OBJECTIVE To evaluate the anticoagulant efficacy and safety of nafamostat mesylate （NM） in the treatment of uremic patients at high risk of bleeding undergoing continuous veno-venous hemofiltration （CVVH） with different methods （pre- dilution and post-dilution）. METHODS A total of 130 uremic patients at high risk of bleeding who underwent CVVH treatment in the nephrology department of Chongqing University Three Gorges Hospital from July 2023 to September 2024 were selected. They were divided into pre-dilution group and post-dilution group according to the random number table method， with 65 cases in each group. Both groups of patients received CVVH treatment under NM anticoagulation. The pre-dilution group adopted the pre-dilution replacement method， while the post-dilution group adopted the post-dilution replacement method. The coagulation， pressure， and usage duration of the filter and dialysis circuit venous reservoirs were compared between the two groups. The changes in prothrombin time （PT）， prothrombin time-international normalized ratio （PT-INR）， activated partial thromboplastin time （APTT）， and fibrinogen （FIB） in the peripheral venous blood before the heparin pump and after the filter at 1， 4 and 7 h of CVVH treatment， as well as 20 min after the end of treatment， were compared between the two groups. The single-compartment urea clearance rate （spKt/V）， β2-microglobulin （β2-MG） clearance rate and the incidence of adverse reactions were duni2007@foxmail.com compared between the two groups. RESULTS Both the pre-dilution and post-dilution groups had 60 patients who completed the study. The incidence of grade Ⅱ-Ⅲ coagulation of the filter and venous reservoirs， as well as the number of patients with transmembrane and venous pressure alarm intervention in the post- dilution group were significantly higher or more than those in the pre-dilution group （P＜0.05）， while usage time of the filter and the pipeline in the post-dilution group was significantly shorter than that in the pre-dilution group （P＜0.05）. The APTT values before the heparin pump as well as PT and APTT values after the filter at 1 h， 4 h， and 7 h of CVVH treatment in the post-dilution group were significantly higher than those in the pre-dilution group （P＜0.001）. There were no significant differences in PT， PT- INR， APTT and FIB between the two groups of patients 20 min after the end of treatment （P＞0.05）. The spKt/v and β2-MG clearance rates in the post-dilution group were significantly higher than those in the pre-dilution group （P＜0.001）. There was no significant difference in the incidence of adverse reactions between the two groups （P＞0.05）. CONCLUSIONS When NM is used as an anticoagulant in the CVVH treatment of uremic patients at high risk of bleeding， compared with the pre-dilution treatment method， the post-dilution treatment method has a higher incidence of filter and dialysis tubing venous reservoir， a shorter usage time of the filter and pipeline， and a greater impact on extracorporeal coagulation， but has a higher solute clearance rate. Clinically， different dilution methods can be selected according to the different treatment needs of patients.

Bronchiolar adenoma (BA) is a rare type of lung tumor characterized by bilayered epithelial cells having a continuous basal layer and a luminal layer. It resembles mucinous adenocarcinoma (MA) on frozen section, with difficulty in distinguishing the basal layer. Immunohistochemistry is the best choice for verifying the diagnosis. This study aimed to comprehensively characterize three cases of BA-combined carcinoma using clinical, histopathological, and genetic features. BA and carcinoma sections were subjected to next-generation sequencing, respectively. It was hypothesized that while different mutation forms matched different regions, BA and lung adenocarcinoma shared the same gene mutation when they co-occurred in the same location. BA with extensive carcinoma is extremely rare and presents diagnostic challenges due to its overlap with conditions such as MA. Because of its distinctive morphological characteristics, BA may be regarded as a low-grade malignancy, particularly during a confusing evaluation. A multifaceted examination of clinical, radiological, immunohistochemical, and genetic data is necessary for an accurate diagnosis.

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 investigate the completion rate of tumor evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients in the national multicenter real-world database.Methods:The prospective real-world study was conducted. The clinicopathological data of 1 074 patients who underwent surgical treatment for mid and low rectal cancer in 47 national medical institutions, including Peking Union Medical College Hospital et al, from May 12,2023 to May 11,2024 were collected. Observation indicators: (1) clinical characteristics of patients with mid and low rectal cancer; (2) initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer; (3) initial imaging evaluation of patients with mid and low rectal cancer; (4) imaging evaluation after neoadjuvant therapy for patients with mid and low rectal cancer. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M( Q1, Q3). Count data were described as absoluter numbers and/or percentages. Results:(1) Clinical characteristics of patients with mid and low rectal cancer. Of the 1 074 patients, there were 713 males and 361 females, aged 63(56,70)years. The body mass index of 1 074 patients was 24(21,26)kg/m 2.For American Society of Anesthesiologists classification, there were 147 cases of stage Ⅰ, 641 cases of stage Ⅱ, 157 cases of stage Ⅲ, 2 cases of stage Ⅳ, and there were 127 cases missing data. (2) Initial colonoscopy and pathologic evaluation of tumors in patients with mid and low rectal cancer. Of the 1 074 patients, there were 787 cases (73.28%) undergoing complete colonoscopy, and there were only 197 cases (18.34%) undergoing immunohistochemical evaluation of all four mismatch repair proteins. (3) Initial imaging evaluation of patients with mid and low rectal cancer. Of the 1 074 patients, there were 842(78.40%) patients completing magnetic resonance imaging (MRI) or ultrasound evaluation, and there were 914(85.10%) patients completing chest, abdomen, and pelvis enhanced computed tomography (CT) evaluation. In the 149 patients completing rectal ultrasound evaluation, there were 122 cases (81.88%) comple-ting T staging evaluation, and there were 81 cases (54.36%) completing N staging evaluation. In the 808 patients completing rectal MRI evaluation, there were 708 cases (87.62%) completing T staging evaluation, and there were 590 cases (73.02%) completing N staging evaluation. (4) Imaging evalua-tion after neoadjuvant therapy for patients with mid and low rectal cancer. Of the 388 patients with neoadjuvant therapy, there were 332 patients (85.57%) completing MRI or ultrasound evaluation, and there were 327 patients (84.28%) completing chest, abdomen, and pelvis enhanced CT evalua-tion. In the 70 patients completing rectal ultrasound evaluation, there were 65 cases (92.86%) com-pleting T staging evaluation, and there were 49 cases (70.00%) completing N staging evaluation. In the 327 patients completing rectal MRI evaluation, there were 246 cases (75.23%) completing T staging, and there were 228 cases (69.72%) completing N staging evaluation. Conclusion:The com-pletion rate of tumor imaging evaluation at initial assessment and after neoadjuvant therapy for mid and low rectal cancer patients on a national scale is relatively good.

Methods:This study was a cross-sectional study. A prospective cohort study enrolled 42 patients with clinically suspected acute cerebrovascular disease and those undergoing follow-up examinations after intracranial vascular stenting at the First Affiliated Hospital of Zhengzhou University from June 2024 to May 2025. All patients underwent UHR PCD-CT examinations of the head and neck. Reconstructions were performed based on raw data, yielding conventional standard resolution (SR group) reconstructions and UHR images reconstructed using four distinct convolution kernels (Hv40, Hv48, Hv56, Hv64) in separate groups (Hv40 UHR group, Hv48 UHR group, Hv56 UHR group, Hv64 UHR group). Regions of interest were selected in the anterior cerebral artery, middle cerebral artery, posterior cerebral artery, posterior communicating artery, and anterior communicating artery. CT values and standard deviation (SD) values were measured for each artery, and signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Additionally, the sharpness of the vessel edges and the full-width-half-maximum (FWHM) of each artery were measured. One-way analysis of variance or the nonparametric Kruskal-Wallis test was used to compare the subjective and objective image quality metrics across the five groups. Pairwise comparisons were performed using the LSD test or Dunn method.Results:Statistically significant differences were observed in the overall comparison of vascular imaging SD, SNR, CNR, vascular edge sharpness, and FWHM among the SR group, Hv40 UHR group, Hv48 UHR group, Hv56 UHR group, and Hv64 UHR group ( P<0.05). No statistically significant differences in CT values were found ( P>0.05). Pairwise comparisons revealed statistically significant differences between all groups ( P<0.05), except that no significant differences were observed in image SD, SNR, CNR, vascular edge sharpness, or FWHM between the Hv56 UHR and Hv64 UHR groups ( P>0.05). Conclusions:UHR PCD-CT provides better image quality for neurovascular imaging. For the display of small intracranial vessels, the Hv64 provides sharper vessel walls and better subjective image quality compared to the less sharp convolutional cores.Objective:To explore the value of ultra-high resolution (UHR) photon-counting detector CT (PCD-CT) to improve the quality of neurovascular images.

Meniere's disease represents an idiopathic inner ear disorder characterized by endolymphatic hy-drops.Currently,the research methods for identifying genes associated with this disease mainly involve first-genera-tion sequencing and second-generation sequencing.This article reviews research on the genetic study of Meniere's disease,mainly summarizing the candidate genes with repeated pedigree validation in familial Meniere's disease,as well as those frequently reported in sporadic Meniere's disease.

AIM To compare the chemical constituents in traditional decoction and formula granule decoction of classical famous prescription Wendan Decoction.METHODS The HPLC fingerprints were established,after which the contents of adenosine,synephrine,liquiritin,naringin,hesperidin,6-gingerol and adenosine cyclophosphate were determined,cluster analysis,principal component analysis and multidimensional scaling analysis were adopted in the investigation of component differences,and the equivalent of formula granules was adjusted.RESULTS The similarities of HPLC fingerprints for 10 batches of traditional decoctions were higher than those of HPLC fingerprints for 9 batches of formula granule decoctions(P＜0.01).Adenosine,synephrine,liquiritin,hesperidin and cyclic adenosine monophosphate demonstrated higher contents in traditional decoctions than those in formula granule decoctions(P＜0.05),6-gingerol displayed lower content than that in the latter produced by manufacturers A,C(P＜0.05),which was higher than that in the latter produced by manufacturer B(P＜0.01).Various batches of traditional decoctions and formula granule decoctions could be obviously distinguished,adenosine,synephrine and hesperidin exhibited great influences on the classification of principal component analysis,and the quality of formula granule decoctions produced by manufacturer C was closer to that of traditional decoctions.After equivalent correction,the contents of various constituents in formula granule decoctions produced by manufacturers A,C showed no significant differences as compared with those in traditional decoction(P＞0.05).CONCLUSION The formula granules of Wendan Decoction from different manufacturers exist quality differences,so the preparation process and extraction process of this preparation should be optimized to improve quality,and equivalent ratio should be adjusted according to actual requirements to ensure its scientific and rational clinical application.

Objective To explore the relationship between community health follow-up management and the mental health of the long-term care insurance residents,and to provide a basis for the construction of an integrated community home care service mode for disabled elders.Methods The residents were selected through cluster sampling who participated in LTCI home care from Jan 1 to Dec 31,2021.After a year of participation,the subjects'mental health was assessed face-to-face by trained community doctors using the Self-Rating Anxiety Scale and the Self-Rating Depression Scale.By referring to residents'electronic health records combined with on-site questionnaire survey,community doctors collected the demographic information and health follow-up management provided by primary medical and health institutions.The multivariate logistic regression were conducted to evaluate the association between follow-up care and mental health outcomes.Results The study consisted of 399 LTCI-enrolled individuals,57.64%(n=230)received follow-up care by family physicians.The prevalence of anxiety and depression among participants was 19.80%(n=79)and 67.67%(n=270),respectively.Univariate analysis found that community health follow-up management could underscore the potential impact of follow-up care in mitigating anxiety(χ2=38.926,P<0.001)and depression(χ2=14.598,P<0.001)among LTCI enrollees.Multivariate analysis revealed that follow-up care was an independent protective factor against anxiety(adjusted OR=0.351,95%CI:0.176-0.701,P=0.003).However,follow-up care did not significantly impact depression prevalence.Additionally,LTCI grade and education level were also identified factors influencing the mental health of participants(P<0.05).Conclusion Community health service centers provide health follow-up management that plays a positive role in alleviating the anxiety symptoms of disabled residents under long-term care insurance home care.It is an effective way to improve the quality of LTCI home care services.

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 explore the relationship between community health follow-up management and the mental health of the long-term care insurance residents,and to provide a basis for the construction of an integrated community home care service mode for disabled elders.Methods The residents were selected through cluster sampling who participated in LTCI home care from Jan 1 to Dec 31,2021.After a year of participation,the subjects'mental health was assessed face-to-face by trained community doctors using the Self-Rating Anxiety Scale and the Self-Rating Depression Scale.By referring to residents'electronic health records combined with on-site questionnaire survey,community doctors collected the demographic information and health follow-up management provided by primary medical and health institutions.The multivariate logistic regression were conducted to evaluate the association between follow-up care and mental health outcomes.Results The study consisted of 399 LTCI-enrolled individuals,57.64%(n=230)received follow-up care by family physicians.The prevalence of anxiety and depression among participants was 19.80%(n=79)and 67.67%(n=270),respectively.Univariate analysis found that community health follow-up management could underscore the potential impact of follow-up care in mitigating anxiety(χ2=38.926,P<0.001)and depression(χ2=14.598,P<0.001)among LTCI enrollees.Multivariate analysis revealed that follow-up care was an independent protective factor against anxiety(adjusted OR=0.351,95%CI:0.176-0.701,P=0.003).However,follow-up care did not significantly impact depression prevalence.Additionally,LTCI grade and education level were also identified factors influencing the mental health of participants(P<0.05).Conclusion Community health service centers provide health follow-up management that plays a positive role in alleviating the anxiety symptoms of disabled residents under long-term care insurance home care.It is an effective way to improve the quality of LTCI home care services.