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.

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*

T-cell acute lymphoblastic leukemia (T-ALL) is a highly aggressive hematologic malignancy with a poor prognosis, despite advancements in treatment. Many patients struggle with relapse or refractory disease. Investigating the role of the super-enhancer (SE) regulated gene ubiquitin-specific protease 20 (USP20) in T-ALL could enhance targeted therapies and improve clinical outcomes. Analysis of histone H3 lysine 27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) data from six T-ALL cell lines and seven pediatric samples identified USP20 as an SE-regulated driver gene. Utilizing the Cancer Cell Line Encyclopedia (CCLE) and BloodSpot databases, it was found that USP20 is specifically highly expressed in T-ALL. Knocking down USP20 with short hairpin RNA (shRNA) increased apoptosis and inhibited proliferation in T-ALL cells. In vivo studies showed that USP20 knockdown reduced tumor growth and improved survival. The USP20 inhibitor GSK2643943A demonstrated similar anti-tumor effects. Mass spectrometry, RNA-Seq, and immunoprecipitation revealed that USP20 interacted with hypoxia-inducible factor 1 subunit alpha (HIF1A) and stabilized it by deubiquitination. Cleavage under targets and tagmentation (CUT&Tag) results indicated that USP20 co-localized with HIF1A, jointly modulating target genes in T-ALL. This study identifies USP20 as a therapeutic target in T-ALL and suggests GSK2643943A as a potential treatment strategy.

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

OBJECTIVE: Blood culture remains the gold standard for diagnosing bloodstream infections. Clinical laboratories must ensure the quality of blood culture processes from receipt to obtaining definitive results. We examined laboratory analytical indicators associated with positive blood culture results. METHODS: Blood cultures collected from Peking Union Medical College Hospital between January 1, 2020, and December 31, 2022, were retrospectively analyzed. The mode of transportation (piping logistics delivery vs. staff), source of blood cultures (outpatient/emergency department vs. inpatient department), rotation of personnel, and time of reception (8:00-19:59 vs. 20:00-07:59) were compared between blood culture-positive and -negative results. RESULTS: Between 2020 and 2022, the total positive rate of blood culture was 8.07%. The positive rate of blood cultures in the outpatient/emergency department was significantly higher than that in the inpatient department (12.46% vs. 5.83%; P < 0.0001). The time-to-detection of blood cultures was significantly affected by the delivery mode and personnel rotation. The blood culture positive rate of the total pre-analytical time within 1 h was significantly higher than that within 1-2 h or > 2 h ( P < 0.0170). CONCLUSION Laboratory analytical indicators such as patient source, transportation mode, and personnel rotation significantly impacted the positive detection rate or time of blood culture.
Blood Culture/statistics & numerical data* ; Humans ; Retrospective Studies ; Emergency Service, Hospital/statistics & numerical data*

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.

This study aims to investigate the effects of aerobic exercise on neuroinflammation in AD mice and explore the mechanisms of neuroinflammation regulated by the blood-brain barrier,lipopolysaccharide(LPS)displacement,and glial cell activation.Twenty 3-month-old male APP/PS1 double transgenic mice were used,which were randomly divided into a sedentary group(SE-AD)and an aerobic exercise group(Run-AD),and 10 3-month-old male C57BL/6 mice were used as the control group(WT).The Run-AD group underwent 12 weeks of aerobic training.The results of the water maze showed that aerobic exercise improved the learning and memory capacity of AD mice(P＜0.05).The results of H&E stai-ning and Nissl staining showed that aerobic exercise reduced necrotic cells and inflammatory cell infiltra-tion in the cerebral cortex,as well as nuclear condensation in the CA1 and GD regions of the hippocam-pus(P＜0.05,P＜0.01),and increased the area of Nissl bodies in the cerebral cortex and hippocam-pal CA3 and DG regions.Western blotting and ELISA results showed that aerobic exercise increased the expression of Occludin,ZO-1 and Claudin-5 proteins in the brain(P＜0.01),and decreased the levels of LPS in the brain(P＜0.01).The qRT-PCR results exhibited that aerobic exercise decreased the ex-pression of TLR4,MyD88,NF-κB,IL-1β,and TNF-α mRNA(P＜0.05,P＜0.01).The results of immunofluorescence staining revealed that aerobic exercise reduced the fluorescence area of brain IL-1βand TNF-α proteins(P＜0.05,P＜0.01),as well as the fluorescence area of Iba-1,GFAP,and TLR4 proteins in the cerebral cortex and hippocampus(P＜0.05,P＜0.01).There was a high degree of overlap between Iba-1 and TLR4 fluorescence in the cerebral cortex,and GFAP was localized around Iba-1.In summary,aerobic exercise attenuates neuroinflammation in AD mice by protecting the blood-brain barrier,reducing the displacement of LPS,and subsequently weakening the immune activation of microglia to regulate the TLR4/MyD88/NF-κB signaling pathway to alleviate neuroinflammation.

This study aims to investigate the effects of aerobic exercise on neuroinflammation in AD mice and explore the mechanisms of neuroinflammation regulated by the blood-brain barrier,lipopolysaccharide(LPS)displacement,and glial cell activation.Twenty 3-month-old male APP/PS1 double transgenic mice were used,which were randomly divided into a sedentary group(SE-AD)and an aerobic exercise group(Run-AD),and 10 3-month-old male C57BL/6 mice were used as the control group(WT).The Run-AD group underwent 12 weeks of aerobic training.The results of the water maze showed that aerobic exercise improved the learning and memory capacity of AD mice(P＜0.05).The results of H&E stai-ning and Nissl staining showed that aerobic exercise reduced necrotic cells and inflammatory cell infiltra-tion in the cerebral cortex,as well as nuclear condensation in the CA1 and GD regions of the hippocam-pus(P＜0.05,P＜0.01),and increased the area of Nissl bodies in the cerebral cortex and hippocam-pal CA3 and DG regions.Western blotting and ELISA results showed that aerobic exercise increased the expression of Occludin,ZO-1 and Claudin-5 proteins in the brain(P＜0.01),and decreased the levels of LPS in the brain(P＜0.01).The qRT-PCR results exhibited that aerobic exercise decreased the ex-pression of TLR4,MyD88,NF-κB,IL-1β,and TNF-α mRNA(P＜0.05,P＜0.01).The results of immunofluorescence staining revealed that aerobic exercise reduced the fluorescence area of brain IL-1βand TNF-α proteins(P＜0.05,P＜0.01),as well as the fluorescence area of Iba-1,GFAP,and TLR4 proteins in the cerebral cortex and hippocampus(P＜0.05,P＜0.01).There was a high degree of overlap between Iba-1 and TLR4 fluorescence in the cerebral cortex,and GFAP was localized around Iba-1.In summary,aerobic exercise attenuates neuroinflammation in AD mice by protecting the blood-brain barrier,reducing the displacement of LPS,and subsequently weakening the immune activation of microglia to regulate the TLR4/MyD88/NF-κB signaling pathway to alleviate neuroinflammation.

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.