Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective To investigate the effects of low-dose ionizing radiation on the thyroid status and hormone levels of radiation workers. Methods Radiation workers who underwent occupational health examinations at a hospital in Guangzhou from 2015 to 2022 were selected as the subjects of this study. The levels of FT3, FT4 and TSH were analyzed, and the thyroid abnormality status of radiation workers in different groups were compared. Results A total of 1152 participants were included in this study, consisting of 885 (76.82%) males and 267 (23.18%) females, with an average age of (35.26 ± 10.16) years. The prevalence of thyroid abnormalities was 9.38%, which was significantly higher in females (13.86%) than in males (8.02%) (P < 0.05). The TSH level of females [(2.15 ± 1.29) mIU/L] was higher than that of males [(1.85 ± 1.20) mIU/L], while the levels of FT3 [(5.10 ± 0.64) pmol/L] and FT4 [(15.84 ± 2.32) pmol/L] in females were lower than those in males [(5.23 ± 0.63) pmol/L and (16.61 ± 2.75) pmol/L, P < 0.05]. The FT3 of industrial workers [(5.25 ± 0.63) pmol/L] was higher than that of medical workers [(5.10 ± 0.63) pmol/L], while the TSH of industrial workers [(1.80 ± 1.12) mIU/L] was lower than that of medical workers [(2.15 ± 1.37) mIU/L]. FT4 levels decreased with increasing age and duration of occupational exposure. Multivariable logistic regression analysis revealed that sex was a significant independent predictor of thyroid abnormalities among radiation workers. Female workers were more likely to experience thyroid abnormalities (β = −0.62, P < 0.05). Conclusion Low-dose ionizing radiation may have a certain impact on the thyroid status of radiation workers, especially for female workers, which requires further attention and research.

This study analyzed and compared the epidemiological characteristics of foodborne listeriosis in the United States and China,to provide evidence for optimizing the listeriosis surveillance program in China.Descriptive statistical analysis was performed on the listeriosis monitoring data from 2009 to 2021 registered in the FDOSS system and the attribution estimates of Listeria monocytogenes(L.monocytogenes)from 2013 to 2021 published by IFSAC.Sporadic and outbreak data on listeriosis in China from the CNKI,Wanfang Medical,and CQVIP databases were collected.From 2009 to 2021,a total of 1 037 listeriosis cases were reported in the United States,including 902 hospitalizations and 165 deaths.The peak of cases caused by Lm con-taminated food was in July.The number of cases,hospitalizations,and deaths accounted for 18.4％(191/1 037),20.5％(185/902),and 22.4％(37/165)of the total,respectively.Most listeriosis outbreaks were attributed to three food groups:dairy products,vegetable crops,and fruits,with attribution percentages ranging from 73.8％to 89.6％.The overall incidence of list-eriosis in China was not high:619 cases were reported from 2009 to 2021,and only 177 cases were recorded in detailed inci-dence years;the maximum number of cases in 2018 was 26.A total of 220 cases were reported with detailed onset months;the highest number of cases in April was 30.Data on listeriosis cases in China are incomplete and sporadic,and only seven cases have been successfully traced to food.Listeriosis surveillance systems in the United States are relatively complete,and there are more foodborne outbreaks.Dairy products,vegetable row crops,and fruits are the most likely causes of disease outbreaks.Although only sporadic cases have been reported in China,China should take actions such as gradually improving multi-department coop-eration mechanisms,achieving data sharing and deepening data mining,and accelerating progress in the detection technology of food-borne pathogenic microorganisms,to ensure food safety and public health.

Investigating the species/biovars,distribution patterns,and genetic correlations of Brucella from sheep in north-west China is critical to reveal the population and epidemiological characteristics of the Brucella melitensis.In this study,con-ventional identification and AMOS-PCR were used to determine the species/biovars of Brucella isolated from 13 regions in northwest China.MLST and MLVA-16 genotyping methods were used to analyze the genetic characteristics of the strains.Con-ventional identification and AMOS-PCR detection revealed that 59 Brucella melitensis were isolated in this study,in-cluding 22 strains from Inner Mongolia,17 strains from Xin-jiang,13 strains from Gansu,and 7 strains from Qinghai,of which 58 strains were B.melitensis biovar 3,and one strain was B.melitensis biovar 1.MLST analysis indicated that 90％(53/59)of B.melitensis were of ST8 sequence type,the dominant epidemic population.The MLVA-11 survey demonstrated that 59 B.melitensis strains clustered into six MLVA-11 genotypes,and 87％of the strains were of MLVA-11 genotype 116.Therefore,the predominant strains in the northwest region were from the Eastern Mediterranean lineage.MLVA-16 divided 59 strains of B.melitensis into 40 gen-otypes,eight of which were shared genotypes.Each genotype was composed of two to seven strains from the same region,thereby indicating that the cases of each shared genotype were outbreaks from a common source of infection.All shared MLVA-16 genotypes comprised strains from the same province,thus indicating apparent regional clustering characteristics of strains in each province.In a genetic comparison between populations and isolated strains from the spleens of sheep,multiple identical MLVA-16 genotypes were found to be composed of strains from different hosts.These findings indicated a transmission path-way from sheep/goats to humans.B.melitensis biovar 3 was the main pathogen causing animal brucellosis in the northwest re-gion,and infected sheep were the main brucellosis infection source in the regional population.The ST8 strains were the domi-nant epidemic population,and the MLVA genotype of strains in each region showed clear regional clustering characteristics.

Objective:To investigate the accuracy of next-generation sequencing technology(NGS)in detecting the polymorphisms of HLA-DRB1,DQB1,DQA1,DRB3,DRB4,DRB5,DPA1 and DPB1 alleles in randomly-selected unrelated healthy individuals from Shenzhen Han population,investigate the potential reason for HLA-DRB1 allele dropout in routine NGS,and establish an internal quality control system.Methods:NGS-based HLA class Ⅱ genotyping was performed on 1 012 samples using the MiSeqDxTM platform.The suspected missed alleles indicated by the quality control software and HLA-DRB1 homozygotes were confirmed by PCR-SSOP or PCR-SBT methods.Results:A total of 139 alleles were detected,including HLA-DRB1(45),DRB3(7),DRB4(5),DRB5(7),DQA1(17),DQB1(21),DPA1(10)and DPB1(27).HLA-DRB 1*09:01(17.09％),15:01(10.72％);DRB3*02:02(25.99％),03:01(10.18％);DRB4*01:03(36.46％);DRB5*01:01(15.42％);DQA1*01:02(20.01％),03:02(17.19％);DQB1*03:01(19.47％),03:03(17.98％),05:02(11.66％),06:01(10.67％);DPA1*02:02(54.45％),01:03(31.18％)and DPB1*05:01(39.13％),02:01(16.90％)alleles were the most common alleles in Shenzhen Han population(frequencies＞10％).There was no statistical difference between the gene frequencies of HLA-DRB1 and DQB1 loci in our study.The HLA Common and Well-Documented Alleles in China(CWD2.4)(x2=12.68,P＞0.05).94 cases of HLA-DRB1 homozygous samples detected by NGS were retested by PCR-SSOP or SBT method,and one case of allele dropout at HLA-DRB1 locus was found.SBT method confirmed that the allele of DRB1*04:03 was missed.The laboratory internal quality control system was established.Two cases of new alleles were detected and named by WHO Nomenclature Committee for Factors of the HLA System.Conclusion:The HLA genotyping results based on NGS showed a significantly lower ambiguity rate.The HLA class Ⅱ alleles exhibit genetic polymorphism in the Han population of unrelated healthy individuals in Shenzhen.The independent method based on NGS in clinical histocompatibility testing has limitations and requires internal quality control strategies to avoid allele-dropout events.

Objective:To investigate the efficacy and safety of daratumumab based regimens in relapse and/or refractory multiple myeloma(RRMM)in the real world,as well as the impact of daratumumab on stem cell collection and engraftment.Methods:The clinical data of patients with RRMM who received daratumumab in hematology department of the First Affiliated Hospital of Xiamen University from February 2019 to March 2023 and had evaluable efficacy were retrospective analysis.Results:All 43 RRMM patients were treated with daratumumab-based combination regimens,including Dd,DVd,DRd,Dkd,DId,and Dara-DECP.With median follow-up time 10.1(2.1-36.6)months,the best overall response rate(ORR)was 74.4％and a best complete response rate(CR)was 25.6％.1-year overall survival rate(OS)was 84.5％.The most common severe hematologic adverse events(Grade＞3)are 3/4 grade leukopenia(18.6％),and the most common severe non-hematologic adverse events were infusion-related reactions(IRRs,20.9％)and infections(7.0％).Multivariate prognostic analysis showed that extramedullary infiltration was an independent adverse prognostic factor affecting OS(P=0.004).The use of daratumumab has no effect on stem cell collection,or engraftment.Conclusion:Daratumumab is safe and effective in RRMM.