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.

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.

Humans ; PPAR gamma/metabolism* ; Multiple Sclerosis ; Transcription Factors/metabolism* ; Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha

Objective:To analysis the job preference and heterogeneity of medical students by distinguishing their birthplaces,and to provide reference for optimizing the management of primary health care resources.Methods:Using a cluster sampling method,an online survey of discrete choice experiment was conducted with 925 medical students from six teaching hospitals in Beijing,741 valid questionnaires were obtained,the effective recovery rate was 80.1%.The mixed logit model was used to perform regression analysis on six job attributes and estimate the willingness to pay.Results:There were significant differences in the choice of work location among medical students from different birthplaces.The subgroup results showed that compared to medical students from city,undergraduates from rural and county district preferred a work with sufficient career development opportunities.The results of undergraduate subgroup showed that undergraduates from rural district preferred a work with good environment than those from other birthplaces.Conclusion:There is heterogeneity in job preferences of medical students from different birthplaces.Policy makers should pay attention to the medical students'birthplace,also take the educational level into account to optimize the diversified job attributes,formulating targeted intervention to attract primary health care talents.

"MS/MS spectrum to structure"plays a critical role in the confirmative identification of complicated matrices and is currently regarded as an extremely challenging endeavor.MS/MS information provides vital clues to structural identification.In this study,a strategy was proposed to facilitate unambiguous identification through matching MS3 with MS2 spectra.Initially,MS3 spectra of the featured ions(c-and y-type ions)generated by the decomposition of ester functional group in esters and the MS2 spectrum of the structural unit([M-H]-)were all captured on the Qtrap-MS platform equipped with two tandem-in-space collision cells,including the second quadrupole cell(q2)and linear ion trap(LIT)chambers(actually the third quadrupole unit).Subsequently,the MS/MS spectrum matching between MS3 spectra of the ester compound and MS2 spectra of the structural unit(s)were achieved.As a result,the findings corresponding to MS3 and MS2 spectra matching were summarized.Finally,based on HR-MS/MS information of total salvianolic acid derivatives(TSA),36 kinds of compounds were preliminarily identified through matching with literature information and database retrieval.The applicability of MS3 and MS2 spectra matching strategy was further justified by the confirmative identification of phenolic acid compounds(Rosmarinic acid and salvianolic acid B)in TSA.Above all,MS3 and MS2 spectra matching strategy was quite meaningful towards advancing"MS/MS spectrum to structure"analysis through recognizing and identifying featured fragment ions,and also provided inspiration and new insights for the structural characterization.

Photothermal therapy is a new type of tumor therapy that uses near-infrared laser to specifically activate the photothermal agent accumulated in the lesion site, so as to achieve thermal ablation of cancer cells. However, the long metabolic cycle and difficult clearance of photothermal agent materials in vivo are also one of the major obstacles hindering their clinical transformation. In this work, we used hemoglobin as a novel stabilizer, hexachloroplatinic acid as a novel oxidant, and pyrrole as a monomer to prepare hemoglobin-stabilized platinum-based polypyrrole nanoparticles (Hb@PtP) by a one-step oxidative polymerization method and investigated in detail to study their physicochemical properties, such as morphology and structure. After polyethylene glycol modification, the particle size of obtained Hb@PtPP was 99.08 ± 8.3 nm and the zeta potential was -18.7 ± 1.2 mV. Transmission electron microscopy showed that the Hb@PtPP nanoparticles exhibited irregular spherical shape and uniform dispersion in the system. Under the irradiation of 808 nm laser with different power densities, Hb@PtPP showed power density-dependent temperature-raising behavior, and CCK-8 and dead-live staining experiments confirmed that they could effectively exert the photothermal effect to kill tumor cells. Small living animal imaging results demonstrated that Hb@PtPP had good tumor targeting and retention ability, and achieved tumor growth inhibition and ablation in vivo under laser excitation. All animal experiments involved in the study were performed in accordance with the program approved by the Animal Care and Use Committee of the Chinese Academy of Medical Sciences, Beijing Union Medical College, Institute of Radiation Medicine [IRM/2-IACUC-2312-005].

Photodynamic therapy is an emerging cancer therapy with clinical prospects, which plays a specific role in the tumor site and causes less harm to the human body. However, the toxicity of small molecules of hydrophobic photosensitizer, the tumor hypoxia microenvironment, and the biodegradability of nano-carrier systems affect its antitumor efficacy and metabolic clearance in vivo. In this paper, hexachloroplatinic acid was used as a novel oxidizing agent to initiate oxidative polymerization of pyrrole/amino pyrrole to achieve the amino functionalization; further reduced platinum acid anion in the nanostructures into platinum nanoclusters by sodium borohydride as a reducing agent to fabricate platinum nanocluster-doped polypyrrole nanoparticles (PtPPy); and finally, this functional nanoparticles delivering meso-tetra (4-carboxyphenyl) porphine (TCPP) were obtained by amide-bonded coupling of photosensitizers TCPP drug (PtPPy@T). The nanomedicine had a spherical structure, uniform morphology, a particle size of 91.93 ± 13.45 nm, and a zeta potential of -18.39 ± 1.4 mV. Experiments demonstrated that PtPPy@T could react with hydrogen peroxide overexpressed in the tumor to generate a large amount of oxygen, which could relieve the tumor hypoxia microenvironment, and at the same time, provided a sufficient substrate for the subsequent PDT; using 658 nm laser irradiation, the photodynamic effect of PtPPy@T was activated, which catalyzed the conversion of oxygen to singlet oxygen, thus triggering oxidative damage and inducing apoptosis in tumor cells; experimental studies showed that the PtPPy@T nanomedicine had a better tumor inhibitory effect in vivo and in vitro. All animal experiments were approved by the Institutional Animal Care and Use Committee of the Institute of Radiological Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College (IRM/2-IACUC-2312-006).