Objective To examine the impact of extreme temperature and drought stress on the survival of Bulinus globosus, so as to provide the theoretical evidence for the genomic research of Bulinus in absence of reference genes. Methods B. globosus snail samples were collected from Kiwani Shehia in Pemba Island, Zanzibar, Tanzania, and offspring snails were obtained through laboratory breeding and reproduction. A total of 120 10-week-old B. globosus snails from the same generation were selected and randomly assigned into four groups, including the high-temperature drought (HD) group, normal temperature drought (D) group, low-temperature drought (LD) group, and the control (C) group, of 30 snails in each group. Snails in HD, D, and LD groups were placed in beakers containing dry soil at the bottom and subsequently housed in climate chambers at 35, 26 ℃, and 10 ℃, respectively, while snails in Group C were maintained in 500 mL petri dishes containing dechlorinated tap water at 26 ℃. Following 3 days of breeding, living snails in each group were collected, and soft tissues were dissected and isolated. Total RNA was extracted from snail soft tissues for library construction, followed by high-throughput sequencing on the Illumina HiSeq 4000 sequencing system. De novo transcriptome assembly was performed using the Trinity software, and the longest transcripts were selected as unigenes. Gene functional annotations of unigenes were conducted using the Diamond software against Gene Ontology (GO) knowledgebase, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database, NCBI non-redundant (NR) protein sequences database, Protein Family (Pfam) database, and UniProtKB/Swiss-Prot (Swiss-Prot) knowledgebase. GO and KEGG enrichment analyses of differentially expressed genes (DEGs) were performed using the topGO and clusterProfiler software, respectively. In addition, four relevant genes were selected for validation using a real-time quantitative PCR (qRT-PCR) assay to verify the reliability of transcriptome sequencing results. Results Following 3 days of breeding, there were 7, 20, 28, and 30 survival B. globosus snails in HD, LD, D, and C groups, with corresponding survival rates of 23.33% (7/30), 66.67% (20/30), 93.33% (28/30), and 100.00% (30/30), respectively (χ² = 52.72, P < 0.001). De novo transcriptome assembly generated 176 942 unigenes, with annotation rates of 0.98%, 13.49%, 26.46%, 12.48%, and 14.39% against GO knowledgebase, KEGG pathway database, NR protein sequences database, Pfam database, and Swiss-Prot knowledgebase, respectively. There were 33 up-regulated and 72 down-regulated genes in Group D, 483 up-regulated and 815 down-regulated genes in Group HD, and 245 up-regulated and 172 down-regulated genes in Group LD relative to in Group C. Following removal of overlapping genes across groups and unmatched genes, 11 candidate genes were identified. GO and KEGG analyses revealed 3 heat shock protein (HSP)-related DEGs in these 11 candidate genes, which were annotated as HSP12.2, HSP70, and HSP20 genes and were all significantly up-regulated in each treatment group. Three immune and nervous system-related DEGs were identified, and were all significantly down-regulated in each treatment group, which were involved in the neural cell adhesion molecule L1-like protein pathway, fibrinogen binding protein pathway, and leukocyte elastase inhibitor-like protein pathway. qRT-PCR assay quantified that the expression trends of four genes related to temperature and drought stress across different treatment groups were highly consistent with transcriptome sequencing data. Conclusion The survival rate of B. globosus significantly reduces under combined stresses of extreme temperature and drought, possibly due to an imbalance in its cellular homeostasis regulatory system.

Three typical failures of large-aperture 16-slice spiral Siemens SOMATOM Sensation Open CT were introduced in terms of phenomenon,cause and treatment method.References were provided for medical engineers to treat similar failures.

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.

Three typical failures of large-aperture 16-slice spiral Siemens SOMATOM Sensation Open CT were introduced in terms of phenomenon,cause and treatment method.References were provided for medical engineers to treat similar failures.

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 investigate lipid metabolism gene mutations and pathogenicity of hypertriglyceridemia acute pancreatitis (HTG-AP) patients.Methods:Clinical data of 495 HTG-AP patients admitted from June 2018 to June 2020 in the center for severe acute pancreatitis of Eastern Theater General Hospital were retrospectively analyzed. Whole-exome sequencing and mutation verification were performed by next-generation sequencing technology and Sanger sequencing. The pathogenicity of gene mutation was analyzed by population mutation ratio, pathogenicity prediction software, conservation scoring software, protein structure prediction, and in vitro experiments. Results:The mutation ratio of lipid metabolism-related genes, namely LPL, APOA5, LMF1, GPIHBP1, and APOC2, were 14.81%, 55.78%, 43.61%, 1.62%, and 0.61%, respectively. Among them, 44 heterozygous mutations in LPL gene were detected including 36 missense mutations, 5 nonsense mutations and 3 frameshift mutations, which were all rarely carried in single patient. Six HTG-AP patients carried the LPL gene heterozygous mutation c.835C>G (p.Leu279Val). The mean level of serum triglyceride at the onset of HTG-AP was 27.4 mmol/L. All of them had a history of recurrent HTG-AP, and most of them had severe acute pancreatitis. The serum LPL concentration and activity were lower than the normal level. The pathogenicity analysis results suggested that the LPL p.Leu279Val was a rare, highly possible pathogenic and highly conserved gene mutation. The in vitro results showed that the LPL p.Leu279Val could significantly reduce the synthesis and secretion ability of LPL as well as its enzymatic activity. Conclusions:The mutation ratio of lipid metabolism-related genes, including LPL, APOA5, LMF1, GPIHBP1, and APOC2, are relatively high in the HTG-AP patients. The LPL p.Leu279Val is a rare and highly possible pathogenic gene mutation, which may lead to recurrent episodes of HTG-AP.

Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

Objective:To investigate lipid metabolism gene mutations and pathogenicity of hypertriglyceridemia acute pancreatitis (HTG-AP) patients.Methods:Clinical data of 495 HTG-AP patients admitted from June 2018 to June 2020 in the center for severe acute pancreatitis of Eastern Theater General Hospital were retrospectively analyzed. Whole-exome sequencing and mutation verification were performed by next-generation sequencing technology and Sanger sequencing. The pathogenicity of gene mutation was analyzed by population mutation ratio, pathogenicity prediction software, conservation scoring software, protein structure prediction, and in vitro experiments. Results:The mutation ratio of lipid metabolism-related genes, namely LPL, APOA5, LMF1, GPIHBP1, and APOC2, were 14.81%, 55.78%, 43.61%, 1.62%, and 0.61%, respectively. Among them, 44 heterozygous mutations in LPL gene were detected including 36 missense mutations, 5 nonsense mutations and 3 frameshift mutations, which were all rarely carried in single patient. Six HTG-AP patients carried the LPL gene heterozygous mutation c.835C>G (p.Leu279Val). The mean level of serum triglyceride at the onset of HTG-AP was 27.4 mmol/L. All of them had a history of recurrent HTG-AP, and most of them had severe acute pancreatitis. The serum LPL concentration and activity were lower than the normal level. The pathogenicity analysis results suggested that the LPL p.Leu279Val was a rare, highly possible pathogenic and highly conserved gene mutation. The in vitro results showed that the LPL p.Leu279Val could significantly reduce the synthesis and secretion ability of LPL as well as its enzymatic activity. Conclusions:The mutation ratio of lipid metabolism-related genes, including LPL, APOA5, LMF1, GPIHBP1, and APOC2, are relatively high in the HTG-AP patients. The LPL p.Leu279Val is a rare and highly possible pathogenic gene mutation, which may lead to recurrent episodes of HTG-AP.

Objective:To analyze the electrocardiogram (ECG) data of congenital long QT syndrome (LQTS) patients, and to identify the ECG parameters for prediction of life-threatening arrhythmic events (LAEs).Methods:This cohort study enrolled patients diagnosed with congenital LQTS at the Department of Cardiology, Beijing Tsinghua Changgung Hospital from September 2014 to May 2023. Baseline clinical and ECG data were collected. Patients were followed with LAEs as the primary endpoint. Based on the occurrence of LAEs, patients were divided into two groups: the event group and the event-free group. Cox regression analysis was used to identify independent predictors of LAEs in LQTS patients.Results:A total of 293 patients diagnosed with congenital LQTS were included, aged 32.5 (19.0, 41.8) years, including 201 females (68.6%). Sixty-six patients experienced LAEs and 227 patients did not. Compared to the event-free group, the event group had a younger onset age (13.0 (5.5, 20.5) years vs. 26.0 (13.0, 35.0) years), a slower heart rate (69.0 (59.5, 76.5) beats/min vs. 77.0 (67.0, 88.0) beats/min), a higher proportion with family history of sudden cardiac death (30.3% vs. 14.5%), as well as longer QT intervals (500.0 (467.0, 594.0) ms vs. 428.0 (402.0, 470.0) ms) and QTc intervals (544.0 (502.5, 589.0) ms vs. 489.0 (480.0, 504.0) ms). Additionally, the event group had higher peak T-wave alternans value (65.0 (42.5, 85.3) μV vs. 44.0 (36.0, 54.0) μV), a higher proportion of patients with documented torsades de pointes (TdP) or ventricular fibrillation (VF) on 24-hour Holter monitoring (39.3% vs. 4.9%), and higher rates of pharmacological treatment (100.0% vs. 9.7%) and device therapy or left cardiac sympathetic denervation (45.5% vs. 2.2%) (all P<0.05). Multivariate Cox regression analysis identified that the heart rate<60 beats/min ( HR=2.0, 95% CI: 1.0-3.7) and QTc interval ≥500 ms ( HR=2.9, 95% CI: 1.5-5.6) on 12-lead ECG, as well as peak T-wave alternans value ≥55.5 μV ( HR=3.2, 95% CI: 1.3-7.8) and documented TdP or VF ( HR=2.0, 95% CI: 1.1-3.7) on 24-hour Holter monitoring were independent predictors of LAEs in LQTS patients (all P<0.05). Conclusion:Heart rate <60 beats/min and QTc interval ≥500 ms on 12-lead ECG, along with peak T-wave alternans value ≥55.5 μV and documented TdP or VF on 24-hour Holter monitoring, have been identified as independent predictors of LAEs in patients with LQTS. These ECG parameters may serve as valuable early indicators of sudden cardiac death in LQTS patients.

Liquiritigenin(LG)is a flavone of pharmacological importance,however,its application potential is severely limited due to its poor water solubility.LG could be disassociated slightly in water to form phenolate anion,therefore,better solubilization effect is expected by inclusion with cationic cyclodextrins(CCDs).In this work,four kinds of CCDs modified with amino groups at the primary face were synthesized,and their solid inclusion complexes with LG were successfully prepared by preparing their saturated solutions.The formation of the solid inclusion complexes was confirmed by scanning electron microscopy(SEM)and powder X-ray diffraction(PXRD),and their supramolecular binding behavior in solution was studied using multiple techniques.A 1∶1 inclusion stoichiometry of inclusion complexation was defined using Job plot by ultraviolet-visible(UV-vis)spectroscopy,and their binding stability constants(Ks)were determined as 2862.77,3494.70,6521.85 and 9599.48 L/mol using UV-vis spectroscopic titration,far more superior to that of nativeβ-CD(Ks=236.79 L/mol).This indicated that the amino side chains on CCDs could actively participate in the inclusion complexation through anion-cation interactions,significantly strengthening the host-guest binding between CCDs and LG.The inclusion modes were further elucidated based on proton and two-dimensional rotating-frame overhauser enhancement spectroscopy(2D-ROESY)nuclear magnetic resonance(NMR)experiments and molecular docking.Water solubility of LG was dramatically promoted up to 4.9 mg/mL,which was 70-fold higher than that of native LG.This study could draw inspiration for the binding and solubilization of phenols such as flavones by design of cationic macrocyclic molecules.