OBJECTIVE: To explore the construction method of a resistant multiple myeloma (MM) patient-derived xenotransplantation (PDX) model. METHODS: 1.0×10⁷ MM patient-derived mononuclear cells (MNCs), 2.0×10⁶ MM.1S cells and 2.0×10⁶ NCI-H929 cells were respectively subcutaneously inoculated into NOD.CB17-Prkdc^scid Il2rg^tm1/Bcgen (B-NDG) mice with a volume of 100 μl per mouse to establish mouse model. The morphologic, phenotypic, proliferative and genetic characteristics of PDX tumor were studied by hematoxylin-eosin staining, immunohistochemical staining (IHC), cell cycle analysis, flow cytometry and fluorescence in situ hybridization (FISH). The sensitivity of PDX tumor to bortezomib and anlotinib monotherapy or in combination was investigated through cell proliferation, apoptosis and in vitro and in vivo experiments. The effects of anlotinib therapy on tumor blood vessel and cell apoptosis were analyzed by IHC, TUNEL staining and confocal fluorescence microscope. RESULTS: MM PDX model was successfully established by subcutaneously inoculating primary MNCs. The morphologic features of tumor cells from MM PDX model were similar to those of mature plasma cells. MM PDX tumor cells positively expressed CD138 and CD38, which presented 1q21 amplification, deletion of Rb1 and IgH rearrangement, and had a lower proliferative activity than MM cell lines. in vitro, PDX, MM.1S and NCI-H929 cells were treated by bortezomib and anlotinib for 24 hours, respectively. Cell viability assay showed that the IC₅₀ value of bortezomib were 5 716.486, 1.025 and 2.775 nmol/L, and IC₅₀ value of anlotinib were 5 5107.337, 0.706 and 5.13 μmol/L, respectively. Anlotinib treatment increased the apoptosis of MM.1S cells (P < 0.01), but did not affect PDX tumor cells (P >0.05). in vivo, there was no significant difference in PDX tumor growth between bortezomib monotherapy group and control group (P >0.05), while both anlotinib monotherapy and anlotinib combined with bortezomib effectively inhibited PDX tumor growth (both P < 0.05). The vascular perfusion and vascular density of PDX tumor were decreased in anlotinib treatment group (both P < 0.01). The apoptotic cells in anlotinib treatment group were increased compared with those in control group (P < 0.05). CONCLUSION Bortezomib-resistant MM PDX model can be successfully established by subcutaneous inoculation of MNCs from MM patients in B-NDG mice. This PDX model, which retains the basic biological characteristics of MM cells, can be used to study the novel therapies.
Animals ; Bortezomib ; Humans ; Multiple Myeloma/pathology* ; Mice ; Apoptosis ; Drug Resistance, Neoplasm ; Cell Line, Tumor ; Xenograft Model Antitumor Assays ; Mice, Inbred NOD ; Disease Models, Animal ; Cell Proliferation ; Transplantation, Heterologous

BACKGROUND: Spicy food consumption has been reported to be inversely associated with mortality from multiple diseases. However, the effect of spicy food intake on the incidence of vascular diseases in the Chinese population remains unclear. This study was conducted to explore this association. METHODS: This study was performed using the large-scale China Kadoorie Biobank (CKB) prospective cohort of 486,335 participants. The primary outcomes were vascular disease, ischemic heart disease (IHD), major coronary events (MCEs), cerebrovascular disease, stroke, and non-stroke cerebrovascular disease. A Cox proportional hazards regression model was used to assess the association between spicy food consumption and incident vascular diseases. Subgroup analysis was also performed to evaluate the heterogeneity of the association between spicy food consumption and the risk of vascular disease stratified by several basic characteristics. In addition, the joint effects of spicy food consumption and the healthy lifestyle score on the risk of vascular disease were also evaluated, and sensitivity analyses were performed to assess the reliability of the association results. RESULTS: During a median follow-up time of 12.1 years, a total of 136,125 patients with vascular disease, 46,689 patients with IHD, 10,097 patients with MCEs, 80,114 patients with cerebrovascular disease, 56,726 patients with stroke, and 40,098 patients with non-stroke cerebrovascular disease were identified. Participants who consumed spicy food 1-2 days/week (hazard ratio [HR] = 0.95, 95% confidence interval [95% CI] = [0.93, 0.97], P <0.001), 3-5 days/week (HR = 0.96, 95% CI = [0.94, 0.99], P = 0.003), and 6-7 days/week (HR = 0.97, 95% CI = [0.95, 0.99], P = 0.002) had a significantly lower risk of vascular disease than those who consumed spicy food less than once a week ( Ptrend <0.001), especially in those who were younger and living in rural areas. Notably, the disease-based subgroup analysis indicated that the inverse associations remained in IHD ( Ptrend = 0.011) and MCEs ( Ptrend = 0.002) risk. Intriguingly, there was an interaction effect between spicy food consumption and the healthy lifestyle score on the risk of IHD ( Pinteraction = 0.037). CONCLUSIONS Our findings support an inverse association between spicy food consumption and vascular disease in the Chinese population, which may provide additional dietary guidance for the prevention of vascular diseases.
Humans ; Male ; Female ; Prospective Studies ; Middle Aged ; Aged ; Vascular Diseases/etiology* ; Risk Factors ; China/epidemiology* ; Adult ; Proportional Hazards Models ; Cerebrovascular Disorders/epidemiology* ; East Asian People

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*

OBJECTIVE: To investigate the molecular mechanism of weak D phenotype in a Chinese family. METHODS: Routine Rh typing tests were performed first, and RHD exons 1-10 of the proband and his family members were sequenced by first-generation sequencing. RHD zygosity was also determined. Third-generation sequencing was used to analyze the haplotypes of the RHD gene. RESULTS: The proband showed a weak D serological phenotype. First-generation sequencing revealed a c.787G>A point mutation in exon 5. The family pedigree investigation showed that the proband and his younger sister had the same serological phenotype and molecular mechanism. His father carried this gene mutation, while his mother and younger brother were normal. Hybrid box was not detected, suggesting that all the family members did not have a haplotype with a complete deletion of the RHD gene. The results of third-generation sequencing showed that the proband and his sister inherited the weak D allele from their father and the non-functional allele RHD -CE(3-9)-D from their mother, respectively. CONCLUSION Third-generation sequencing technology enables haplotype analysis of the RHD gene and can detect complex genotypes such as genetic exchanges between RHD and RHCE combined with other mutations.
Female ; Humans ; Male ; Alleles ; Exons ; Genotype ; Haplotypes ; High-Throughput Nucleotide Sequencing ; Pedigree ; Phenotype ; Rh-Hr Blood-Group System/genetics* ; East Asian People/genetics*

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

Digital technologies have become an integral part of complete denture restoration. With advancement in computer-aided design and computer-aided manufacturing (CAD/CAM), tools such as intraoral scanning, facial scanning, 3D printing, and numerical control machining are reshaping the workflow of complete denture restoration. Unlike conventional methods that rely heavily on clinical experience and manual techniques, digital technologies offer greater precision, predictability, and efficacy. They also streamline the process by reducing the number of patient visits and improving overall comfort. Despite these improvements, the clinical application of digital complete denture restoration still faces challenges that require further standardization. The major issues include appropriate case selection, establishing consistent digital workflows, and evaluating long-term outcomes. To address these challenges and provide clinical guidance for practitioners, this expert consensus outlines the principles, advantages, and limitations of digital complete denture technology. The aim of this review was to offer practical recommendations on indications, clinical procedures and precautions, evaluation metrics, and outcome assessment to support digital restoration of complete denture in clinical practice.
Humans ; Denture, Complete ; Computer-Aided Design ; Denture Design/methods* ; Consensus ; Printing, Three-Dimensional

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*

Nano liquid chromatography-high resolution tandem mass spectrometry(LC-HRMS/MS)is widely used for body fluid peptidome analysis,yet the impact of replicate analyses remains overlooked.Using salivary peptidome,in this work,10 replicate analyses of the same sample were conducted.It was found that although m/z and molecular weight ranges were consistent across replicates,single runs identified only 348-576 unique peptides from 32-39 degraded proteins.Merging all replicates revealed 1237 peptides from 77 proteins,a 2.5 folds increase in peptides and 2 folds increase in proteins.Instrument stability was confirmed via intensity/retention time of 12 peptides.Merged peptides primarily derived from high-abundance proteins(e.g.,Statherin,PRP1/2).Analysis of 20 peptides showed that the some peptides were detected in single analysis but confidence varying(19%-99%),low-confidence peptides(<95%)exceeded 95%after replicate.signal intensity alone didn't determine confidence and peptides spanning the sequence region between the longest and the shortest detected fragments could be identified.The above findings suggested that single-run LC-MS peptidomics analysis carried inherent false negatives and uncertainties.However,by integrating the results of a single analysis with the mechanism of enzymatic hydrolysis for endogenous peptides,it was possible to make reasonable inferences and extrapolations regarding peptides derived from highly abundant degraded proteins.

Objective To propose a high-precision deep learning-based image assessment method of osteosarcoma chemotherapy efficacy for clinical treatment,as existing methos have low accuracy of osteosarcoma assessment.Methods The low incidence of osteosarcoma led to the small scale of its imaging data and the problem of imbalance in data categories.This study combined deep learning with clinical medical information,combined the bone sarcoma generation module of BoneGAN and the scale lesion information capture module,and proposed OMLA-Net,a deep learning assessment network for chemotherapy effect of bone sarcoma based on multi-scale lesion attention network,which achieved computer-aided bone tumor assessment with integrated data augmentation and focused lesion information through pre-training and generalized loss training.Results In this study,40 cases of osteosarcoma MRI data were used as the basis for the comparison test on the generated dataset,and the OMLA-Net assessment outperformed the SOTA method Conv-LSTM-GAN in terms of the assessment effects such as accuracy and F1 scores,and the difference was statistically significant(Bootstrap statistical method P＜0.05);the subsequent K-fold cross-validation ablation experiments further demonstrated the effectiveness of each module proposed by OMLA-Net.Conclusion OMLA-Net can effectively perform the impact assessment of chemotherapy effect on osteosarcoma,which provides a new idea for subsequent clinical application.

Nucleic acid-based molecular diagnostic methods are considered the gold standard for detecting infectious pathogens.However,when applied to portable or on-site rapid diagnostics,they still face various limitations and challenges,such as poor specificity,cumbersome operation,and portability difficulties.The CRISPR(Clustered regularly interspaced short palindromic repeats)/CRISPR-associated protein(Cas)-fluorescence detection method holds the potential to significantly enhance the specificity and signal-to-noise ratio of nucleic acid detection.In this study,we developed a portable grayscale reader detection system based on loop-mediated isothermal amplification(LAMP)-CRISPR/Cas.On one hand,in the presence of CRISPR RNA(crRNA),the CRISPR/Cas12a system was employed to achieve precise fluorescent detection of self-designed LAMP amplification reactions for influenza A and influenza B viruses.This further validated the high selectivity and versatility of the CRISPR/Cas system.On the other hand,the accompanying independently developed portable grayscale reader allowed for low-cost collection of fluorescence signals and high-reliability visual interpretation.At the end of the detection process,it directly provided positive or negative results.Practical sample analyses using this detection system have verified its reliability and utility,demonstrating that this system can achieve highly sensitive and highly specific portable analysis of influenza viruses.