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.

The injury of the posterior Angle of the medial meniscus of the knee joint is very common in clinic, and the arthroscopic treatment of the knee joint has been the first choice. However, there are many difficulties in arthroscopic treatment, such as narrow space in the medial posterior corner of the knee joint, insufficient space to deal with the injured meniscus, varion and lateral rotation under 30° flexion, release of the medial collateral ligament of the knee joint, and expansion of the knee joint cavity spinner, all of which could expose and expand the medial space of knee joint. Therefore, it is necessary to master and balance the use to avoid collateral injury. It is also necessary to determine the cause of meniscus injury during arthroscopic treatment, such as degenerative injury, simple meniscus repair and forming can hardly solve the pain of patients. Anterior cross injury is easy to cause instability of the knee joint, which is closely related to the injury of the posterior angle of the medial meniscus of the knee joint. In order to achieve the maximum therapeutic effect, physiological repair should be performed at the same time. There are various types of medial meniscus posterior angle injury, among which the Ramp injury, root fracture and laminae meniscus injury are greatly affected by joint degeneration, narrow knee space or knee stability, and all influencing factors should be fully considered in treatment.
Humans ; Arthroscopy/methods* ; Tibial Meniscus Injuries/surgery* ; Knee Joint/surgery* ; Menisci, Tibial/surgery* ; Knee Injuries/surgery*

Objective To investigate the effects of palmatine on migration,invasion and epithelial mesenchymal transformation(EMT)in human oral cancer KB cells.Methods KB cells were divided into control group and palmatine-L,-M,-H groups,cultured with 0,4,8 and 16 μmol·L-1 palmatine.After incubation for 48 h,scratch assay was used to detect migration;Traswell assay was used to detect invasion;matrix metalloproteinase 2(MMP-2),MMP-9 and fibronectin(FN)contents were detected by enzyme-linked immunosorbent assay;the expression of Vimentin,N-cadherin and E-cadherin mRNA were detected by real-time quantitative polymerase chain reaction;the expression of Vimentin,N-cadherin,E-cadherin,Wnt3 and β-catenin protein were detected by Western blot.Results Cell mobility in control group and palmatine-L,-M,-H groups were(69.27±8.62)％,(52.94±4.49)％,(45.22±5.05)％and(37.63±4.88)％;the number of transmembrane cells were 197.33±20.26,125.33±12.01,97.00±9.17 and 62.67±7.51;the content of MMP-2 were(2.93±0.21),(1.49±0.13),(1.16±0.15)and(0.95±0.09)ng·mL-1;the content of MMP-9 were(3.51±0.36),(2.37±0.23),(2.06±0.35)and(1.72±0.16)ng·mL-1;the content of FN were(41.28±4.02),(24.03±3.17),(20.67±2.63)and(13.82±2.19)ng·mL-1;the above indexes in palmatine-L,-M,-H groups were compared with the control group,and the differences were statistically significant(P＜0.05,P＜0.01).The mRNA and protein expressions of Vimentin,N-cadherin and E-cadherin,and the expressions of Wnt3 and β-catenin protein in palmatine-L,-M,-H groups were statistically significant compared with those in control group(P＜0.05,P＜0.01).Conclusion Palmatine can inhibit the migration,invasion and EMT of human oral cancer KB cells,and its mechanism is related to the regulation of Wnt/β-catenin signaling pathway.

OBJECTIVE: To provide an overview of the incidence of knee donor -site morbidity after autologous osteochondral mosaicplasty. METHODS: A comprehensive search was conducted in PubMed, EMbase, Wanfang Medical Network, and CNKI databases from January 2010 to April 20, 2021. Relevant literature was selected based on predefined inclusion and exclusion criteria, and data were evaluated and extracted. The correlation between the number and size of transplanted osteochondral columns and donor-site morbidity was analyzed. RESULTS: A total of 13 literatures were included, comprising a total of 661 patients. Statistical analysis revealed an incidence of knee donor-site morbidity at 8.6% (57/661), with knee pain being the most common complaint, accounting for 4.2%(28/661). There was no significant correlation between the number of osteochondral columns and postoperative donor-site incidence (P=0.424, N=10), nor between the diameter size of osteochondral columns and postoperative donor-site incidence(P=0.699, N=7). CONCLUSION Autologous osteochondral mosaicplasty is associated with a considerable incidence of knee donor-site morbidity, with knee pain being the most frequent complaint. There is no apparent correlation between donor-site incidence and the number and size of transplanted osteochondral columns. Donors should be informed about the potential risks.
Humans ; Incidence ; Cartilage/transplantation* ; Knee ; Knee Joint/surgery* ; Pain ; Cartilage, Articular ; Transplantation, Autologous ; Bone Transplantation

Ongoing global pandemic of Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has promoted the unprecedented rapid development and large-scale rolling out of different platform-based COVID-19 vaccines worldwide. How to effectively respond to the expected scale increasing adverse events after vaccination campaign of COVID-19 vaccines is a common problem faced by the world. A lot of countries and regions around the world have arranged in advance at different levels, optimizing the original vaccine safety monitoring system from the perspectives of strengthening the foundation and capabilities, promoting internal and external cooperation, upgrading methods, as well as improving transparency and public communication, which has ensured the good and efficient operation of the system and can provide reference for the construction of relevant fields in China.
Humans ; COVID-19/prevention & control* ; COVID-19 Vaccines ; Pandemics/prevention & control* ; SARS-CoV-2 ; Viral Vaccines/adverse effects*