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.

Atrial functional mitral regurgitation (AFMR) is mitral regurgitation in patients with atrial fibrillation (AF), whose left atrium (LA) is enlarged, the left ventricle is not enlarged or only slightly enlarged, the left ventricular ejection fraction is preserved, and the mitral valve itself has no apparent lesion. At present, the etiology, pathophysiology and mechanism of this disease have not been completely clear yet. Existing studies have found that the causes of AFMR mainly include AF, enlargement of LA and mitral annulus, destruction of mitral annular shape, inability of mitral valve remodeling to compensate for mitral annular expansion, and hamstringing of the posterior mitral leaflet by atriogenic tethering. AFMR is demonstrated to be associated with an increased risk of mortality and readmission due to heart failure. Therefore, it serves as a primary therapeutic target for patients with heart failure and AF. However, the optimal treatment of AFMR still remains controversial. Therefore, this article will mainly expound the current definition, etiology, pathophysiological mechanism, treatment, and prognosis of AFMR.

ObjectiveTo explore the risk factors and survival analysis of chemotherapy compliance in ≥65 years old patients with non-small cell lung cancer. MethodsFrom December 2018 to August 2020， 110 patients with non-small cell lung cancer ≥65 years old in our hospital were selected for study. According to their chemotherapy compliance， the patients were divided into untreated （25 cases）， partial chemotherapy （30 cases） and full chemotherapy （55 cases）. Multivariate Cox regression was used to analyze the independent risk factors affecting the compliance of chemotherapy among the three groups， and constructed a column chart prediction model and evaluated the diagnostic effectiveness of the model using receiver operating characteristic （ROC） curves， calibration curves， and clinical decision curves. The patients were followed up until August 2023. Kaplan-Meyer survival curve and Log-rank test were used to compare the differences in survival time between the groups. ResultsThere were significant differences among the three groups in gender， long-term smoking history， education level， Charlson complication index， toxic and side effects of chemotherapy drugs and dosage， pathological type， operation mode， place of residence， payment mode， chemotherapy stage， white blood cell count and neutrophils （P<0.05）. Multivariate Cox analysis showed that patients' education level， pathological TNM stage， toxic and side effects of chemotherapy drugs and dosage， operation mode， residence， payment mode and chemotherapy stage were independent risk factors affecting chemotherapy compliance of patients with non-small cell lung cancer （all P<0.05）. There were significant differences in the survival rates between the non-chemotherapy group and the full chemotherapy group， and between the partial chemotherapy group and the full chemotherapy group （P<0.05）， but there was no significant difference between the non-chemotherapy group and the partial chemotherapy group （P>0.05）. And based on this， a prediction model was constructed， and the ROC curve was drawn to show that the AUC of the model was 0.758 （95%CI： 0.743‒0.855）， the sensitivity was 0.788， and the specificity was 0.853， indicating that the model had high discrimination， the calibration curve indicated that the prediction model had good accuracy， the clinical decision curve indicated that the predictive model had strong clinical practicality. ConclusionNSCLC tends to occur in the elderly. We should focus on the patients with low educational level， late pathological TNM stage， severe toxicity and side effects， high dose of chemotherapy drugs， having undergone open chest surgery， living in rural areas， without medical insurance， and in the period of chemotherapy consolidation and refractory relapse， so as to improve their compliance with chemotherapy.