OBJECTIVE To form an expert consensus on the clinical application of parenteral direct thrombin inhibitors （DTIs） in patients during the perioperative period. METHODS Led by Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital （the Affiliated Hospital of UESTC）， a multidisciplinary working group was established. Through literature review and the Delphi method， clinical questions related to the rational perioperative use of parenteral DTIs were identified. A structured design was adopted using the “Population-Intervention-Comparison-Outcome” framework； systematic searches were conducted in CNKI， Medline， Embase and other databases. Relevant evidence from randomized controlled trials and cohort studies was included and synthesized. Evidence quality was assessed using the Grades of Recommendations Assessment，Development and Evaluation （GRADE） approach， and recommendations were formulated through multiple rounds of Delphi surveys and expert consensus meetings. RESULTS &CONCLUSIONS Seven recommendations （each with an expert consensus rate exceeding 90%） on the use of parenteral DTIs in perioperative patients were developed. These recommendations specify drug selection， dosing ranges， key monitoring points， and safety management strategies for parenteral DTIs in various scenarios， including the perioperative period of ventricular assist device implantation， the perioperative period of cardiac surgery， perioperative patients with lower-extremity atherosclerotic disease， the perioperative period of percutaneous coronary intervention in patients with acute coronary syndrome， the perioperative period of carotid artery stenting in patients with carotid stenosis， the perioperative period of patients with right heart thrombosis， and patients who develop related thrombosis and dysfunction after a central venous catheter insertion. In addition， warning and management pathways for perioperative bleeding and thrombotic events were proposed. This expert consensus， which is formulated based on the best available evidence， provides evidence-based guidance for standardized and individualized use of parenteral DTIs in perioperative period.

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.

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

OBJECTIVE: To investigate the predictive value of endothelial activation and stress index (EASIX) for the prognosis of patients with mantle cell lymphoma (MCL). METHODS: A retrospective analysis was conducted to assess prognosis and compare the clinical features of patients diagnosed with MCL who were admitted to the Affiliated Hospital of Xuzhou Medical University from January 2010 to June 2023, had therapeutic indications and received standard treatment. RESULTS: A total of 66 patients were included and divided into high EASIX group and low EASIX group, according to a cutoff value of 0.97 determined by the receiver operating characteristic (ROC) curve. Multivariate Cox regression analysis showed that prealbumin <0.2 g/L, high EASIX, and ECOG PS score ≥2 were independent risk factors influencing overall survival (OS) in MCL patients. The median OS of patients in the high and low EASIX group was 13.0 and 37.5 months, and the median progression-free survival was 8.8 and 26.0 months, respectively. The proportions of patients with ECOG PS score ≥2 and prealbumin <0.2 g/L at onset significantly increased in the high EASIX group compared to those in the low EASIX group. CONCLUSION At the time of initial diagnosis, EASIX can serve as an independent prognostic indicator impacting OS in patients with MCL. Furthermore, patients in the high EASIX group experience a poorer prognosis and shorter survival duration compared with those in the low EASIX group.
Humans ; Lymphoma, Mantle-Cell/pathology* ; Prognosis ; Retrospective Studies ; Male ; Female ; Middle Aged ; Aged ; ROC Curve

OBJECTIVE: To investigate the predictive role of the modified Endothelial Activation and Stress Index (mEASIX) in the efficacy of chimeric antigen receptor T-cell (CAR-T) therapy and cytokine release syndrome (CRS). METHODS: The clinical data of 70 relapsed and refractory (R/R) B-cell tumor patients who were treated with CAR-T therapy from September 1, 2018 to February 28, 2023 in the Department of Hematology, Affiliated Hospital of Xuzhou Medical University, were retrospectively analyzed. The value of log-2 mEASIX before conditioning (-7 d) was calculated, and the patients were divided into a low-mEASIX group (42 patients) and a high-mEASIX group (28 patients) based on the cut-off value of 5.443 determined by the receiver operating characteristic (ROC) curve. Eventually, the predictive role of mEASIX before conditioning on the efficacy of CAR-T cell therapy and CRS was analyzed. RESULTS: The high-mEASIX group exhibited significantly worse median overall survival (OS) and median progression-free survival (PFS) in comparison to the low mEASIX group (OS: 3.2 months vs not reached, P < 0.01; PFS: 1.3 months vs 6.0 months, P =0.009). The incidence of grade ≥2 CRS in the high-mEASIX group was substantially higher than that in the low-mEASIX group (57.1% vs 19.0%, P =0.007). The degree of remission after CAR-T therapy (P =0.001), whether CRS occurs or not (P =0.041), the lactate dehydrogenase (LDH) level before conditioning (P =0.046), and the mEASIX score before conditioning (P =0.047) were independent influencing factors for the OS of patients receiving CAR-T cell therapy. CONCLUSION The mEASIX score before conditioning can predict OS and the incidence of grade ≥2 CRS in patients with relapsed and refractory B-cell tumors who receive CAR-T cell therapy.
Cytokine Release Syndrome/therapy* ; Immunotherapy, Adoptive/methods* ; Humans ; Lymphoma, B-Cell/therapy* ; Retrospective Studies ; Hematology ; China ; Receptors, Chimeric Antigen/blood* ; Predictive Value of Tests

OBJECTIVE: To explore the mechanism of crocin, a major active component of Crocus sativus (Zanghonghua), in regulating amyloid beta (Aβ) generation, endoplasmic reticulum (ER) stress, and autophagy in neuronal cells, with potential therapeutic applications in Alzheimer's disease (AD). METHODS: Mouse neuroblastoma Neuron2a (N2a) cells stably transfected with the human amyloid precursor protein (APP) Swedish mutant was used as a cellular model for AD (N2a/APP). Control cells were vector transfected (N2a/vector). The effects of 3 different doses of crocin on reactive oxygen species (ROS) generation, cytosolic calcium, and apoptosis were evaluated by flow cytometry. Aβ levels were determined by enzyme-linked immunosorbent assay. APP processing and ER stress proteins expressions were determined by Western blot. Autophagosome formation was evaluated by autophagy detection kit and confocal microscope. RESULTS: Crocin inhibited APP expression in N2a/APP cells and promoted α-cleavage of APP processing, while modestly reduced beta-secretase 1 (BACE1) and presenilin 1 (PS1, P<0.05 or P<0.01). ER stress markers, including the binding immunoglobulin protein/78-kD glucose-regulated protein (Bip/GRP78) and C/EBP homologous protein (CHOP), were elevated in N2a/APP cells compared to N2a/vector cells (P<0.05). Crocin could effectively reduce the levels of ER stress (P<0.05 or P<0.01). In addition, crocin enhanced autophagy by promoting formation of autophagosome (P<0.05 or P<0.01). CONCLUSION Crocin significantly inhibited Aβ generation by promoting α-cleavage of APP processing, inhibiting ER stress-associated unfolded protein response, and regulating autophagy.
Endoplasmic Reticulum Stress/drug effects* ; Autophagy/drug effects* ; Animals ; Endoplasmic Reticulum Chaperone BiP ; Mice ; Amyloid beta-Peptides/metabolism* ; Amyloid beta-Protein Precursor/metabolism* ; Carotenoids/pharmacology* ; Humans ; Cell Line, Tumor ; Reactive Oxygen Species/metabolism* ; Apoptosis/drug effects* ; Calcium/metabolism*