The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

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 establish a method for determining the contents of clopidogrel （CLP）， clopidogrel carboxylate （CLP-C）， clopidogrel acyl-β-D-glucuronide （CLP-G） and contents of clopidogrel active metabolite （CAM） in rat plasma， and to investigate their in vivo pharmacokinetic characteristics. METHODS The Shisedo CAPCELL ADME column was used with a mobile phase consisting of water and acetonitrile （both containing 0.1% formic acid） in a gradient elution. The flow rate was 0.4 mL/min， and the column temperature was maintained at 20 ℃. The injection volume was 2 μL. The analysis was performed in positive ion mode using electrospray ionization with multiple reaction monitoring. The ion pairs for quantitative analysis were m/z 322.1→211.9 （for CLP）， m/z 308.1→197.9 （for CLP-C）， m/z 322.1→154.8 （for CLP-G）， m/z 504.1→154.9 [for racemic CAM derivative （CAMD）]. Six rats were administered a single intragastric dose of CLP （10 mg/kg）. Blood samples were collected before medication and at 0.08， 0.33， 0.66， 1， 2， 4， 6， 10， 23 and 35 hours after medication. The established method was used to detect the serum contents of various components in rats. Pharmacokinetic parameters were then calculated using WinNonlin 6.1 software. RESULTS The linear ranges for CLP， CLP-C and CAMD were 0.08-20.00， 205.00-8 000.00， and 0.04-25.00 ng/mL， respectively （r≥0.990）. The relative standard deviations for both intra-day and inter-day precision tests were all less than 15%， and the relative errors for accuracy ranged from －11.68% to 14.40%. The coefficients of variation for the matrix factors were all less than 15%， meeting the requirements for bioanalytical method validation. The results of the pharmacokinetic study revealed that， following a single intagastric administration of CLP in rats， the exposure to the parent CLP in plasma was extremely low. Both the area under the drug concentration-time curve （AUC0-35 h） and the peak concentration of the parent CLP were lower than those of its metabolites. The AUC0-35 h of the active metabolite CAM was approximately 43 times that of CLP， though it had a shorter half-life （2.53 h）. The inactive metabolite CLP-C exhibited the highest exposure level， but it reached its peak concentration the latest and was eliminated slowly. The AUC0-35 h of CLP-G was about four times that of CAM， and its half-life was similar to that of CLP-C. CONCLUSIONS This study successfully established an liquid chromatography-tandem mass spectrometry method for the determination of CLP and its three metabolites， and revealed their pharmacokinetic characteristics in rats. Specifically， the parent drug CLP was rapidly eliminated， while the inactive metabolites CLP-C and CLP-G exhibited long half-lives， and active metabolite CAM displayed a transient exposure pattern.

Objective: To explore the relationship of physical activity (PA) and sedentary behavior (SB) with cardiorespiratory fitness (CRF) among middle schoold students in Tibet, so as to provide empirical references for improving the cardiorespiratory fitness and health levels of adolescents in Tibet. Methods: From August to December 2020, 1 225 junior and senior high school students were selected from 2 middle schools in Lhasa, Tibet Autonomous Region, using the stratified cluster random sampling method. Triaxial accelerometers were used to evaluate PA and SB behaviors, and the 20 meter shuttle run was employed to assess CRF among the middle school students. Isochronous substitution modeling was used to analyze the associations of SB, low intensity physical activity (LPA), and moderate vigorous physical activity (MVPA) with CRF, and the saturation threshold effect in the dose response relationship between MVPA and CRF was analyzed through restricted cubic spline and two stage linear regression. Results: After adjusting for covariates such as gender, body mass index and sleep quality score, isotemporal substitution analysis showed that among junior high school students aged 13-15, replacing 30 minutes of SB ( B =1.73) or LPA ( B =2.38) with MVPA were positively associated with CRF (both P <0.05). Among senior high school students aged 16-18, replacing SB ( B =0.99) or LPA ( B =1.38) with MVPA were also positively associated with CRF (both P <0.05). Restricted cubic spline and two piecewise linear regression analyses indicated that only middle school girls aged 13-18 exhibited a saturation threshold effect between MVPA and CRF (logarithmic likelihood ratio test=0.03), with the optimal CRF improvement observed at 60 minutes of MVPA per day ( B=0.13, P ＜ 0.01). Conclusions Reducing SB and LPA while increasing MVPA can improve CRF in Tibetan middle school students. To maximize CRF improvement, middle school girls should engage in at least 60 minutes of MVPA daily.

Objective: To investigate the current status of screen exposure among preschool children in Shanghai and its association with family screen environment, so as to provide a scientific basis for family screen management. Methods: Using a convenient sampling method, a total of 349 preschool children aged 4-6 years were selected from 36 kindergarten classes in Xuhui District and Pudong New Area in Shanghai during April to June in 2023. Demographic characteristics and family screen environment were surveyed through an online questionnaire. Screen exposure of children was assessed using a diary method, with parents recording the activities over a 7day period. Multiple Logistic regression analysis was employed to identify factors influencing childrens screen content. Results: The average daily screen exposure time for children was (61.2±40.2) minutes, with an average of (12.4±17.6) minutes spent on educational screen content, 80.8% predominantly watched noneducational screen content. The percentages of time spent on educational screen content for 4yearold boys, 4yearold girls, 5yearold boys, 5yearold girls, 6yearold boys, and 6yearold girls were 20.1%, 14.7%, 21.3%, 21.9%, 20.6%, and 26.9%, respectively. Multivariate Logistic regression showed that children aged 5yearold (OR=0.49, 95%CI=0.25-0.96) and 6yearold (OR=0.45, 95%CI=0.21-0.95) were negatively associated with more noneducational screen content (P<0.05). However, occasional (OR=2.02, 95%CI=1.09-3.75) and sometimes (OR=4.50, 95%CI=1.70-11.90) using electronic devices to calm young child when crying, as well as children using electronic devices without adult supervision (OR=1.81, 95%CI=1.01-3.24) were positively associated with more noneducational screen content (P<0.05). Conclusions Preschool children in Shanghai exhibit high exposure to noneducational screen content, and family screen environment and parentchild interaction are associated with noneducational screen exposure. Strategies for family screen management should be developed to regulate childrens screen exposure behaviors, allowing electronic devices to play a positive role in their developmental process.

The main protease (M^pro) of SARS-CoV-2 is an attractive target in anti-COVID-19 therapy for its high conservation and major role in the virus life cycle. The covalent M^pro inhibitor nirmatrelvir (in combination with ritonavir, a pharmacokinetic enhancer) and the non-covalent inhibitor ensitrelvir have shown efficacy in clinical trials and have been approved for therapeutic use. Effective antiviral drugs are needed to fight the pandemic, while non-covalent M^pro inhibitors could be promising alternatives due to their high selectivity and favorable druggability. Numerous non-covalent M^pro inhibitors with desirable properties have been developed based on available crystal structures of M^pro. In this article, we describe medicinal chemistry strategies applied for the discovery and optimization of non-covalent M^pro inhibitors, followed by a general overview and critical analysis of the available information. Prospective viewpoints and insights into current strategies for the development of non-covalent M^pro inhibitors are also discussed.