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 classification of impacted third molars is important in clinical diagnosis and surgical selection. At present, the common clinical impacted third molar classification is different in the maxillary and mandibular classification criteria. Through the review and analysis of various classification methods of impacted third molar, this paper proposes a more comprehensive and unified classification proposal for the classification of impacted third molar, in order to form a widely accepted application classification method.

Objective To investigate how flavokawain B(FKB)affects the proliferation and migration of triple-negative breast cancer(TNBC)cells by downregulating the androgen receptor(AR).Methods The expression of AR in breast cancer and normal tissues was analyzed using the GEPIA2 database.Expression of estrogen receptor(ER),human epidermal growth factor receptor 2(HER2),progesterone receptor(PR),and AR was detected in six breast cancer cell lines(SUM159PT,MCF-7,T47D,BT474,Hs-578T,and MDB-MA-231)by Western blotting.The effect of FKB(0,10,20,30,40,50,60 μmoL/L)treatment of 24,48,and 72 h on the proliferative activity of SUM159PT breast cancer cells was assessed using the CCK-8 assay under normal or androgen deprivation conditions.The mRNA and protein of AR expression was measured by qRT-PCR and Western blotting after 30 μmoL/L FKB treatment of SUM159PT cells for 0,4 and 8 h.SUM159PT cells were set as control group(treatment with 0.1%DMSO),dihydrotestosterone(DHT)group(treatment with 10 nmol/L DHT),FKB group(treatment with 15 μmol/L FKB),DHT+FKB group(treatment with 10 nmol/L DHT and 15 μmol/L FKB),AR antagonist enzalutamide(ENZA)group(treatment with 40 μmol/L ENZA),and DHT+ENZA group(treatment with 10 nmol/L DHT and 40 μmol/L ENZA)under androgen deprivation conditions.Cell proliferation,migration,and colony formation abilities in the above groups were determined using the CCK-8 method,Transwell assay,and clone formation test.Western blotting was also used to detect the expression levels of EMT-related proteins(N-cadherin,Occludin,Vimentin)and AR protein.Results AR mRNA expression level was significantly higher in breast cancer tissue than in normal breast tissue(P<0.05).AR was expressed at comparable levels in five different breast cancer cell lines(SUM159PT,MCF-7,T47D,BT474,and Hs-578T)in addition to MDB-MA-231.FKB can downregulate AR mRNA and protein levels(P<0.05).Western blotting results showed that DHT could upregulate AR protein levels in SUM159PT cells,but FKB could prevent the DHT-induced upregulation of AR protein levels(P<0.05).FKB and ENZA decreased SUM159PT cell proliferation and migration and DHT-mediated cell proliferation and migration(P<0.05).FKB and ENZA can reduce N-cadherin and Vimentin protein levels and counteract DHT-induced increases in N-cadherin and Vimentin protein levels(P<0.05).In addition,FKB may increase Occludin expression and counteract the DHT-induced decrease in Occludin protein expression(P<0.05).Conclusion Flavokawain B could inhibit the proliferation,migration,and clonogenic ability of TNBC cells by regulating AR expression.

Objective To explore the role of resveratrol in the immune response and proliferation of macrophages induced by homocysteine(Hcy).Methods ANA-1 cells were divided into control group(conventional culture),model group(100 μmol·L-1 Hcy),experimental-L,-M,-H groups(adding 25,50 and 100 μmol·L-1 resveratrol to model group,respectively),Hcy+Ad-SIRT1 group(100 μmol·L-1 Hcy+Ad-SIRT1),Hcy+si-FOXO1 group(100 μmol·L-1 Hcy+si-FOXO1),Hcy+Res-L+Ad-SIRT1+si-FOXO1 group(100 μmol·L-1 Hcy+25 μmol·L-1 Resveratrol transfected with Ad-SIRT1+si-FOXO1).The cell proliferation was detected by methyl thiazolyl tetrazolium(MTT),and the concentration of interleukin-6(IL-6)and tumor necrosis factor-α(TNF-α)in the supernatant of cell culture medium was detected by enzyme-linked immunosorbent assay.The gene and protein expression of silencing information regulator 1(SIRT1)and forkhead protein 01(FOXO1)were detected by Western blot.Results The optical density of 450 nm in control group,model group and experimental-L,-M,-H groups were 0.25±0.02,0.36±0.02,0.33±0.01,0.30±0.02 and 0.29±0.01,respectively.Compared with the control group,the cell proliferation in the model group was significantly increased(P＜0.05).Cell proliferation in experimental-L,-M,-H groups was significantly decreased compared with model group(all P＜0.05).IL-6 in the supernatant of cell culture medium of control group,model group and experimental-L group were(394.04±20.06),(614.23±21.09)and(501.53±16.52)pg·mL-1,respectively;TNF-α were(516.54±18.96),(717.22±24.81)and(632.74±19.11)pg·mL-1,respectively;SIRT1 relative protein expression were(1.00±0.05),(0.57±0.05)and(0.77±0.04),respectively;the relative protein expression of FOXO1 were 1.00±0.05,2.31±0.18 and 1.58±0.11,respectively.Compared with the control group,the above indexes in the experimental-L group had statistical significance(all P＜0.05).The contents of IL-6 and TNF-α in cell culture fluid supernatant in model group,experimental-L group,Hcy+Ad-SIRT1 group and Hcy+si-FOXO1 group were significantly lower than those in model group,with statistical significance(all P＜0.05).After co-transfection with Ad-SIRT1 and si-FOXO1,the contents of IL-6 and TNF-α in cell culture medium superserum of experimental-L group were significantly lower than those of Ad-SIRT1 group and si-FOXO1 group(all P＜0.05).Conclusion Resveratrol can attenuate the immune response and proliferation of macrophages induced by Hcy,which may be related to the alteration of SIRT1/FOXO1 pathway.

The blood-brain barrier (BBB) plays a crucial role in maintaining the homeostasis of the brain's internal environment, which poses challenges to the treatment of central nervous system diseases. Drug carriers can aid in the delivery of therapeutic agents across the BBB to exert their pharmacological effects. The article reviewed the pathways for drug delivery across the BBB, the intracerebral fate and the classification of drug carriers and focuses on the functions and characteristics of liposomes, exosomes, apoptotic bodies, cell-penetrating peptides, and cell-targeting peptides. The review will provide an outlook on the future and challenge of research in the field of drug delivery across the BBB.

Objective: To analyze the spatial and temporal distribution characteristics of seasonal A(H3N2) influenza [influenza A(H3N2)] in China and to provide a reference for scientific prevention and control. Methods: The influenza A(H3N2) surveillance data in 2014-2019 was derived from China Influenza Surveillance Information System. A line chart described the epidemic trend analyzed and plotted. Spatial autocorrelation analysis was conducted using ArcGIS 10.7, and spatiotemporal scanning analysis was conducted using SaTScan 10.1. Results: A total of 2 603 209 influenza-like case sample specimens were detected from March 31, 2014, to March 31, 2019, and the influenza A(H3N2) positive rate was 5.96%(155 259/2 603 209). The positive rate of influenza A(H3N2) was statistically significant in the north and southern provinces in each surveillance year (all P<0.05). The high incidence seasons of influenza A (H3N2) were in winter in northern provinces and summer or winter in southern provinces. Influenza A (H3N2) clustered in 31 provinces in 2014-2015 and 2016-2017. High-high clusters were distributed in eight provinces, including Beijing, Tianjin, Hebei, Shandong, Shanxi, Henan, Shaanxi, and Ningxia Hui Autonomous Region in 2014-2015, and high-high clusters were distributed in five provinces including Shanxi, Shandong, Henan, Anhui, and Shanghai in 2016-2017. Spatiotemporal scanning analysis from 2014 to 2019 showed that Shandong and its surrounding twelve provinces clustered from November 2016 to February 2017 (RR=3.59, LLR=9 875.74, P<0.001). Conclusion: Influenza A (H3N2) has high incidence seasons with northern provinces in winter and southern provinces in summer or winter and obvious spatial and temporal clustering characteristics in China from 2014-2019.
Humans ; Influenza, Human/epidemiology* ; China/epidemiology* ; Influenza A Virus, H3N2 Subtype ; Seasons ; Cluster Analysis