AIM: To compare the preoperative ocular biometry between Pentacam AXL and IOL Master 700 in cataract patients.METHODS:Prospective study. A total of 150 patients(150 eyes)with cataracts who were treated in our hospital from May to December 2024 were selected. The IOL Master 700 and Pentacam AXL were preoperatively used to measure axial length(AL), corneal curvature(K1, K2 and Km), anterior chamber depth(ACD), and white-to-white(WTW). The difference and consistency of the results of the two instruments were compared.RESULTS: There was no significant difference between the two instruments in the AL, K1, K2, Km, ACD, and WTW(all P>0.05). The Spearman correlation analysis showed that the two instruments positively correlated with the AL, K1, K2, Km, ACD and WTW of the operated eye(all P<0.001). The Bland-Altman analysis showed that for the Pentacam AXL and IOL Master 700, there were 5/150(3.3%), 7/150(4.7%), 4/150(2.7%), 5/150(3.3%), and 0 points outside the 95%LoA for the AL, K1, K2, Km, ACD, and WTW of the examined eyes, respectively, with all of these values less than 5%, indicating good consistency.CONCLUSION:The AL, K1, K2, Km, ACD and WTW of Pentacam AXL and IOL Master 700 in cataract patients before cataract phacoemulsification combined with IOL implantation show no significant differences, and have good correlation and consistency. The two instruments can be used interchangeably.

Sensorineural hearing loss (SNHL), the most commonly-occurring form of hearing loss, is caused mainly by injury to or the loss of hair cells and spiral ganglion neurons in the cochlea. Numerous environmental and physiological factors have been shown to cause acquired SNHL, such as ototoxic drugs, noise exposure, aging, infections, and diseases. Several programmed cell death (PCD) pathways have been reported to be involved in SNHL, especially some novel PCD pathways that have only recently been reported, such as ferroptosis, necroptosis, and pyroptosis. Here we summarize these PCD pathways and their roles and mechanisms in SNHL, aiming to provide new insights and potential therapeutic strategies for SNHL by targeting these PCD pathways.
Humans ; Hearing Loss, Sensorineural/metabolism* ; Necroptosis/drug effects* ; Pyroptosis/drug effects* ; Ferroptosis/drug effects* ; Animals

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:Near-infrared(NIR)spectroscopy technology faces the problem of insufficient model generalization due to individual differences in non-invasive blood glucose testing,in order to solve this problem,to improve data utilization,and to build predictive models with stronger generalization ability,this study introduces a transfer learning method to study the NIR spectroscopy non-invasive glucose testing.Methods:Migration learning is a machine learning technique that aims to improve task performance in the target domain by transferring knowledge from the source domain to the target domain.In this study,we used community population data as the source domain and student population data as the target domain to improve the performance of the noninvasive glucose detection model on the target domain.In order to verify the effectiveness of migration learning,this study compares the performance of the model before and after migration learning.Results:the model's performance on the noninvasive glucose detection task is significantly improved by the migration learning strategy,and the MAPE and MAE of the migrated model decreases by 52.5460％and 6.0805％,respectively,and the RMSE and MSE decreases by 10.7215％and 12.1135％.Conclusions:This study demonstrates the promising application of transfer learning in the field of non-invasive blood glucose detection,which is expected to realize portable and continuous blood glucose monitoring in the future by migrating the features that are difficult to access in the source domain but are related to blood glucose values to the target domain,which will greatly improve the quality of life of diabetic patients.Advances in noninvasive glucose testing technology will not only reduce patients' pain,but also provide a more convenient means of glucose monitoring,which will provide strong support for diabetes management.

This study analyzed the epidemiological characteristics of imported malaria in Yunnan Province from 2020 to 2023,to provide scientific evidence for formulating measures to decrease imported malaria and prevent re-establishment of malaria transmission.Malaria data reported by the China Disease Prevention and Control Information System were analyzed to determine parasite species;sources of infection;temporal,spatial,and population distributions;and importation routes.A total of 828 malaria cases were reported in the province.Plasmodium vivax and Plasmodium falciparum accounted for 89.98％and 8.33％of cases,respectively.A total of 47.58％of cases were imported from Myanmar,and all P.falciparum malaria ca-ses were from Africa.Thirteen(81.25％)prefectures or municipalities reported malaria,among which Dehong,Baoshan,Kunming,and Lincang reported 94.32％of cases.A total of 52.54％of cases were in young men.The proportion of cross-bor-der personnel flow,land input,and aircraft input were 88.89％and 11.11％respectively.A total of 98.19％of patients sought medical care within 7 days after fever onset,and 82.85％initiated diagnosis for malaria,and 84.90％of diagnoses were con-firmed by health facilities at or below the county level.Imported malaria is a major challenge in preventing re-establishment of transmission in Yunnan.Most imported cases involved cross-border malaria transmission of mainly Plasmodium vivax between China and Myanmar.To achieve malaria elimination,vigilance of health staff in malaria diagnosis and treatment should be pro-moted,and intensive malaria health education should be provided to people traveling to malaria endemic territories,to enable individual protection,and timely diagnosis and treatment after return from endemic countries.

This study analyzed the epidemiological characteristics of imported malaria in Yunnan Province from 2020 to 2023,to provide scientific evidence for formulating measures to decrease imported malaria and prevent re-establishment of malaria transmission.Malaria data reported by the China Disease Prevention and Control Information System were analyzed to determine parasite species;sources of infection;temporal,spatial,and population distributions;and importation routes.A total of 828 malaria cases were reported in the province.Plasmodium vivax and Plasmodium falciparum accounted for 89.98％and 8.33％of cases,respectively.A total of 47.58％of cases were imported from Myanmar,and all P.falciparum malaria ca-ses were from Africa.Thirteen(81.25％)prefectures or municipalities reported malaria,among which Dehong,Baoshan,Kunming,and Lincang reported 94.32％of cases.A total of 52.54％of cases were in young men.The proportion of cross-bor-der personnel flow,land input,and aircraft input were 88.89％and 11.11％respectively.A total of 98.19％of patients sought medical care within 7 days after fever onset,and 82.85％initiated diagnosis for malaria,and 84.90％of diagnoses were con-firmed by health facilities at or below the county level.Imported malaria is a major challenge in preventing re-establishment of transmission in Yunnan.Most imported cases involved cross-border malaria transmission of mainly Plasmodium vivax between China and Myanmar.To achieve malaria elimination,vigilance of health staff in malaria diagnosis and treatment should be pro-moted,and intensive malaria health education should be provided to people traveling to malaria endemic territories,to enable individual protection,and timely diagnosis and treatment after return from endemic countries.

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 construct a nursing norm for extracorporeal membrane oxygenation in adults, so as to provide a reference for improving the nursing care of adult extracorporeal membrane oxygenation.Methods:The first draft was developed through literature search and expert discussion. From September to October 2023, 16 experts were selected using the Delphi method to conduct two rounds of expert consultation on the first draft, and the final draft was revised with reference to the experts' comments. The expert positivity coefficient was expressed as the effective recovery rate of the questionnaire, and the degree of expert authority was evaluated with the authority coefficient, and the degree of harmonization of expert opinions was assessed with the Kendall's harmony coefficient.Results:Literature search screened a total of four guidelines and five expert consensus. In the two rounds of consultation, the effective recovery rates of the questionnaires were all 100% (16/16), and the expert authority coefficients were all 0.900, and the Kendall's harmony coefficients of the overall indicators were 0.581 and 0.666, respectively (both P<0.01). The final constructed nursing norm for extracorporeal membrane oxygenation in adults included five primary indicators, 27 secondary indicators, and 17 tertiary indicators. Conclusions:The constructed nursing norm for extracorporeal membrane oxygenation in adults is scientific, reliable and feasible, and can guide clinical nursing staff to carry out nursing care for extracorporeal membrane oxygenation.

OBJECTIVE To explore the optimal parameters of simmered Rhei Radix et Rhizoma and the correlation between the chroma values and the intrinsic composition of simmered Rhei Radix et Rhizoma decoction pieces powder.METHODS The single-factor-response surface method was used to investigate the simmering temperature,simmering time,paper dosage and plant ash dos-age,the response surface experiment was carried out on the basis of the single factor experiment,the appearance traits,total anthraqui-nones,free anthraquinones,leachables,sennoside A and B contents were taken as indicators,the analytic hierarchy process(AHP)was used to give weights to each index,and the process was optimized.The chroma values of raw and simmered products were deter-mined by electronic eye,the correlation and regression analysis were carried out by SPSS22.0 software,and the chroma-component re-gression equation was constructed.RESULTS The optimal process of simmering Rhei Radix et Rhizoma was 140 ℃,5 times of plant ash,2 layers of wet paper wrapped and being simmered for 2.5 h.CONCLUSION The simmering process of Rhei Radix et Rhizoma optimized by AHP combined with response surface method is reasonable and feasible,the color of decoction pieces has a significant correlation with the component content,and the regression equation constructed is reliable,which can predict the intrinsic component content of decoction pieces through chroma values.

Objective:To improve the understanding of acute lymphoblastic leukemia (ALL) secondary to Burkitt lymphoma (BL) in children.Methods:The clinical data of a child with ALL secondary to BL who was admitted to Children's Hospital Affiliated to Zhengzhou University in June 2024 were retrospectively analyzed, and the relevant literature was reviewed.Results:The patient was a boy with the age of 8 years and 8 months. He presented with a neck mass at the age of 4 years and 6 months, and pathological examination revealed a diagnosis of BL with clinical stage Ⅲ. The patient was given regular chemotherapy according to the Chinese Children's Lymphoma Group non-Hodgkin lymphoma mature B-cell 2017 protocol-B2 regimen. PET-CT showed recurrence of lymphoma in 6 months after the suspension of treatment. The patient was given with placement of 125I particles, oral etoposide and dexamethasone, and traditional Chinese medicine. The patient was admitted to hospital at the age of 8 years and 8 months with fever and skin hemorrhagic spots, bone marrow morphology, immunology, cytogenetics and molecular biology typing indicated a diagnosis of B-ALL with TCF3::PBX1 fusion gene. The patient received induction chemotherapy according to the Chinese Children's Leukemia Group-ALL 2018 protocol. A review of bone marrow cytology achieved complete remission on the 33rd day of chemotherapy, and minimal residual disease detected by flow cytometry indicated less than 0.01%. TCF3::PBX1 fusion gene was negative. Conclusions:ALL secondary to BL in children is rare, and the ALL treatment regimens are effective.