To elucidate the mechanism by which steaming affects the quality of Curcuma kwangsiensis root tubers, methods such as LSCM, RVA, dual-wavelength spectrophotometry, LF-NMR, and LC-MS were employed to qualitatively and quantitatively detect changes in starch gelatinization characteristics, water distribution, and material composition of C. kwangsiensis root tubers under different steaming durations. Based on multivariate statistical analysis, the correlation between differences in gelatinization parameters, water distribution, and terpenoid material composition was investigated. The results indicate that steaming affects both starch gelatinization and water distribution in C. kwangsiensis. During the steaming process, transformations occur between amylose and amylopectin, as well as between semi-bound water and free water. After 60 min of steaming, starch gelatinization and water distribution reached an equilibrium state. The content of amylopectin, the amylose-to-amylopectin ratio, and parameters such as gelatinization temperature, viscosity, breakdown value, and setback value were significantly correlated(P≤0.05). Additionally, the amylose-to-amylopectin ratio was significantly correlated with total free water and total water content(P≤0.05). Steaming induced differences in the material composition of C. kwangsiensis root tubers. Clustering of primary metabolites in the OPLS-DA model was distinct, while secondary metabolites were classified into 9 clusters using the K-means clustering algorithm. Differential terpenoid metabolites such as(-)-α-curcumene were significantly correlated with zerumbone, retinal, and all-trans-retinoic acid(P<0.05). Curcumenol was significantly correlated with isoalantolactone and ursolic acid(P<0.05), while all-trans-retinoic acid was significantly correlated with both zerumbone and retinal(P<0.05). Alpha-tocotrienol exhibited a significant correlation with retinal and all-trans-retinoic acid(P<0.05). Amylose was extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and α-tocotrienol(P<0.05). Amylopectin was significantly correlated with zerumbone(P<0.05) and extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and 9-cis-retinoic acid(P<0.01). The results provide scientific evidence for elucidating the mechanism of quality formation of steamed C. kwangsiensis root tubers as a medicinal material.
Curcuma/chemistry* ; Starch/chemistry* ; Multivariate Analysis ; Water/chemistry* ; Terpenes/analysis* ; Plant Roots/chemistry* ; Plant Tubers/chemistry* ; Drugs, Chinese Herbal/chemistry*

OBJECTIVE: To detect the expression level of T-complex polypeptide 1 (TCP1) in the bone marrow of newly diagnosed acute myeloid leukemia (AML) patients, and explore its correlation with clinical characteristics and prognosis. METHODS: The bone marrow samples from 80 newly diagnosed AML patients and 30 iron deficiency anemia (IDA) patients were collected, and real time fluorescence quantitative PCR was used to detect the expression level of TCP1 . The clinical data of AML patients were collected, and the correlation of TCP1 expression with clinical characteristics and prognosis of patients were analyzed. The impact of TCP1 on overall survival (OS) of AML patients was identified by using Kaplan-Meier curve analysis. Cox regression analysis was used to identify the factors affecting prognosis of AML patients. RESULTS: Compared with IDA patients, the expression of TCP1 was significantly increased in AML patients (P < 0.01). The high expression group of TCP1 showed a higher proportion of patients with ≥60 years and non-remission after treatment, more accompanied by TET2 mutation and poor prognosis but shorter OS compared to the low expression group (all P < 0.05). The results of multivariate Cox regression analysis showed that age, chromosomal abnormalities, therapeutic efficacy and TCP1 expression were independent risk factors affecting prognosis of AML patients (all P < 0.05). CONCLUSION TCP1 is significantly upregulated in AML patients, and its expression is associated with partial clinical features and poor prognosis. It can serve as a prognostic indicator and potential therapeutic target for AML patients.
Gene Expression Regulation, Leukemic ; Leukemia, Myeloid, Acute/metabolism* ; Humans ; Gene Expression Profiling ; Bone Marrow/metabolism* ; Anemia, Iron-Deficiency/metabolism* ; Polymerase Chain Reaction ; Prognosis ; Kaplan-Meier Estimate ; Proportional Hazards Models ; Multivariate Analysis ; Risk Factors ; Chaperonin Containing TCP-1

Objective:To investigate the clinical characteristics of residual dizziness（RD） after repositioning in patients with benign paroxysmal positional vertigo（BPPV）, identify its potential risk factors, and develop a predictive risk model. Methods:A total of 137 patients diagnosed with BPPV at the First Affiliated Hospital of Xi'an Jiaotong University between January 2023 and June 2023 were enrolled. Based on the presence or absence of subjective discomfort within 3 months after successful repositioning, patients were divided into the non-RD group（NRD, n=93） and the RD group（n=44）. Differences in demographic characteristics, comorbidities, and disease-related features were compared between groups. Multivariate logistic regression analysis was used to identify independent risk factors for RD, and a nomogram was constructed based on these factors. The predictive performance of the model was assessed using the area under the curve（AUC）. Results:The RD group showed significantly higher values in body mass index, prevalence of diabetes and motion sickness history, dizziness duration before repositioning, history of repositioning at external hospitals, number of treatments, and recurrence（all P<0.001）. Multivariate logistic regression revealed that diabetes（adjusted OR=8.73, P=0.039）, motion sickness history（adjusted OR=23.08, P<0.001）, dizziness duration ≥30 days before repositioning（adjusted OR=15.16, P<0.001）, and recurrence（adjusted OR=15.72, P=0.001） were independent risk factors for RD. The nomogram model based on these variables demonstrated good predictive ability, with an AUC of 0.804（95%CI 0.684-0.924）. Conclusion:Diabetes, motion sickness history, dizziness duration ≥30 days, and recurrence are independent risk factors for RD after repositioning in patients with BPPV. The nomogram model based on these variables shows good predictive performance, with recurrence having the highest predictive value. This model can aid in early identification of high-risk patients and guide individualized intervention strategies.
Humans ; Nomograms ; Benign Paroxysmal Positional Vertigo/therapy* ; Dizziness/etiology* ; Risk Factors ; Risk Assessment ; Multivariate Analysis ; Male ; Female ; Logistic Models ; Middle Aged ; Patient Positioning ; Adult

INTRODUCTION: We investigated the factors associated with readmission in patients with congestive heart failure (HF) receiving long-term administration of tolvaptan (TLV) to support treatment decisions for HF. METHODS: This retrospective cohort study included 181 patients with congestive HF who received long-term administration of TLV. Long-term administration of TLV was defined as the administration of TLV for 60 days or longer. The outcome was a readmission event for worsening HF within 1 year after discharge. Significant factors associated with readmission were selected using multivariate analysis. To compare the time to readmission using significant factors extracted in a multivariate analysis, readmission curves were constructed using the Kaplan-Meier method and analysed using the log-rank test. RESULTS: The median age was 78 years (range, 38-96 years), 117 patients (64.6%) were males, and 77 patients (42.5%) had a hospitalisation history of HF. Readmission for worsening HF within 1 year after long-term TLV treatment occurred in 62 patients (34.3%). In the multivariate analysis, estimated glomerular filtration rate (eGFR) <30 mL/min/1.73 m 2 (odds ratio, 3.22; 95% confidence interval, 1.661-6.249; P = 0.001) was an independent significant factor. When eGFR at discharge was divided into two groups (eGFR < 30 vs. eGFR ≥ 30), readmission rates within 1 year were 53.3% vs. 25.4%, respectively ( P = 0.001). CONCLUSION We revealed that eGFR was strongly associated with readmission in patients with HF who received long-term administration of TLV. Furthermore, we showed that eGFR is an important indicator in guiding treatment of HF in patients receiving TLV.
Humans ; Tolvaptan/therapeutic use* ; Heart Failure/drug therapy* ; Male ; Female ; Patient Readmission/statistics & numerical data* ; Aged ; Retrospective Studies ; Aged, 80 and over ; Middle Aged ; Glomerular Filtration Rate ; Adult ; Antidiuretic Hormone Receptor Antagonists/therapeutic use* ; Risk Factors ; Kaplan-Meier Estimate ; Multivariate Analysis

A method based on ultra-high performance liquid chromatography coupled with triple quadrupole linear ion trap-tandem mass spectrometry(UHPLC-QTRAP-MS/MS) was developed for the simultaneous determination of 41 bioactive constituents of flavonoids, organic acids, nucleosides, and amino acids in Lysimachiae Herba. The content of multiple bioactive constituents was compared among the samples from different habitats. The chromatographic separation was performed in a Waters XBridge®C_(18) column(4.6 mm×100 mm, 3.5 μm) at 30 ℃. The gradient elution was performed with 0.4% methanol(A)-formic acid water(B) as the mobile phase at a flow rate of 0.8 mL·min~(-1), and the multiple-reaction monitoring(MRM) mode was adopted. According to the content of 41 constituents, hierarchical cluster analysis(HCA), orthogonal partial least squares discriminant analysis(OPLS-DA), and gray relational analysis(GRA) were perfomed to comprehensively evaluate the samples from different habitats. The results showed that the 41 constituents exhibited good linear relationship within the tested concentration ranges, with the correlation coefficients(r) greater than 0.999 4. The method featured good precision, repeatability, and stability with the relative standard deviations(RSDs) less than 5.0%. The average recoveries of the 41 constituents ranged from 98.06% to 101.9%, with the RSDs of 0.62%-4.6%. HCA and OPLS-DA separated 48 batches of Lysimachiae Herba samples from different habitats into three categories: the producing areas in Sichuan and Chongqing, the producing areas in Jiangsu, Zhejiang, and Jiangxi, and the producing areas in Guizhou. The content of 41 constituents varied among the Lysimachiae Herba samples from different habitats. The GRA results revealed that the Lysimachiae Herba sample from Nanchong City, Sichuan Province had the best comprehensive quality. The method developed in this study was accurate and reliable and thus can be used for comprehensive evaluation of Lysimachiae Herba quality and provide basic information for the selection of habitats.
Tandem Mass Spectrometry/methods* ; Multivariate Analysis ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Amino Acids/analysis*

OBJECTIVE: To investigate humanistic practice ability of nurses in a general hospital in Hunan Province and analyze the factors affecting their practices to provide evidence for interventions to improve humanistic practice ability of the nurses. METHODS: A total of 1196 nurses were surveyed using a self-designed questionnaire and a nurse humanistic practice ability assessment scale questionnaire for assessment of their abilities for humanistic care practice, psychological adjustment, interpersonal communication, self-management, ethics and legal practice. Univariate and multivariate analyses were performed for analysis of the factors affecting the practice abilities of the nurses. RESULTS: The total score of humanistic practice ability of the 1196 nurses was 105.69±16.45 (the full score of the scale was 130), and the scores of humanistic care practice ability, psychological adjustment ability, interpersonal communication ability, self-management ability, ethics and legal practice ability were 40.95±6.46, 16.41±2.66, 16.41±2.66, 11.32±2.05 and 12.43±2.00, respectively. Univariate analysis and multiple linear regression analysis showed that gender (P=0.033), age (P < 0.001), department (P=0.015), working years (P < 0.001), professional title (P < 0.001), first academic degree (P < 0.001), highest academic degree (P < 0.001), family location (P=0.010), marital status (P=0.023), number of patients to care for (P=0.022), number of children (P=0.001), previous humanities related training (P < 0.001), training times (P < 0.001), and care received from family members (P < 0.001) and colleagues (P < 0.001) were all the factors affecting humanistic practice ability of the nurses. Among these factors, age, working in department of obstetrics and gynecology and emergency department, professional title, humanities training, and care from family and colleagues explained 20.7% of the variance. CONCLUSION The humanistic practice ability of nurses in this general hospital is above the average level, but their self-management ability needs to be improved. Intervention measures should be implemented to improve the nurses' humanistic practice ability including more attentions to the key groups and departments, strengthening the training of humanistic practice ability, and improving the promotion assessment system.
Child ; Female ; Pregnancy ; Humans ; Hospitals, General ; Emergency Service, Hospital ; Multivariate Analysis ; Research Design

This study explored the feasibility of mineral element content and ratios of nitrogen isotopes to discriminate the cultivation mode of Dendrobium nobile in order to provide theoretical support for the discrimination of the cultivation mode of D. nobile. The content of 11 mineral elements(N, K, Ca, P, Mg, Na, Fe, Cu, Zn, Mn, and B) and nitrogen isotope ratios in D. nobile and its substrate samples in three cultivation methods(greenhouse cultivation, tree-attached cultivation, and stone-attached cultivation) were determined. According to the analysis of variance, principal component analysis, and stepwise discriminant analysis, the samples of different cultivation types were classified. The results showed that the nitrogen isotope ratios and the content of elements except for Zn were significantly different among different cultivation types of D. nobile(P<0.05). The results of correlation analysis showed that the nitrogen isotope ratios, mineral element content, and effective component content in D. nobile were correlated with the nitrogen isotope ratio and mineral element content in the corresponding substrate samples to varying degrees. Principal component analysis can preliminarily classify the samples of D. nobile, but some samples overlapped. Through stepwise discriminant analysis, six indicators, including δ~(15)N, K, Cu, P, Na, and Ca, were screened out, which could be used to establish the discriminant model of D. nobile cultivation methods, and the overall correct discrimination rates after back-substitution test, cross-check, and external validation were all 100%. Therefore, nitrogen isotope ratios and mineral element fingerprints combined with multivariate statistical analysis could effectively discriminate the cultivation types of D. nobile. The results of this study provide a new method for the identification of the cultivation type and production area of D. nobile and an experimental basis for the quality evaluation and quality control of D. nobile.
Dendrobium ; Minerals ; Discriminant Analysis ; Multivariate Analysis ; Nitrogen Isotopes

A comprehensive analytical method based on ultra-fast liquid chromatography coupled with triple quadrupole/linear ion trap tandem mass spectrometry(UFLC-QTRAP-MS/MS) was established for simultaneous determination of the content of 45 bioactive constituents including flavonoids, alkaloids, amino acids, phenolic acids, and nucleosides in Epimedium brevicornum. The multiple bioactive constituents in leaves, petioles, stems and rhizomes of E. brevicornum were analyzed. The gradient elution was performed at 30 ℃ in an XBridge~® C_(18) column(4.6 mm×100 mm, 3.5 μm) with 0.4% formic acid aqueous solution-acetonitrile as the mobile phase at a flow rate of 0.8 mL·min~(-1). Single factor experiment and response surface methodology were employed to optimize the extraction conditions. Multivariate statistical analyses including systematic cluster analysis(SCA), principal component analysis(PCA), partial least squares discriminant analysis(PLS-DA), and one-way analysis of variance(One-way ANOVA) were carried out to classify the samples from different parts and identify different constituents. Grey relation analysis(GRA) and entropy weight-TOPSIS analysis were performed to build a multi-index comprehensive evaluation model for different parts of E. brevicornum. The results showed that there was a good relationship between the mass concentrations of 45 constituents and the corresponding peak areas, with the correlation coefficients(r) not less than 0.999 0. The precision, repeatability, and stability of the established method were good for all the target constituents in this study, with the relative standard deviations(RSDs) less than 5.0%(0.62%-4.9%) and the average recovery of 94.51%-105.7%. The above results indicated that the bioactive constituents varied in different parts of E. brevicornum, and the overall quality followed the trend of leaves > petioles > rhizomes > stems. This study verified the rationality of the Chinese Pharmacopoeia(2020 edition) stipulating that the medicinal part of E. brevicornum is the leaf. Moreover, our study indicated that the rhizome had the potential for medicinal development. The established method was accurate and reliable, which can be used to comprehensive evaluate and control the quality of E. brevicornum. This study provides data reference for clarifying the medicinal parts and rationally utilizing the resources of E. brevicornum.
Chromatography, High Pressure Liquid ; Epimedium ; Tandem Mass Spectrometry ; Chromatography, Liquid ; Multivariate Analysis

OBJECTIVES: To estimate postmortem interval (PMI) by analyzing the protein changes in skeletal muscle tissues with the protein chip technology combined with multivariate analysis methods. METHODS: Rats were sacrificed for cervical dislocation and placed at 16 ℃. Water-soluble proteins in skeletal muscles were extracted at 10 time points (0 d, 1 d, 2 d, 3 d, 4 d, 5 d, 6 d, 7 d, 8 d and 9 d) after death. Protein expression profile data with relative molecular mass of 14 000-230 000 were obtained. Principal component analysis (PCA) and orthogonal partial least squares (OPLS) were used for data analysis. Fisher discriminant model and back propagation (BP) neural network model were constructed to classify and preliminarily estimate the PMI. In addition, the protein expression profiles data of human skeletal muscles at different time points after death were collected, and the relationship between them and PMI was analyzed by heat map and cluster analysis. RESULTS: The protein peak of rat skeletal muscle changed with PMI. The result of PCA combined with OPLS discriminant analysis showed statistical significance in groups with different time points (P<0.05) except 6 d, 7 d and 8 d after death. By Fisher discriminant analysis, the accuracy of internal cross-validation was 71.4% and the accuracy of external validation was 66.7%. The BP neural network model classification and preliminary estimation results showed the accuracy of internal cross-validation was 98.2%, and the accuracy of external validation was 95.8%. There was a significant difference in protein expression between 4 d and 25 h after death by the cluster analysis of the human skeletal muscle samples. CONCLUSIONS The protein chip technology can quickly, accurately and repeatedly obtain water-soluble protein expression profiles in rats' and human skeletal muscles with the relative molecular mass of 14 000-230 000 at different time points postmortem. The establishment of multiple PMI estimation models based on multivariate analysis can provide a new idea and method for PMI estimation.
Animals ; Humans ; Rats ; Multivariate Analysis ; Postmortem Changes ; Protein Array Analysis ; Technology

BACKGROUND: Pneumonia-like primary pulmonary lymphoma (PPL) was commonly misdiagnosed as infectious pneumonia, leading to delayed treatment. The purpose of this study was to establish a computed tomography (CT)-based radiomics model to differentiate pneumonia-like PPL from infectious pneumonia. METHODS: In this retrospective study, 79 patients with pneumonia-like PPL and 176 patients with infectious pneumonia from 12 medical centers were enrolled. Patients from center 1 to center 7 were assigned to the training or validation cohort, and the remaining patients from other centers were used as the external test cohort. Radiomics features were extracted from CT images. A three-step procedure was applied for radiomics feature selection and radiomics signature building, including the inter- and intra-class correlation coefficients (ICCs), a one-way analysis of variance (ANOVA), and least absolute shrinkage and selection operator (LASSO). Univariate and multivariate analyses were used to identify the significant clinicoradiological variables and construct a clinical factor model. Two radiologists reviewed the CT images for the external test set. Performance of the radiomics model, clinical factor model, and each radiologist were assessed by receiver operating characteristic, and area under the curve (AUC) was compared. RESULTS: A total of 144 patients (44 with pneumonia-like PPL and 100 infectious pneumonia) were in the training cohort, 38 patients (12 with pneumonia-like PPL and 26 infectious pneumonia) were in the validation cohort, and 73 patients (23 with pneumonia-like PPL and 50 infectious pneumonia) were in the external test cohort. Twenty-three radiomics features were selected to build the radiomics model, which yielded AUCs of 0.95 (95% confidence interval [CI]: 0.94-0.99), 0.93 (95% CI: 0.85-0.98), and 0.94 (95% CI: 0.87-0.99) in the training, validation, and external test cohort, respectively. The AUCs for the two readers and clinical factor model were 0.74 (95% CI: 0.63-0.83), 0.72 (95% CI: 0.62-0.82), and 0.73 (95% CI: 0.62-0.84) in the external test cohort, respectively. The radiomics model outperformed both the readers' interpretation and clinical factor model ( P <0.05). CONCLUSIONS The CT-based radiomics model may provide an effective and non-invasive tool to differentiate pneumonia-like PPL from infectious pneumonia, which might provide assistance for clinicians in tailoring precise therapy.
Humans ; Retrospective Studies ; Pneumonia/diagnostic imaging* ; Analysis of Variance ; Tomography, X-Ray Computed ; Lymphoma/diagnostic imaging*