Objective:To develop an artificial intelligence（AI）-based sequential ultrasound-magnetic resonance imaging（US-MRI）diagnostic strategy to optimize the imaging workflow for ovarian masses.Methods:A total of 1 120 patients with pathologically confirmed ovarian masses who underwent both preoperative pelvic ultrasound and MRI between January 2021 and December 2023 at Women's Hospital，Zhejiang University School of Medicine were retrospectively included. Patients were randomly divided into the training（ n=672）and internal test set（ n=448）at a ratio of 6∶4. An external test set（ n=128）was established at the Forth Affiliated Hospital of School of Medicine. Deep learning was used for automated segmentation of MRI lesions，followed by radiomic feature extraction and machine learning classification to construct both a US-MRI multimodal model and sequential US-MRI strategy. Diagnostic performance and potential healthcare cost-saving effects were evaluated across strategies. Results:In the internal test set（ n=448），the AI-based sequential US-MRI strategy achieved a F1 score of 0.863 and a diagnostic accuracy of 82.14%，with no significant difference compared to the US-MRI multi-modal model（ P>0.05）. The sequential strategy identified 82 cases（18.30%，82/448）of patients as low-risk true negatives during initial ultrasound screening，suggesting a potential to reduce the need for MRI examinations in future clinical practice. In the external test set（ n=128），the strategy achieved an F1 score of 0.800 and a confirmed diagnosis rate of 85.94%，with a theoretical reduction of 26.56%（34 cases）in MRI utilization while maintaining a diagnostic accuracy rate higher than that of the multi-modal model（82.18%）. Conclusions:The AI-based US-MRI sequential diagnostic strategy demonstrates favorable diagnostic accuracy while offering the potential to optimize MRI utilization. This approach may enhance the efficiency of imaging resource allocation and reduce healthcare burden in the management of ovarian masses.

Objective:To develop an artificial intelligence（AI）-based sequential ultrasound-magnetic resonance imaging（US-MRI）diagnostic strategy to optimize the imaging workflow for ovarian masses.Methods:A total of 1 120 patients with pathologically confirmed ovarian masses who underwent both preoperative pelvic ultrasound and MRI between January 2021 and December 2023 at Women's Hospital，Zhejiang University School of Medicine were retrospectively included. Patients were randomly divided into the training（ n=672）and internal test set（ n=448）at a ratio of 6∶4. An external test set（ n=128）was established at the Forth Affiliated Hospital of School of Medicine. Deep learning was used for automated segmentation of MRI lesions，followed by radiomic feature extraction and machine learning classification to construct both a US-MRI multimodal model and sequential US-MRI strategy. Diagnostic performance and potential healthcare cost-saving effects were evaluated across strategies. Results:In the internal test set（ n=448），the AI-based sequential US-MRI strategy achieved a F1 score of 0.863 and a diagnostic accuracy of 82.14%，with no significant difference compared to the US-MRI multi-modal model（ P>0.05）. The sequential strategy identified 82 cases（18.30%，82/448）of patients as low-risk true negatives during initial ultrasound screening，suggesting a potential to reduce the need for MRI examinations in future clinical practice. In the external test set（ n=128），the strategy achieved an F1 score of 0.800 and a confirmed diagnosis rate of 85.94%，with a theoretical reduction of 26.56%（34 cases）in MRI utilization while maintaining a diagnostic accuracy rate higher than that of the multi-modal model（82.18%）. Conclusions:The AI-based US-MRI sequential diagnostic strategy demonstrates favorable diagnostic accuracy while offering the potential to optimize MRI utilization. This approach may enhance the efficiency of imaging resource allocation and reduce healthcare burden in the management of ovarian masses.

Objective:To study the clustered regularly interspaced short palindromic repeats (CRISPR) genotype of Yersinia pestis and its regional distribution characteristics in natural plague focus of Tibet Autonomous Region. Methods:A total of 125 representative Yersinia pestis strains isolated from natural plague focus in Tibet Autonomous Region at different times, regions, hosts and vectors were selected as experimental strains, and the phenol chloroform mixed extraction method was used to extract Yersinia pestis DNA. Three pairs of CRISPR primers (for YPa, YPb, YPc locus) were used to amplify the DNA of the experimental strains, and the CRISPR genotype of Yersinia pestis was determined by sequencing. Results:All 125 strains of Yersinia pestis had three CRISPR locus: YPa, YPb, and YPc. A total of 18 spacer were found, including 8 in YPa loci, 6 in YPb loci, and 4 in YPc loci. Two new types of spacers had been discovered, namely b52 and c14. CRISPR typing revealed 10 genotypes, including G1, G7, G7-b4''', G7-b52, G7-c2 -, G8, G22, G22-a4 -, G22-b4''', and G22-c14, of which 6 were newly discovered genotypes. Among the 125 experimental strains, G7 was the main genotype, accounting for 65.6% (82/125), which was distributed in 6 prefecture level citys and 1 region of Tibet Autonomous Region. Next were G22 and G7-c2 - genetypes, accounting for 14.4% (18/125) and 11.2% (14/125), respectively. G22 gene type was distributed in Nagqu, Changdu, Lhasa citys, and Ngari Prefecture, while G7-c2 - genetype was distributed in Shigatse and Shannan cities. Conclusion:The CRISPR locus of Yersinia pestis in natural plague focus of Tibet Autonomous Region is highly polymorphic, and the Yersinia pestis strains with different genotypes have obvious regional distribution characteristics.

Abstract: Objective To understand the phenotypic and genetic characteristics of Yersinia pestis strains isolated from Himalayan marmot natural focus area and domestic rat plague focus area in southern China, and provide reference for mastering the pathogenic characteristics of Yersinia pestis of two plague foci. Methods A total of 412 of Yersinia pestis strains isolated from Himalayan marmot plague focus and domestic rat plague focus of southern China were subjected to to sorbitol fermentation assays, virulence factor, different region (DFR) typing, and clustered regularly interspaced palindromic repeats (CRISPR) typing. Results The biochemical types of Y. pestis from the two plague foci showed distinct regional distribution features. Five biochemical phenotypes were identified in Yersinia pestis isolated from Himalayan marmot natural focus area, while only one biochemical phenotype was identified in strains isolated from the domestic rat plague focus of Southern China. Most of the Yersinia pestis isolated from the two plague foci were capable of producing the virulence factors of Fl and PstI. Among the strains from Himalayan marmot focus, 70.53% (201/285) were VW-positive, 75.09% (214/285) were Pgm-positive, 20.00% (57/285) of the strains were Pgm-negative, and 5.26% (15/285) were Pgm mixed-type strains. Among strains from domestic rat plague focus of southern China, 37.80% (48/127) were VW-positive, 29.13% (37/127) were Pgm-positive, 58.27% (74/127) were Pgm-negative, and 12.60% (16/127) were Pgm mixed-type strains. DFR typing revealed 22 genotypes of Y. pestis from the Himalayan marmot plague focus, with the main genotypes being type 5, 7, 8, 10, 19, 32 and 49. All strains from domestic rat plague focus area in southern China belonged to type 9. CRISPR typing revealed that all strains from the Himalayan marmot natural focus were classified into 7 CRISPR gene clusters and 14 CRISPR genotypes, with the main genotypes being G7, G22, G26-a1'and G22-A1'. All strains from domestic rat plague focus area in southern China belonged to CRISPR genotype G30, with the gene cluster being Ca8. Conclusions The phenotypes and genotypes of the Yersinia pestis of Himalayan marmot plague focus are diverse, with an obvious characteristics of geographical distribution. The phenotype and genotype of the Yersinia pestis of domestic rat plague focus of Southern China are single. DFR and CRISPR genotyping methods with phenotypic characteristics can effectively identify the Yersinia pestis isolated from the two plague foci, thereby meeting the needs of identification and traceability research.

Objective:To learn about the clustered regularly interspaced short palindromic repeats (CRISPR) genotyping of Yersinia pestis in Yushu Tibetan Autonomous Prefecture (Yushu for short), Qinghai Province, and to explore its genetic characteristics. Methods:In this study, 44 representative strains isolated from local natural plague focus in Yushu from 1963 to 2007 were selected as experimental objects to extract DNA. Primers targeting the three CRISPR loci (YPa, YPb, and YPc) were designed for PCR amplification. The amplified products were sequenced and analyzed to identify the CRISPR spacer, and to determine the CRISPR genotypes and clusters.Results:Twenty-three spacers including 14 of YPa, 6 of YPb and 3 of YPc were observed among 44 strains, of which 2 spacers (a106 and a107) were firstly identified. According to the spacer arrays, the strains were divided into 15 CRISPR genotypes and classified into 6 CRISPR clusters which were Cb4, Cc3', Ca7, Ca7', CaΔ5' and Ca35', respectively. Among them, Ca7 was the most epidemic dominant cluster (34 strains) in Yushu.Conclusion:The CRISPR loci of Yersinia pestis in Yushu have multiple genotypes, high genetic polymorphism, and complex population structure.

Objective:To study the phenotype and genotype distribution of Yersinia pestis ( Y. pestis) in different natural foci of plague in China, so as to provide scientific basis for plague prevention and control. Methods:A total of 2 184 strains of Y. pestis isolated from different time periods, regions, hosts and vectors in 11 plague natural foci of China since 1943 were selected for biochemical type identification, glycolysis test, virulence factor test [capsule antigen (F1), pesticin Ⅰ (Pst Ⅰ), virulence antigen factor (VWa), pigmentation factor (Pgm)], different region (DFR) typing and clustered regularly interspaced short palindromic repeats (CRISPR) typing. Results:There were 16 biochemical types of Y. pestis in the natural foci of plague in China, and each biochemical type showed obvious regional distribution in each foci. Most strains were positive for ass hide glue glycolysis (89.79%, 1 961/2 184), maltose (80.13%, 1 750/2 184), glycerol (94.23%, 2 058/2 184), and denitrification (82.78%, 1 808/2 184), and negative for rhamnose (88.78%, 1 939/2 184) and melibiose (85.62%, 1 870/2 184). Virulence factor test results showed that 99.95% (2 183/2 184) of Y. pestis were F1 positive; 99.73% (2 178/2 184) of Y. pestis can produce Pst Ⅰ; 73.31% (1 601/2 184) of Y. pestis were VWa positive and 26.69% (583/2 184) were VWa negative; Pgm positive strains accounted for 72.62% (1 586/2 184), Pgm negative strains accounted for 21.52% (470/2 184), and Pgm mixed type strains accounted for 5.86% (128/2 184). According to DFR typing results, there were 52 genotypes in 2 184 strains of Y. pestis, of which 19 were major genotypes and 33 were minor genotypes. CRISPR typing revealed 16 major genotypes, of which 7 were newly discovered. Conclusion:The phenotypes and genotypes of Y. pestis in various natural foci of plague in China are diverse and have geographical distribution characteristics.

Objective:To investigate the genotypes of clustered regularly interspaced short palindromic repeats (CRISPR) of Yersinia pestis ( Y. pestis) and it's regional distribution in the plague natural foci of Qinghai-Tibet Plateau. Methods:In this study, 1 004 strains of Y. pestis isolated from different hosts and vectors in different regions from 1954 to 2011 were selected as experimental objects, which preserved in Qinghai Institute for Endemic Disease Prevention and Control, and DNA of Y. pestis was extracted by traditional phenol-chloroform method. Three CRISPR loci (YPa, YPb and YPc) were amplified by PCR and sequenced, respectively, and the CRISPR sequences were compared with the CRISPRDictionary database recently reported in the literature to identify CRISPR spacer. For the spacer discovered for the first time at each CRISPR locus, Blast sequence alignment was performed in the National Center for Biotechnology Information (NCBI) database to speculate the source of gene sequence. Genotyping of Y. pestis from Qinghai-Tibet Plateau was performed based on the polymorphism of CRISPR spacer array. Results:A total of 53 spacers were found in 1 004 strains of Y. pestis, of which 6 spacers were newly discovered, namely a105, a106, a107, b51, b52 and c14. The 1 004 strains of Y. pestis were divided into 10 groups with 44 different CRISPR genotypes, and 15 new genotypes were found. The dominant genotypes of Y. pestis were G26-a1', G7, G22, G24-a1', G22-a1', G9 and G26-a1'a60 in Himalayan Marmot plague natural foci, and G37-a6' in Qinghai Microtinae plague natural foci. Conclusion:The CRISPR genotypes of Y. pestis in the plague natural foci of Qinghai-Tibet Plateau are high diverse and have significant regional distribution characteristics.

Objective:To understand whether there are drug resistant and disinfectant resistant Yersinia pestis strains in China, and to provide accurate information for clinical treatment of plague. Methods:A total of 2 753 Yersinia pestis strains isolated from 10 natural plague foci in China from 1943 to 2016 were collected. According to National Center for Biotechnology Information (NCBI) released sequences of aminoglycoside streptomycin resistant genes strA, strB, β-lactam antibiotics resistant genes TEM, SHV and CTX-M, sulfamilamide resistant genes sul1, sul2 and sul3, and disinfectant resistant gene qacE△1-sul1, a pair of primers of each gene was designed for above-mentioned genes. Genomic DNA of 2 753 strains of Yersinia pestis was extracted, and the 9 target genes of all DNA samples were amplified by PCR. Results:Negative and positive controls of PCR detection were established. No corresponding target bands of aminoglycoside streptomycin resistant genes strA, strB, β-lactam antibiotics resistant genes TEM, SHV and CTX-M, sulfamilamide resistant genes sul1, sul2 and sul3, and disinfectant resistant gene qacE△1-sul1 were found in the DNA samples of 2 753 strains of Yersinia pestis.Conclusion:The above-mentioned genes of drug resistance and disinfectant resistance have not been detected in Yersinia pestis of China, but the monitoring of drug resistance of Yersinia pestis still needs to be carried out continuously.

Objective:To investigate the drug resistance of Yersinia pestis to 11 kinds of antibiotics in the natural foci of plague in Inner Mongolia Autonomous Region, and to provide a theoretical basis for scientifically and effectively selecting antibiotics for treatment of the plague. Methods:A total of 137 strains of Yersinia pestis isolated from the natural foci of plague in Inner Mongolia Autonomous Region at different times, regions, hosts and vectors were collected. According to Clinical and Laboratory Standard Institute (CLSI), the agar plate dilution method was used to determine the minimum inhibitory concentration (MIC) of the 11 kinds of antibiotics against 137 strains of Yersinia pestis, including ofloxacin, ciprofloxacin, kanamycin, streptomycin, ceftriaxone, ampicillin, chloramphenicol, spectinomycin, cefuroxime, tetracycline and sulfamethoxazole-trimethoprim. The MIC 50 and MIC 90 (the minimum concentration of drug which could inhibit 50% and 90% of bacterial growth) were calculated, and their sensitivity was determined according to CLSI standards. Results:Among 137 strains of Yersinia pestis tested, no strains of Yersinia pestis had single or multiple resistance to ofloxacin, ciprofloxacin, kanamycin, streptomycin, ceftriaxone, ampicillin, chloramphenicol, spectinomycin, cefuroxime, tetracycline and sulfamethoxazole-trimethoprim. According to CLSI standards, 137 strains of Yersinia pestis were all sensitive to the 11 kinds of antibiotics; among them, ofloxacin, ciprofloxacin, ceftriaxone and sulfamethoxazole-trimethoprim had higher antibacterial activity, with MIC 90 < 0.250 μg/ ml; the antibacterial activity of spectinomycin was the lowest, with MIC 90 of 16.000 μg/ml. Conclusions:The Yersinia pestis isolated from the natural foci of plague in Inner Mongolia Autonomous Region is not found to have single or multiple resistance to the 11 kinds of antibiotics. Continuous drug resistance monitoring of Yersinia pestis should be carried out to provide a basis for clinical medication.

Objective:To analyze the pathogenic characteristics of Yersinia pestis in a plague natural foci in Qinghai-Tibet Plateau. Methods:In this study, 1 378 strains of Yersinia pestis isolated from different regions, hosts and vectors in Qinghai-Tibet Plateau from 1954 to 2016 were taken as the research objects. Phenotypic characteristics, plasmid spectrum and genotype of the strains were studied by using conventional techniques and molecular biological techniques. The etiology and geographical distribution of the plague were studied. Results:There were 6 biochemical types of Yersinia pestis in Qinghai-Tibet Plateau, namely Qinghai-Tibet Plateau, Qilian Mountain, Gangdis Mountain, Kunlun Mountain A, Kunlun Mountain B and Chuanqing Plateau. This study found that the Qinghai-Tibet Plateau type strain was not only distributed in north Tibet Plateau, but also distributed in south Tibet, and the distribution of Gangdis Mountain type strain extended to south Tibet. Four virulence factors (capsule antigen, yersinin, virulence antigen and pigmentation factor) were found in 79.97% (1 102/1 378) Yersinia pestis. The results also showed that there were 12 kinds of plasmids carried by Yersinia pestis strains in Qinghai-Tibet Plateau, which constituted 17 kinds of plasmid spectrum. There were 3 kinds of the largest plasmids with taxonomic properties, forming their respective relatively independent distribution areas. The study of different regions (DFR) type showed that 5, 8, 14, 19, 32 and 44 of 1 378 strains were the main genotypes, and the main genome types had obvious geographical distribution. Conclusions:All the tested strains have the characteristics of plague pathogen in Qinghai-Tibet Plateau. The polymorphism of the main hosts, vectors and the ecological landscape of plague geography in the plague foci in Qinghai-Tibet Plateau may lead to the diversity of biochemical characters, plasmid spectrum and geno types of Yersinia pestis.