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.

Aim To express and purify recombinant hCGH-CTP fusion protein in high-density suspension culture of Chinese hamster ovary cells (CHO-S), and to verify the lipid accumulation effect of rhCGH-CTP on 3T3-L1 mature adipocytes. Methods The recombinant protein expression vector (pcDNA3. 1-rhCGH-CTP) was constructed, achieved by fusing the human glycoprotein hormone beta 5/alpha 2 cDNA with CTP Linker. The expression plasmid was transiently transfected into the suspended CHO-S to express rhCGH-CTP protein and then purified, and the protein biological activity was verified. Intervention with 3T3-L1 mature adipocyte cells for 24 h was performed to detect the changes of intracellular triglyceride (TG) level. Results Western blot results showed that rhCGH-CTP protein was successfully expressed in CHO-S cells, and the yield was up to 715. 4 mg • L~ . The secreted protein was purified by AKTA pure system with higher purity that was up to 90% as identified by SDS-PAGE. In addition, the intracellular cAMP content of mature adipocytes with high expression of TSHR gene significantly increased after intervention with different concentrations of rhCGH-CTP protein by ELISA kit, indicating that rhCGH-CTP protein had biological activity. Oil red 0 staining showed that compared with the control group, the lipid content of mature adipocytes in the intervention groups with different concentrations of rhCGH-CTP protein significantly decreased (P < 0. 05) . Conclusions The rhCGH-CTP protein has been successfully expressed and purified with biological activity, and effectively reduce TG. This research provides an important theoretical basis for further revealing the physiological role of CGH protein and its potential application in clinical practice.

Field effect transistor(FET)biochemical sensors show great potential in the fields of environmental monitoring,food safety,disease diagnosis and clinical treatment due to their low noise,low power consumption,label-free,easy integration and miniaturization characteristics.Two-dimensional(2D)materials,as a new generation of channel materials for FET biochemical sensors,have atomic-level thickness,high carrier mobility,high specific surface area and tunable bandgap,which can further improve the performance of FET biochemical sensors,extend their application areas,and promote the rapid development of FET biochemical sensors.This review focused on the development and latest progress of 2D material-based FET biochemical sensors,along with the challenges and prospects of 2D material-based FET biochemical sensors,which aimed to provide new device design conceptions and promote the further development of biochemical sensing technology.

Amantadine(AMD)residue can accumulate in organisms through the food chain and cause serious harm to human body.AMD can specifically bind to AMD specific aptamer and cause its conformation to change from a random single strand to a stem-loop structure.To avoid the influence of excess nucleotides on binding of aptamer to AMD,the truncation of the AMD original aptamer J was optimized by retaining an appropriate stem-loop structure,and a new type of truncation aptamers was developed in this work.By comparing the truncated aptamer with the original aptamer,it was found that the truncated aptamer J-7 had better affinity and specificity with AMD.The detection limit of AMD was 0.11 ng/mL by using J-7 as specific recognition element and molybdenum disulfide nanosheet(MoS2Ns)as signal amplification element.The developed method base on truncated aptamer J-7 was used for detection of AMD in milk,yogurt and SD rat serum samples for the first time with recoveries of 86.6%-108.2%.This study provided a reference for truncating other long sequence aptamers and provided a more sensitive detection method for monitoring AMD residues in food.

Objective To establish a rapid screening method for 34 emerging contaminants in surface water by ultra-high performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS).Methods The pretreatment conditions of solid phase extraction(SPE)were op-timized by orthogonal experimental design and the surface water samples were concentrated and ex-tracted by Oasis? HLB and Oasis? MCX SPE columns in series.The extracts were separated by Kine-tex? EVO C18 column,with gradient elution of 0.1%formic acid aqueous solution and 0.1%formic acid methanol solution.Q-TOF-MS'fullscan'and'targeted MS/MS'modes were used to detect 34 emerging contaminants and to establish a database with 34 emerging contaminants precursor ion,prod-uct ion and retention times.Results The 34 emerging contaminants exhibited good linearity in the con-centration range respectively and the correlation coefficients(r)were higher than 0.97.The limit of de-tection was 0.2-10 ng/L and the recoveries were 81.2%-119.2%.The intra-day precision was 0.78%-18.70%.The method was applied to analyze multiple surface water samples and 6 emerging contaminants were detected,with a concentration range of 1.93-157.71 ng/L.Conclusion The method is simple and rapid for screening various emerging contaminants at the trace level in surface water.

Objective To investigate the toxicokinetic differences of 3,4-methylenedioxy-N-methylamphetamine(MDMA)and its metabolite 4,5-methylene dioxy amphetamine(MDA)in rats af-ter single and continuous administration of MDMA,providing reference data for the forensic identifica-tion of MDMA.Methods A total of 24 rats in the single administration group were randomly divided into 5,10 and 20 mg/kg experimental groups and the control group,with 6 rats in each group.The ex-perimental group was given intraperitoneal injection of MDMA,and the control group was given intraperi-toneal injection of the same volume of normal saline as the experimental group.The amount of 0.5 mL blood was collected from the medial canthus 5 min,30 min,1 h,1.5 h,2 h,4 h,6 h,8 h,10 h,12 h after administration.In the continuous administration group,24 rats were randomly divided into the experi-mental group(18 rats)and the control group(6 rats).The experimental group was given MDMA 7 d by continuous intraperitoneal injection in increments of 5,7,9,11,13,15,17 mg/kg per day,respectively,while the control group was given the same volume of normal saline as the experimental group by in-traperitoneal injection.On the eighth day,the experimental rats were randomly divided into 5,10 and 20 mg/kg dose groups,with 6 rats in each group.MDMA was injected intraperitoneally,and the con-trol group was injected intraperitoneally with the same volume of normal saline as the experimental group.On the eighth day,0.5 mL of blood was taken from the medial canthus 5 min,30 min,1 h,1.5 h,2 h,4 h,6 h,8 h,10 h,12 h after administration.Liquid chromatography-triple quadrupole tandem mass spectrometry was used to detect MDMA and MDA levels,and statistical software was employed for data analysis.Results In the single-administration group,peak concentrations of MDMA and MDA were reached at 5 min and 1 h after administration,respectively,with the largest detection time limit of 12 h.In the continuous administration group,peak concentrations were reached at 30 min and 1.5 h af-ter administration,respectively,with the largest detection time limit of 10 h.Nonlinear fitting equations for the concentration ratio of MDMA and MDA in plasma and administration time in the single-administration group and continuous administration group were as follows:T=10.362C-1.183,R2=0.974 6;T=7.397 3C-0.694,R2=0.961 5(T:injection time;C:concentration ratio of MDMA to MDA in plasma).Conclusions The toxicokinetic data of MDMA and its metabolite MDA in rats,obtained through single and continuous administration,including peak concentration,peak time,detection time limit,and the relationship between concentration ratio and administration time,provide a theoretical and data foundation for relevant forensic identification.