ObjectiveTo compare the effects of different sterilization methods on the quality of pneumococcal capsular polysaccharides and screen the best sterilization method, so as to reduce the content of impurities in purified polysaccharides and improve the safety of polysaccharide vaccines.MethodsAfter fermentation culture, type 5 pneumococcus was sterilized with 0. 1% sodium deoxycholate(DOC), 0. 1% beta-propiolactone(BPL) and 1% formaldehyde at the early and middle logarithmic growth phase, the end of logarithmic phase and plateau phase, as well as the end of plateau phase and decline phase,separately. The morphology of the bacteria was observed by microscope, and the capsular polysaccharide content in the supernatant of fermentation broth at each stage was determined by rate nephelometry to calculate the polysaccharide release rate(based on the polysaccharide content after DOC sterilization). Pneumococci types 5, 7F, 14, and 15B were fermented and cultured, and sterilized using the same sterilization method in the end of plateau phase. Capsular polysaccharides were purified by ultrafiltration concentration, acid precipitation, alcohol precipitation, and secondary ultrafiltration. According to the related methods in Chinese Pharmacopoeia(VolumeⅢ, 2020 edition), the quality indicators such as the content and molecular size distribution of impurity proteins, nucleic acids, total nitrogen, phosphorus, uronic acid, hexosamine, and methylpentose in purified polysaccharides were detected.ResultsDOC sterilization caused complete lysis of the bacteria, while BPL and formaldehyde sterilization could maintain the integrity of the bacteria. In the late stage of fermentation(the end of plateau phase), the polysaccharide release rate of BPL and formaldehyde sterilization reached 60%-80%, which was higher than that in the early and middle logarithmic growth phase(20%-30%) and the end of logarithmic phase and plateau phase(40%-70%). Compared with DOC sterilization, the content of impurity proteins in the four types of purified polysaccharides obtained by BPL and formaldehyde sterilization was significantly reduced. Among them, the content of impurity proteins in type 5 polysaccharide was reduced to 4. 2%(decrease > 30%), and the content of impurity proteins in types 14, 7F and 15B polysaccharides was reduced to 0. 4%-0. 6%, 0. 4%-0. 6% and 0. 3%-0. 4%(decrease of 50%-70%), respectively. The nucleic acid content also decreased. The polysaccharide release rate of BPL sterilization(67%-70%) was higher than that of formaldehyde sterilization(48%-52%). All the quality indicators of the purified polysaccharides met the pharmacopoeia standards.ConclusionBoth BPL and formaldehyde sterilization can effectively reduce the content of impurity proteins in purified capsular polysaccharides and improve the quality. Among them, the polysaccharide release rate of BPL sterilization is better than that of formaldehyde, and it can maintain the integrity of bacteria, which is conducive to simplifying the downstream purification process.

Objective:To analyze the short-term hospital-based transmission characteristics and gene variation of Carbapenem-Resistant Klebsiella pneumoniae (CRKP) by genome-wide technique to provide evidence for transmission control. Methods:The experimental strain was derived from all the CRKP isolated in Affiliated Hospital of North China University of Science and Technology from October 2022 to December 2023. Strain identification and drug susceptibility were tested with VITEK 2-Compact automatic bacterial identification drug susceptibility analyzer or disk method, and the results were interpreted through whole genome sequencing. The ST type, carbapenem resistance gene, virulence factor, and O serotype of the collected strains were analyzed.Results:Among the 115 strains of CRKP, 94 strains were isolated from the intensive care unit (ICU), accounting for 81.7%, and 21 strains were isolated from the non-intensive care unit (NICU), accounting for 18.3%. The 115 strains of CRKP can be divided into 11 ST types, of which ST11 type was the most (54.8%, 63/115), followed by ST15 type (22.6%, 26/115) and ST5492 type (15.7%, 18/115). Type ST5492 was a new clonal group in the region. The 115 strains of CRKP could be divided into 7 O serotypes, most of which were O2a type(32.2%,37/115), followed by O5 type(30.4%,35/115) and O1 type(27.8%,32/115). The resistance genes of carbapenem antibiotics showed that there were 107 strains carrying the blaKPC-2 gene, one strain with the blaNDM-1 gene, and one strain with both the blaKPC-2 and blaNDM-13 genes. Virulence genes were detected in 55 CRKP strains (47.8%, 55/115), among which six strains detected peg-344, iucA, iroB, rmpA, and rmpA2 virulence genes (5.2%, 6/115). Four virulence genes ( peg-344, iucA, rmpA, and rmpA2) were detected in 34 strains (29.6%, 34/115). Three virulence genes ( iucA, iroB and rmpA) were detected in two strains (1.7%, 2/115). Three virulence genes ( peg-344, iucA and rmpA) were detected in one strain (0.8%, 1/115). IucA and rmpA virulence genes were detected in 12 strains (10.4%, 12/115). KPC-2_ST11_O2a, KPC-2_ST15_O1 and KPC-2_ST5492_O5 were dominant clones, and their distribution was mainly in the intensive care unit. The whole genome sequence analysis showed that there were three dominant clones, among which ST11 clones were subdivided into three dominant O serotypes, all of which were mainly in the intensive care unit. Conclusion:The popular strain in the hospital of CRKP is a KPC-2_ST11 clone group carrying iucA, rmpA/rmpA2, with cross-department transmission and mutation. ST5492 is a newly-launched clone type. The intensive care unit of hvKP carrying five virulence genes, including peg-344, should be alert to the epidemic risk of CR-hvKP outbreak.

Objective:To analyze the carriage status, subtype distribution and flanking gene sequence characteristics of oxacillinases (OXA enzyme) in 241 clinical strains of Pseudomonas aeruginosa, and assess their roles in the drug resistance of Pseudomonas aeruginosa and ability to horizontally transfer across species. Methods:Clinical P. aeruginosa isolates were collected from four hospitals in Sanya, Tangshan, Zhangjiakou, and Beijing. The prevalence of oxacillinases and their flanking gene sequences was analyzed by whole-genome sequencing (NGS) and bioinformatic approaches. Results:A total of 241 isolates of P. aeruginosa were gathered, and 35 blaOXA subtypes were identified through screening of 252 blaOXA genes. These genes were classified into three subfamilies: blaOXA-50-like (241, 95.6%), blaOXA-1-like (9, 3.6%) and blaOXA-10-like (2, 0.8%). Among these, 11 subtypes (11, 31.4%) were novel blaOXA subtypes. Nine of these belonged to the blaOXA-50-like subfamily and were designated as blaOXA-1244, blaOXA-1245, blaOXA-1246, blaOXA-1250, blaOXA-1252, blaOXA-1253, blaOXA-1254, blaOXA-1255, and blaOXA-1256. The remaining two belonged to the blaOXA-10-like subfamily and were named blaOXA-1247 and blaOXA-1248. Compared to the amino acid sequence of OXA-10, the newly identified subtype OXA-1247 exhibited a mutation at position 117, where a valine was replaced by a leucine. This change was thought to improve the enzyme′s ability to hydrolyze carbapenems. In the analysis of the flanking sequences of the blaOXA genes, Class I integrons were identified in four bacterial strains. The variable regions of these integrons carried three distinct patterns of resistance gene cassettes: aac( 6′) -Ib-blaOXA-1247-ant( 3′′) -Ia, aac( 6′) -Ib-blaOXA-1248 and aac( 6′) -Ib- blaIMP-45-blaOXA-1-catB3. Among these, the strain BJ2326 carried a class I integron that was connected to the downstream IS CR1 element to form a composite class I integron structure, additionally carrying the resistance gene blaPER-1. Out of the 223 non-wild-type P. aeruginosa strains, 127 strains exhibited non-wild-type profiles to the four beta-lactam antibiotics MEM, CAZ, FEP, and TZP, with the combination of MEM+CAZ+FEP being the most prevalent, representing 57.0% of the total. Conclusions:The blaOXA genes in 241 clinical P. aeruginosa strains showed diversity. Some blaOXA genes had a co-transfer risk with the metallo-β-lactamase resistance gene blaIMP-45. Among the 11 newly discovered blaOXA subtypes, the new subtype OXA-1247 may have carbapenemase activity and potential for horizontal transfer.

Purpose To analyze the value of a deep learning(DL)radiomics model based on dynamic contrast-enhanced MRI images in predicting the expression of Ki-67 status in breast cancer.Materials and Methods A retrospective analysis of 152 breast cancer patients confirmed by pathological results at Guangdong Women and Children Hospital,MRI images and clinical pathological data were reviewed,and based on postoperative immunohistochemistry results,the images of the high and low expression groups of Ki-67 were randomly sampled in a ratio of 8∶2 to form a training set of 122 cases and a validation set of 30 cases.Single-factor and multi-factor Logistic regression analyses of clinical data were performed to select independent predictors of breast cancer expressing Ki-67 status.The ResNet-18 model was used as the basic model for DL feature extraction.Hand-crafted radiomic features and DL features were extracted.Eight machine learning models were constructed based on clinical features,hand-crafted radiomic features,DL features,and their combinations.The area under the receiver operating characteristic curve was used to evaluate the predictive performance of the models,and the best model was determined as the output model.Results The progesterone receptor status(OR=0.764,P=0.040)and human epidermal growth factor receptor-2 status(OR=1.187,P=0.046)were independent clinical predictors of breast cancer expressing Ki-67 status.The combined feature models demonstrated superior performance over the individual feature models,and the support vector machine algorithm had the highest prediction performance in the validation set,with an area under the curve of 0.847.Conclusion The DL radiomics model based on dynamic contrast-enhanced MRI images can effectively predict the expression of Ki-67 status in breast cancer.The support vector machine algorithm combined with feature model is the best,which can help the clinical diagnosis and treatment of breast cancer and prognosis evaluation.

Purpose To analyze the value of a deep learning(DL)radiomics model based on dynamic contrast-enhanced MRI images in predicting the expression of Ki-67 status in breast cancer.Materials and Methods A retrospective analysis of 152 breast cancer patients confirmed by pathological results at Guangdong Women and Children Hospital,MRI images and clinical pathological data were reviewed,and based on postoperative immunohistochemistry results,the images of the high and low expression groups of Ki-67 were randomly sampled in a ratio of 8∶2 to form a training set of 122 cases and a validation set of 30 cases.Single-factor and multi-factor Logistic regression analyses of clinical data were performed to select independent predictors of breast cancer expressing Ki-67 status.The ResNet-18 model was used as the basic model for DL feature extraction.Hand-crafted radiomic features and DL features were extracted.Eight machine learning models were constructed based on clinical features,hand-crafted radiomic features,DL features,and their combinations.The area under the receiver operating characteristic curve was used to evaluate the predictive performance of the models,and the best model was determined as the output model.Results The progesterone receptor status(OR=0.764,P=0.040)and human epidermal growth factor receptor-2 status(OR=1.187,P=0.046)were independent clinical predictors of breast cancer expressing Ki-67 status.The combined feature models demonstrated superior performance over the individual feature models,and the support vector machine algorithm had the highest prediction performance in the validation set,with an area under the curve of 0.847.Conclusion The DL radiomics model based on dynamic contrast-enhanced MRI images can effectively predict the expression of Ki-67 status in breast cancer.The support vector machine algorithm combined with feature model is the best,which can help the clinical diagnosis and treatment of breast cancer and prognosis evaluation.

Objective:To analyze the short-term hospital-based transmission characteristics and gene variation of Carbapenem-Resistant Klebsiella pneumoniae (CRKP) by genome-wide technique to provide evidence for transmission control. Methods:The experimental strain was derived from all the CRKP isolated in Affiliated Hospital of North China University of Science and Technology from October 2022 to December 2023. Strain identification and drug susceptibility were tested with VITEK 2-Compact automatic bacterial identification drug susceptibility analyzer or disk method, and the results were interpreted through whole genome sequencing. The ST type, carbapenem resistance gene, virulence factor, and O serotype of the collected strains were analyzed.Results:Among the 115 strains of CRKP, 94 strains were isolated from the intensive care unit (ICU), accounting for 81.7%, and 21 strains were isolated from the non-intensive care unit (NICU), accounting for 18.3%. The 115 strains of CRKP can be divided into 11 ST types, of which ST11 type was the most (54.8%, 63/115), followed by ST15 type (22.6%, 26/115) and ST5492 type (15.7%, 18/115). Type ST5492 was a new clonal group in the region. The 115 strains of CRKP could be divided into 7 O serotypes, most of which were O2a type(32.2%,37/115), followed by O5 type(30.4%,35/115) and O1 type(27.8%,32/115). The resistance genes of carbapenem antibiotics showed that there were 107 strains carrying the blaKPC-2 gene, one strain with the blaNDM-1 gene, and one strain with both the blaKPC-2 and blaNDM-13 genes. Virulence genes were detected in 55 CRKP strains (47.8%, 55/115), among which six strains detected peg-344, iucA, iroB, rmpA, and rmpA2 virulence genes (5.2%, 6/115). Four virulence genes ( peg-344, iucA, rmpA, and rmpA2) were detected in 34 strains (29.6%, 34/115). Three virulence genes ( iucA, iroB and rmpA) were detected in two strains (1.7%, 2/115). Three virulence genes ( peg-344, iucA and rmpA) were detected in one strain (0.8%, 1/115). IucA and rmpA virulence genes were detected in 12 strains (10.4%, 12/115). KPC-2_ST11_O2a, KPC-2_ST15_O1 and KPC-2_ST5492_O5 were dominant clones, and their distribution was mainly in the intensive care unit. The whole genome sequence analysis showed that there were three dominant clones, among which ST11 clones were subdivided into three dominant O serotypes, all of which were mainly in the intensive care unit. Conclusion:The popular strain in the hospital of CRKP is a KPC-2_ST11 clone group carrying iucA, rmpA/rmpA2, with cross-department transmission and mutation. ST5492 is a newly-launched clone type. The intensive care unit of hvKP carrying five virulence genes, including peg-344, should be alert to the epidemic risk of CR-hvKP outbreak.

Objective:To analyze the carriage status, subtype distribution and flanking gene sequence characteristics of oxacillinases (OXA enzyme) in 241 clinical strains of Pseudomonas aeruginosa, and assess their roles in the drug resistance of Pseudomonas aeruginosa and ability to horizontally transfer across species. Methods:Clinical P. aeruginosa isolates were collected from four hospitals in Sanya, Tangshan, Zhangjiakou, and Beijing. The prevalence of oxacillinases and their flanking gene sequences was analyzed by whole-genome sequencing (NGS) and bioinformatic approaches. Results:A total of 241 isolates of P. aeruginosa were gathered, and 35 blaOXA subtypes were identified through screening of 252 blaOXA genes. These genes were classified into three subfamilies: blaOXA-50-like (241, 95.6%), blaOXA-1-like (9, 3.6%) and blaOXA-10-like (2, 0.8%). Among these, 11 subtypes (11, 31.4%) were novel blaOXA subtypes. Nine of these belonged to the blaOXA-50-like subfamily and were designated as blaOXA-1244, blaOXA-1245, blaOXA-1246, blaOXA-1250, blaOXA-1252, blaOXA-1253, blaOXA-1254, blaOXA-1255, and blaOXA-1256. The remaining two belonged to the blaOXA-10-like subfamily and were named blaOXA-1247 and blaOXA-1248. Compared to the amino acid sequence of OXA-10, the newly identified subtype OXA-1247 exhibited a mutation at position 117, where a valine was replaced by a leucine. This change was thought to improve the enzyme′s ability to hydrolyze carbapenems. In the analysis of the flanking sequences of the blaOXA genes, Class I integrons were identified in four bacterial strains. The variable regions of these integrons carried three distinct patterns of resistance gene cassettes: aac( 6′) -Ib-blaOXA-1247-ant( 3′′) -Ia, aac( 6′) -Ib-blaOXA-1248 and aac( 6′) -Ib- blaIMP-45-blaOXA-1-catB3. Among these, the strain BJ2326 carried a class I integron that was connected to the downstream IS CR1 element to form a composite class I integron structure, additionally carrying the resistance gene blaPER-1. Out of the 223 non-wild-type P. aeruginosa strains, 127 strains exhibited non-wild-type profiles to the four beta-lactam antibiotics MEM, CAZ, FEP, and TZP, with the combination of MEM+CAZ+FEP being the most prevalent, representing 57.0% of the total. Conclusions:The blaOXA genes in 241 clinical P. aeruginosa strains showed diversity. Some blaOXA genes had a co-transfer risk with the metallo-β-lactamase resistance gene blaIMP-45. Among the 11 newly discovered blaOXA subtypes, the new subtype OXA-1247 may have carbapenemase activity and potential for horizontal transfer.

Objective:To explore the capability of deep learning image reconstruction (DLIR) compared to adaptive statistical iterative reconstruction (ASiR-V) in improving the image quality and myocardial edge sharpness of dynamic stress myocardial CT perfusion imaging (CTP).Methods:Thirty subjects who underwent dynamic stress myocardial CTP at Guangdong Provincial People′s Hospital from September 2023 to February 2024 were recruited. Image data of all enrolled patients were reconstructed using ASiR-V 50%, ASiR-V 80%, medium-intensity DLIR(DLIR-M), and high-intensity DLIR(DLIR-H), respectively. Regions of interest were selected in the left ventricular cavity, interventricular septum, and left ventricular lateral wall for measurement of CT values and standard deviations (SD), and calculation of signal to noise ratio (SNR) and contrast to noise ratio (CNR). Matlab was utilized to obtain the differences (d) and slopes (s) of CT value changes at four left ventricular myocardial edges for objective edge sharpness evaluation. Two radiologists subjectively scored the images for noise, natural appearance, and edge sharpness. In case of disagreement between the two radiologists, a third senior radiologist′s score was decisive. Left ventricular myocardial blood flow (MBF) of ASiR-V and DLIR images with lower SD, higher SNR and CNR were calculated, respectively. When the normal distribution was satisfied, the independent sample t test was used for comparison between two groups, and the random block design ANOVA was used for comparison between multiple groups. And analysis was conducted using Friedman test for non-normally distributed data, and Bonferroni correction for pairwise comparisons. Results:There were statistically significant differences in SD, SNR, and CNR among the four images in the interventricular septum and left ventricular lateral wall (all P<0.05), with ASiR-V 80% and DLIR-H demonstrating the lowest SD, highest SNR and CNR, and the subjective image noise score. Statistically significant differences were observed in d and s for the four left ventricular myocardial edges (all P<0.05), with DLIR-M and DLIR-H exhibiting the best objective edge sharpness [5 (5, 5)], and ASiR-V 80% the worst [3.5 (3, 4)]. In the subjective scores for natural appearance, DLIR-M and DLIR-H received the highest scores [5 (5, 5)], while ASiR-V 80% received the lowest scores [3 (3, 4)], with statistically significant differences (all P<0.05). There was no statistically significant difference in MBF values calculated from ASiR-V 80% and DLIR-H images (all P>0.05). Conclusions:The SD value, SNR and CNR of dynamic stress myocardial CTP images reconstructed by DLIR-H are equivalent to ASiR-V 80%, and using DLIR-H can improve the edge sharpness of left ventricular myocardium without affecting the calculation of MBF.

Objective:To explore the capability of deep learning image reconstruction (DLIR) compared to adaptive statistical iterative reconstruction (ASiR-V) in improving the image quality and myocardial edge sharpness of dynamic stress myocardial CT perfusion imaging (CTP).Methods:Thirty subjects who underwent dynamic stress myocardial CTP at Guangdong Provincial People′s Hospital from September 2023 to February 2024 were recruited. Image data of all enrolled patients were reconstructed using ASiR-V 50%, ASiR-V 80%, medium-intensity DLIR(DLIR-M), and high-intensity DLIR(DLIR-H), respectively. Regions of interest were selected in the left ventricular cavity, interventricular septum, and left ventricular lateral wall for measurement of CT values and standard deviations (SD), and calculation of signal to noise ratio (SNR) and contrast to noise ratio (CNR). Matlab was utilized to obtain the differences (d) and slopes (s) of CT value changes at four left ventricular myocardial edges for objective edge sharpness evaluation. Two radiologists subjectively scored the images for noise, natural appearance, and edge sharpness. In case of disagreement between the two radiologists, a third senior radiologist′s score was decisive. Left ventricular myocardial blood flow (MBF) of ASiR-V and DLIR images with lower SD, higher SNR and CNR were calculated, respectively. When the normal distribution was satisfied, the independent sample t test was used for comparison between two groups, and the random block design ANOVA was used for comparison between multiple groups. And analysis was conducted using Friedman test for non-normally distributed data, and Bonferroni correction for pairwise comparisons. Results:There were statistically significant differences in SD, SNR, and CNR among the four images in the interventricular septum and left ventricular lateral wall (all P<0.05), with ASiR-V 80% and DLIR-H demonstrating the lowest SD, highest SNR and CNR, and the subjective image noise score. Statistically significant differences were observed in d and s for the four left ventricular myocardial edges (all P<0.05), with DLIR-M and DLIR-H exhibiting the best objective edge sharpness [5 (5, 5)], and ASiR-V 80% the worst [3.5 (3, 4)]. In the subjective scores for natural appearance, DLIR-M and DLIR-H received the highest scores [5 (5, 5)], while ASiR-V 80% received the lowest scores [3 (3, 4)], with statistically significant differences (all P<0.05). There was no statistically significant difference in MBF values calculated from ASiR-V 80% and DLIR-H images (all P>0.05). Conclusions:The SD value, SNR and CNR of dynamic stress myocardial CTP images reconstructed by DLIR-H are equivalent to ASiR-V 80%, and using DLIR-H can improve the edge sharpness of left ventricular myocardium without affecting the calculation of MBF.

Objective:To apply cardiovascular magnetic resonance (CMR) to quantitatively evaluate the morphology and tissue characteristics of thoracic skeletal muscle (TSM) in patients with Danon disease and hypertrophic cardiomyopathy (HCM), in order to provide auxiliary differential diagnostic information.Methods:A retrospective study was conducted on 15 Danon disease patients (Danon disease group) who completed CMR examination, and 15 HCM patients (HCM group) and 15 healthy volunteers (control group) who were matched by gender and age were compared. TSM (pectoralis major, pectoralis minor, erector spinae, and subscapularis) area index (TSMAi), T1 relaxation time of four groups, and extracellular volume (ECV) of skeletal muscles of two groups (pectoralis major and subscapularis) were measured for all subjects. Single factor analysis of variance and KruskalWallis test were used to compare three sets of values.Results:The total TSMAi of the Danon disease group was lower than that of the HCM group and the control group [(15.37±3.28)cm 2/m 2 vs (23.02±3.88)cm 2/m 2 vs (22.33±4.67)cm 2/m 2, P<0.001], and the TSMAi of each TSM was also lower than that of the HCM group and the control group (all P<0.05). There was no statistically significant difference in TSMAi between the HCM group and the control group (all P>0.05). The native T1 values of the pectoralis major muscle in the Danon disease group and HCM group were higher than those in the control group (all P<0.05). The ECV of the pectoralis major muscle and subscapularis muscle in the Danon disease group were higher than those in the HCM group and control group, and the enhanced T1 values were lower than those in the HCM group and control group (all P<0.05); There was no statistically significant difference in ECV and the enhanced T1 values between the HCM group and the control group ( P>0.05). Conclusions:The application of CMR can effectively evaluate the changes in TSM morphology and tissue characteristics in Danon disease patients. Compared with HCM patients, Danon disease patients showed significant atrophy of TSM with increased extracellular volume. CMR provides a quantitative reference for TSM in the differential diagnosis of the two.