fluoroscopy times and may have more advantages in improving the first-attempt success rate of puncture and early postoperative lumbar function.However,its reliability needs to be further verified through large-sample randomized controlled studies with multivariate analysis.

Objective To evaluate the effectiveness of CT angiography(CTA)imaging and fluoroscopic fusion navigation techniques in left atrial appendage closure(LAAC).Methods A total of 82 patients underwent LAAC in this prospective study and were matched(1:1)according to whether they underwent image fusion or not.The fusion group(41 cases)consisted of patients who received LAAC with the support of CTA and X-ray fluoroscopy fusion technology;The non fusion group(41 cases)consisted of patients who underwent surgery using traditional surgical methods without the support of this technology.Record the intraoperative indicators,perioperative complications,and postoperative follow-up outcomes of both groups.Results The surgical time in the fusion group was significantly shorter than that in the non fusion group[(50.23±25.23)min vs.(65.71±29.15)min,P=0.012],The difference is statistically significant.Compared with the non fusion group,the fusion group significantly reduced the total radiation dose[(195.15±205.59)mGy vs.(351.08±196.54)mGy],dose area product[(22.47±20.05)Gy·cm2vs.(38.12±19.38)Gy·cm2],and X-ray fluoroscopy time[(9.03±3.58)min vs.(13.35±4.23)min].Correspondingly to the radiation dose,the amount of contrast agent used in the fusion group was also relatively reduced[(59.32±24.65)ml vs.(93.12±35.08)ml],and the differences were statistically significant(all P＜0.001).There was a significant difference in the rate of repeated interval puncture(2.44％vs.12.20％,P=0.090),but the difference was not statistically significant.Occluder implantation success rates were identical(100.00％vs.100.00％).No statistically significant differences in procedural complications were observed between the groups.Conclusions Three-dimensional CTA and fluoroscopic fusion navigation techniques are not only feasible and safe but also enhance the efficiency of LAAC procedures.

Objective To evaluate the effectiveness of CT angiography(CTA)imaging and fluoroscopic fusion navigation techniques in left atrial appendage closure(LAAC).Methods A total of 82 patients underwent LAAC in this prospective study and were matched(1:1)according to whether they underwent image fusion or not.The fusion group(41 cases)consisted of patients who received LAAC with the support of CTA and X-ray fluoroscopy fusion technology;The non fusion group(41 cases)consisted of patients who underwent surgery using traditional surgical methods without the support of this technology.Record the intraoperative indicators,perioperative complications,and postoperative follow-up outcomes of both groups.Results The surgical time in the fusion group was significantly shorter than that in the non fusion group[(50.23±25.23)min vs.(65.71±29.15)min,P=0.012],The difference is statistically significant.Compared with the non fusion group,the fusion group significantly reduced the total radiation dose[(195.15±205.59)mGy vs.(351.08±196.54)mGy],dose area product[(22.47±20.05)Gy·cm2vs.(38.12±19.38)Gy·cm2],and X-ray fluoroscopy time[(9.03±3.58)min vs.(13.35±4.23)min].Correspondingly to the radiation dose,the amount of contrast agent used in the fusion group was also relatively reduced[(59.32±24.65)ml vs.(93.12±35.08)ml],and the differences were statistically significant(all P＜0.001).There was a significant difference in the rate of repeated interval puncture(2.44％vs.12.20％,P=0.090),but the difference was not statistically significant.Occluder implantation success rates were identical(100.00％vs.100.00％).No statistically significant differences in procedural complications were observed between the groups.Conclusions Three-dimensional CTA and fluoroscopic fusion navigation techniques are not only feasible and safe but also enhance the efficiency of LAAC procedures.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.