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.

The academic literature on near-infrared brain functional imaging in the field of resuscitation medicine published in the Web of Science core collection,MEDLINE and PubMed databases from January 2006 to May 2025 were collected,which underwent statistical and visualized analyses with CiteSpace and VOSviewer software in terms of annual publication trends,authors,countries/regions,institutions,co-cited literature and keyword co-occurrence,clustering and emergence.It was pointed out that the overall number of publications in this research field had been on the rise in the past two decades.Stroke patients were the core research group in this field,and cortical activation mechanisms had always been the focus of research.Motor imagery was a high-frequency research content in this field,and multimodal technology integration was the trend of research in this field.New research ideas and methods were provided for relevent research in the field of rehabilitation medicine in China.

Objective:To evaluate the treatment outcome of liver transplantation for patients with polycystic liver disease (PLD).Methods:Clinical data of 28 PLD patients admitted to the Affiliated Hospital of Qingdao University from May 2014 to November 2023 were retrospectively analyzed, including 10 males and 18 females, aged (50.4±6.6) years. Patients were divided into liver transplantation group ( n=15) and non-liver transplantation group ( n=13). In the liver transplantation group, we analyzed seve-ral critical parameters including methods of liver transplantation, intra-abdominal fluid volume, intraoperative blood loss, intraoperative red blood cell transfusion requirements, and postoperative complications. The prognosis of the two groups were also compared. Results:Among the 28 patients with PLD, 15 underwent liver transplantation, including 11 classic in situ liver transplantations, one modified back-to-back liver transplantation, and three liver-kidney combined transplantations. The 15 patients had 2 000 (300, 4 000) ml of abdominal fluid, 1 000 (600, 2 000) ml of intraoperative blood loss, and 8.0 (6.0, 17.0) U of red blood cells transfused during the operation. Postoperative complications occurred in eight cases, with four of which were managemed successfully, and the other four died. The 1-, 5-, and 10-year survival rates of after liver transplantation were 80.0%, 80.0%, and 73.3%, respectively. The 1-, 5-, and 10-year survival rates of patients with PLD without liver transplantation were 69.2%, 46.2%, and 38.5%, respectively. The difference between the two groups was statistically significant ( χ2=3.91, P=0.048). Conclusion:Liver transplantation is a treatment option for patients with PLD, with a better long-term survival compared to patients without liver transplantation.

AIM To establish LC-MS and GC-MS method and analyze the chemical constituents of Dendrobium huoshanense C.Z.Tang & S.J.Cheng flowers.METHODS LC-MS was performed on a Zorbax Eclipse C18 column(2.1 mm×100 mm,1.8 μm),with the mobile phase comprising of water(containing 0.1％formic acid)-acetonitrile flowing at 0.3 mL/min,and electrospray ionization was operated in both positive and negative ion modes.The GC-MS employed headspace solid-phase microextraction for sample preparation,and the analysis was performed on an HP-5MS column(30 m×0.25 mm,0.25 μm),with the following temperature program:initial temperature 50 ℃(held for 2 min),increased at 5 ℃/min to 180 ℃(held for 5 min),then raised at 10 ℃/min to 250 ℃(held for 5 min),and electron impact ion source was employed.RESULTS A total of 62 compounds were identified by LC-MS,including 35 flavonoids,4 coumarins,6 alkaloids,6 terpenoids,3 amino acids,2 polyphenols,2 ketones and 4 others.A total of 101 volatile components were identified by GC-MS,including ketones,aldehydes,alcohols,esters,ethers,and acid.CONCLUSION This method can comprehensively analyze the chemical constituents of D.huoshanense flowers,and provide a scientific basis for elucidating its pharmacodynamic material basis.

Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans ; Consensus ; Dental Implants ; Mouth Mucosa/surgery* ; Keratins

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.

The academic literature on near-infrared brain functional imaging in the field of resuscitation medicine published in the Web of Science core collection,MEDLINE and PubMed databases from January 2006 to May 2025 were collected,which underwent statistical and visualized analyses with CiteSpace and VOSviewer software in terms of annual publication trends,authors,countries/regions,institutions,co-cited literature and keyword co-occurrence,clustering and emergence.It was pointed out that the overall number of publications in this research field had been on the rise in the past two decades.Stroke patients were the core research group in this field,and cortical activation mechanisms had always been the focus of research.Motor imagery was a high-frequency research content in this field,and multimodal technology integration was the trend of research in this field.New research ideas and methods were provided for relevent research in the field of rehabilitation medicine in China.

Objective:To evaluate the treatment outcome of liver transplantation for patients with polycystic liver disease (PLD).Methods:Clinical data of 28 PLD patients admitted to the Affiliated Hospital of Qingdao University from May 2014 to November 2023 were retrospectively analyzed, including 10 males and 18 females, aged (50.4±6.6) years. Patients were divided into liver transplantation group ( n=15) and non-liver transplantation group ( n=13). In the liver transplantation group, we analyzed seve-ral critical parameters including methods of liver transplantation, intra-abdominal fluid volume, intraoperative blood loss, intraoperative red blood cell transfusion requirements, and postoperative complications. The prognosis of the two groups were also compared. Results:Among the 28 patients with PLD, 15 underwent liver transplantation, including 11 classic in situ liver transplantations, one modified back-to-back liver transplantation, and three liver-kidney combined transplantations. The 15 patients had 2 000 (300, 4 000) ml of abdominal fluid, 1 000 (600, 2 000) ml of intraoperative blood loss, and 8.0 (6.0, 17.0) U of red blood cells transfused during the operation. Postoperative complications occurred in eight cases, with four of which were managemed successfully, and the other four died. The 1-, 5-, and 10-year survival rates of after liver transplantation were 80.0%, 80.0%, and 73.3%, respectively. The 1-, 5-, and 10-year survival rates of patients with PLD without liver transplantation were 69.2%, 46.2%, and 38.5%, respectively. The difference between the two groups was statistically significant ( χ2=3.91, P=0.048). Conclusion:Liver transplantation is a treatment option for patients with PLD, with a better long-term survival compared to patients without liver transplantation.

AIM To establish LC-MS and GC-MS method and analyze the chemical constituents of Dendrobium huoshanense C.Z.Tang & S.J.Cheng flowers.METHODS LC-MS was performed on a Zorbax Eclipse C18 column(2.1 mm×100 mm,1.8 μm),with the mobile phase comprising of water(containing 0.1％formic acid)-acetonitrile flowing at 0.3 mL/min,and electrospray ionization was operated in both positive and negative ion modes.The GC-MS employed headspace solid-phase microextraction for sample preparation,and the analysis was performed on an HP-5MS column(30 m×0.25 mm,0.25 μm),with the following temperature program:initial temperature 50 ℃(held for 2 min),increased at 5 ℃/min to 180 ℃(held for 5 min),then raised at 10 ℃/min to 250 ℃(held for 5 min),and electron impact ion source was employed.RESULTS A total of 62 compounds were identified by LC-MS,including 35 flavonoids,4 coumarins,6 alkaloids,6 terpenoids,3 amino acids,2 polyphenols,2 ketones and 4 others.A total of 101 volatile components were identified by GC-MS,including ketones,aldehydes,alcohols,esters,ethers,and acid.CONCLUSION This method can comprehensively analyze the chemical constituents of D.huoshanense flowers,and provide a scientific basis for elucidating its pharmacodynamic material basis.