Objective To explore the clinical value of artificial intelligence (AI) quantitative parameters in distinguishing pathological grades of stageⅠ invasive adenocarcinoma (IAC). Methods Clinical data of patients with clinical stageⅠ IAC admitted to Yantaishan Hospital Affiliated to Binzhou Medical University from October 2018 to May 2023 were retrospectively analyzed. Based on the 2021 WHO pathological grading criteria for lung adenocarcinoma, IAC was divided into gradeⅠ, grade Ⅱ, and grade Ⅲ. The differences in parameters among the groups were compared, and logistic regression analysis was used to evaluate the predictive efficacy of AI quantitative parameters for grade Ⅲ IAC patients. Parameters were screened using least absolute shrinkage and selection operator (LASSO) regression analysis. Three machine learning models were constructed based on these parameters to predict grade Ⅲ IAC and were internally validated to assess their efficacy. Nomograms were used for visualization. Results A total of 261 IAC patients were included, including 101 males and 160 females, with an average age of 27-88 (61.96±9.17) years. Six patients had dual primary lesions, and different lesions from the same patient were analyzed as independent samples. There were 48 patients of gradeⅠ IAC, 89 patients of grade Ⅱ IAC, and 130 patients of grade Ⅲ IAC. There were statitical differences in the AI quantitive parameters such as consolidation/tumor ratio (CTR), ect among the three goups. (P<0.05). Univariate analysis showed that the differences in all variables except age were statistically significant (P<0.05) between the group gradeⅠ+grade Ⅱand the group grade Ⅲ . Multivariate analysis suggested that CTR and CT standard deviation were independent risk factors for identifying grade Ⅲ IAC, and the two were negatively correlated. Grade Ⅲ IAC exhibited advanced TNM staging, more pathological high-risk factors, higher lymph node metastasis rate, and higher proportion of advanced structure. CTR was positively correlated with the proportion of advanced structures in all patients. This correlation was also observed in grade Ⅲ but not in gradeⅠand grade ⅡIAC. CTR and CT median value were selected by using LASSO regression. Logistic regression, random forest, and XGBoost models were constructed and validated, among which, the XGBoost model demonstrated the best predictive performance. Conclusion Cautious consideration should be given to grade Ⅲ IAC when CTR is higher than 39.48% and CT standard deviation is less than 122.75 HU. The XGBoost model based on combined CTR and CT median value has good predictive efficacy for grade Ⅲ IAC, aiding clinicians in making personalized clinical decisions.

Objective To describe and analyze the current situation of the four same type of departments in an hospital in order to provide a reference for the construction of"the most cost-effective medical care".Methods The CN-DRG were used to automatically group and compare the medical capacity and inpatient service efficiency of the hospital department groups,and in the refined analysis,one DRG disease group of in situ cancer and non-malignant disease loss uterine surgery and single species uterine fibroid was included,and the Kruskal-Wallis H test was used to further compare the differences in length of stay and various costs.Results It included a total of 22630 patients,whose weights varied from a maximum of 3948.62 in diagnostic group 1 to a minimum of 133.55 in diagnostic group 11.The cost consumption indexes ranged from a minimum of 0.89 in diagnostic group 5 to a maximum of 1.04 in diagnostic group 2,while the time consumption indexes ranged from a minimum of 0.48 in diagnostic group 11 to a maximum of 0.81 in diagnostic group 5.When comparing the diagnostic groups,there were statistically significant differences(P＜0.05)in hospitalization days,total cost,diagnostic cost,therapeutic cost,and cost of supplies.Specifically,when comparing the diagnostic and treatment groups within departments,the differences in hospitalization days and all costs were statistically significant(P＜0.05)in departments 1 and 2,the differences in diagnostic cost,therapeutic cost,and cost of supplies were statistically significant(P＜0.05)in department 3.Conclusion There exists a notable disparity in the extent to which each diagnostic and treatment group contributes to the hospital's service capacity and cost variability.Consequently,it is necessary to reasonably evaluate the length of hospital stay and medical cost of patients to achieve the highest cost-effective medical treatment.

ObjectiveTo observe the clinical efficacy of Tongfu Xiezhuo enema in treating stage 3-4 chronic kidney disease （CKD） and the effect of the therapy on the neutrophil-to-lymphocyte ratio （NLR） as an inflammation marker. MethodSixty patients diagnosed with stage 3-4 CKD who visited the Nephrology Department of the First Affiliated Hospital of Heilongjiang University of Chinese Medicine from December 2022 to June 2023 were included and randomly assigned into observation and control groups in a ratio of 1∶1. The control group received conventional therapy plus Shenkang suppositories， while the observation group received conventional therapy plus Tongfu Xiezhuo enema. After 8 weeks of treatment， the clinical efficacy was assessed based on the changes in traditional Chinese medicine （TCM） symptom scores， renal function indicators， and NLR. Result① Both groups showed decreases in TCM symptom scores after treatment （P<0.01）， and the decreases were more significant in the observation group than in the control group （P<0.05）. The total response rate of TCM symptoms in the observation group was 79.31% （23/29）， which was higher than that （62.96%， 17/27） in the control group （Z=0.604，P<0.05）. ② After treatment， the observation group showed declined serum levels of creatinine （SCr）， blood urea nitrogen （BUN）， and cystatin C （Cys C） and increased glomerular filtration rate （GFR） （P<0.01）， and the control group showed lowered SCr level and increased GFR （P<0.05）. The observation group had lower SCr level and higher GFR than the control group after treatment （P<0.05）. The total response rate of renal function in the observation group was 79.31% （23/29）， which was higher than that （55.56%， 15/27） in the control group （Z=1.127，P<0.01）. ③ The NLR in the observation group decreased after treatment （P<0.05）， and it was lower than that in the control group （P<0.05）. ④ There were no significant differences in safety indicators between the two groups before and after treatment. ConclusionTongfu Xiezhuo enema ameliorated symptoms and improved renal function indicators in the patients with stage 3-4 CKD by reducing the NLR and inhibiting inflammation.

The covalent binding of drugs and their metabolites to proteins forms drug-protein adducts, which may cause adverse reactions in the body. The development of adductomics technology is helpful for the identification of covalent adducts between drugs and human plasma proteins. For many drugs, such as beta-lactam antibiotics, acyl glucuronides, covalent tyrosine kinases inhibitors, and reactive metabolites, human serum albumin (HSA) is a potential target and biomarker for the formation of drug-protein adducts. In this review, we will describe the relevant technical advances, describe the methods for the identification of covalent adducts of drugs and HSA, define the chemical reactions that form adducts, and preliminarily explore the role of drug-HSA adducts in adverse drug reactions and the potential effect on pharmacokinetics.

The purpose of this study was to identify the tick species native to Xindi Township,Yumin County,Xinjiang,China.Preliminary morphological identification of parasitic ticks collected from animals in the area was conducted with an ultra-depth of field three-dimensional VHX 600 digital stereo microscope.Total DNA of the ticks was extracted,amplified by PCR based on the COI and ITS2 gene loci,and the posi-tive PCR products were sequenced.The sequence were a-ligned with reference sequences from the NCBI database were aligned with the Basic Local Alignment Search Tool.A genet-ic phylogenetic tree was generated with the neighbor-joining method of MEGA 7.0 software to determine the evolutionary biological characteristics of ticks.Morphological identification showed that the ticks collected from Xindi Township of Yu-min County were consistent with the characteristics of Hya-lomma asiaticum.An evolutionary tree based on the COI and ITS2 gene sequences showed that the ticks collected in this study were clustered with known H.asiaticum sequences.The PCR products of COI and ITS2 were sequenced and compared,which confirmed that the collected tick species were H.asiaticum,in agreement with the morphological and molecular biological results.These findings help to clarify the distribution of ticks in Xindi Township of Xinjiang,and provide basic data for the analysis of tick genetic and evolutionary characteristics,as reference for surveillance and control of ticks in the Xinjiang Uygur Autonomous Region.

Humans ; Aged ; Processing Speed ; Cross-Sectional Studies ; Cognition ; Hearing Loss/psychology* ; Cohort Studies ; Cognitive Dysfunction

OBJECTIVE: To analyze the clinicopathological features, molecular changes and prognostic factors in angioimmunoblastic T-cell lymphoma (AITL). METHODS: Sixty-one cases AITL diagnosed by Department of Pathology of Peking University Cancer Hospital were collected with their clinical data. Morphologically, they were classified as typeⅠ[lymphoid tissue reactive hyperplasia (LRH) like]; typeⅡ[marginal zone lymphoma(MZL)like] and type Ⅲ [peripheral T-cell lymphoma, not specified (PTCL-NOS) like]. Immunohistochemical staining was used to evaluate the presence of follicular helper T-cell (TFH) phenotype, proliferation of extra germinal center (GC) follicular dendritic cells (FDCs), presence of Hodgkin and Reed-Sternberg (HRS)-like cells and large B transformation. The density of Epstein-Barr virus (EBV) + cells was counted with slides stained by Epstein-Barr virus encoded RNA (EBER) in situ hybridization on high power field (HPF). T-cell receptor / immunoglobulin gene (TCR/IG) clonality and targeted exome sequencing (TES) test were performed when necessary. SPSS 22.0 software was used for statistical analysis. RESULTS: Morphological subtype (%): 11.4% (7/61) cases were classified as type Ⅰ; 50.8% (31/61) as type Ⅱ; 37.8% (23/61) as type Ⅲ. 83.6% (51/61) cases showed classical TFH immunophenotype. With variable extra-GC FDC meshwork proliferation (median 20.0%); 23.0% (14/61) had HRS-like cells; 11.5% (7/61) with large B transformation. 42.6% (26/61) of cases with high counts of EBV. 57.9% (11/19) TCR⁺/IG^-, 26.3% (5/19) TCR⁺/IG⁺, 10.5% (2/19) were TCR^－/IG^－, and 5.3% (1/19) TCR^－/IG⁺. Mutation frequencies by TES were 66.7% (20/30) for RHOA, 23.3% (7/30) for IDH2 mutation, 80.0% (24/30) for TET2 mutation, and 33.3% (10/30) DNMT3A mutation. Integrated analysis divided into four groups: (1) IDH2 and RHOA co-mutation group (7 cases): 6 cases were type Ⅱ, 1 case was type Ⅲ; all with typical TFH phenotype; HRS-like cells and large B transformation were not found; (2) RHOA single mutation group (13 cases): 1 case was type Ⅰ, 6 cases were type Ⅱ, 6 cases were type Ⅲ; 5 cases without typical TFH phenotype; 6 cases had HRS-like cells, and 2 cases with large B transformation. Atypically, 1 case showed TCR^－/IG^－, 1 case with TCR^－/IG⁺, and 1 case with TCR⁺/IG⁺; (3) TET2 and/or DNMT3A mutation alone group (7 cases): 3 cases were type Ⅱ, 4 cases were type Ⅲ, all cases were found with typical TFH phenotype; 2 cases had HRS-like cells, 2 cases with large B transformation, and atypically; (4) non-mutation group (3 cases), all were type Ⅱ, with typical TFH phenotype, with significant extra-GC FDC proliferation, without HRS-like cells and large B transformation. Atypically, 1 case was TCR^－/IG^－. Univariate analysis confirmed that higher density of EBV positive cell was independent adverse prognostic factors for both overall survival (OS) and progression free survival(PFS), (P=0.017 and P=0.046). CONCLUSION Pathological diagnoses of ALTL cases with HRS-like cells, large B transformation or type Ⅰ are difficult. Although TCR/IG gene rearrangement test is helpful but still with limitation. TES involving RHOA, IDH2, TET2, DNMT3A can robustly assist in the differential diagnosis of those difficult cases. Higher density of EBV positive cells counts in tumor tissue might be an indicator for poor survival.
Humans ; Epstein-Barr Virus Infections/genetics* ; Herpesvirus 4, Human/genetics* ; T-Lymphocytes, Helper-Inducer/pathology* ; Immunoblastic Lymphadenopathy/pathology* ; Lymphoma, T-Cell, Peripheral/pathology* ; Receptors, Antigen, T-Cell

Objective:To explore the teaching evaluation of online open course of hematology based on small private online course (SPOC) platform by means of quantitative method.Methods:The fourth-year undergraduates of clinical medicine major were selected to receive online course learning of hematology, including video viewing, rich text browsing, in-class quizzes, and seminars. The teaching contents covered the basis of hematological diseases, anemic diseases, hematological tumors, bleeding and coagulation disorders. Teaching evaluation was conducted through teaching behavior assessment, unit test, course examination and SPOC scoring. Linear regression analysis was used to analyze the correlation between the duration of the teaching video and student learning behavior. The correlation between video learning quantity and viewing time and course test scores and SPOC scores was analyzed. Kruskal-Wallis test was used to compare the differences in curriculum learning behavior (participation rate). T-test was used to compare the differences between the two results of two unit tests and to calculate the alternative-form reliability. Chi-square test was used to compare the differences in scores of different sub-specialty questions in hematology, and the differences of participation rate of different examination points of hematological tumors. Results:The teaching video viewing rate was significantly higher than the participation rate of rich text browsing and in-class quizzes ( P < 0.001; P < 0.001). There was no obvious correlation between video duration and video viewing, rich text browsing, in-class quizzes ( R = 0.168, F = 0.81, P = 0.376; R = 0.057, F = 0.07, P=0.802; R=0.124, F=0.37, P=0.546). There was a significant positive correlation between the participation rate of video viewing and rich text browsing and in-class quizzes ( R =0.890, F=76.41, P<0.001; R=0.934, F=163.67, P < 0.001). The participation rate of anemic disease unit test was significantly higher than that of hematological tumors ( χ2 = 49.08, P<0.001), bleeding and coagulation disorders ( χ2= 25.97, P< 0.001), and the second results were significantly improved ( t=-2.09, P=0.040), and the alternative-form reliability was 0.750. There was no significant difference in the participation rate of different sub-specialty courses ( χ2=5.20, P=0.074); the number of video watching was significantly positively correlated with SPOC scores ( R=0.523, F=196.22, P<0.001); the participation rate of molecular genetics and molecular biology tests of blood tumor was significantly lower than that of general clinical information questions ( P < 0.05). Conclusion:Teaching videos are the foundation of online courses. Increasing the number of video viewing and improving video viewing rate can effectively mobilize the enthusiasm of extensive learning, such as rich text browsing and in-class quizzes, and improve learning participation. It is conducive to the improvement of students' academic performance. Simple behavior factors such as video viewing time are not recommended as performance evaluation indicators. Unit test takes two times to get the highest score, which is conducive to improving professional learning level through learning behavior, without affecting the reliability of the performance evaluation. The online open course based on the SPOC platform is conducive to the balanced development of the course teaching of Hematology.

Rocuronium bromide is an acetylcholine N2 receptor antagonist, which can be used as an auxiliary drug for general anesthesia. It has been reported that rocuronium has two possible metabolic pathways: N-dealkylation and O-deacetylation, which are mainly taken up by liver and excreted by bile in the form of primary drugs. In this paper, the metabolites of rocuronium in human bile were detected by UHPLC-QE-orbitrap-MS, thirteen metabolites were detected, including eleven phase I metabolites and two phase II metabolites, eleven of which had not been previously reported. At the same time, HEK293 cells overexpressing transporter were used to explore the transmembrane transport mechanism of rocuronium, the results showed that rocuronium was the substrate of MATE1, OCT1, OATP1B1 and OATP1B3. The above research results enrich the metabolic pathway of rocuronium in vivo, and put forward the possible transport mechanism of liver uptake and bile excretion, which can better guide the accurate and safe clinical drug application. The collection of human bile samples in this study was approved by the ethics committee of Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine (Approval Number: 2019-775-130-01).

Objective     To explore the clinical value of artificial intelligence (AI) quantitative parameters of pulmonary ground-glass nodules (GGN) in predicting the degree of infiltration. Methods     A retrospective analysis of 168 consecutive patients with 178 GGNs in our hospital from October 2019 to May 2021 was performed, including 43 males and 125 females, aged 21-78 (55.76±10.88) years. Different lesions of the same patient were analyzed as independent samples. Totally, 178 GGNs were divided into two groups, a non-invasive group (24 adenocarcinoma in situ and 77 minimally invasive adenocarcinoma), and an invasive group (77 invasive adenocarcinoma). We compared the difference of AI quantitative parameters between the two groups, and evaluated predictive valve by receiver operating characteristic curve and binary logistic regression model. Results     (1) Except for the gender (P=0.115), the other parameters, such as maximal diameter [15.10 (11.50, 21.60) mm vs. 8.90 (7.65, 11.15) mm], minimum diameter [10.80 (8.85, 15.20) mm vs. 7.40 (6.10, 8.95) mm], proportion of consolidation/tumor ratio [13.58% (1.61%, 63.76%) vs. 0.00% (0.00%, 0.67%)], mean CT value [–347.00 (–492.00, –101.50) Hu vs. –598.00 (–657.50, –510.00) Hu], CT maximum value [40.00 (–40.00, 94.50) Hu vs. –218.00 (–347.00, –66.50) Hu], CT minimum value [–584.00 (–690.50, –350.00) Hu vs. –753.00 (–786.00, –700.00) Hu], danger rating (proportion of high-risk nodules, 92.2% vs. 66.3%), malignant probability [91.66% (85.62%, 94.92%) vs. 81.81% (59.98%, 90.29%)] and age (59.93±8.53 years vs. 52.04±12.10 years) were statistically significant between the invasive group and the non-invasive group (all P<0.001). (2) The highest predictive value of a single quantitative parameter was the maximal diameter (area under the curve=0.843), the lowest one was the risk classification (area under the curve=0.627), the combination of two among the three parameters (maximal diameter, mean CT value, and consolidation/tumor ratio) improved the predictive value entirely. (3) Logistic regression analysis showed that maximal diameter and mean CT value both were the independent risk factor for predicting invasive adenocarcinoma. (4) When the threshold of v was 1.775%, the diagnostic sensitivity of invasive adenocarcinoma was 0.753 and the specificity was 0.851. Conclusion     AI quantitative parameters can effectively predict the degree of infiltration of GGNs and provide a reliable reference basis for clinicians.