Objective To establish and validate the diagnostic model of ferroptosis genes for acute myocardial infarction (AMI) based on bioinformatics. Methods Five AMI gene expression data were obtained from Gene Expression Omnibus (GEO), namely GSE66360, GSE48060, GSE60993, GSE83500, GSE34198. Among them, GSE66360 was used as the training set to perform differential analysis, and intersection of differential genes and ferroptosis genes was taken to obtain differentially expressed ferroptosis genes in AMI. GO and KEGG enrichment analyses were performed using Metascape website. Subsequently, random forest (RF) algorithm was used to screen out key genes with high classification performance according to the Keeny coefficient score, and artificial neural network (ANN) diagnostic model of AMI ferroptosis feature gene was constructed by model group GSE83500. The area under the receiver operating characteristic curve (AUC) of 10-fold cross-validation was used to evaluate the performance and generalization ability of the model, and 3 external independent datasets were used to verify the diagnostic performance of this model. The single sample gene set enrichment analysis was used to explore the difference in immune cell infiltration between infarcted myocardium and normal myocardium after AMI. In addition, correlation analysis between immune cells and key genes was also conducted. Finally, potential drugs that would prevent and treat AMI by regulating ferroptosis were screened out from the Coremin Medical platform. Results A total of 16 differentially expressed ferroptosis genes were obtained in the training set, GO enrichment analysis showed that they mainly participated in biological functions such as cellular response to biological stimuli and chemical stress, and regulation of interleukin 17. KEGG enrichment analysis showed that these genes were significantly enriched in NOD-like receptor signaling pathway, programmed cell necrosis, Leishmaniasis and other pathways. Four genes with good classification performance were screened out using RF algorithm, namely EPAS1, SLC7A5, FTH1, and ZFP36. The results of 10-fold cross-validation showed that the minimum AUC value was 0.746, the maximum value was 0.906, and the average value was 0.805. The AUC of the ANN model was 0.859, and the AUC values of the three independent validation sets were 0.763 (GSE48060), 0.673 (GSE60993), 0.698 (GSE34198). Immune cell infiltration found that macrophages, mast cells and monocytes were significantly active after AMI. Correlation analysis found that there were positive correlations between 4 key genes and activated dendritic cells, eosinophils and γδT cells. A total of 20 potential western medicines were predicted which could prevent and treat AMI by regulating ferroptosis, and the predicted potential Chinese medicine was mainly heat-clearing and detoxifying and blood-activating and removing blood stasis drugs. Conclusion The identified AMI ferroptosis genes by bioinformatics method have certain diagnostic significance, which provides a reference for disease diagnosis and treatment.

Objective: o develop an onset risk prediction nomogram for patients with homocysteine-type (H-type) hypertension (HTH) based on pulse diagram parameters to assist early clinical prediction and diagnosis of HTH. Methods: Patients diagnosed with essential hypertension and admitted to Shanghai Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai Hospital of Traditional Chinese Medicine, and Shanghai Hospital of Integrated Traditional Chinese and Western Medicine from July 6th 2020 to June 16th 2021, and from August 11th 2023 to January 22nd 2024, were enrolled in this retrospective research. The baselines and clinical biochemical indicators of patients were collected. The SMART-I TCM pulse instrument was applied to gather pulse diagram parameters. Multivariate logistic regression was adopted to analyze the risk factors for HTH. RStudio was employed to construct the nomogram model, receiver operating characteristic (ROC) curve, and calibration curve (bootstrap self-sampling 200 times), and clinical decision curve were drawn to evaluate the model’s discrimination and clinical effectiveness. Results: A total of 168 hospitalized patients with essential hypertension were selected and divided into non-HTH group (n = 29) and HTH group (n = 139). Compared with non-HTH group, HTH group had a lower body mass index (BMI), and higher proportions of male patients and drinkers (P < 0.05). The ventricular wall thickening (VWT) could not be determined. The proportions of left common carotid intima-media wall thickness (LCCIMWT) and serum creatinine (SCR) were higher in HTH group (P < 0.05). The pulse diagram parameter As was significantly higher, and H4/H1 and T1/T were lower in HTH group (P < 0.05). Gender, alcohol consumption, serum creatinine, and the pulse diagram parameter H4/H1 were identified as independent risk factors for HTH (P < 0.05). The nomogram’s area under the ROC curve (AUC) was 0.795 [95% confidence interval (CI): (0.706 6, 0.882 8)], with a specificity of 0.724 and sensitivity of 0.799. After 200 times repeated bootstrap self-samplings, the calibration curve showed that the simulated curve fits well with the actual curve (x2 = 9.5002, P = 0.301 9). The clinical decision curve indicated that the nomogram’s applicability was optimal when the threshold for predicting HTH was between 0.38 and 1.00. Conclusion The nomogram model could be valuable for predicting the onset risk of HTH and pulse diagram parameters can facilitate early screening and prevention of HTH.

Objective:To distinguish Hedyotis diffusa Willd. and its common countrerfeit, Hedyotis corymbosa. and Hedyotis tenelliflora. by analyzing and comparing their macroscopical identification, microscopic character and HPLC fingerprints. Methods:The features of macroscopical identification, microscopic character including cross-sections of stem, leaf, fruit and seed, and herbal powders were observed in the three samples by traditional methods. The difference of chromatographic peaks among the three samples were also analyzed by HPLC methods.Results:The stems of Hedyotis diffusa Willd. were cylindrical, and the capsules were solitary or double born in the leaf axils, oblate, 2-3 mm in diameter, with a long petiole; the Hedyotis corymbosa. and Hedyotis tenelliflora. were tetragonal, and the Hedyotis corymbosa. was 2-5 capsules born in leaf axils in corymbose inflorescences, globular, 1-1.5 mm in diameter, with a slender petiole; the Hedyotis tenelliflora. were 1-3 capsules clustered in the leaf axils, ovoid with longitudinal ribs around the margin, about 1.5 mm in diameter, without the long petiole, about 1.5 mm in diameter, sessile, the edge of the leaf drying revolute long needle-like. Under the identification, the cross section of the Hedyotis diffusa Willd. stem was almost round, the middle vein of the leaves was protrusion below, the inner pericarp fiber layer consisted of two layers of fiber cells, the surface of the seed coat cells was polygon, and the wall was densely covered with small reddish brown or yellow-brown warty spots. The cross section of the Hedyotis corymbosa. stem was quadrilateral, the surface of the seed coat cell was polygon, the wall was wavy and curved, and there was no warty point on the wall. The middle veins of the Hedyotis tenelliflora. were slightly sunken in the upper part, but not protruding in the lower part; the endocarp fiber layer consisted of 8 to 13 layers of fiber cells. Moreover, the HPLC fingerprint analysis demonstrated substantial dissimilarities in the characteristic peaks of these herbs. Conclusion:The traditional and modern analysis technology show that there are some differences in the characteristics, microscopical cross section, the powder characteristics, which can effectively distinguish the Hedyotis diffusa Willd. and its two local varieties.

Objective To propose a frequency-domain pulse wave prediction model based on fusion attention mechanism,improving the low classification accuracy and poor generalization performance of hypertension time-domain pulse wave classification based on artificial intelligence technology.Methods Firstly,the time-domain pulse wave was transformed into frequency-domain Mel-scale frequency cepstral coefficient features to enhance its discriminability.Then,temporal convolutional network and Transformer structures were employed to extract the deep features of pulse waves,and self-attention mechanism and selective kernel attention were combined for decision fusion to extract relevant features.Floodings regularization method was used to indirectly control the training loss and prevent overfitting.A 5-fold cross-verification experiment was conducted based on 527 clinical pulse diagnosis data provided by Longhua Hospital,Shanghai University of Traditional Chinese Medicine and Shanghai Traditional Chinese Medicine-Integrated Hospital.Additionally,the extreme gradient boosting algorithm was employed to calculate the contribution rate ranking of frequency-domain pulse wave features,and the key factors affecting the classification accuracy of the model were analyzed to provide reference for the clinical auxiliary diagnosis of traditional Chinese medicine.Results The evaluation metrics accuracy,F1 score,precision,recall rate and area under curve value of the model proposed in this study were 0.939 6,0.924 9,0.940 9,0.929 5,and 0.993 4,respectively.The static characteristics of the pulse wave,the contribution rate of the first-order difference and the second-order difference coefficients were relatively balanced,indicating that the degree of hypertension risk was not only related to the static characteristics of the pulse wave,but also to the dynamic characteristics of the pulse wave.Conclusion The proposed model has higher classification accuracy and generalization performance compared to typical pulse wave classification models.

In order to understand the infection and molecular genetic characteristics of goose astro-virus(GAstV)in Hotan,Xinjiang,visceral organs and swabs of dead goslings were collected asep-tically from three goose farms in Hotan,Yutian and Pashan counties,and GAstV was detected by RT-PCR.The positive samples were screened and identified in LMH cells,and the whole genome was sequenced,and the genetic characteristics of the isolates were analyzed.The results showed that the total positive rate of GAstV was 11.25％(65/578).Two strains of GAstV named as GAstV/XJHT-1 and GAstV/XJHT-2 were isolated and the lengths of their genome sequences were determined as 7 190 bp and 7 125 bp,respectively.Whole genome homology analysis showed that the homology of the two isolates with GAstV-1 and GAstV-2 was higher than 95％,and the homology with other sources(chicken,duck,and turkey)ranged from 54.1％to 61.5％.Genetic e-volution analysis showed that the genetic distance between GAstV isolates from Henan and Anhui was relatively close,suggesting that the isolated GAstV may be related to the introduction of gos-lings or goose eggs from these two places.The findings provide a basis for further development of vaccines or control products.

Objective The MMV-Net,a deep learning framework based on mammogram multiple views,was constructed to evaluate the classification performance of the model for benign and malignant masses.Methods A retrospective analysis was conduc-ted on a dataset of 1 585 breast X-ray images from Harbin Medical University Cancer Hospital from 2018 to 2020,including 806 be-nign cases and 779 malignant cases.The dataset was divided into the training set(n=1268)and the test set(n=317)according to an 8∶2 ratios,and the training set was stratified according to the 5-fold cross validation.The integrated DDSM dataset and INBreast dataset were used as external test sets(n=1645)to evaluate the model performance.Each case in the input layer contained 4 views.The MMV-Net model was constructed by removing the last two layers of the ResNet22 network structure and adding an average poo-ling layer as the feature extraction layer,as well as fully connection layer and softmax activation function as the decision layers.Bayes-ian hyperparameter optimization was used.The performance of MMV-Net,MFA Net,and ensemble inception V4 models in AUC val-ues,accuracy,precision,recall and F1 scores were compared.Results The AUC values of MMV-Net model for distinguishing benign and malignant masses on the test set were 0.913,0.882 for MFA-Net,and 0.865 for inception V4.The accuracy and precision evalu-ation metrics of the MMV-Net model were also higher than the other two models.Conclusion The deep learning MMV-Net model based on multiple views of mammogram is helpful for the classification of benign and malignant breast masses.

Objective:To analyze the clinical characteristics and outcomes of patients with invasive fungal sinusitis (invasive fungal rhinosinusitis, IFR) after allogeneic hematopoietic stem cell transplantation (allo-HSCT) and explored the risk factors for IFR after allo-HSCT.Methods:Nineteen patients with IFR after allo-HSCT at Peking University People’s Hospital from January 2012 to December 2021 were selected as the study group, and 95 patients without IFR after allo-HSCT during this period were randomly selected as the control group (1:5 ratio) .Results:Nineteen patients, including 10 males and 9 females, had IFR after allo-HSCT. The median age was 36 (10–59) years. The median IFR onset time was 68 (9–880) days after allo-HSCT. There were seven patients with acute myeloid leukemia, five with acute lymphoblastic leukemia, two with myelodysplastic syndrome, two with chronic myeloid leukemia, one with acute mixed-cell leukemia, one with multiple myeloma, and one with T-lymphoblastic lymph node tumor. There were 13 confirmed cases and 6 clinically diagnosed cases. The responsible fungus was Mucor in two cases, Rhizopus in four, Aspergillus in four, and Candida in three. Five patients received combined treatment comprising amphotericin B and posaconazole, one patient received combined treatment comprising voriconazole and posaconazole, nine patients received voriconazole, and four patients received amphotericin B. In addition to antifungal treatment, 10 patients underwent surgery. After antifungal treatment and surgery, 15 patients achieved a response, including 13 patients with a complete response and 2 patients with a partial response. Multivariate analysis revealed that neutropenia before transplantation ( P=0.021) , hemorrhagic cystitis after transplantation ( P=0.012) , delayed platelet engraftment ( P=0.008) , and lower transplant mononuclear cell count ( P=0.012) were independent risk factors for IFR after allo-HSCT. The 5-year overall survival rates in the IFR and control groups after transplantation were 29.00%±0.12% and 91.00%±0.03%, respectively ( P<0.01) . Conclusion:Although IFR is rare, it is associated with poor outcomes in patients undergoing allo-HSCT. The combination of antifungal treatment and surgery might be effective.

Objectives:To determine the effect of glucose-6-phosphate-dehydrogenase (G6PD) deficiency on patients’ complications and prognosis following allogeneic stem cell hematopoietic transplantation (allo-HSCT) .Methods:7 patients with G6PD deficiency (study group) who underwent allo-HSCT at Peking University People's Hospital from March 2015 to January 2021 were selected as the study group, and thirty-five patients who underwent allo-HSCT during the same period but did not have G6PD deficiency were randomly selected as the control group in a 1∶5 ratio. Gender, age, underlying diseases, and donors were balanced between the two groups. Collect clinical data from two patient groups and perform a retrospective nested case-control study.Results:The study group consisted of six male patients and one female patient, with a median age of 37 (range, 2-45) years old. The underlying hematologic diseases included acute myeloid leukemia ( n=3), acute lymphocytic leukemia ( n=2), and severe aplastic anemia ( n=2). All 7 G6PD deficiency patients achieved engraftment of neutrophils within 28 days of allo-HSCT, while the engraftment rate of neutrophils was 94.5% in the control group. The median days of platelet engraftment were 21 (6–64) d and 14 (7–70) d ( P=0.113). The incidence rates of secondary poor graft function in the study group and control group were 42.9% (3/7) and 8.6% (3/35), respectively ( P=0.036). The CMV infection rates were 71.4% (5/7) and 31.4% (11/35), respectively ( P=0.049). The incidence rates of hemorrhagic cystitis were 57.1% (4/7) and 8.6% (3/35), respectively ( P=0.005), while the bacterial infection rates were 100% (7/7) and 77.1% (27/35), respectively ( P=0.070). The infection rates of EBV were 14.3% (1/7) and 14.3% (5/35), respectively ( P=1.000), while the incidence of fungal infection was 14.3% (1/7) and 25.7% (9/35), respectively ( P=0.497). The rates of post-transplant lymphoproliferative disease (PTLD) were 0% and 5.7%, respectively ( P=0.387) . Conclusions:The findings of this study indicate that blood disease patients with G6PD deficiency can tolerate conventional allo-HSCT pretreatment regimens, and granulocytes and platelets can be implanted successfully. However, after transplantation, patients should exercise caution to avoid viral infection, complications of hemorrhagic cystitis, and secondary poor graft function.

Objective To evaluate the efficacy of medroxyprogesterone acetate(MA)plus metformin as the primary fertility-sparing treatment for atypical endometrial hyperplasia(AEH)and early-stage grade 1 endometrial adenocarcinoma(G1 EAC)and the recurrence rate after treatment.Methods Sixty patients(aged 20-42 years)with AEH and/or grade 1 EAC limited to the endometrium were enrolled prospectively and randomized into two groups(n=30)to receive oral MA treatment at the daily dose of 160 mg(control)or MA plus oral metformin(850 mg,twice a day)for at least 6 months.The treatment could extend to 12 months until a complete response(CR)was achieved,and follow-up hysteroscopy and curettage were performed every 3 months.For all the patients who achieved CR,endometrial expressions of IGFBP-rP1,p-Akt and p-AMPK were detected immunohistochemically.Results A total of 58 patients completed the treatment.After 9 months of treatment,23(76.7%)patients in the combined treatment group and 20(71.4%)in the control group achieved CR;two patients in the control group achieved CR after converting to the combined treatment.The recurrence rate did not differ significantly between the control group and combined treatment group(30.0%vs 22.7%,P>0.05).Ten(35.7%)patients in the control group experienced significant weight gain of 5.7±6.1 kg,while none of the patients receiving the combined treatment exhibited significant body weight changes.Compared with the control group,the patients receiving the combined treatment showed enhanced endometrial expressions of IGFBP-rP1 and p-AMPK with lowered p-Akt expression.Conclusion Metformin combined with MA may provide an effective option for fertility-sparing treatment of AEH and grade 1 stage IA EAC,and the clinical benefits of metformin for controlling MA-induced weight gain and promoting endometrial expressions of IGFBP-rP1 and p-AMPK while inhibiting p-Akt expression warrants further study.

Objective To establish a scientific training program that takes into account both anaerobic and aerobic training for pilots,and to explore the appropriate ratio of aerobic and anaerobic training.Methods According to the physical examination standards for pilots,a total of 16 healthy subjects aged 18-24 were selected from two batches.The two batches of subjects were trained with different aerobic and anaerobic ratios.Training period was 3 months.The changes in cardiopulmonary function of the subjects before and after training were evaluated using the cardiopulmonary function exercise testing system(CPET),and the changes in anaerobic capacity were evaluated using changes in strength as an indicator.Results After training,the weight load of the subjects in the two training programs,including barbell squats,leg flexion and hard pull,and barbell under 10RM and 3RM,was significantly increased(P<0.001),and there was no statistically significant difference in anaerobic strength growth between the two groups.The results of CPET showed that the maximum load,maximum heart rate,and respiratory quotient in the two groups were significantly increased after than before the training(P<0.01).The maximum load(Experiment group 1:29.12±19.69,Experiment group 2:72.00±46.24)and respiratory quotient(Experiment grouop 1:0.11±0.09,Experiment group 2:0.28±0.16)of the subjects in experiment group 2 before and after training were greater than those in experiment group 1.The difference was statistically significant(P<0.05).Conclusion The anaerobic and aerobic capacities of the subjects in the experiment group 2 are effectively improved,indicating that ratio of aerobic and anaerobic of the training scheme is better.