OBJECTIVE To develop the quality evaluation standard indicator system for hospital cough and wheeze pharmaceutical care clinic （CWPC） pharmacist training within the layered learning practice model （LLPM）， and apply it in clinical practice. METHODS Our teaching team established an LLPM model to train cough and wheeze pharmacists， according to the actual conditions of our college. Using qualitative interview methods， expert questionnaires were compiled with literature research； the expert correspondence methods were employed to conduct two rounds of consultation with 10 domestic respiratory medicine experts， thus constructing an evaluation index system for the teaching quality of cough and wheeze pharmacists. The experts’ positive coefficient， authority coefficient， Kendall’s harmony coefficient， and the degree of concentration of opinions were calculated. The analytic hierarchy process （AHP） was used to determine the weight of each indicator within the index system. From June 2023 to June 2024， the teaching team enrolled 21 pharmacists in the training program. The teaching team assessed and scored the trial group （LLPM） and control group （traditional teaching model） based on the benefit indicators for pharmacists and patients in the evaluation index system， and compared the results. RESULTS This study explored the establishment of a training system for cough and wheeze pharmacists under the LLPM model， and initially established an evaluation index system using the Delphi method. In two rounds of Delphi method questionnaires， the recovery rate was 100%， with an authority coefficient exceeding 0.8， Kendall’s harmony coefficient ranging from 0.235 to 0.459， and all P-values being less than 0.05. Four primary （comprising trainee feedback， learning gains， behavioral improvements， and training performance）， 12 secondary and 33 tertiary indicators were finalized. In the empirical evaluation， the results of the two groups showed a significant benefit to the pharmacists in the trial group. Specifically， the percentage of patients receiving corticosteroids for COPD or wheeze service patients per month （80.5%）， an average increase in the number of cough and wheeze team service outpatient visits per month （compared to the same period of the previous year） of 14.8 visits per month， and the patient satisfaction score （4.9） were all significantly higher than those in the control group （P＜0.05）. CONCLUSIONS The application of the LLPM in competency training for pharmacists specializing in cough and wheeze care yields multiple benefits and holds significant guiding value. The constructed training quality evaluation index system under this model is scientific and reliable.

Objective To identify potential drug target genes associated with idiopathic pulmonary fibrosis(IPF)and predict therapeutic candidates using a two-sample Mendelian randomization(MR)approach across the druggable genome.Methods Druggable genome data from the DGIdb database and Finan were integrated to identify overlapping genes.A two-sample MR analysis was performed to infer causal relationships between genes and IPF.Functional enrichment analyses,including Gene Ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG),were conducted to explore biological pathways.Drug-target interactions were predicted via DSigDB database screening,followed by molecular docking simulations to evaluate binding affinities.Results Among the 2588 overlapping druggable genes,thirty exhibited significant causal associations with IPF(P＜0.05).Four hub genes(NOD2,LATS2,LTA,and TCF7L2)were enriched in IPF-related pathways,notably Hippo and TNF signaling.Six potential therapeutics were identified:oxyphenbutazone,moexipril,α-galactosylceramide,GSK429286A,CGP74514A,and JW-7-24-1.Molecular docking confirmed strong binding affinities between these drugs and their targets.Conclusion This study has identified thirty druggable gene targets and six candidate drugs for IPF.The enrichment of hub genes in key pathways and validated drug-target interactions provide insights into IPF therapies.

Objective:To summarize the clinical features and genetic effects of cases of fetal chromosomal structural abnormalities caused by maternal complex chromosomal rearrangements (CCR).Methods:Three female CCR carriers referred to the Prenatal Diagnostic Center at Guangzhou Women and Children's Medical Center, Guangzhou Medical University between October 2023 and June 2024 were retrospectively enrolled. Genetic analyses included chromosomal karyotyping, chromosomal microarray analysis (CMA), and low-coverage whole-genome copy number variation (CNV) sequencing. Clinical features of the three cases with fetal chromosomal structural abnormalities caused by maternal CCR were systematically reviewed using descriptive statistics.Results:(1) Case 1: CNV sequencing identified an 11.95 Mb duplication at 1q43q44 region of chromosome (CNV of uncertain significance) and a 36.09 Mb deletion at 5p15.33p13.2 region of chromosome (pathogenic CNV) in the fetus (maternally inherited). Maternal karyotype was 46,XX,t(1;8;3;5)(q43;q22.1;q26.2;p13.2). The pregnancy was terminated after genetic counseling. (2) Case 2: Maternal karyotype 46,XX,t(3;20)(p25;q13.1),t(6;12)(q25.2;q21.2),ins(11;14)(q23;q24q13) was transmitted to the fetus [46,XX,ins(11;14)(q23;q24q13)mat]. CMA of the fetus showed no abnormalities and the pregnancy was continued after genetic counseling. (3) Case 3: CMA of the products of conception revealed a 71.59 Mb duplication at 2p24.3p11.2 (pathogenic CNV). Maternal karyotype was 46,XX,der(2)t(2;3)(q21;q23)ins(11;2)(p13;p24p11.2),der(3)t(2;3),der(11)ins(11;2). The abnormal chromosome 2 segment in products of conception was maternally inherited.Conclusions:All three cases of fetal/abortus chromosomal abnormalities originated from maternal CCR. Early combined cytogenetic and molecular prenatal diagnosis is critical for CCR carriers during pregnancy.

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.

Ivonescimab is a humanized bispecific antibody targeting human vascular endothelial growth factor-A(VEGF-A)and programmed death protein-1(PD-1).It was approved by National Medi-cal Products Administration on May 24th,2024,and can be used in combination with pemetrexed and carboplatin for locally advanced or positive EG-FR gene mutation after treatment with epidermal growth factor receptor(EGFR)tyrosine kinase inhib-itor.This paper mainly introduces the research progress of the world's first PD-1/VEGF bispecific antibody ivonescimab,and summarizes the mecha-nism of action,pharmacokinetics,phase Ⅰ-Ⅲ clinical trials and drug safety.

Ivonescimab is a humanized bispecific antibody targeting human vascular endothelial growth factor-A(VEGF-A)and programmed death protein-1(PD-1).It was approved by National Medi-cal Products Administration on May 24th,2024,and can be used in combination with pemetrexed and carboplatin for locally advanced or positive EG-FR gene mutation after treatment with epidermal growth factor receptor(EGFR)tyrosine kinase inhib-itor.This paper mainly introduces the research progress of the world's first PD-1/VEGF bispecific antibody ivonescimab,and summarizes the mecha-nism of action,pharmacokinetics,phase Ⅰ-Ⅲ clinical trials and drug safety.

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.

Objective:To summarize the clinical features and genetic effects of cases of fetal chromosomal structural abnormalities caused by maternal complex chromosomal rearrangements (CCR).Methods:Three female CCR carriers referred to the Prenatal Diagnostic Center at Guangzhou Women and Children's Medical Center, Guangzhou Medical University between October 2023 and June 2024 were retrospectively enrolled. Genetic analyses included chromosomal karyotyping, chromosomal microarray analysis (CMA), and low-coverage whole-genome copy number variation (CNV) sequencing. Clinical features of the three cases with fetal chromosomal structural abnormalities caused by maternal CCR were systematically reviewed using descriptive statistics.Results:(1) Case 1: CNV sequencing identified an 11.95 Mb duplication at 1q43q44 region of chromosome (CNV of uncertain significance) and a 36.09 Mb deletion at 5p15.33p13.2 region of chromosome (pathogenic CNV) in the fetus (maternally inherited). Maternal karyotype was 46,XX,t(1;8;3;5)(q43;q22.1;q26.2;p13.2). The pregnancy was terminated after genetic counseling. (2) Case 2: Maternal karyotype 46,XX,t(3;20)(p25;q13.1),t(6;12)(q25.2;q21.2),ins(11;14)(q23;q24q13) was transmitted to the fetus [46,XX,ins(11;14)(q23;q24q13)mat]. CMA of the fetus showed no abnormalities and the pregnancy was continued after genetic counseling. (3) Case 3: CMA of the products of conception revealed a 71.59 Mb duplication at 2p24.3p11.2 (pathogenic CNV). Maternal karyotype was 46,XX,der(2)t(2;3)(q21;q23)ins(11;2)(p13;p24p11.2),der(3)t(2;3),der(11)ins(11;2). The abnormal chromosome 2 segment in products of conception was maternally inherited.Conclusions:All three cases of fetal/abortus chromosomal abnormalities originated from maternal CCR. Early combined cytogenetic and molecular prenatal diagnosis is critical for CCR carriers during pregnancy.

Objective:This study aimed to construct a risk prediction model for obstructive sleep apnea（OSA） related hypertension based on the nomogram, and to explore the independent risk factors for OSA-related hypertension, so as to provide reference for clinical treatment decision-making. Methods:The clinical data of OSA patients diagnosed by polysomnography from October 2019 to December 2021 were collected retrospectively and randomly divided into training sets and validation sets. A total of 1 493 OSA patients with 27 variables were included. The least absolute shrinkage and selection operator（Lasso） logistic regression model was used to select potentially relevant features and establish a nomogram for OSA-related hypertension.The performance and clinical benefits of this nomogram were verified in terms of discrimination, calibration ability and clinical net benefit. Results:Multivariate logistic regression showed that body mass index（BMI）, family history of hypertension, lowest oxygen saturation（LSaO2）, age and cumulative percentage of total sleep time with oxygen saturation below 90% were independent risk factors for OSA-related hypertension. Lasso logistic regression identified BMI, family history of hypertension, LSaO2 and age as predictive factors for inclusion in the nomogram. The nomogram provided a favorable discrimination, with a C-indexes of 0.835（95% confidence interval[CI ]0.806-0.863） 0.865（95%CI 0.829-0.900） for the training and validation cohort, respectively, and well calibrated. The clinical decision curve analysis displayed that the nomogram was clinically useful. Conclusion:Compared with cumulative percentage of total sleep time with blood oxygen saturation below 90%, LSaO2 may have a greater impact on the incidence of OSA-related hypertension, and the effects of different times and degrees of hypoxia on OSA-related hypertension should be further explored in the future. Apnea hypopnea index involvement is weak in predicting OSA-related hypertension, and the blood oxygen index may be a better predictor variable. Furthermore, we established a risk prediction model for OSA-related hypertension patients using nomogram, and demonstrated that this prediction model was helpful to identify high-risk OSA-related hypertension patients. This model can provide early and individualized diagnosis and treatment plans, protect patients from the serious.
Humans ; Sleep Apnea, Obstructive/complications* ; Nomograms ; Hypertension/epidemiology* ; Male ; Female ; Risk Factors ; Middle Aged ; Retrospective Studies ; Polysomnography ; Logistic Models ; Body Mass Index ; Adult

BACKGROUND:As a unique structure of the cervical spine,the occurrence,development and progression of the uncovertebral joint directly affect the stability and range of motion of the cervical spine,and are also closely related to the pathogenesis of cervical spondylosis.A thorough understanding of the developmental characteristics of the uncovertebral joint is of great significance for the pathogenesis,diagnosis,and treatment of cervical spondylosis. OBJECTIVE:By using imaging and three-dimensional reconstruction technology to measure and observe the cervical uncinate process-related angle in a large sample of different age groups,the aim is to reveal the characteristics of its changes with age and vertebral growth,as well as its relationship with cervical spine stability. METHODS:Using a retrospective research design,we collected 1 447 cases of raw CT imaging data that meet the study requirements for complete cervical spine segments.The raw data were imported into Mimics 21.0 software in DICOM format for post-processing and measurement of angle of uncinate process and sagittal angle of uncinate process.The data were grouped based on gender,age,and side. RESULTS AND CONCLUSION:(1)With the increase of vertebral sequence,the angle of uncinate process increased in a V-shaped shape,and the lowest peak was at C5.The overall population showed a sharp peak with the increase of age,and the peak value mostly occurred in the age range of 30-39 years.(2)The sagittal angle of the uncinate process increased like a fishhook with the increase of the vertebral sequence,and the overall angle of the uncinate process increased with age,and the peak value mostly occurred in the age range of 20-29 years.The uncinate process angle and sagittal angle showed only partial significant differences between sides and genders(P<0.05).(3)It is concluded that the angle of the uncinate process increased with the increase of vertebral sequence in a V-shaped manner.The sagittal angle of the uncinate process increases like a fish hook with increasing vertebral order,while the two angles generally peak with increasing age.The angle of the uncinate process is about 131°,which may be closely related to the stability of the cervical spine,while the sagittal angle of the uncinate process is about 14°,and its function may play a certain role in limiting the excessive rotation of the cervical spine.