Objective:To analyze the clinical features associated with pelvic lymph node metastasis(PLNM)in prostate cancer and to construct a preoperative prediction model for PLNM,thereby reducing unnecessary extended pelvic lymph node dissection(ePLND).Methods:Based on predefined inclusion and exclusion criteria,344 patients who underwent radical prostatectomy and ePLND at the First Affilia-ted Hospital of Zhengzhou University between 2014 and 2024 were retrospectively enrolled,among whom,77 patients(22.4％)were pathologically confirmed to have lymph node-positive disease.The clinical characteristics,MRI reports,and pathological results were collected.The data were then randomly divi-ded into a training cohort(241 cases,70％)and a validation cohort(103 cases,30％).Univariate and multivariate Logistic regression analysis were employed to construct a preoperative prediction model for PLNM.Results:Univariate Logistic regression analysis revealed that total prostate specific antigen(tPSA)(P=0.021),free prostate specific antigen(fPSA)(P=0.002),fPSA to tPSA ratio(fPSA/tPSA)(P=0.011),percentage of positive biopsy cores(P＜0.001),prostate imaging reporting and data system(PI-RADS)score(P=0.004),biopsy Gleason score ≥8(P=0.005),clinical T stage(P＜0.001),and MRI-indicated lymph node involvement(MRI-LNI)(P＜0.001)were significant predictors of PLNM.Multivariate Logistic regression analysis demonstrated that the percentage of positive biopsy cores(OR=91.24,95％CI:13.34-968.68),PI-RADS score(OR=7.64,95％ CI:1.78-138.06),and MRI-LNI(OR=4.67,95％ CI:1.74-13.24)were independent risk factors for PLNM.And a novel nomogram for predicting PLNM was developed by integrating all these three variables.Com-pared with the individual predictors:percentage of positive biopsy cores[area under curve(AUC)=0.806],PI-RADS score(AUC=0.679),and MRI-LNI(AUC=0.768),the multivariate model incor-porating all three variables demonstrated significantly superior predictive performance(AUC=0.883).Consistently,calibration curves and decision curve analyses confirmed that the multivariable model had high predictive accuracy and provided significant net clinical benefit relative to single-variable models.And using a cutoff of 6％,the multiparameter model missed only approximately 5.2％of PLNM cases(4/77),while reducing approximately 53％of ePLND procedures(139/267),demonstrating favorable predictive efficacy.Conclusion:Percentage of positive biopsy cores,PI-RADS score and MRI-LNI are independent risk factors for PLNM.The constructed multivariate model significantly improves predictive efficacy,offering a valuable tool to guide clinical decisions on ePLND.

Objective:To investigate the efficacy of a predictive model for differentiating benign and malignant renal tumors based on CT radiomic features and clinical features.Methods:A retrospective study was conducted on 1 395 patients with renal tumors admitted to the First Affiliated Hospital of Zhengzhou University from December 2011 to December 2021, including 842 males and 553 females. The median age was 55 (44, 59) years, and the median tumor diameter was 3.6 (2.7, 4.6) cm. All patients underwent contrast-enhanced CT scaning before surgery, and radiomic features were extracted from non-contrast, arterial, and venous phase images. Prediction models for distinguishing benign and malignant renal tumors were constructed using five machine learning algorithms (logistic regression, support vector machine, neural network, random forest, and extreme gradient boosting), and these models were then ensembled to construct a stacking classifier. All patients underwent partial nephrectomy, and they were divided into a training group (941 cases, December 2011 to June 2020) and a validation group (454 cases, July 2020 to December 2021) based on the date of surgery. A clinical-radiomic model was developed by combining the result of stacking classifier, clinical features and CT report results, and its predictive performance was evaluated in the validation group.Results:The radiomic signature based on the combined features and five machine learning algorithms(AUC 0.835-0.844) showed higher accuracy in predicting benign and malignant renal tumors compared to single phases (AUC 0.744-0.831). After integrating the five machine learning algorithms, the AUC of the three-phase combined radiomic model in the validation group improved to 0.847(95% CI 0.802-0.892). The clinical-radiomic model, incorporating radiomic features, clinical features, and CT report results, achieved a significantly higher AUC in the validation group compared to radiologists [0.919(95% CI 0.889-0.950)vs. 0.835(95% CI 0.786-0.883), P<0.01]. Conclusions:The predictive model integrating CT radiomics features, clinical characteristics, and CT report results demonstrates excellent discriminative ability in distinguishing benign and malignant renal tumors.

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome

Objective:To analyze the clinical features associated with pelvic lymph node metastasis(PLNM)in prostate cancer and to construct a preoperative prediction model for PLNM,thereby reducing unnecessary extended pelvic lymph node dissection(ePLND).Methods:Based on predefined inclusion and exclusion criteria,344 patients who underwent radical prostatectomy and ePLND at the First Affilia-ted Hospital of Zhengzhou University between 2014 and 2024 were retrospectively enrolled,among whom,77 patients(22.4％)were pathologically confirmed to have lymph node-positive disease.The clinical characteristics,MRI reports,and pathological results were collected.The data were then randomly divi-ded into a training cohort(241 cases,70％)and a validation cohort(103 cases,30％).Univariate and multivariate Logistic regression analysis were employed to construct a preoperative prediction model for PLNM.Results:Univariate Logistic regression analysis revealed that total prostate specific antigen(tPSA)(P=0.021),free prostate specific antigen(fPSA)(P=0.002),fPSA to tPSA ratio(fPSA/tPSA)(P=0.011),percentage of positive biopsy cores(P＜0.001),prostate imaging reporting and data system(PI-RADS)score(P=0.004),biopsy Gleason score ≥8(P=0.005),clinical T stage(P＜0.001),and MRI-indicated lymph node involvement(MRI-LNI)(P＜0.001)were significant predictors of PLNM.Multivariate Logistic regression analysis demonstrated that the percentage of positive biopsy cores(OR=91.24,95％CI:13.34-968.68),PI-RADS score(OR=7.64,95％ CI:1.78-138.06),and MRI-LNI(OR=4.67,95％ CI:1.74-13.24)were independent risk factors for PLNM.And a novel nomogram for predicting PLNM was developed by integrating all these three variables.Com-pared with the individual predictors:percentage of positive biopsy cores[area under curve(AUC)=0.806],PI-RADS score(AUC=0.679),and MRI-LNI(AUC=0.768),the multivariate model incor-porating all three variables demonstrated significantly superior predictive performance(AUC=0.883).Consistently,calibration curves and decision curve analyses confirmed that the multivariable model had high predictive accuracy and provided significant net clinical benefit relative to single-variable models.And using a cutoff of 6％,the multiparameter model missed only approximately 5.2％of PLNM cases(4/77),while reducing approximately 53％of ePLND procedures(139/267),demonstrating favorable predictive efficacy.Conclusion:Percentage of positive biopsy cores,PI-RADS score and MRI-LNI are independent risk factors for PLNM.The constructed multivariate model significantly improves predictive efficacy,offering a valuable tool to guide clinical decisions on ePLND.

Objective:To investigate the efficacy of a predictive model for differentiating benign and malignant renal tumors based on CT radiomic features and clinical features.Methods:A retrospective study was conducted on 1 395 patients with renal tumors admitted to the First Affiliated Hospital of Zhengzhou University from December 2011 to December 2021, including 842 males and 553 females. The median age was 55 (44, 59) years, and the median tumor diameter was 3.6 (2.7, 4.6) cm. All patients underwent contrast-enhanced CT scaning before surgery, and radiomic features were extracted from non-contrast, arterial, and venous phase images. Prediction models for distinguishing benign and malignant renal tumors were constructed using five machine learning algorithms (logistic regression, support vector machine, neural network, random forest, and extreme gradient boosting), and these models were then ensembled to construct a stacking classifier. All patients underwent partial nephrectomy, and they were divided into a training group (941 cases, December 2011 to June 2020) and a validation group (454 cases, July 2020 to December 2021) based on the date of surgery. A clinical-radiomic model was developed by combining the result of stacking classifier, clinical features and CT report results, and its predictive performance was evaluated in the validation group.Results:The radiomic signature based on the combined features and five machine learning algorithms(AUC 0.835-0.844) showed higher accuracy in predicting benign and malignant renal tumors compared to single phases (AUC 0.744-0.831). After integrating the five machine learning algorithms, the AUC of the three-phase combined radiomic model in the validation group improved to 0.847(95% CI 0.802-0.892). The clinical-radiomic model, incorporating radiomic features, clinical features, and CT report results, achieved a significantly higher AUC in the validation group compared to radiologists [0.919(95% CI 0.889-0.950)vs. 0.835(95% CI 0.786-0.883), P<0.01]. Conclusions:The predictive model integrating CT radiomics features, clinical characteristics, and CT report results demonstrates excellent discriminative ability in distinguishing benign and malignant renal tumors.

[Objective]To elucidate the experience of treating radial nerve injury with external treatment based on"treatment for flaccid paralysis aiming at Yangming meridian".[Methods]Based on the symptoms and manifestations of radial nerve injury,the etiology and pathogenesis were analyzed,and the connotation of"treatment for flaccid paralysis aiming at Yangming meridian"was deeply analyzed.The strategies of treating radial nerve injury with external treatment were expounded with the guidance of classical articles,and a typical medical case was presented for demonstration.[Results]The causes of radial nerve injury are nothing more than deficiency and excess.The deficiency symptoms are deficiency of the spleen and stomach,deficiency of the liver and kidney,and the excess symptoms include dampness,heat,blood stasis,phlegm turbidity block,and it is easy to be mixed with deficiency and excess."Treatment for flaccid paralysis aiming at Yangming meridian"not only focuses on the spleen and stomach,but also not blindly tonifying the spleen and stomach,but paying attention to regulating the spleen and stomach as the core,distinguishing deficiency and excess,taking into account the five viscera,and clearing and tonifying Qi and blood as the fundamental.The external treatment strategy under the guidance of"treatment for flaccid paralysis aiming at Yangming meridian"can be summarized as"use acupuncture treatment,and focus on selecting Yangming""use acupressure to promote Qi and blood""external use of traditional Chinese medicine to promote blood circulation and remove meridian obstruction""rehabilitation exercise,supplemented by physiotherapy"and"combining Chinese and western,and get results quickly",clinical flexible cooperation of many means can harvest significant results.In the medical case cited,the patient suffered from the radial nerve injury due to a car accident,and identified as the flaccidity syndrome of blood stasis block.The treatment was based on the principle of promoting blood circulation and removing blood stasis,clearing the channels and relieving pain,and the comprehensive use of acupuncture,massage and traditional Chinese medicine fumigation and washing was used to treat the patient's wrist freely for one month,with remarkable results.[Conclusion]"Treatment for flaccid paralysis aiming at Yangming meridian"is not only tonifying the deficiency of the spleen and stomach,but focusing on dredging Yangming Qi and blood,and producing normally.The theory guides the thinking of treating radial nerve injury from the angle of promoting blood circulation and removing blood stasis,attaches importance to the advantages of acupuncture,massage and traditional Chinese medicine fumigation and washing.

Objective: To ensure the quality of Perilla frutescens (L.) Britt. and improve the associated benefits for stakeholders, this study analyzed the influences of different circulation channels and stakeholders on the quality, price, and other factors of P. frutescens with consideration to P. frutescens distribution. Method: We interviewed the local stakeholders and e-commerce platforms in Oroqen Autonomous Banner and Morin Dawa Daur Autonomous Banner regarding the origin, circulation, distribution, and prices of different medicinal parts of P. frutescens. In addition, the maximum entropy model was used to predict the potential distribution of P. frutescens in the study area. According to the Chinese Pharmacopeia (2020 edition), we measured the content of index components in the collected Perillae Folium, Perillae Caulis, and Perillae Fructus samples and evaluated the quality of the samples by quantitative and cluster analyses. Remote sensing was employed to distinguish and calculate the P. frutescens area in highly suitable regions. The autoregressive integrated moving average model was adopted to analyze the Perillae Fructus price in the study area. Result: The results showed 8 value chains for P. frutescens. The cooperation chain between farmers and enterprises in the study area could maximize the benefits for all stakeholders and guarantee the quality of the medicinal materials. The results of the regionalization analysis showed that themost suitable area for planting P. frutescens was the junction between Oroqen Autonomous Banner and Morin Dawa Daur Autonomous Banner. Chemical results showed that Perillae Fructus and Perillae Caulis samples were unqualified andmostly purchased from e-commerce platforms. We identified 5 land types, among which the cultivated land area was 3247.7501 km . The price of Perillae Fructus in the study area showed a rising trend, although this trend slowed down. Conclusion: This study involved various links in the production and circulation of medicinal materials from planting to consumption by consumers, which can help to facilitate the future research on any link. The findings help to guarantee the quality of medicinal materials and benefits of all stakeholders and promote the development of the P. frutescens industry in the study area.

Dracaena marginata is a widely cultivated horticultural plant in the world, which has high ornamental and medicinal value. In this study, the whole genome of leaves from D. marginata was sequenced by Illumina HiSeq 4000 platform. The chloroplast genome were assembled for functional annotation, sequence characteristics and phylogenetic analysis. The results showed that the chloroplast genome of D. marginata composed of four regions with a size of 154 926 bp, which was the smallest chloroplast genome reported for Dracaena species to date. A total of 132 genes were identified, including 86 coding genes, 38 tRNA genes and 8 rRNA genes. Codon bias analysis found that the codon usage bias was weak and there was a bias for using A/U base endings. 46 simple sequence repeat and 54 repeats loci were detected in the chloroplast genome, with the maximum detection rate in the large single copy region and inverted repeat region, respectively. The inverted repeats boundaries of D. marginata and Dracaena were highly conserved, whereas gene location differences occurred. Phylogenetic analysis revealed that D. serrulata and D. cinnabari form a monophyletic clade, which was the closest relationship and conformed to the morphological classification characteristics. The analysis of the chloroplast genome of D. marginata provides important data basis for species identification, genetic diversity and chloroplast genome engineering of Dracaena.
Phylogeny ; Dracaena ; Genome, Chloroplast/genetics* ; Base Sequence ; Genes, Plant

Objective: To deliver macro understanding of the latest research progress on clinical trials and approved products of cancer drugs in China in 2019. Methods: The number of clinical trials and related investigational products by domestic and foreign enterprises in 2019 were acquired in the China Food and Drug Administration Registration and Information Disclosure Platform for Drug Clinical Studies, while listed drugs were obtained in the China Food and Drug Administration Query System for Domestic and Imported Drug. Characteristics on stage, scope, indication of those trials, classification and mechanism of involved products, as well as listed anticancer drugs were summarized and depicted. Results: There were 474 cancer drug trials registered in China in 2019, accounting for 21.8% of the total, and 397 (83.8%) were initiated by domestic pharmaceutical enterprises. Overall, international multicenter trials accounted for 13.1%, and phase I trials accounted for 47.3%. Compared with global enterprises, the proportion of international multi-center trials initiated by domestic companies is lower (4.8% vs. 55.8%, P<0.001), and the proportion of phase I clinical trials and bioequivalence trials is higher (51.9% vs. 23.4%, 19.4% vs. 1.3%, P<0.001). An accumulative of 27 cancer types were involved for all the cancer drug trials, and lung cancer, solid tumor, and breast cancer were the most common cancer types, with 103, 95 and 49 trials, respectively. For the three cancer types unique to Chinese population, gastric, liver and esophageal cancer, the total number of initiated trials was 47. For all those trials, there were 335 cancer drug varieties, with 86.0% developed by domestic pharmaceutical enterprises, including 300 therapeutic drugs, 30 adjunctive drugs and 5 preventive drugs. In terms of mechanism, targeted drugs and immune drugs were the most popular, accounting for 74.6% and 20.3%, respectively. In addition, 17 anticancer drugs targeting on 11 cancer types were approved in China in 2019. Conclusions Clinical trials on cancer drugs in China have ushered a booming era, with large number of innovative agents represented by targeted drugs and immune drugs under clinical development or putting into clinical practice. Those local enterprises are playing more and more critical roles. Strengthening clinical research and development on Chinese unique cancer types is the key direction of future work.

Objective To investigate the relationship between fasting blood glucose(FBG) with coronary arterial vulnerable plaque in civil airline pilots and its risk factors.Methods One hundred and twenty civil airline pilots with coronary heart disease were divided into the vulnerable plaque group and non-vulnerable plaque group based on the virtual histology intravascular ultrasound(VH-IVUS) results.Then the clinical data were collected.Logistic regression analysis was used to analyze the risk factors of vulnerable plaque.Results The FBG level in the vulnerable plaque group was much higher(P＜0.05);FBG,high-sensitivity C-reactive protein and low density lipoprotein were the risk factors for vulnerable plaque;FBG was positively correlated with the plaque necrosis core constituent ratio(r=0.44,P＜0.05).The area under curve of ROC curve efficiency for diagnosing vulnerable plaque was 0.72(95％CI:0.66-0.81),at FBG cut-off value of 6.39,the sensitivity was 71.35％ and specificity was 76.15％.Conclusion The FBG level is an independent risk factor of coronary arterial vulnerable plaque,which can assist in the identification of vulnerable plaque in civil airline pilots.