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.

To clarify the occurrence and distribution of broad bean wilt virus 2(BBWV2) on Rehmannia glutinosa, this study collected 87 R. glutinosa samples with typical symptoms of viral disease such as chlorosis and crumple from Wenxian county and Wuzhi county in Jiaozuo city, Henan province and Qiaocheng district in Bozhou city, Anhui province. The BBWV2 CP target band was amplified from 37 R. glutinosa samples by RT-PCR technology. The total detection rate reached 42.5%, among which 43.0% was detected in samples from Henan province. The detection rate in samples from Anhui province was 37.5%. 37 BBWV2 CP sequences were obtained by cloning and sequencing of BBWV2 positive samples(data has been submitted to GenBank, accession numbers: PP407959-PP407995), and the sequence analysis of these CP sequences with 91 other BBWV2 isolates in GenBank showed a high genetic diversity with a consistency rate of 70.8%-100%. Meanwhile, phylogenetic analysis showed that BBWV2 could be divided into three groups according to CP sequences, among which the BBWV2 in R. glutinosa isolates obtained in this study were all located in group 3. This study identified the differences in the occurrence, distribution, and genetic diversity of BBWV2 in R. glutinosa from Henan province and Anhui province and provided a theoretical basis for the prevention and control of BBWV2.
Rehmannia/virology* ; Phylogeny ; Plant Diseases/virology* ; China ; Molecular Sequence Data ; Fabavirus/classification*

Lipopolysaccharides (LPS) are major outer membrane components of Gram-negative bacteria. Unlike most Gram-negative bacteria, Acinetobacter baumannii can still survive and acquire polymyxin resistance after complete loss of LPS. Previous studies of LPS-deficient Acinetobacter baumannii mostly focused on LPS-deficient strains induced by polymyxin, whose background was complex and unstable. To investigate LPS loss-mediated polymyxin resistant-Acinetobacter baumannii, this study constructed a stable and clear background LPS-deficient strain by knocking out lpxC gene in Acinetobacter baumannii ATCC 19606 with CIRSPR/Cas9, and then studied the phenotypic changes of the lpxC-deficient strain including morphology, growth rate, antibiotic susceptibility, virulence, membrane permeability, and membrane potential. Animal experiments were approved by the Animal Care and Welfare Committee Institute of Medicinal Biotechnology, CAMS and PUMC (approval number: IMB-20240119D₉). The results indicated that the lpxC gene of Acinetobacter baumannii ATCC 19606 was successfully knocked out. After losing the lpxC, the strain underwent the morphological change from rod-shaped to spherical. Furthermore, it leads to reduced growth rate, enhanced membrane permeability, decreased membrane potential, lower virulence, and increased antibiotic susceptibility to β-lactams, quinolones, aminoglycosides, macrolides, glycopeptides. The lpxC deletion results in significant changes in membrane homeostasis and adaptability of Acinetobacter baumannii. Understanding the phenotypic changes of colistin-resistant Acinetobacter baumannii mediated by LPS loss is useful for exploring the resistance mechanism of Acinetobacter baumannii and developing new therapeutic strategies.

Objective:To assess the value eosin-nigrosine(E-N)staining and hypo-osmotic swelling test(HOST)in the diag-nosis of necrospermia and investigate the correlation of the degree of sperm necrosis with sperm DNA fragmentation index(DFI)and high DNA stainability(HDS).Methods:Using computer-assisted sperm analysis(CASA),we examined the sperm motility of 7 333 males seeking medical care in Maternal and Child Health Hospital of Hunan Province from May 2023 to July 2024,detected the sperm viability of those with asthenozoospermia by E-N staining and HOST,and measured the sperm DFI and HDS of those with necro-spermia by sperm chromatin structure assay(SCSA).Based on sperm progressive motility(PR％),we divided the asthenozoospermia patients into three groups(PR％20％-＜30％,PR％10％-＜20％and PR％＜10％),assessed the value of E-N staining and HOST in the diagnosis of necrospermia,and analyzed the correlation of the severity of sperm necrosis with sperm DFI and HDS.Results:Asthenozoospermia was diagnosed in 1 374(18.74％)of the 7 333 males.The incidence rates of necrospermia revealed by E-N staining in the mild,moderate and severe asthenozoospermia groups were 0.55％(5/913),3.80％(12/316)and 35.86％(52/145),respectively,with a total incidence of 0.94％(69/7333),while those detected by HOST were 0.99％(9/913),6.96％(22/316)and 46.21％(67/145),respectively,with a total incidence of 1.34％(98/7333).There were no statistically significant differences in the results of diagnosis between the two methods(x2=0.97,P＞0.05).Both E-N staining and HOST showed that sperm DFI in the necrospermia males was negatively correlated with sperm viability(r=-0.366,r=-0.333,P＜0.05),and so was sperm HDS,though with no statistically significant difference(P＞0.05).Conclusion:For males with PR％＜30％,sperm viability test should be conducted,with E-N staining as the choice of priority for the diagnosis of necrospermia.Sperm necrosis and sperm nuclear chromatin damage may be interactive risk factors.

Objective:To evaluate the diagnostic performance of the Prostate Imaging Reporting and Data System version 2.1(PI-RADS v2.1)for clinically significant prostate cancer(CSPCa)in the peripheral zone(PZ),transitional zone(TZ)and multiple zones(MZs).Methods:We retrospectively studied the clinical data on 108 patients undergoing multiparametric magnetic resonance imaging(mpMRI)and transperineal prostate biopsy in our hospital from January 2021 to January 2023.Using PI-RADS v2.1,we ex-amined the MR images of the patients with suspected PCa,compared the PI-RADS v2.1 scores with the results of prostate biopsy,and analyzed the correlation of the PI-RADS v2.1 scores with CSPCa.We calculated the area under the receiver operating characteristic(ROC)curve(AUC),and described the diagnostic performance of PI-RADS v2.1 for CSPCa in the PZ,TZ and MZs.Results:Transperineal prostate puncture biopsy was successfully completed in all the patients,which revealed 66(61.11％)cases of CSPCa with Gleason score(GS)7-10.Suspected CSPCa was observed in 45(95.74％)of the 47 PZ lesions,8(47.06％)of the 17 TZ le-sions,and 40(90.91％)of the 44 MZ lesions.The PZ,TZ and MZ lesions diagnosed by PI-RADS v2.1 were significantly correlated with CSPCa(r=0.492,P＜0.001).The AUCs of PI-RADS v2.1 for PZ,TZ and MZs were 0.644,0.732 and 0.811,with specificities of 66.8％,57.6％and 62.1％,and sensitivities of 57.2％,78.4％and 93.2％,respectively.The negative predictive values were 46.5％,85.7％and 79.2％,and the positive predictive values 76.2％,43.4％and 84.8％,respectively.Conclusion:The PI-RADS v2.1 score has a high diagnostic value for CSPCa in the PZ,TZ and MZs,with the best performance for that in the MZs.

OBJECTIVES: To investigate the risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture and establish a nomogram model for predicting the risk of neonatal asphyxia. METHODS: A retrospective study was conducted with 613 cases of neonatal asphyxia treated in 20 cooperative hospitals in Enshi Tujia and Miao Autonomous Prefecture from January to December 2019 as the asphyxia group, and 988 randomly selected non-asphyxia neonates born and admitted to the neonatology department of these hospitals during the same period as the control group. Univariate and multivariate analyses were used to identify risk factors for neonatal asphyxia. R software (4.2.2) was used to establish a nomogram model. Receiver operator characteristic curve, calibration curve, and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the model for predicting the risk of neonatal asphyxia, respectively. RESULTS: Multivariate logistic regression analysis showed that minority (Tujia), male sex, premature birth, congenital malformations, abnormal fetal position, intrauterine distress, maternal occupation as a farmer, education level below high school, fewer than 9 prenatal check-ups, threatened abortion, abnormal umbilical cord, abnormal amniotic fluid, placenta previa, abruptio placentae, emergency caesarean section, and assisted delivery were independent risk factors for neonatal asphyxia (P<0.05). The area under the curve of the model for predicting the risk of neonatal asphyxia based on these risk factors was 0.748 (95%CI: 0.723-0.772). The calibration curve indicated high accuracy of the model for predicting the risk of neonatal asphyxia. The decision curve analysis showed that the model could provide a higher net benefit for neonates at risk of asphyxia. CONCLUSIONS The risk factors for neonatal asphyxia in Hubei Enshi Tujia and Miao Autonomous Prefecture are multifactorial, and the nomogram model based on these factors has good value in predicting the risk of neonatal asphyxia, which can help clinicians identify neonates at high risk of asphyxia early, and reduce the incidence of neonatal asphyxia.
Infant, Newborn ; Humans ; Male ; Pregnancy ; Female ; Nomograms ; Retrospective Studies ; Cesarean Section ; Risk Factors ; Asphyxia Neonatorum/etiology*