Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Objective: Para-aortic lymph node dissection (PALND) is a widely used treatment that causes many complications. This study is to evaluate the efficacy and safety of nerve-sparing para-aortic lymph node dissection (NSPALND) by comparing it with conventional PALND in gynecological malignancies and to prove whether locating the superior hypogastric plexus (SHP) can help reveal the para-aortic nerves. Methods: This is a retrospective study of the patients who underwent para-aortic lymphadenectomy from January 2020 to December 2022 at Zhejiang Cancer Hospital. All of them were divided into NSPALND and PALND groups according to whether or not nervesparing was performed. The surgical, functional and oncological outcomes were evaluated. Results: There were 43 patients enrolled, of which, 20 patients underwent NSPALND and 23 patients underwent PALND. The para-aortic nerves were successfully revealed by locating the SHP in all 20 cases of NSPALND. The post-operative anal exhaust time in the NSPALND group was significantly shorter than that in the PALND group (2.5 vs. 4 days, p=0.006), and the incidence of acute intestinal obstruction in the NSPALND group was significantly lower than that in the PALND group (10% vs. 39%, p=0.029). There was no difference between the two groups in terms of catheterization duration, urinary retention, dysuria, as well as the number of lymph nodes removed and the para-aortic recurrence rate. Conclusion NSPALND can significantly reduce the rate of acute intestinal obstruction and improve post-operative intestinal function. Locating the SHP and using it as an anatomical landmark to reveal the para-aortic nerves is feasible. Its exact clinical value needs to be further studied.

Objective: Para-aortic lymph node dissection (PALND) is a widely used treatment that causes many complications. This study is to evaluate the efficacy and safety of nerve-sparing para-aortic lymph node dissection (NSPALND) by comparing it with conventional PALND in gynecological malignancies and to prove whether locating the superior hypogastric plexus (SHP) can help reveal the para-aortic nerves. Methods: This is a retrospective study of the patients who underwent para-aortic lymphadenectomy from January 2020 to December 2022 at Zhejiang Cancer Hospital. All of them were divided into NSPALND and PALND groups according to whether or not nervesparing was performed. The surgical, functional and oncological outcomes were evaluated. Results: There were 43 patients enrolled, of which, 20 patients underwent NSPALND and 23 patients underwent PALND. The para-aortic nerves were successfully revealed by locating the SHP in all 20 cases of NSPALND. The post-operative anal exhaust time in the NSPALND group was significantly shorter than that in the PALND group (2.5 vs. 4 days, p=0.006), and the incidence of acute intestinal obstruction in the NSPALND group was significantly lower than that in the PALND group (10% vs. 39%, p=0.029). There was no difference between the two groups in terms of catheterization duration, urinary retention, dysuria, as well as the number of lymph nodes removed and the para-aortic recurrence rate. Conclusion NSPALND can significantly reduce the rate of acute intestinal obstruction and improve post-operative intestinal function. Locating the SHP and using it as an anatomical landmark to reveal the para-aortic nerves is feasible. Its exact clinical value needs to be further studied.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Objective: Para-aortic lymph node dissection (PALND) is a widely used treatment that causes many complications. This study is to evaluate the efficacy and safety of nerve-sparing para-aortic lymph node dissection (NSPALND) by comparing it with conventional PALND in gynecological malignancies and to prove whether locating the superior hypogastric plexus (SHP) can help reveal the para-aortic nerves. Methods: This is a retrospective study of the patients who underwent para-aortic lymphadenectomy from January 2020 to December 2022 at Zhejiang Cancer Hospital. All of them were divided into NSPALND and PALND groups according to whether or not nervesparing was performed. The surgical, functional and oncological outcomes were evaluated. Results: There were 43 patients enrolled, of which, 20 patients underwent NSPALND and 23 patients underwent PALND. The para-aortic nerves were successfully revealed by locating the SHP in all 20 cases of NSPALND. The post-operative anal exhaust time in the NSPALND group was significantly shorter than that in the PALND group (2.5 vs. 4 days, p=0.006), and the incidence of acute intestinal obstruction in the NSPALND group was significantly lower than that in the PALND group (10% vs. 39%, p=0.029). There was no difference between the two groups in terms of catheterization duration, urinary retention, dysuria, as well as the number of lymph nodes removed and the para-aortic recurrence rate. Conclusion NSPALND can significantly reduce the rate of acute intestinal obstruction and improve post-operative intestinal function. Locating the SHP and using it as an anatomical landmark to reveal the para-aortic nerves is feasible. Its exact clinical value needs to be further studied.

Background/Aims: The purpose of this study was to develop a diagnostic model utilizing multimodal ultrasound parameters to aid in the detection of cervical lymph node metastasis in papillary thyroid cancer (PTC) patients. Methods: The study included 84 suspicious lymph nodes from 69 PTC patients, all of whom underwent fine needle aspiration with pathological results. Data from conventional grayscale ultrasound, shear wave elastography (SWE), and superb microvascular imaging were analyzed. Key ultrasound features were compared between benign and metastatic groups to create a diagnostic model using Fisher’s stepwise discriminant analysis. The model’s effectiveness was assessed with self-testing, cross-validation, and receiver operating characteristic curve analysis. Results: Four features, namely lymphatic hilum (X1), cortical hyperechogenicity (X2), vascular pattern (X4), and SWEmean (X7), were integral to the discriminant analysis, resulting in the equation: Y1 = -3.461 + 2.423X1 + 0.321X2 + 1.620X4 + 0.109X7, Y2 = -8.053 + 0.414X1 + 2.600X2 + 2.504X4 + 0.192X7. If Y1 < Y2, the LN would be diagnosed as metastatic lymph nodes. The model demonstrated an area under the curve of 0.833, with a sensitivity of 83.33% and specificity of 83.33%. Conclusions The multimodal ultrasound diagnostic model, established through Fisher’s stepwise discriminant analysis, proved effective in identifying metastatic lymph nodes in PTC patients.

Seeds are the source for the production of Chinese medicinal materials. The seed authenticity and quality of directly affect the effectiveness and safety of Chinese medicinal materials. The seed quality is faced with the problems such as mixed sources， existence of adulterants and seeds stocked for years， low maturity， and low purity. To ensure the high-quality and sustainable development of the Chinese medicinal material industry， it is urgent to standardize the seed market and identify and evaluate the quality of the seeds circulating in the market. Seed identification methods include visual inspection， microscopic observation， micro-character identification， chemical fingerprinting， molecular identification， electronic nose， X-ray diffraction， electrochemical fingerprinting， spectral imaging， and artificial intelligence. These methods have different application scopes and unique advantages and disadvantages. According to the different species of Chinese herbal medicines and different requirements of testing sites， suitable methods can be selected to achieve rapid and accurate identification with low costs. In the future， the seed identification methods should be developed based on emerging technologies with interdisciplinary knowledge， and intelligent， nondestructive， and single-grain detection methods are needed for the modern Chinese medicinal material industry. This paper introduces the seed identification technologies currently applied in research and production， compares the principles， applicability， advantages， and disadvantages of different technologies， and provides an outlook on the future development of seed identification technologies， aiming to provide a reference for the identification and quality evaluation of seeds of Chinese medicinal material.

ObjectiveTo identify Lycium chinense and L. barbarum as the original plants of Lycii Cortex simply and efficiently by multiple allele-specific polymerase chain reaction （PCR）. MethodThe chloroplast genome sequences of L. chinense and L. barbarum were downloaded from the Chloroplast Genome Information Resource （CGIR）， and then IdenDSS was employed to screen out the specific single nucleotide polymorphism （SNP） sites between the two plants. Primer 5.0 was used to design the specific primers， including primers GQ-F/R for identifying L. chinense and primers NX-F/R for identifying L. barbarum. Furthermore， the primer concentration ratio， annealing temperature， cycles， and Taq enzyme were optimized to establish the optimal PCR system and conditions for plant identification. Finally， the applicability of the established method was examined with the plant samples collected from different regions. ResultThe PCR with GQ-F/R∶NX-F/R concentration ratio of 2∶1 at the annealing temperature at 59 ℃ and for 30 cycles showed specific bands at 183 bp and 295 bp， respectively， for L. chinense and L. barbarum samples from different regions. ConclusionThe established PCR approach can simply， rapidly， and efficiently identify the original plants of Lycii Cortex， serving as a new method for the discrimination between L. chinense and L. barbarum. Moreover， the method provides technical support for the research and development of classic famous prescriptions containing Lycii Cortex.