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 evaluate the partial biomechanical properties of the posterior occipital muscles (rectus capitis posterior major, rectus capitis posterior minor, and obliquus capitis inferior) in patients with cervical vertigo. METHODS: A total of 30 patients with cervical vertigo admitted from April 2024 to September 2024 were included in the vertigo group, and 30 age-and gender-matched healthy subjects were recruited as the normal group. In the vertigo group, there were 21 females and 9 males, with an average age of (24.00±2.25) years;in the normal group, there were 22 females and 8 males, with an average age of (23.00±3.00) years. Shear wave elastography was used to measure the thickness and stiffness of the posterior occipital muscles in both groups. RESULTS: In the vertigo group, there were no statistically significant differences in the Young's modulus values (E) of stiffness of the posterior occipital muscles (rectus capitis posterior major, rectus capitis posterior minor, obliquus capitis inferior) between the left and right sides(P>0.05). The Young's modulus values(E) of stiffness of the right posterior occipital muscles (rectus capitis posterior major, rectus capitis posterior minor, obliquus capitis inferior) in the cervical vertigo group were (39.66±8.21) kPa, (45.61±5.85) kPa, and (43.73±5.22) kPa, respectively, which were significantly higher than those in the normal group 33.97(17.76) kPa, 41.38(8.99) kPa, 38.27(12.58) kPa, with statistically significant differences (P<0.05). In the vertigo group, the Young's modulus values(E) of stiffness of the left rectus capitis posterior major and left obliquus capitis inferior were (40.41±9.13) kPa and (42.11±6.20) kPa, respectively, which were significantly greater than those in the normal group (33.30±11.31) kPa, 38.94(14.62) kPa, with statistically significant differences(P<0.05);however, there was no statistically significant difference in the left rectus capitis posterior minor between the two groups(P>0.05). In the vertigo group, there were no statistically significant differences in the stiffness of the posterior occipital muscles (rectus capitis posterior major, rectus capitis posterior minor, obliquus capitis inferior) between the left and right sides(P>0.05). Additionally, there were no statistically significant differences in the thickness of the bilateral posterior occipital muscles between the vertigo group and the normal group (P>0.05). CONCLUSION The posterior occipital muscles of patients with cervical vertigo are stiffer than those of healthy individuals, while there is no significant difference in muscle thickness between the two groups.
Humans ; Female ; Male ; Elasticity Imaging Techniques/methods* ; Adult ; Vertigo/physiopathology* ; Neck Muscles/physiopathology* ; Young Adult

Glutamine provides carbon and nitrogen to support the proliferation of cancer cells. However, the precise reason why cancer cells are particularly dependent on glutamine remains unclear. In this study, we report that glutamine modulates the tumor suppressor F-box and WD repeat domain-containing 7 (FBW7) to promote cancer cell proliferation and survival. Specifically, lysine 604 (K604) in the sixth of the 7 substrate-recruiting WD repeats of FBW7 undergoes glutaminylation (Gln-K604) by glutaminyl tRNA synthetase. Gln-K604 inhibits SCFFBW7-mediated degradation of c-Myc and Mcl-1, enhances glutamine utilization, and stimulates nucleotide and DNA biosynthesis through the activation of c-Myc. Additionally, Gln-K604 promotes resistance to apoptosis by activating Mcl-1. In contrast, SIRT1 deglutaminylates Gln-K604, thereby reversing its effects. Cancer cells lacking Gln-K604 exhibit overexpression of c-Myc and Mcl-1 and display resistance to chemotherapy-induced apoptosis. Silencing both c-MYC and MCL-1 in these cells sensitizes them to chemotherapy. These findings indicate that the glutamine-mediated signal via Gln-K604 is a key driver of cancer progression and suggest potential strategies for targeted cancer therapies based on varying Gln-K604 status.
Glutamine/metabolism* ; Myeloid Cell Leukemia Sequence 1 Protein/genetics* ; Humans ; Proto-Oncogene Proteins c-myc/genetics* ; Cell Proliferation ; Signal Transduction ; Neoplasms/pathology* ; F-Box-WD Repeat-Containing Protein 7/genetics* ; Cell Survival ; Cell Line, Tumor ; Apoptosis

In recent years,the isolation rate of carbapenem-resistant Klebsiella pneunoniae(CRKP)in China has increased year by year.Due to its multidrug resistance and high mortality in patients,CRKP brings severe challen-ges to the clinical treatment.The major mechanism of drug resistance in CRKP is the production of carbapenemases,with Ambler A,B,and D being the common types while Ambler type C comparativly rare.Klebsiella pneumoniae carbapenemase(KPC)is the most common carbapenemase,which belongs to type A.KPC-producing Klebsiella pneumoniae(KPC-KP)widely spreads in the world,with very limited number of effective clinical drugs.In this re-view,advances in the treatment KPC-KP were summarized to provide reference for clinical treatment.

ObjectiveTo explore the correlation between skeletal muscle mass and metabolic syndrome （MS） disease risk among middle-aged and elderly community residents in Urumqi， and to provide a theoretical basis for understanding the relationship between skeletal muscle mass and MS among middle-aged and elderly community residents in China. MethodsA total of 1 438 community residents ≥ 50 years old were selected as the research subjects from July 2018 to January 2019 in Urumqi. They were selected from a multi-ethnic natural population cohort in Xinjiang. Data were collected through questionnaires， physical examination， bioelectrical impedance analysis （BIA）， laboratory tests， etc. Skeletal muscle mass was evaluated using the limb skeletal muscle mass index （SMI） corrected for body weight； MS was defined as it at least includes three of the following： abdominal obesity， hypertension， hyperglycemia， high triglycerides and low high-density lipoprotein cholesterol. SMI was divided into four quantile arrays of Q₁‒Q₄. Trend χ² test was applied to explore whether there was a correlation between SMI changes and MS. A multivariate logistic regression model was used to analyze whether there is a difference in the risk of MS between the higher SMI group （Q₂， Q₃， Q₄） and the reference group Q₁. ResultA total of 560 MS patients were detected in this study， with a prevalence rate of 38.94%. Among them， the prevalence rate of MS was 39.16% in males and 38.80% in females. The increase in male SMI grading level is not correlated with the prevalence of MS （trend P>0.05）； After adjusting for confounding factors （model 4）， the increase in SMI was still not related to the prevalence of MS （P_trend=0.995）. There was no statistical difference in the risk of MS between the lowest quartile group Q₁ and the highest quartile group Q₄ （OR=1.01， 95%CI： 0.69‒1.78）. The prevalence of MS in women gradually decreased with the increase of SMI grading level （P_trend<0.001）； After adjusting for confounding factors （model 4）， there was still a correlation between the increase of SMI and the prevalence of MS （P_trend=0.005）. With the lowest quartile of SMI Q₁ as the reference group， the risk of MS in Q₂ （OR=0.63， 95%CI： 0.40‒1.00）， Q₃ （OR=0.56， 95%CI： 0.34‒0.94）， Q₄ （OR=0.42， 95%CI： 0.23‒0.76） decreased. ConclusionAn increase in skeletal muscle mass may be beneficial for preventing MS， especially among middle-aged and elderly female residents. Considering the intensification of aging in China and the close relationship between MS and related comorbidities， managing skeletal muscle mass may contribute to potential MS prevention.

Objective: To explore the relationship between air pollutants and pediatric outpatient volumes in Baoshan District, Shanghai Municipality. Methods: Data of meteorological factors, air pollutants and pediatric outpatient volumes in four general hospitals were collected in Baoshan District from 2015 to 2019, and a generalized additive model was used to fit the Poisson-like distribution. The exposure-response relationship between fine particulate matter (PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3) and total pediatric outpatient volumes and pediatric respiratory outpatients. Results: The median of the average daily temperature and relative humidity were 18.7 (interquartile range, 14.4) ℃ and 74.5% (interquartile range, 18.0%) in Baoshan District from 2015 to 2019, respectively. The median of the average daily concentrations of PM2.5, SO2, NO2 and O3 were 35.0 (interquartile range, 35.0), 11.0 (interquartile range, 7.0), 45.0 (interquartile range, 31.8) and 84.5 (interquartile range, 50.0) μg/m3, respectively. The median of the average daily total and respiratory pediatric outpatient volumes were 680 (interquartile range, 246) and 392 (interquartile range, 253). Spearman rank correlation analysis showed that temperature, relative humidity, PM2.5, SO2, NO2 and O3 were associated with total and respiratory pediatric outpatient volume (all P<0.05). Under the single pollutant model, the excess risk of total and respiratory pediatric outpatient volume due to PM2.5 (ER=0.318, 0.257), SO2 (ER=1.610, 2.546), and NO2 (ER=0.808, 0.839) reached the maximum effect on the same day, and the effect of O3 (ER=0.102, 0.222) reached its maximum at the first day of lag. Under the multi-pollutant model, after O3, SO2, NO2 and PM2.5 were introduced, a exposure-response relationship between air pollutants and total pediatric outpatient volumes was the largest on the sixth day after the lag (ER=0.419). There was no exposure-response relationship between air pollutants and respiratory pediatric outpatient volumes. Conclusion PM2.5, SO2, NO2 and O3 are associated with total and respiratory pediatric outpatient volumes, and the lag effects due to different air pollutants are different.