OBJECTIVE: To observe the clinical efficacy and safety of automatic pressure-controlled pressure cupping in patients with lumbar disc herniation, and compare it with traditional cupping. METHODS: A total of 100 patients diagnosed with lumbar disc herniation from January 2022 to August 2024 were selected and divided into two groups:the automatic pressure-controlled pressure cupping group (controlled pressure cupping group) and the traditional cupping group (control group), 50 cases in each group. In the controlled pressure cupping group, there were 18 males and 32 females, with an age of (51.98±12.69) years;in the control group, there were 16 males and 34 females, with an age of (51.32±12.05) years. The visual analogue scale(VAS), comfort score, and lumbar range of motion were observed before treatment and after the 1st, 3rd, and 7th treatments to evaluate the efficacy and safety. RESULTS: All patients completed the treatment intervention, with complete follow-up data collected. No adverse reactions or complications occurred during treatment and follow-up. After the 3rd treatment, the VAS score of the controlled pressure cupping group was (2.38±0.49), which was lower than that of the control group (2.94±0.68), with a statistically significant difference (P<0.001). In the controlled pressure cupping group, the VAS scores after the 1st, 3rd, and 7th treatments were significantly better than those before treatment (P=0.026);in the control group, the VAS scores after the 3rd and 7th treatments were better than those before treatment, but the difference was not statistically significant(P=0.182). Repeated-measures analysis of variance (ANOVA) on VAS scores at different time points in both groups showed that there were statistically significant differences in inter-group, time, and interaction effects (P<0.05). After the 1st treatment, in the controlled pressure cupping group, 0 patients felt comfortable, 42 patients (84%) felt mild discomfort, and 8 patients (16%) felt moderate discomfort;in the control group, 0 patients felt comfortable, 28 patients (56%) felt mild discomfort, and 22 patients(44%) felt moderate discomfort;the difference between the two groups was statistically significant(P=0.005). After the 3rd treatment, in the controlled pressure cupping group, 30 patients(60%) felt comfortable, 20 patients (40%) felt mild discomfort, and 0 patients felt moderate discomfort; in the control group, 9 patients (18%) felt comfortable, 41 patients (82%) felt mild discomfort, and 0 patients felt moderate discomfort;the difference between the two groups was statistically significant(P<0.001). There was no statistically significant difference in comfort between the two groups after the 7th treatment(P>0.001). There was no statistically significant difference in lumbar range of motion between the two groups before and after treatment(P>0.05);compared with before treatment, the lumbar range of motion of both groups after treatment was significantly improved, with statistically significant differences (P<0.001). CONCLUSION Automatic pressure-controlled pressure cupping can effectively relieve symptoms in patients with lumbar disc herniation, with excellent safety.
Humans ; Female ; Male ; Intervertebral Disc Displacement/physiopathology* ; Middle Aged ; Adult ; Lumbar Vertebrae/physiopathology* ; Cupping Therapy/methods* ; Pressure ; Aged ; Treatment Outcome

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.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

The lab module of exploratory experiment is newly designed in the practical course of bio-chemistry.Here we describe one of the experimental projects,and it originates from new scientific re-search results on the dynamic structure of ATP synthase.This exploratory experiment is organized in the form of real scientific research,which would fully mobilize the initiative and creativity of students in learning theoretical knowledge and experimental technology.Students work in groups and start with refer-ence reading.Through cooperation,they must develop certain experimental plan,handle samples with photocrosslinking technique and utilize the high-throughput electrophoresis method to analyze the dynamic structural change of ε subunit in ATP synthase under different physiological conditions.High quality re-sults from high-throughput electrophoresis can only be obtained through optimized operation and treat-ment,from which students would experience the process of technological innovation.The teaching process of this lab module embodies the student-centered teaching concept and is widely approved and supported by students.The project of ATP synthase closely combines the content of lab course with cut-ting-edge technology.Students can deeply experience the importance of experimental technology innova-tion in solving scientific problems.The practical ability of students would be comprehensively improved through this lab module.

The β-barrel outer membrane protein is a kind of membrane integration protein widely existing in the outer membranes of Gram-negative bacteria,mitochondria and chloroplasts.The biogenesis of β-barrel outer membrane proteins in living bacterial cells is an extremely complex process,including the synthesis of nascent polypeptide chains in the cytoplasm,the translocation across the inner membrane,the transportation through the hydrophilic periplasmic space and finally the folding,assembly and inser-tion to the outer membrane to complete the whole process.During the biogenesis of β-barrel outer mem-brane proteins,it is critical to unveil how the periplasmic quality control factors such as SurA,Skp and DegP assist the folding and transportation of the nascent β-barrel outer membrane proteins through the hy-drophilic periplasmic space,and how the SecYEG-SecDF-Yidc complex on the inner membrane and the BAM complex on the outer membrane act during the biogenesis of β-barrel outer membrane proteins.This review delves into the research progress of the mechanism of β-barrel outer membrane protein biogenesis in Gram-negative bacteria and also the application of various new technologies such as in vivo protein pho-to-crosslinking analysis and high through-put protein electrophoresis(SDS-PAGE)for exploring such dy-namic cellular processes as protein biogenesis.

Purpose To investigate the clinical,imaging,and pathological features of Kikuchi-Fujimoto disease(KFD).Methods A retrospective analysis was conducted on 123 pathologically confirmed KFD cases.Clinical and imaging data were collected,and histopathological features were evaluated using HE staining,immunohistochemistry,in situ hybridization for EBER,and molecular analyses(TCR/Ig gene rearrangements by PCR with capillary electro-phoresis).Results Among the 123 patients,the male-to-female ratio was 1∶2,with a median age of 30 years.All patients presented with lymphadenopathy.Among 30 hospitalized patients,63.3％(19/30)had fever,and 23.3％(7/30)had concurrent autoimmune diseases.Of the 12 patients who underwent PET-CT,91.7％(11/12)were sus-pected of malignancy,prompting biopsy recommendations.Among 47 consultation cases,27.7％(13/47)were ini-tially misdiagnosed as lymphoma.Histopathological examination revealed proliferative,necrotic,and xanthomatous phases,which coexisted or occurred independently.The proliferative phase was characterized by atypical lymphocytes and histiocytes,the necrotic phase by abundant eosinophilic fibrin deposits and nuclear debris,and the xanthomatous phase by clusters of foam-like histiocytes.Immunohistochemically analyses revealed that atypical lymphocytes were neg-ative for CD20,CD4,and CD56 but positive for CD3,CD8,TIA1,Granzyme B,and Perforin.Histiocytes expressed CD68,CD163,and MPO,while CD123-positive plasmacytoid dendritic cells were predominantly located around the le-sions and blood vessels.EBER was positive in individual cells in 4 cases.TCR gene rearrangement was positive in 2 cases and suspected positive in 3 cases,while Ig rearrangement was positive and suspected positive in 1 case each.Conclusion KFD exhibits clinical,imaging,and pathological features that can mimic lymphoma,highlighting the im-portance of accurate diagnosis to avoid misdiagnosis and inappropriate treatment.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Purpose To investigate the clinical,imaging,and pathological features of Kikuchi-Fujimoto disease(KFD).Methods A retrospective analysis was conducted on 123 pathologically confirmed KFD cases.Clinical and imaging data were collected,and histopathological features were evaluated using HE staining,immunohistochemistry,in situ hybridization for EBER,and molecular analyses(TCR/Ig gene rearrangements by PCR with capillary electro-phoresis).Results Among the 123 patients,the male-to-female ratio was 1∶2,with a median age of 30 years.All patients presented with lymphadenopathy.Among 30 hospitalized patients,63.3％(19/30)had fever,and 23.3％(7/30)had concurrent autoimmune diseases.Of the 12 patients who underwent PET-CT,91.7％(11/12)were sus-pected of malignancy,prompting biopsy recommendations.Among 47 consultation cases,27.7％(13/47)were ini-tially misdiagnosed as lymphoma.Histopathological examination revealed proliferative,necrotic,and xanthomatous phases,which coexisted or occurred independently.The proliferative phase was characterized by atypical lymphocytes and histiocytes,the necrotic phase by abundant eosinophilic fibrin deposits and nuclear debris,and the xanthomatous phase by clusters of foam-like histiocytes.Immunohistochemically analyses revealed that atypical lymphocytes were neg-ative for CD20,CD4,and CD56 but positive for CD3,CD8,TIA1,Granzyme B,and Perforin.Histiocytes expressed CD68,CD163,and MPO,while CD123-positive plasmacytoid dendritic cells were predominantly located around the le-sions and blood vessels.EBER was positive in individual cells in 4 cases.TCR gene rearrangement was positive in 2 cases and suspected positive in 3 cases,while Ig rearrangement was positive and suspected positive in 1 case each.Conclusion KFD exhibits clinical,imaging,and pathological features that can mimic lymphoma,highlighting the im-portance of accurate diagnosis to avoid misdiagnosis and inappropriate treatment.

The lab module of exploratory experiment is newly designed in the practical course of bio-chemistry.Here we describe one of the experimental projects,and it originates from new scientific re-search results on the dynamic structure of ATP synthase.This exploratory experiment is organized in the form of real scientific research,which would fully mobilize the initiative and creativity of students in learning theoretical knowledge and experimental technology.Students work in groups and start with refer-ence reading.Through cooperation,they must develop certain experimental plan,handle samples with photocrosslinking technique and utilize the high-throughput electrophoresis method to analyze the dynamic structural change of ε subunit in ATP synthase under different physiological conditions.High quality re-sults from high-throughput electrophoresis can only be obtained through optimized operation and treat-ment,from which students would experience the process of technological innovation.The teaching process of this lab module embodies the student-centered teaching concept and is widely approved and supported by students.The project of ATP synthase closely combines the content of lab course with cut-ting-edge technology.Students can deeply experience the importance of experimental technology innova-tion in solving scientific problems.The practical ability of students would be comprehensively improved through this lab module.

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.