ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.

BACKGROUND:At present,osteoarthritis has become a major disease affecting the quality of life of the elderly,and the therapeutic effect is poor,often focusing on preventing the disease process,and the pathogenesis of osteoarthritis is still not fully understood.Bioinformatics analysis was carried out to explore the main pathogenesis of osteoarthritis and related mechanisms of gene coding regulation. OBJECTIVE:To screen core differential genes with a major role in osteoarthritis by gene expression profiling. METHODS:Datasets were downloaded from the Gene Expression Omnibus(GEO):GSE114007,GSE117999,and GSE129147.Differential genes in the GSE114007 and GSE117999 data collections were screened using R software,performing differential genes to weighted gene co-expression network analysis.The module genes most relevant to osteoarthritis were selected to perform protein interaction analysis.Candidate core genes were selected using the cytocape software.The candidate core genes were subsequently subjected to least absolute shrinkage and selection operator regression and COX analysis to identify the core genes with a key role in osteoarthritis.The accuracy of the core genes was validated using an external dataset,GSE129147. RESULTS AND CONCLUSION:(1)A total of 477 differential genes were identified,265 differential genes associated with osteoarthritis were obtained by weighted gene co-expression network analysis,and 8 candidate core genes were identified.The least absolute shrinkage and selection operator regression analysis finally yielded a differential gene ASPM with core value that was externally validated.(2)It is concluded that abnormal gene ASPM expression screened by bioinformatics plays a key central role in osteoarthritis.

Clinical practice guidelines represent the best recommendations for patient care. They are developed through systematically reviewing currently available clinical evidence and weighing the relative benefits and risks of various interventions. However, clinical practice guidelines have to go through a long translation cycle from development and revision to clinical promotion and application, facing problems such as scattered distribution, high duplication rate, and low actual utilization. At present, the clinical practice guideline information platform can directly or indirectly solve the problems related to the lengthy revision cycles, decentralized dissemination and limited application of clinical practice guidelines. Therefore, this paper systematically examines different types of clinical practice guideline information platforms and investigates their corresponding challenges and emerging trends in platform design, data integration, and practical implementation, with the aim of clarifying the current status of this field and providing valuable reference for future research on clinical practice guideline information platforms.

OBJECTIVE: To investigate the safety and efficacy of avatrombopag（AVA） combined with rhIL-11 in treating thrombocytopenia induced by chemotherapy in acute myeloid leukemia. METHODS: The clinical information of 8 patients in the real world who received avatrombopag combined with rhIL-11 in cancer treatment-induced thrombocytopenia(CTIT) after AML chemotherapy were retrospectively analyzed, and at the same time, 8 patients who received rhIL-11 only in CTIT after AML chemotherapy served as the control group, A preliminary observation was to summarize and compare the therapeutic efficacy and adverse effects between the two groups. RESULTS: D3 and D7 platelet counts were not significantly different between the observation group and the control group after treatment. The platelet counts in the observation group was significantly higher than those of the control group on the 10th day after treatment (P < 0.01). The adverse reactions, such as weakness, abdominal pain, fatigue, nausea and edema after treatment were mild in the observation group and the control group. Except for one patient in the observation group who had a history of cerebral infarction before the onset of the disease and was routinely taking antiplatelet drugs, no thrombosis events occurred in the patients in the observation and control groups during the period of administration of the drug, and the total incidence rate of adverse reactions was not significantly different between the two groups. CONCLUSION The combination of AVA and rhIL-11 can enhance platelet recovery in CTIT of AML patients after chemotherapy. Compared with the rhIL-11 alone group, the platelet recovery time in AVA+rhIL-11 group was significantly shorter, the platelet count on the 10th day after drug administration was significantly higher. No statistically significant difference in the total incidence rate of adverse reactions was observed between rhIL-11 alone group and AVA+rhIL-11 group.
Humans ; Leukemia, Myeloid, Acute/drug therapy* ; Thrombocytopenia/chemically induced* ; Interleukin-11/therapeutic use* ; Retrospective Studies ; Adult ; Thiophenes/therapeutic use* ; Platelet Count ; Female ; Male ; Middle Aged ; Thiazoles

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese. METHODS: Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics. RESULTS: The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05). CONCLUSIONS In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.

OBJECTIVES: This study aimed to construct a risk prediction model for the occurrence of the demora-lization syndrome in patients with oral cancer and provide a scientific basis for the prevention of this syndrome in patients with oral cancer and the development of personalized care programs. METHODS: A total of 486 patients with oral cancer in West China Hospital of Stomatology of Sichuan University and Sun Yat-sen Memorial Hospital of Sun Yat-sen University from 2024 March to July were selected by convenience sampling. We integrated clinical data and evidence from previous studies to identify the key variables affecting the demoralization syndrome in patients with oral cancer. The 486 patients were divided into a training set and a validation set in an 8∶2 ratio. A clinical risk prediction model was established based on the individual data of 365 patients in the development cohort. Through least absolute shrinkage and selection operator (LASSO) regression, a moderate to severe risk prediction model of demoralization syndrome in oral cancer was constructed, and a clinical machine-learning nomogram was constructed. Bootstrap resampling was used for internal validation. The data of 121 patients in the validation cohort were externally validated. RESULTS: The incidence of the demoralization syndrome in patients with oral cancer was 405 cases (83.3%), of which 279 cases (57.4%) were mild, 176 cases (36.2%) were moderate, and 31 cases (6.4%) were severe. The core model, including patient education level, disease understanding, and MDASI-HN score, was used to predict the risk of outcome. Internal validation of the model yielded C statistic of 0.783 6 (95% CI: 0.78-0.87), beta of 0.843 4, and calibration intercept of -0.040 6. Through external validation, the validation set C statistic was 0.80 (95%CI: 0.71-0.87), beta was 0.80, and calibration intercept was -0.08. CONCLUSIONS Our risk prediction mo-del of the demoralization syndrome in patients with oral cancer performed robustly in validation cohorts of different nur-sing environments. The model has good correction and good discrimination and can be used as an evaluation and prediction item at admission.
Humans ; Mouth Neoplasms/complications* ; Male ; Female ; Nomograms ; Middle Aged ; Syndrome ; Aged ; Adult ; Risk Factors ; Risk Assessment ; Machine Learning

Objective To understand the timeliness of antiretroviral therapy (ART) in newly reported HIV/AIDS cases in Yichang from 2016 to 2022 and its influencing factors, and to provide a scientific basis for improving the timeliness of ART in Yichang City. Methods HIV/AIDS cases data from January 1, 2016 to December 31, 2022 were collected, and chi-square tests and logistic regression were used to analyze the factors influencing the timeliness of ART. Results A total of 1 126 HIV/AIDS cases were collected, with local reported cases accounting for 83.13%. The male to female ratio was 5.15:1. The median age was 42 years old (28-53 years old). 41.03% of the cases were unmarried. 38.99% of cases had a first-time CD4+T lymphocytes (CD4 cells) count < 200 cells/µL. Cases with timely first CD4 cell test accounted for 67.85%. The overall timely rate of ART from 2016 to 2022 was 57.19%, with a median time from diagnosis to initiation of ART of 20 days. There was no statistically significant difference in the trend of ART timely rate from 2016 to 2022 (P=0.251). Cases with timely first CD4 cell test were more likely to initiate ART in time (OR=3.831, 95% CI:2.454-5.981), while cases reported from other areas (OR=0.497, 95% CI:0.345-0.716) and cases with higher first CD4 cell count levels (OR_≥500=0.473, 95% CI:0.312-0.718) were less likely to initiate ART in time. Conclusion The timely rate of antiviral treatment in Yichang City needs to be further improved. High attention should be paid to cases reported from other places, cases with delayed CD4 cell testing, and cases with high CD4 cell count levels. Treatment mobilization and referral should be done well, and early detection services should be provided in time.

Objective To evaluate the bioequivalence and safety of ezetimibe tablets in healthy Chinese subjects.Methods The study was designed as a single-center,randomized,open-label,two-period,two-way crossover,single-dose trail.Subjects who met the enrollment criteria were randomized into fasting administration group and postprandial administration group and received a single oral dose of 10 mg of the subject presparation of ezetimibe tablets or the reference presparation per cycle.The blood concentrations of ezetimibe and ezetimibe-glucuronide conjugate were measured by high-performance liquid chromatography-tandem mass spectrometry(HPLC-MS/MS),and the bioequivalence of the 2 preparations was evaluated using the WinNonlin 7.0 software.Pharmacokinetic parameters were calculated to evaluate the bioequivalence of the 2 preparations.The occurrence of all adverse events was also recorded to evaluate the safety.Results The main pharmacokinetic parameters of total ezetimibe in the plasma of the test and the reference after a single fasted administration:Cmax were(118.79±35.30)and(180.79±51.78)nmol·mL-1;tmax were 1.40 and 1.04 h;t1/2 were(15.33±5.57)and(17.38±7.24)h;AUC0-t were(1 523.90±371.21)and(1 690.99±553.40)nmol·mL-1·h;AUC0-∞ were(1 608.70±441.28),(1 807.15±630.00)nmol·mL-1·h.The main pharmacokinetic parameters of total ezetimibe in plasma of test and reference after a single meal:Cmax were(269.18±82.94)and(273.93±87.78)nmol·mL-1;Tmax were 1.15 and 1.08 h;t1/2 were(22.53±16.33)and(16.02±5.84)h;AUC0_twere(1 463.37±366.03),(1 263.96±271.01)nmol·mL-1·h;AUC0-∞ were(1 639.01±466.53),(1 349.97±281.39)nmol·mL-1·h.The main pharmacokinetic parameters Cmax,AUC0-tand AUC0-∞ of the two preparations were analyzed by variance analysis after logarithmic transformation.In the fasting administration group,the 90％CI of the log-transformed geometric mean ratios were within the bioequivalent range for the remaining parameters in the fasting dosing group,except for the Cmax of ezetimibe and total ezetimibe,which were below the lower bioequivalent range.The Cmax of ezetimibe,ezetimibe-glucuronide,and total ezetimibe in the postprandial dosing group was within the equivalence range,and the 90％CI of the remaining parameters were not within the equivalence range for bioequivalence.Conclusion This test can not determine whether the test preparation and the reference preparation of ezetimibe tablets have bioequivalence,and further clinical trials are needed to verify it.

Temporomandibular joint (TMJ) diseases are common clinical conditions. The number of patients with TMJ diseases is large, and the etiology, epidemiology, disease spectrum, and treatment of the disease remain controversial and unknown. To understand and master the current situation of the occurrence, development and prevention of TMJ diseases, as well as to identify the patterns in etiology, incidence, drug sensitivity, and prognosis is crucial for alleviating patients′suffering.This will facilitate in-depth medical research, effective disease prevention measures, and the formulation of corresponding health policies. Cohort construction and research has an irreplaceable role in precise disease prevention and significant improvement in diagnosis and treatment levels. Large-scale cohort studies are needed to explore the relationship between potential risk factors and outcomes of TMJ diseases, and to observe disease prognoses through long-term follw-ups. The consensus aims to establish a standard conceptual frame work for a cohort study on patients with TMJ disease while providing ideas for cohort data standards to this condition. TMJ disease cohort data consists of both common data standards applicable to all specific disease cohorts as well as disease-specific data standards. Common data were available for each specific disease cohort. By integrating different cohort research resources, standard problems or study variables can be unified. Long-term follow-up can be performed using consistent definitions and criteria across different projects for better core data collection. It is hoped that this consensus will be facilitate the development cohort studies of TMJ diseases.