Objective To explore the application value of dual-phase dual-energy CT (DECT) perfusion imaging in preoperative lung function assessment of lung cancer patients. Methods Data were collected from patients with stageⅠA non-small cell lung cancer who underwent surgical treatment in the Department of Thoracic Surgery, the First Affiliated Hospital of Nanjing Medical University, from November 2022 to June 2024. All patients underwent DECT perfusion imaging and pulmonary function testing (PFT) before surgery. PFT observation indicators included ventilation function indicators such as forced expiratory volume in one second (FEV1), forced vital capacity (FVC), 1-second rate (FEV1/FVC), maximal voluntary ventilation (MVV), and diffusion function indicators such as diffusing capacity for carbon monoxide (DLCO) and DLCO per liter of alveolar volume (DLCO/VA). The software eXamine was used to obtain quantitative parameters of DECT perfusion imaging, including volume parameters and perfusion parameters of both lungs and each lung lobe. The correlation between the volume parameters and perfusion parameters of both lungs and the ventilation and diffusion function indicators of the patients, as well as the differences in quantitative parameters of each lung lobe, was analyzed. Results The end-inspiration lung volume and biphasic volume difference were strongly positively correlated with FEV1 and FVC (r=0.636, r=0.682, r=0.614, r=0.624, P<0.001) and moderately positively correlated with MVV and DLCO (r=0.499, r=0.514, r=0.549, r=0.447, P<0.001); the end-expiration lung volume was weakly negatively correlated with DLCO/VA (r=−0.295, P=0.026); the volume ratio was positively correlated with FEV1, FVC, MVV, and MVV% (r=0.424, r=0.399, r=0.415, r=0.310, P<0.05); the end-inspiration iodine content was weakly positively correlated with DLCO/VA% (rs=0.292, P=0.030); the end-expiration iodine content was weakly positively correlated with FEV1, FVC, MVV, DLCO%, and DLCO/VA (r=0.307, r=0.299, r=0.295, r=0.366, r=0.320, P<0.05) and moderately positively correlated with DLCO (r=0.439, P<0.001); the end-inspiration iodine concentration was negatively correlated with FEV1, FVC, MVV, and MVV% (rs=−0.407, rs=−0.426, rs=−0.352, rs=−0.277, P＜0.05); the end-expiratory phase iodine concentration was moderately positively correlated with DLCO/VA (r=0.403, P=0.002); both the iodine concentration difference and the iodine concentration ratio were moderately positively correlated with FEV1, FEV1%, FVC, MVV, MVV% (P<0.05). The lung volume and iodine concentration ratio values were both highest in the left upper lung lobe and lowest in the right middle lung lobe; the differences in lung volume, lung volume ratio, intrapulmonary iodine content, and intrapulmonary iodine concentration were all highest in the lower lobes of both lungs and lowest in the middle lobe of the right lung. Conclusion Dual-phase DECT perfusion imaging can accurately assess overall lung function and quantify regional lung function.

[Objective] To resolve the ambiguities of HLA genotyping generated by next generation sequencing (NGS) using nanopore sequencing technology. [Methods] A total of 38 samples with ambiguous HLA genotyping by NGS in our laboratory were collected, and HLA-A, -B, -C, -DRB1, -DRB3/4/5, -DQA1, -DQB1, -DPA1 and -DPB1 loci in these samples were amplified using primers in the same commercial NGS HLA genotyping kit, then subjected to third-generation library construction, and sequenced on the nanopore sequencer. The sequencing data were converted into Fastq files and analyzed by software, and the genotypes of 11 HLA loci were obtained. The ambiguities were counted directly. [Results] The high-resolution genotyping at the second domain of 11 HLA loci of 38 samples using the third generation sequencing (TGS) were consistent with the results of the NGS method at a rate of 100%. The genotypes for the HLA-A, -B, -C, -DRB3, -DRB4, -DQA1 and -DPA1 loci by TGS were all only one result, and the discrimination rate for ambiguities of the HLA-A, -B, -C, and -DQA1 loci (all caused by the difficulty in phasing due to the short NGS read length) was 100%. Among the HLA-DRB1, -DRB5, -DQB1 and -DPB1 loci, the discrimination rate of TGS for the ambiguities caused by non-amplification of exon 1 was 0% and by the short NGS read length was 100%. [Conclusion] Nanopore technology was used to identify the ambiguities of 11 HLA loci in this study, and the ambiguities caused by the short read length disadvantage of the NGS method could be solved effectively and the accuracy of HLA genotyping would be improved.

BACKGROUND: Whether adherence to a healthy lifestyle is associated with a lower risk of developing pneumonia and a better long-term prognosis remains unclear. This study aimed to investigate associations of individual and combined lifestyle factors (LFs) with the incidence risk and long-term prognosis of pneumonia hospitalization. METHODS: Using data from the China Kadoorie Biobank study, we used the multistate models to investigate the role of five high-risk LFs, including smoking, excessive alcohol drinking, unhealthy dietary habits, physical inactivity, and unhealthy body shape, alone or in combination in the transitions from a generally healthy state at baseline to pneumonia hospitalization or cardiovascular disease (CVD, regarded as a reference outcome), and subsequently to mortality. RESULTS: Most of the five high-risk LFs were associated with increased risks of transitions from baseline to pneumonia and from pneumonia to death, but with different risk estimates. The greater the number of high-risk LFs, the higher the risk of developing pneumonia and long-term mortality risk after pneumonia, with the strength of associations comparable to that of LFs and CVD. Compared to participants with 0-1 high-risk LF, the adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for transitions from baseline to pneumonia and from pneumonia to death in those with five high-risk LFs were 1.43 (1.28-1.60) and 1.98 (1.61-2.42), respectively. Correspondingly, the respective HRs (95% CIs) for transitions from baseline to CVD and from CVD to death were 2.00 (1.89-2.11) and 1.44 (1.30-1.59), respectively. The risk estimates changed slightly when further adjusting for the presence of major chronic diseases. CONCLUSION In this Chinese population, unhealthy LFs were associated with an increased incidence and long-term mortality risk of pneumonia.
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Cardiovascular Diseases/etiology* ; China/epidemiology* ; Life Style ; Pneumonia/etiology* ; Prognosis ; Risk Factors ; Smoking

Peptide receptor radionuclide therapy (PRRT) with radiolabeled SSTR2 agonists is a treatment option that is highly effective in controlling metastatic and progressive neuroendocrine tumors (NETs). Previous studies have shown that an SSTR2 agonist combined with albumin binding moiety Evans blue (denoted as ¹⁷⁷Lu-EB-TATE) is characterized by a higher tumor uptake and residence time in preclinical models and in patients with metastatic NETs. This study aimed to enhance the in vivo stability, pharmacokinetics, and pharmacodynamics of ¹⁷⁷Lu-EB-TATE by replacing the maleimide-thiol group with a polyethylene glycol chain, resulting in a novel EB conjugated SSTR2-targeting radiopharmaceutical, ¹⁷⁷Lu-LNC1010, for PRRT. In preclinical studies, ¹⁷⁷Lu-LNC1010 exhibited good stability and SSTR2-binding affinity in AR42J tumor cells and enhanced uptake and prolonged retention in AR42J tumor xenografts. Thereafter, we presented the first-in-human dose escalation study of ¹⁷⁷Lu-LNC1010 in patients with advanced/metastatic NETs. ¹⁷⁷Lu-LNC1010 was well-tolerated by all patients, with minor adverse effects, and exhibited significant uptake and prolonged retention in tumor lesions, with higher tumor radiation doses than those of ¹⁷⁷Lu-EB-TATE. Preliminary PRRT efficacy results showed an 83% disease control rate and a 42% overall response rate after two ¹⁷⁷Lu-LNC1010 treatment cycles. These encouraging findings warrant further investigations through multicenter, prospective, and randomized controlled trials.

OBJECTIVE: To identify the nucleotide sequence of a novel HLA-DRB1*12:106 allele. METHODS: A blood donor who was joined into the database for platelet matching transfusion at the Blood Center of Zhejiang Province in 2023 was selected as the study subject. HLA genotyping was carried out through next-generation sequencing based on AllType NGS 11 locus, AllType FASTPlex NGS reagents, and Sanger sequencing method. The HLA genotype of the donor by Sanger sequencing and next generation sequencing were assigned by using uTYPE 7.3 and TypeStream Visual 3.0 software, respectively. This study was approved by Medical Ethics Committee of the Zhejiang Blood Center (Ethics No. Provincial Blood Center Ethics Review 2022 Research No. 001). RESULTS: A novel HLA-DRB1*12 allele has been identified, and the full coding sequence has been submitted to the GenBank database (No. OR101190), and the length of submitted sequence was 801 bp, which was officially named as HLA-DRB1*12:106 by the WHO Nomenclature Committee for Factors of the HLA System (submission No. HWS10066755). Compared with the sequence of the highest homology (HLA-DRB1*12:01:01:01 allele), a single nucleotide change was identified at position 344 T>G in the exon 2 of the HLA-DRB1*12:106, which has resulted in replacement of Valine by Glycine at residue 86. The HLA genotype of the proband was determined as HLA-A*02:01, 11:01;-B*13:02, 40:01;-C*01:02, 03:03;-DRB1*07:01, 12:106;-DRB3*01:01;-DRB4*01:03;-DQA1*02:01,04:01;-DQB1*02:02,04:02;-DPA1*01:03,01:03; -- DPB1*02:01:02G,04:01:01G. CONCLUSION A novel HLA-DRB1 allele has been identified in the Chinese population. The mutated amino acid, located in the peptide binding region of the β chain, may affect the binding characteristics of antigen peptides.
Humans ; HLA-DRB1 Chains/genetics* ; Alleles ; Base Sequence ; Genotype ; Male ; High-Throughput Nucleotide Sequencing ; Blood Donors

Neurofibromatosis type 1（NF1）is one of the most common autosomal dominant disorders. The disease is caused by mutations in the NF1 gene，which can involve multiple systems and have a variety of clinical manifestations，including café au lait macules，lisch nodules，neuroglioma，autism spectrum disorder，learning difficulties，neurofibromas，and skeletal dysplasia，et al.In previous studies on the pathogenesis of NF1，most of them have focused on the regulation of the RAS signaling pathway by neurofibromin. In recent years，researchers start exploring pathways other than RAS signaling to explore the potential functions of neurofibromin. This article reviews the research progress on the pathogenesis of NF1 in recent years，aiming to provide new ideas for treatment.

BACKGROUND:Based on different algorithms of machine learning,how to carry out clinical research on lumbar disc herniation with the help of various algorithmic models has become a trend and hot spot in the development of intelligent medicine at present. OBJECTIVE:To review the characteristics of different algorithmic models of machine learning in the diagnosis and treatment of lumbar disc herniation,and summarize the respective advantages and application strategies of algorithmic models for the same purpose. METHODS:The computer searched PubMed,Web of Science,EMBASE,CNKI,WanFang,VIP and China Biomedical(CBM)databases to extract the relevant articles on machine learning in the diagnosis and treatment of lumbar disc herniation.Finally,96 articles were included for analysis. RESULTS AND CONCLUSION:(1)Different algorithm models of machine learning provide intelligent and accurate application strategies for clinical diagnosis and treatment of lumbar disc herniation.(2)Traditional statistical methods and decision trees in supervised learning are simple and efficient in exploring risk factors and establishing diagnostic and prognostic models.Support vector machine is suitable for small data sets with high-dimensional features.As a nonlinear classifier,it can be applied to the recognition,segmentation and classification of normal or degenerative intervertebral discs,and to establish diagnostic and prognostic models.Ensemble learning can make up for the shortcomings of a single model.It has the ability to deal with high-dimensional data and improve the precision and accuracy of clinical prediction models.Artificial neural network improves the learning ability of the model,and can be applied to intervertebral disc recognition,classification and making clinical prediction models.On the basis of the above uses,deep learning can also optimize images and assist surgical operations.It is the most widely used model with the best performance in the diagnosis and treatment of lumbar disc herniation.The clustering algorithm in unsupervised learning is mainly used for disc segmentation and classification of different herniated segments.However,the clinical application of semi-supervised learning is relatively less.(3)At present,machine learning has certain clinical advantages in the identification and segmentation of lumbar intervertebral discs,classification and grading of the degenerative intervertebral discs,automatic clinical diagnosis and classification,construction of the clinical predictive model and auxiliary operation.(4)In recent years,the research strategy of machine learning has changed to the neural network and deep learning,and the deep learning algorithm with stronger learning ability will be the key to realizing intelligent medical treatment in the future.

To develop a framework for clinical teaching management (CTM) position competencies, and to initiate the preliminary application of this framework.

Objective To explore the effects of Qingshen Granules(QSG)on adenine-induced renal fibrosis in mice and in uric acid(UA)-stimulated NRK-49F cells and its mechanism for regulating exosomes,miR-330-3p and CREBBP.Methods A mouse model of adenine-induced renal fibrosis were treated daily with QSG at 8.0 g·kg-1·d-1 via gavage for 12 weeks.An adeno-associated virus vector was injected into the tail vein,and renal tissues of the mice were collected for analyzing exosomal marker proteins CD9,Hsp70,and TSG101 and expressions of Col-Ⅲ,α-SMA,FN,and E-cad using Western blotting and immunofluorescence and for observing pathological changes using HE and Masson staining.In the cell experiment,NRK-49F cells were stimulated with uric acid(400 μmol/L)followed by treatment with QSG-medicated serum from SD rats,and the changes in expressions of the exosomal markers and Col-Ⅲ,α-SMA,FN,and E-cad were analyzed.Dual luciferase reporter assay was employed to examine the targeting relationship between miR-330-3p and CREBBP,whose expressions were detected by RT-qPCR and Western blotting in treated NRK-49F cells.Results The mouse models of adenine-induced renal fibrosis showed significantly increased levels of CD9,Hsp70,and TSG101,which were decreased by treatment with QSG.The expressions of Col-Ⅲ,α-SMA,and FN increased and E-cad decreased in the mouse models but these changes were reversed by QSG treatment.QSG treatment obviously alleviated renal fibrosis in the mouse models.Intravenous injection of adeno-associated viral vector obviously inhibited miR-330-3p,increased CREBBP levels,and reduced fibrosis in the mouse models.Dual luciferase assay confirmed CREBBP as a target of miR-330-3p,which was consistent with the results of the cell experiments.Conclusion QSG inhibits renal fibrosis in mice by regulating the exosomes,reducing miR-330-3p levels,and increasing CREBBP expression.

Objective:To analyze the sequence of a novel HLA- DPB1 allele in an individual. Methods:A individual identified from the database of blood donors for matched platelet transfusion at the Blood Center of Zhejiang Province in May 2022 was selected as the study subject. HLA genotype of the individual was determined by next-generation sequencing (NGS) on an Ion Torrent S5 platform. The sequence of the HLA- DPB1 locus was also determined by NGS on an Illumina Miseq platform and third generation sequencing using Oxford Nanopore MinION. This study was approved by Medical Ethics Committee of the Blood Center of Zhejiang Province (Ethics No. 2021-001). Results:A novel HLA- DPB1*02 allele was identified in the specimen, for which the closest genotype was HLA- DPB1*02: new, 17: 01: 01G, with the variant located in exon 3. Meanwhile, the NGS also revealed a novel HLA- DPB1*17 allele, with the closest genotype being HLA- DPB1*02: 01: 02G, 17: new. Both the HLA- DPB1*17: 01: 01: 01 and novel HLA- DPB1*02 alleles were identified by third-generation sequencing. Compared with the HLA- DPB1*02: 01: 02: 01 allele, the novel allele had a G>A variation at position 369 in the exon 3, which did not result in amino acid change. Conclusion:A novel HLA- DPB1 allele has been identified and validated by both NGS and TGS, which has been named as HLA- DPB1*02: 01: 69 by the World Health Organization Committee on Nomenclature of Factors of the HLA System.