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 value of high-throughput sequencing(HTS)data reanalysis that does not include ERBB2 copy number variation(CNV)analysis,in identifying ERBB2 amplification in patients with colorectal cancer.Methods The HTS data of 252 cases of colorectal cancer diagnosed by pathological biopsy who received peripheral blood cfDNA HTS detection samples were retrospectively analyzed.According to the HTS data of ERBB2 non-amplified samples judged by immunohistochemistry(IHC)and/or fluorescence in situ hybridization(FISH),the number of chromosome 17(Chr17)reads in the total number of reads was calculated the range of the ratio was initially determined as the threshold for prompting ERBB2 amplification.Suspected positive samples were screened according to thresholds and verified by digital PCR,IHC and FISH.Results The proportion of the number of Chr17 reads accounts for the number of total reads in the 89 cases of ERBB2 non-amplified samples determined by IHC and/or FISH ranged from 0.188 to 0.299(0.239±0.192).Using 0.298(1.25 times the mean)as the threshold indicating ERBB2 amplification,the data of 163 samples were analyzed,of which 7 cases were suspected to be positive,and the ratio ranged from 0.302 to 0.853.Among them,5 cases were determined to be positive by IHC and/or FISH,and 6 cases were confirmed to be positive by digital PCR.The ratio of the number of Chr17 reads to the number of total reads was positively correlated with the ratio of ERBB2/EIF2C1,and the correlation was good(r2=0.909).Conclusion The high-throughput sequencing data that does not cover the ERBB2 CNV analysis has a certain hint value for ERBB2 amplification in patients with colorectal cancer.

BACKGROUND:With the further development of minimally invasive concepts,unicompartmental knee arthroplasty has become an important treatment for osteoarthritis of the knee;however,early postoperative pain adversely affects the recovery process,so effective analgesic measures are necessary.Femoral nerve block and cocktail therapy are common analgesic methods for unicompartmental knee arthroplasty,but there is a lack of studies confirming the analgesic effect and safety of their combined application. OBJECTIVE:To investigate the analgesic effect of cocktail therapy combined with femoral nerve block in unicompartmental knee arthroplasty. METHODS:One hundred patients who received unicompartmental knee arthroplasty from October 2021 to January 2023 were selected as the study subjects.They were divided into a control group(n=50)and a study group(n=50)using a random number table method.The femoral nerve block was used in the control group,while cocktail therapy combined with femoral nerve block was used in the study group during unicompartmental knee arthroplasty.Postoperative analgesia effect,analgesic frequency of dezocine injection within 2 days after surgery,motion range of affected knee joint,KSS function scores,and the occurrence of postoperative adverse reactions were compared between the two groups. RESULTS AND CONCLUSION:(1)Visual analog scale scores in the study group were lower than those in the control group at 12,24,and 48 hours after surgery(P<0.05).(2)The analgesic frequency of dezocine in the study group was less than that in the control group within 2 days after surgery(P<0.05).(3)The motion range in the study group was higher than that in the control group 1 and 3 days after surgery(P<0.05).On day 14 after surgery,there was no significant difference in motion range between the two groups(P>0.05).(4)The knee KSS score in the study group was higher than that in the control group at 2 weeks after surgery(P<0.05).There was no statistically significant difference in knee KSS scores between the two groups from 6 weeks to 6 months after surgery(P>0.05).(5)The difference in the occurrence of adverse reactions within 14 days after surgery was not significant between the two groups(P>0.05).(6)These results show that the use of cocktail therapy combined with femoral nerve block in unicompartmental knee arthroplasty can effectively reduce postoperative pain,improve the analgesic effect,reduce the frequency of analgesic drugs,and improve motion range of the early affected knee joint of patients.

ObjectiveTo explore the correlation between skeletal muscle mass and metabolic syndrome （MS） disease risk among middle-aged and elderly community residents in Urumqi， and to provide a theoretical basis for understanding the relationship between skeletal muscle mass and MS among middle-aged and elderly community residents in China. MethodsA total of 1 438 community residents ≥ 50 years old were selected as the research subjects from July 2018 to January 2019 in Urumqi. They were selected from a multi-ethnic natural population cohort in Xinjiang. Data were collected through questionnaires， physical examination， bioelectrical impedance analysis （BIA）， laboratory tests， etc. Skeletal muscle mass was evaluated using the limb skeletal muscle mass index （SMI） corrected for body weight； MS was defined as it at least includes three of the following： abdominal obesity， hypertension， hyperglycemia， high triglycerides and low high-density lipoprotein cholesterol. SMI was divided into four quantile arrays of Q₁‒Q₄. Trend χ² test was applied to explore whether there was a correlation between SMI changes and MS. A multivariate logistic regression model was used to analyze whether there is a difference in the risk of MS between the higher SMI group （Q₂， Q₃， Q₄） and the reference group Q₁. ResultA total of 560 MS patients were detected in this study， with a prevalence rate of 38.94%. Among them， the prevalence rate of MS was 39.16% in males and 38.80% in females. The increase in male SMI grading level is not correlated with the prevalence of MS （trend P>0.05）； After adjusting for confounding factors （model 4）， the increase in SMI was still not related to the prevalence of MS （P_trend=0.995）. There was no statistical difference in the risk of MS between the lowest quartile group Q₁ and the highest quartile group Q₄ （OR=1.01， 95%CI： 0.69‒1.78）. The prevalence of MS in women gradually decreased with the increase of SMI grading level （P_trend<0.001）； After adjusting for confounding factors （model 4）， there was still a correlation between the increase of SMI and the prevalence of MS （P_trend=0.005）. With the lowest quartile of SMI Q₁ as the reference group， the risk of MS in Q₂ （OR=0.63， 95%CI： 0.40‒1.00）， Q₃ （OR=0.56， 95%CI： 0.34‒0.94）， Q₄ （OR=0.42， 95%CI： 0.23‒0.76） decreased. ConclusionAn increase in skeletal muscle mass may be beneficial for preventing MS， especially among middle-aged and elderly female residents. Considering the intensification of aging in China and the close relationship between MS and related comorbidities， managing skeletal muscle mass may contribute to potential MS prevention.

Objective: To explore the relationship between air pollutants and pediatric outpatient volumes in Baoshan District, Shanghai Municipality. Methods: Data of meteorological factors, air pollutants and pediatric outpatient volumes in four general hospitals were collected in Baoshan District from 2015 to 2019, and a generalized additive model was used to fit the Poisson-like distribution. The exposure-response relationship between fine particulate matter (PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3) and total pediatric outpatient volumes and pediatric respiratory outpatients. Results: The median of the average daily temperature and relative humidity were 18.7 (interquartile range, 14.4) ℃ and 74.5% (interquartile range, 18.0%) in Baoshan District from 2015 to 2019, respectively. The median of the average daily concentrations of PM2.5, SO2, NO2 and O3 were 35.0 (interquartile range, 35.0), 11.0 (interquartile range, 7.0), 45.0 (interquartile range, 31.8) and 84.5 (interquartile range, 50.0) μg/m3, respectively. The median of the average daily total and respiratory pediatric outpatient volumes were 680 (interquartile range, 246) and 392 (interquartile range, 253). Spearman rank correlation analysis showed that temperature, relative humidity, PM2.5, SO2, NO2 and O3 were associated with total and respiratory pediatric outpatient volume (all P<0.05). Under the single pollutant model, the excess risk of total and respiratory pediatric outpatient volume due to PM2.5 (ER=0.318, 0.257), SO2 (ER=1.610, 2.546), and NO2 (ER=0.808, 0.839) reached the maximum effect on the same day, and the effect of O3 (ER=0.102, 0.222) reached its maximum at the first day of lag. Under the multi-pollutant model, after O3, SO2, NO2 and PM2.5 were introduced, a exposure-response relationship between air pollutants and total pediatric outpatient volumes was the largest on the sixth day after the lag (ER=0.419). There was no exposure-response relationship between air pollutants and respiratory pediatric outpatient volumes. Conclusion PM2.5, SO2, NO2 and O3 are associated with total and respiratory pediatric outpatient volumes, and the lag effects due to different air pollutants are different.

Objective To evaluate the predictive ability and influencing factors of individualized drug administration adjuvant decision-making system Java PK? for Desktop(JPKD)for tacrolimus blood concentration in kidney transplant recipients.Methods The monitoring data of tacrolimus blood concentration from 149 recipients early after kidney transplantation were collected.The trough blood concentration of tacrolimus was predicted by JPKD.The absolute weighted deviation and relative prediction deviation between the actual and predicted concentration were calculated.The influencing factors of the absolute weighted deviation were analyzed by univariate and multivariate logistic regression analyses,and the predictive values of these influencing factors on the accuracy of software prediction were assessed by delineating the receiver operating characteristic(ROC)curve.Results Two hundred and sixty-six samples of tacrolimus blood concentration data were collected from 149 patients.The measured blood concentration of tacrolimus was(6.5±3.0)ng/mL(1.1-16.6 ng/mL),and the predicted value calculated by JPKD was(5.6±2.5)ng/mL(1.4-14.4 ng/mL).The absolute weighted deviation of the calculated data was 28.38％,and the relative prediction deviation was-13.55％.Univariate analysis showed that gender,albumin,changes in hematocrit,cytochrome P450(CYP)3A5*3 genotype and C3435T genotype were associated with the inaccurate prediction results.Multivariate logistic regression analysis found that CYP3A5*3 genotype of AA and the changes in hematocrit were the independent risk factors affecting the accuracy of tacrolimus blood concentration predicted by JPKD.ROC curve analysis showed that when the changes in hematocrit exceeded 2.25％,the risk of inaccurate software prediction was increased.Conclusions JPKD possesses certain accuracy in predicting the blood concentration of tacrolimus in kidney transplant recipients,which may improve the qualified rate of tacrolimus blood concentration.Nevertheless,CYP3A5*3 genotype and the changes of hematocrit may affect the accuracy of predictions.