OBJECTIVE: To investigate the clinical characteristics and genetic etiology in a fetus with 12q14 microdeletion syndrome. METHODS: A fetus diagnosed with 12q14 microdeletion syndrome at Wenzhou People's Hospital in July 2019 was selected as the study subject. The fetus was from a twin pregnancy by in vitro fertilization-embryo transfer, with ultrasound findings including growth restriction, cleft lip/palate, ventricular septal defect, tricuspid regurgitation, and pericardial effusion. Clinical data and family history were collected. Amniotic fluid sample was collected from both twins, and peripheral blood samples were obtained from their parents. Amniocytic karyotyping analysis and chromosomal microarray analysis (CMA) were performed, and familial validation was conducted. This study was approved by the Medical Ethics Committee of Wenzhou People's Hospital (Ethics No.: KY-202408-034). RESULTS: Prenatal ultrasound showed no significant abnormality in one of the twins, whilst the other twin exhibited severe growth restriction accompanied by cleft lip/palate, ventricular septal defect, tricuspid regurgitation, and pericardial effusion. Karyotyping and CMA analyses of first twin showed no abnormalities, whilst the second twin had a chromosomal karyotype of 46,XN,t(3;12)(q26.3;q14), and CMA revealed a 4.9 Mb deletion in the 12q14.3-q15 region (arr[hg19]12q14.3q15(65,574,059_70,488,106)x1). Karyotyping and CMA analyses of both parents revealed no abnormalities, confirming that the fetus deletion was de novo in origin. Literature review suggested that prenatal diagnosis of 12q14 microdeletion syndrome has been extremely rare. CONCLUSION The fetus was diagnosed with 12q14 microdeletion syndrome. This de novo deletion may have dervied from chromosomal translocation. As a first-tier prenatal diagnostic technique, CMA can effectively detect microdeletion/microduplications missed by conventional karyotyping analysis.
Humans ; Female ; Pregnancy ; Chromosome Deletion ; Chromosomes, Human, Pair 12/genetics* ; Karyotyping ; Adult ; Prenatal Diagnosis ; Chromosome Disorders/diagnosis* ; Ultrasonography, Prenatal ; Fetus ; Male

Objective In view of the potential threat of adverse drug reaction(ADR)to patients'health and the limitations of traditional monitoring methods,this study investigates the construction method of an ADR knowledge graph based on a knowledge-driven technology path to promote the intelligent upgrading of pharmacovigilance field.Methods In this study,an adverse drug reaction knowledge base was established,and the data within the knowledge base were preprocessed.The BERT-CRF model was utilized to identify and extract the relevant entities,relationships and attribute information,and knowledge alignment was carried out by combining the rule method and statistical method.The knowledge fusion data was stored in the Neo4j graph database to construct the knowledge graph.Results Based on the established knowledge base,this study explored the method of constructing knowledge graph of adverse drug reaction by knowledge-driven technology,laying the groundwork for data mining and the development of intelligent auxiliary system tools based on knowledge graph.Conclusions The study on the construction method of an ADR knowledge graph based on a knowledge-driven technology path provides a new perspective and technical path for the intelligent upgrading of pharmacovigilance field.It holds important theoretical and practical significance for improving drug safety,protecting patients'health,and promoting the healthy development of pharmaceutical industry.

Bone marrow adipose tissue(BMAT)is not merely a filler of bone marrow cavity,but also possesses active endocrine and paracrine functions related to metabolic diseases,bone diseases and hematological disorders,etc.Non-invasive quantitative measurement of BMAT has great clinical significances.Currently,imaging methods for quantitative measurement of BMAT include conventional MRI,hydrogen proton MR spectroscopy,chemical shift imaging,Dixon technique and CT.Their principles and clinical applications were reviewed in this article.

Objective In view of the potential threat of adverse drug reaction(ADR)to patients'health and the limitations of traditional monitoring methods,this study investigates the construction method of an ADR knowledge graph based on a knowledge-driven technology path to promote the intelligent upgrading of pharmacovigilance field.Methods In this study,an adverse drug reaction knowledge base was established,and the data within the knowledge base were preprocessed.The BERT-CRF model was utilized to identify and extract the relevant entities,relationships and attribute information,and knowledge alignment was carried out by combining the rule method and statistical method.The knowledge fusion data was stored in the Neo4j graph database to construct the knowledge graph.Results Based on the established knowledge base,this study explored the method of constructing knowledge graph of adverse drug reaction by knowledge-driven technology,laying the groundwork for data mining and the development of intelligent auxiliary system tools based on knowledge graph.Conclusions The study on the construction method of an ADR knowledge graph based on a knowledge-driven technology path provides a new perspective and technical path for the intelligent upgrading of pharmacovigilance field.It holds important theoretical and practical significance for improving drug safety,protecting patients'health,and promoting the healthy development of pharmaceutical industry.

Bone marrow adipose tissue(BMAT)is not merely a filler of bone marrow cavity,but also possesses active endocrine and paracrine functions related to metabolic diseases,bone diseases and hematological disorders,etc.Non-invasive quantitative measurement of BMAT has great clinical significances.Currently,imaging methods for quantitative measurement of BMAT include conventional MRI,hydrogen proton MR spectroscopy,chemical shift imaging,Dixon technique and CT.Their principles and clinical applications were reviewed in this article.

Objective To investigate the longitudinal association between alcohol abstinence and accelerated biological aging among middle-aged and older adults and to explore the potential effect modifiers influencing the association.Methods Utilizing the clinico-biochemical and anthropometric data from the baseline and first repeat survey of the UK Biobank(UKB),we employed the Klemera and Doubal method(KDM)to construct the biological age(BA)and calculate BA acceleration.Change analysis based on multivariate linear regression models was employed to explore the association between changes in alcohol abstinence and changes in BA acceleration.Age,sex,smoking status,tea and coffee consumption,and body mass index were considered as the stratification factors for conducting stratified analysis.Results A total of 5 412 participants were included.Short-term alcohol abstinence(β=1.00,95%confidence interval[CI]:0.15-1.86)was found to accelerate biological aging when compared to consistent never drinking,while long-term abstinence(β=-0.20,95%CI:-1.12-0.71)did not result in a significant acceleration of biological aging.Body mass index may be a potential effect modifier.Conclusion Short-term alcohol abstinence was associated with accelerated biological aging,but the effect gradually diminishes over extended periods of abstinence.

Objective This study analyzes the risk points in the quality control of bioink and the main processes of bioprinting,clarifies and explores the quality control and supervision model for bioprinting medical devices,and provides theoretical and practical guidance to ensure the safety and effectiveness of bioprinting medical devices.Methods The quality control risk points throughout the bioprinting process were comprehensively analyzed,with a particular focus on bioprinting materials and key processes.The regulatory model and methods for bioprinting medical devices were examined.This research concentrated on critical technologies such as extrusion,laser-assisted,and in situ bioprinting,assessing their potential for clinical applications and regulatory challenges.Results Bioink from different sources should meet regulatory requirements.It is essential to ensure aseptic handling of raw materials and to validate sterilization under"worst-case"conditions.Conclusion As bioprinting technology advances rapidly,corresponding research into materials,processes,and quality risk control should be conducted to ensure the concurrent development of the regulatory system.This will continuously contribute to the orderly progression of the entire industry and human health.

Deficiency of natural killer (NK) cells shows a significant impact on tumor progression and failure of immunotherapy. It is highly desirable to boost NK cell immunity by upregulating active receptors and relieving the immunosuppressive tumor microenvironment. Unfortunately, mobilization of NK cells is hampered by poor accumulation and short retention of drugs in tumors, thus declining antitumor efficiency. Herein, we develop an acid-switchable nanoparticle with self-adaptive aggregation property for co-delivering galunisertib and interleukin 15 (IL-15). The nanoparticles induce morphology switch by a decomposition-metal coordination cascade reaction, which provides a new methodology to trigger aggregation. It shows self-adaptive size-enlargement upon acidity, thus improving drug retention in tumor to over 120 h. The diameter of agglomerates is increased and drug release is effectively promoted following reduced pH values. The nanoparticles activate both NK cell and CD8⁺ T cell immunity in vivo. It significantly suppresses CT26 tumor in immune-deficient BALB/c mice, and the efficiency is further improved in immunocompetent mice, indicating that the nanoparticles can not only boost innate NK cell immunity but also adaptive T cell immunity. The approach reported here provides an innovative strategy to improve drug retention in tumors, which will enhance cancer immunotherapy by boosting NK cells.

ObjectiveTo investigate the status of self-efficacy, quality of care and quality of life of people with physical disabilities, and analyze the relationship among them. MethodsFrom January, 2019 to December, 2020, 357 people with physical disabilities in Shandong were selected with cluster stratified random sampling, and all the participants were investigated with a general questionnaire, World Health Organization Quality of Life-Disability Scales, General Self-Efficacy Scale and World Health Organization Quality of Care and Support Scale-Disability Scale on internet. ResultsA total of 357 questionnaires were collected, in which 350 were valid. The total score was (115.00±20.70) for quality of life, (23.33±5.78) for self-efficacy, and (50.43±10.56) for quality of care. The quality of life and its each domain was positively correlated with self-efficacy (r > 0.282, P < 0.01), quality of care, care information acquisition, care giving and care environment (r > 0.369, P < 0.01). Employment, self-efficacy and quality of care associated with the quality of life (t > 4.386, P < 0.001); employment, self-efficacy, care giving and care environment associated with the physiological, psychological and environment domains of the quality of life (t > 2.926, P < 0.01); parents as main caregivers, employment, self-efficacy, care giving and care environment associated with social relationships domain of the quality of life (|t| > 2.525, P < 0.05); parents as main caregivers, employment, care giving and care environment associated with the disability domain of the quality of life (|t| > 2.209, P < 0.05). ConclusionThe quality of life needs to be improved for the people with physical disabilities. Self-efficacy and quality of care may impact the quality of life; and it is needed to focus on the people with physical disabilities who are unemployed and whose parents are the main caregivers.

Objective:To investigate the predictive value of pan-immune-inflammation value (PIV) for in-hospital mortality in patients with acute ischemic stroke (AIS) admitted to intensive care unit (ICU).Methods:The clinical data of the first-ever AIS patients admitted to the ICU in the Medical Information Mart for Intensive Care (MIMIC) -Ⅳ of the United States were retrospectively included and analyzed. According to whether the patients died in the hospital, they were divided into a survival group and a death group, and the differences in baseline data between the two groups were compared. Multivariate logistic regression model was used to analyze independent influencing factors of in-hospital mortality in patients. Receiver operating characteristic curve was used to evaluate the predictive value of PIV on in-hospital mortality. Results:A total of 1 068 first-ever AIS patients admitted to the ICU were included, with a median age of 69 years. There were 543 males (50.84%), and 182 (17.05%) experienced in-hospital mortality. Multivariate logistic regression analysis showed that after adjusting for potential confounding factors, a higher PIV (>1 555.71) was an independent risk factor for in-hospital mortality in patients (odds ratio 1.924, 95% confidence interval 1.093-3.387; P=0.023). The receiver operating characteristic curve analysis showed that the area under the curve for predicting in-hospital mortality by PIV was 0.605 (95% confidence interval 0.556-0.654), with an optimal cutoff value of 1 199.93. The sensitivity and specificity for predicting in-hospital mortality were 48.9% and 70.2%, respectively. Conclusions:A higher PIV is an independent risk factor for in-hospital mortality in AIS patients admitted to ICU, which may help identify AIS patients with a higher risk of in-hospital mortality in the ICU.