Objective: To develop a RHCE genotyping assay based on kompetitive allele-specific PCR (KASP) and assess its clinical accuracy for RhCE blood group determination. Methods: KASP primers were designed to interrogate three RHCE loci: the 109 bp insertion/deletion in intron 2, c. 307T>C, and c. 676C>G. A total of 1 194 RhD-positive inpatients from Chengdu were typed by both KASP genotyping and manual tube serology. Discordant samples (n=10) were retested by both methods and further resolved by Sanger sequencing. An additional 377 cases were tested for the c. 48C>G locus to evaluate the predictive accuracy of individual loci and combined locus testing for RhC antigen. Results: Genotyping concordance with serology was 100.0% for both the c. 676C>G locus (RhE/Rhe) and the c. 307T>C locus (Rhc). For RhC prediction using the 109 bp insertion, overall accuracy was 99.7% (1 191/1 194); the 3 discordant cases were confirmed by Sanger sequencing to be false negatives attributable to 109 bp deletion in intron 2. Testing the c. 48C>G allele for RhC prediction yielded 7 false positives, with an accuracy of 98.1% (370/377). RhC antigen status was determined by combining the 109 bp insertion and the c. 48C allele. After excluding 10 samples with inconsistent results between the two loci, the accuracy reached 100% in the remaining 367 samples. When both loci were applied in combination, accuracy reached 100% in the 367 cases with concordant results. Among the 1 194 patients, CCee (45.8%) and CcEe (31.7%) were the most common RhCE phenotypes. The e antigen had the highest positivity rate (92.2%), and the Ce haplotype was the most frequent (66.9%). Conclusion: The KASP-based RHCE genotyping method achieves high accuracy for clinical RhCE typing. Combining the 109 bp insertion/deletion with the c. 48C allele significantly improves RhC antigen prediction compared with either locus alone. This method was applied to RhCE genotyping of 1 194 RhD-positive inpatients in Chengdu, providing local RhCE phenotype and haplotype distribution data to support RhCE-matched transfusion practice.

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Objective To identify the multi-dimensional needs of symptom management for oral cancer patients based on the journey map,and provide references for optimizing the symptom management of oral cancer patients.Methods From September 2023 to March 2024,the purposive sampling was used to select 15 perioperative oral cancer patients from a tertiary A general hospital in Zhengzhou for semi-structured interviews.The content analysis method was used to analyze the data and create a patient journey map.Results According to the time axis of diagnosis and treatment,the symptom management of patients with oral cancer was subdivided into 22 themes including identifying abnormal symptoms,clarifying diagnosis,anxiety,fear and uncertainty,guilt,high-risk behavioral inertia solidification,diagnostic trust crisis and so on from 3 dimensions of task,emotion,and pain point,and a journey map was formed.Conclusion The journey of symptom management for patients with oral cancer is long and complex,and the needs of patients'physiological and psychological symptom management are dynamically changing.In the future,the digital intelligence of big data technology can be combined to achieve whole-process,personalized and precise symptom management to improve the quality of life of oral cancer patients.

OBJECTIVE: To explore the expression and clinical significance of programmed death receptor 1 (PD-1), Th1, Th2, and Th17 cytokines in multiple myeloma (MM). METHODS: A total of 76 MM patients treated in the Tengzhou Central People's Hospital from May 2021 to May 2023 were collected as MM group, and 48 healthy individuals who underwent physical examination during the same period were included as control group. The expression of PD-1 on the surface of CD4⁺ and CD8⁺ T cells and the levels of serum Th1 cytokines ［interleukin (IL) -2, interferon γ (IFN-γ), tumor necrosis factor α (TNF-α)］, Th2 cytokines (IL-4, IL-6, IL-10) and Th17 cytokines (IL-17) were detected in the two groups. Spearman correlation was used to examine the relationship between PD-1, Th1, Th2 and Th17 cytokines and clinical stage and immune typing of MM patients. Multivariate logistic regression analysis was used to analyze the related factors affecting the efficacy of chemotherapy in MM patients, and the factors were tested for multicollinearity. Receiver operating characteristic (ROC) curve was drawn to analyze the predictive value of PD-1, Th1, Th2 and Th17 cytokines in chemotherapy efficacy of MM patients. RESULTS: The levels of CD4⁺T PD-1, CD8⁺T PD-1, IL-4, IL-6, IL-10, and IL-17 in the MM group were higher than those in the control group, while the levels of IL-2, IFN-γ, and TNF-α were lower (all P <0.001). The levels of CD4⁺T PD-1, CD8⁺T PD-1, IL-4, IL-6, IL-10, and IL-17 in R-ISS stage III patients were higher than those in stage II and I patients, and the levels in stage II patients were higher than those in stage I patients (all P <0.05). The IL-2 level in R-ISS stage III patients was lower than that in stage II and I patients, and IL-2 level in R-ISS stage II patients was lower than that in stage I patients (all P <0.05). The levels of CD4⁺T PD-1, CD8⁺T PD-1, IL-4, IL-6, IL-10, and IL-17 in IgG patients were higher than those in IgA, light chain, and non secretory patients, while the level of IL-2 was lower (all P <0.05). Correlation analysis showed that CD4⁺T PD-1, CD8⁺T PD-1, IL-4, IL-6, IL-10, and IL-17 were positively correlated with R-ISS staging in MM patients (r =0.623, 0.635, 0.728, 0.330, 0.742, 0.412), and negatively correlated with immune classification (r =-0.664, -0.756, -0.642, -0.479, -0.613, -0.323). IL-2 was negatively correlated with R-ISS staging in MM patients (r =-0.280), and positively correlated with immune classification (r =0.483). The levels of CD4⁺T PD-1, CD8⁺T PD-1, IL-4, IL-6, IL-10, and IL-17 in the non-remission group were higher than those in the remission group, while the level of IL-2 was lower (all P <0.001). Multivariate logistic regression analysis showed that the increased CD4⁺T PD-1, CD8⁺T PD-1, IL-4, IL-6, IL-10 and IL-17 were risk factors for the efficacy of chemotherapy in MM patients (OR >1, P <0.05), while the increased IL-2 was a protective factor (OR < 1, P <0.05). The results of multicollinearity test showed that the tolerance of the seven factors included was between 0.714-0.885, and the variance inflation factor was between 1.130-1.400. There was no multicollinearity. The ROC curve analysis results showed that the area under the curve for the combined prediction of chemotherapy efficacy in MM patients by the above 7 factors was 0.942, with specificity of 0.741 and sensitivity of 0.909. CONCLUSION The expression levels of PD-1 on the surface of CD4⁺ and CD8⁺ T cells and serum Th2 and Th17 cytokines in MM patients are high, while Th1 cytokines are low. PD-1, Th1, Th2, and Th17 cytokines are related to clinical stage and immune classification of MM patients. The combined detection of these indicators can help predict the chemotherapy efficacy of MM patients.
Humans ; Programmed Cell Death 1 Receptor/metabolism* ; Multiple Myeloma/blood* ; Cytokines/metabolism* ; Th17 Cells/metabolism* ; Th1 Cells/metabolism* ; Th2 Cells/metabolism* ; Female ; Male ; Interleukin-10 ; Interferon-gamma ; Middle Aged ; Interleukin-17 ; Interleukin-2 ; Interleukin-4 ; Tumor Necrosis Factor-alpha ; Interleukin-6 ; Aged

Promoting the international acceptance of clinical studies about traditional Chinese medicine (TCM) interventions is a key strategy for internationalization of TCM. However, the complexities of TCM interventions—in terms of the theories, practice patterns, and components—pose challenges to the design and implementation of clinical studies that are well accepted by the international community. This article summarized the current status of clinical studies about TCM interventions that were published in international journals, explored underlying barriers hindering the international acceptance, and discussed potential strategies for future development.

Promoting the international acceptance of clinical studies about traditional Chinese medicine (TCM) interventions is a key strategy for internationalization of TCM. However, the complexities of TCM interventions—in terms of the theories, practice patterns, and components—pose challenges to the design and implementation of clinical studies that are well accepted by the international community. This article summarized the current status of clinical studies about TCM interventions that were published in international journals, explored underlying barriers hindering the international acceptance, and discussed potential strategies for future development.

Promoting the international acceptance of clinical studies about traditional Chinese medicine (TCM) interventions is a key strategy for internationalization of TCM. However, the complexities of TCM interventions—in terms of the theories, practice patterns, and components—pose challenges to the design and implementation of clinical studies that are well accepted by the international community. This article summarized the current status of clinical studies about TCM interventions that were published in international journals, explored underlying barriers hindering the international acceptance, and discussed potential strategies for future development.

Apical microsurgery is accurate and minimally invasive, produces few complications, and has a success rate of more than 90%. However, due to the lack of awareness and understanding of apical microsurgery by dental general practitioners and even endodontists, many clinical problems remain to be overcome. The consensus has gathered well-known domestic experts to hold a series of special discussions and reached the consensus. This document specifies the indications, contraindications, preoperative preparations, operational procedures, complication prevention measures, and efficacy evaluation of apical microsurgery and is applicable to dentists who perform apical microsurgery after systematic training.
Microsurgery/standards* ; Humans ; Apicoectomy ; Contraindications, Procedure ; Tooth Apex/diagnostic imaging* ; Postoperative Complications/prevention & control* ; Consensus ; Treatment Outcome

Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans ; Diagnostic Imaging/methods* ; Precision Medicine/methods* ; Image Processing, Computer-Assisted/methods*

Diterpenoid ferruginol is a key intermediate in biosynthesis of active ingredients such as tanshinone and carnosic acid.However, the traditional process of obtaining ferruginol from plants is often cumbersome and inefficient. In recent years, the increasingly developing gene editing technology has been gradually applied to the heterologous production of natural products, but the production of ferruginol in microbe is still very low, which has become an obstacle to the efficient biosynthesis of downstream chemicals, such as tanshinone. In this study, miltiradiene was produced by integrating the shortened diterpene synthase fusion protein,and the key genes in the MVA pathway were overexpressed to improve the yield of miltiradiene. Under the shake flask fermentation condition, the yield of miltiradiene reached about(113. 12±17. 4)mg·L~(-1). Subsequently, this study integrated the ferruginol synthase Sm CYP76AH1 and Sm CPR1 to reconstruct the ferruginol pathway and thereby realized the heterologous synthesis of ferruginol in Saccharomyces cerevisiae. The study selected the best ferruginol synthase(Il CYP76AH46) from different plants and optimized the expression of pathway genes through redox partner engineering to increase the yield of ferruginol. By increasing the copy number of diterpene synthase, CYP450, and CPR, the yield of ferruginol reached(370. 39± 21. 65) mg·L~(-1) in the shake flask, which was increased by 21. 57-fold compared with that when the initial ferruginol strain JMLT05 was used. Finally, 1 083. 51 mg·L~(-1) ferruginol was obtained by fed-batch fermentation, which is the highest yield of ferruginol from biosynthesis so far. This study provides not only research ideas for other metabolic engineering but also a platform for the construction of cell factories for downstream products.
Saccharomyces cerevisiae/genetics* ; Diterpenes/metabolism* ; Metabolic Engineering ; Fermentation ; Abietanes