Natural human leukocyte antigen (HLA) antibodies refer to preformed antibodies present in the body that are not induced by prior exposure to allogeneic HLA antigens. In healthy individuals without a sensitization history, the detection rate of natural HLA antibodies is approximately 20%-29% when using screening assays with low sensitivity, and can reach up to 63% when more sensitive HLA-specific detection methods are employed. It is therefore inferred that natural HLA antibodies may also be present in transplant candidates with a similar prevalence. This review comprehensively discusses the potential mechanisms of natural HLA antibody generation, the characteristics of the recognized epitopes, detection techniques, clinical relevance in transplantation, their potential to confound therapeutic decisions, and approaches to distinguish and mitigate their impact. The goal is to raise clinician awareness of the objective existence of natural HLA antibodies, provide guidance on evaluating their association with allograft rejection, and inform appropriate clinical management strategies when encountering natural HLA antibody-positive transplant candidates.

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 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.

Natural human leukocyte antigen (HLA) antibodies refer to preformed antibodies present in the body that are not induced by prior exposure to allogeneic HLA antigens. In healthy individuals without a sensitization history, the detection rate of natural HLA antibodies is approximately 20%-29% when using screening assays with low sensitivity, and can reach up to 63% when more sensitive HLA-specific detection methods are employed. It is therefore inferred that natural HLA antibodies may also be present in transplant candidates with a similar prevalence. This review comprehensively discusses the potential mechanisms of natural HLA antibody generation, the characteristics of the recognized epitopes, detection techniques, clinical relevance in transplantation, their potential to confound therapeutic decisions, and approaches to distinguish and mitigate their impact. The goal is to raise clinician awareness of the objective existence of natural HLA antibodies, provide guidance on evaluating their association with allograft rejection, and inform appropriate clinical management strategies when encountering natural HLA antibody-positive transplant candidates.

Objective To investigate the association between the serum creatinine/cystatin C ratio(SCr/Cys C)as a Sarcopenia index(SI)and the incidence of in-hospital adverse events in patients with acute myocardial infarction(AMI)undergoing emergency percutaneous coronary intervention(PCI).Additionally,we evaluate the predictive efficacy of the SI in predicting major adverse cardiovascular events(MACEs)during hospitalization.Methods A total of 306 patients with AMI who underwent emergency PCI in the 904th Hospital of PLA Joint Logistics Support Force from January 2020 to March 2023 were consecutively included in this retrospective analysis.Patients were divided into two groups based on the occurrence of MACEs during hospitalization:MACEs group(n=43)and non-MACEs group(n=263).Clinical characteristics and pre-PCI laboratory test results were collected.Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for MACEs.The predictive performance of SI was assessed using receiver operating characteristic(ROC)curve analysis.Results The incidence of in-hospital MACEs in AMI patients was 14.1%.The results of the independent samples t-test showed that the SI level in MACEs group was significantly lower than that in non-MACEs group,with a statistically significant difference(P<0.001).The results of the multivariate logistic regression analysis suggested that new-onset atrial fibrillation,Killip class 2-4,SI,and TG were independent risk factors for in-hospital adverse events after emergency PCI.The ROC curve results showed that the predictive value of SI(AUC=0.741,95%CI 0.666-0.816)using the SCr/Cys C ratio was superior to that of single Cys C(AUC=0.658,95%CI 0.570-0.746)for predicting post-PCI MACEs,with a statistically significant difference(P<0.05),and the optimal cutoff value for SI was 78.14.After stratifying SI based on the cutoff value,the results of the independent samples t-test showed that compared to the higher SI group,the lower SI group had a higher occurrence of specific adverse events such as heart failure(P<0.001),malignant arrhythmias(P=0.009),and strokes(P=0.003),with statistically significant differences.Conclusions The results highlight SI as an independent risk factor for MACEs during hospitalization after emergency PCI in AMI patients.Furthermore,SI has proven to be an effective prognostic index for patient outcomes.

Atrial Fibrillation ; Catheter Ablation ; Esophageal Diseases ; Esophageal Perforation/etiology* ; Humans ; Treatment Outcome ; Ulcer

In the central nervous system, hyperpolarization-activated cyclic nucleotide-gated (HCN) channels are essential to maintain normal neuronal function. Recent studies have shown that HCN channels may be involved in the pathological process of ischemic brain injury, but the mechanisms remain unclear. Autophagy is activated in cerebral ischemia, but its role in cell death/survival remains controversial. In this study, our results showed that the HCN channel blocker ZD7288 remarkably decreased the percentage of apoptotic neurons and corrected the excessive autophagy induced by oxygen-glucose deprivation followed by reperfusion (OGD/R) in hippocampal HT22 neurons. Furthermore, in the OGD/R group, p-mTOR, p-ULK1 (Ser), and p62 were significantly decreased, while p-ULK1 (Ser), atg5, and beclin1 were remarkably increased. ZD7288 did not change the expression of p-ULK1 (Ser), ULK1 (Ser), p62, Beclin1, and atg5, which are involved in regulating autophagosome formation. Besides, we found that OGD/R induced a significant increase in Cathepsin D expression, but not LAMP-1. Treatment with ZD7288 at 10 μmol/L in the OGD/R group did not change the expression of cathepsin D and LAMP-1. However, chloroquine (CQ), which decreases autophagosome-lysosome fusion, eliminated the correction of excessive autophagy and neuroprotection by ZD7288. Besides, shRNA knockdown of HCN2 channels significantly reduced the accumulation of LC3-II and increased neuron survival in the OGD/R and transient global cerebral ischemia (TGCI) models, and CQ also eliminated the effects of HCN2-shRNA. Furthermore, we found that the percentage of LC3-positive puncta that co-localized with LAMP-1-positive lysosomes decreased in Con-shRNA-transfected HT22 neurons exposed to OGD/R or CQ. In HCN2-shRNA-transfected HT22 neurons, the percentage of LC3-positive puncta that co-localized with LAMP-1-positive lysosomes increased under OGD/R; however, the percentage was significantly decreased by the addition of CQ to HCN2-shRNA-transfected HT22 neurons. The present results demonstrated that blockade of HCN2 channels provides neuroprotection against OGD/R and TGCI by accelerating autophagic degradation attributable to the promotion of autophagosome and lysosome fusion.

OBJECTIVE: This study aimed to explore the influence of Rce1 on invasion and migration of tongue squamous cell carcinoma cells by silencing the Rce1 gene with RNA interference. METHODS: The tongue squamous cell carcinoma Cal-27 and SCC-4 cells were cultured in vitro. The small interfering RNA (siRNA) of the Rce1 gene was designed, and the Rcel gene expression was silenced vialiposome transfection. According to the siRNA transfected by liposome, the experimental group was divided into three groups, namely, Rce1-siRNA-1, Rce1-siRNA-2, and Rce1-siRNA-3 groups. Negative control group was transfected by siCON, and the blank control group was untransfected by siRNA. The Rce1, RhoA, and K-Ras gene expression levels in each group were analyzed by real-time quantitative polymerase chain reaction. The Rce1, RhoA, K-Ras, MMP-2, and MMP-9 protein expression levels were analyzed by Western blot. The invasiveness of tongue cancer cell Cal-27 and SCC-4 were determined by Transwell invasion assay, and cell migration assay was performed by cell scratch assay. RESULTS: Real-time quantitative polymerase chain reaction and Western blot results showed that compared with the negative and blank control groups, the Rce1 gene and protein expression levels in three experimental groups decreased (P<0.05). The RhoA, K-Ras gene and protein expression levels were insignificantly different among groups (P>0.05). Meanwhile, the MMP-2 and MMP-9 expression levels decreased (P<0.05). Transwell invasion assay results showed that the total number of cells in the PET film of the experimental groups was significantly decreased compared with the control group (P<0.05). The cell scratch test showed that the cell closure time of the scratch in the interference group was significantly longer than those in the control and blank groups (P<0.05). CONCLUSIONS Silencing Rce1 in vitro can effectively downregulate its expression in tongue squamous cell carcinoma cells Cal-27 and SCC-4 and reduce the migration and invasion abilities of these cells.
Cell Line, Tumor ; Cell Movement ; Cell Proliferation ; Endopeptidases ; metabolism ; Humans ; Neoplasm Invasiveness ; RNA Interference ; RNA, Small Interfering ; Tongue Neoplasms ; metabolism ; therapy ; Transfection

To study the immune protection of the inactivated vaccine against the enteropathogenic E.coli in Tibetan pigs,the strains isolated from the dead pig was identified by biochemistry and PCR methods.After that,the biological adjuvant vaccine was prepared by following procession.Firstly,selected enteropathogenic E.coli strain was cultured.Then,we harvested the bacteria and inactived it to prepare the antigen.Finally,we added the recombined cholera toxin B subunit as the biological adjuvant,added the mannose in solution 3 ％-5％ (W/V),distributed in ampoule,and freeze-dried.The performances of the vaccine was evaluated by administration for the nine groups of KM mice in oral and intramuscular immuno strategies,respectively.Results demonstrated that the effect of intramuscular injection of low dose containing adjuvant group were better than those without adjuvant group.The oral group contained both high dose of adjuvant group and low dose effect of immune adjuvant group were better than that of high and low dose not containing adjuvant group,and high dose of immune effect was better than low dose immune effect.The antibody titers proved that immunization for 4 times was much better than those immunization for times less than that.The data showed the vaccine was high protection against Tibetan Pig enteropathogenic E.coli challenge,especially the high dose of adjuvant vaccine was 100％ protection rate against enteropathogenic E.coli when orally immunization for 4 times in mice.