[Objective] To investigate the antigen and gene frequency distribution of the MNS blood group system in the Han population of voluntary blood donors in Suzhou, and to explore the polymorphism of rare MNS blood group genes, in order to improve the construction of the local rare blood group database. [Methods] A total of 8 034 whole blood samples were randomly collected from Han blood donors at our station from October 2023 to June 2024. The MNS blood group phenotypes were identified using serological methods. Gene frequencies were analyzed and compared with those of ethnic populations in other regions. Rare MNS phenotype samples were subjected to gene sequencing. [Results] The distribution of MNS blood group system phenotypes within the population was as follows: the MM, NN, and MN phenotypes accounted for 23.00%, 27.12%, and 49.88% respectively; the SS, ss, and Ss phenotypes accounted for 0.30%, 90.99%, and 8.70% respectively. The gene frequencies of M, N, S, and s were 0.4794, 0.5206, 0.0465, and 0.9534 respectively. Chi-squared tests confirmed adherence to Hardy-Weinberg equilibrium with P-values of 0.997 and 0.349, showing statistical significance compared to some other regional ethnic populations (P<0.05). Additionally, one rare serological phenotype, S-s-, with a frequency of 0.01%, was identified. [Conclusion] The MNS blood group system in the Han population of voluntary blood donors in Suzhou exhibits polymorphism and regional distribution characteristics. Gene frequencies differ from those observed in other regions of China. It is essential to enhance the establishment of a rare blood type database in Suzhou to provide data support for precise clinical transfusion.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

ObjectiveTo explore the mechanism of the anti-cancer compound formula Feiyanning in inhibiting epithelial-mesenchymal transition （EMT） and invasion and metastasis of non-small cell lung cancer （NSCLC）. MethodsCell proliferation and activity were assessed using the cell counting kit-8（CCK-8） assay to evaluate the effect of Feiyanning on the proliferation of A549 and H1299 cells. Wound healing and Transwell assays were conducted to examine Feiyanning's impact on the metastasis of A549 and H1299 cells. The effects of Feiyanning on EMT and the transforming growth factor-β₁ （TGF-β₁）/Smad signaling pathway proteins in A549 and H1299 cells were detected by Western blot. Exogenous TGF-β₁ was used to induce EMT in A549 and H1299 cells. The effects of Feiyanning on TGF-β₁-induced NSCLC cell metastasis， EMT， and the TGF-β₁/Smad pathway proteins were assessed by wound healing assay， Transwell assay， and Western blot. In vivo， an A549 lung metastasis model was established via tail vein injection in nude mice. A total of 28 SPF male nude mice were randomly divided into four groups： Model （NC） group， Feiyanning low-dose （FYN1） group， Feiyanning high-dose （FYN2） group， and the positive control group （TGF-β receptor kinase inhibitor SB431542 group）. The corresponding interventions were performed. After 40 days， the mice were euthanized， and lung metastases were analyzed. The expression of E-cadherin， N-cadherin， p-Smad2， and p-Smad3 in each group was detected by immunohistochemistry （IHC）. ResultsAfter Feiyanning intervention， compared to the blank group， Feiyanning inhibited the proliferation of A549 and H1299 cells in a concentration-dependent manner （P<0.01）. The metastasis ability of Feiyanning-treated cells was significantly decreased compared to the blank group （P<0.01）. The expression of EMT marker proteins N-cadherin and zinc finger transcription factors （Zeb1， Snail， Slug） was significantly reduced in the Feiyanning groups compared to the blank group （P<0.05， P<0.01）. The expression of p-Smad2/3， Smad2/3， TβRI， and TβRⅡ， key proteins in the TGF-β₁/Smad signaling pathway， was also significantly decreased （P<0.01）. In the TGF-β₁-induced EMT model， compared to the TGF-β₁ group， the cell metastasis ability in the Feiyanning groups was reduced （P<0.01）， and the expression levels of N-cadherin， Zeb1， Snail， and Slug were significantly lower （P<0.01）. The expression levels of p-Smad2/3， Smad2/3， TβRI， and TβRⅡ were also significantly reduced （P<0.01）. In vivo results showed that compared to the model group， the number of lung metastases in the FYN1， FYN2， and SB431542 groups was reduced （P<0.01）， and the range of cell infiltration was narrowed. Immunohistochemical results showed that compared to the model group， the expression of E-cadherin in the FYN1， FYN2， and SB431542 groups was increased （P<0.01）， the expression of N-cadherin decreased （P<0.05， P<0.01）， and the expression of p-Smad2 and p-Smad3， key proteins of the TGF-β₁/Smad pathway， was reduced （P<0.01）. ConclusionFeiyanning inhibits the invasion and metastasis of NSCLC cells and EMT. The mechanism is related to the inhibition of TGF-β₁/Smad signaling pathway.

ObjectiveTo explore the mechanism of the anti-cancer compound formula Feiyanning in inhibiting epithelial-mesenchymal transition （EMT） and invasion and metastasis of non-small cell lung cancer （NSCLC）. MethodsCell proliferation and activity were assessed using the cell counting kit-8（CCK-8） assay to evaluate the effect of Feiyanning on the proliferation of A549 and H1299 cells. Wound healing and Transwell assays were conducted to examine Feiyanning's impact on the metastasis of A549 and H1299 cells. The effects of Feiyanning on EMT and the transforming growth factor-β₁ （TGF-β₁）/Smad signaling pathway proteins in A549 and H1299 cells were detected by Western blot. Exogenous TGF-β₁ was used to induce EMT in A549 and H1299 cells. The effects of Feiyanning on TGF-β₁-induced NSCLC cell metastasis， EMT， and the TGF-β₁/Smad pathway proteins were assessed by wound healing assay， Transwell assay， and Western blot. In vivo， an A549 lung metastasis model was established via tail vein injection in nude mice. A total of 28 SPF male nude mice were randomly divided into four groups： Model （NC） group， Feiyanning low-dose （FYN1） group， Feiyanning high-dose （FYN2） group， and the positive control group （TGF-β receptor kinase inhibitor SB431542 group）. The corresponding interventions were performed. After 40 days， the mice were euthanized， and lung metastases were analyzed. The expression of E-cadherin， N-cadherin， p-Smad2， and p-Smad3 in each group was detected by immunohistochemistry （IHC）. ResultsAfter Feiyanning intervention， compared to the blank group， Feiyanning inhibited the proliferation of A549 and H1299 cells in a concentration-dependent manner （P<0.01）. The metastasis ability of Feiyanning-treated cells was significantly decreased compared to the blank group （P<0.01）. The expression of EMT marker proteins N-cadherin and zinc finger transcription factors （Zeb1， Snail， Slug） was significantly reduced in the Feiyanning groups compared to the blank group （P<0.05， P<0.01）. The expression of p-Smad2/3， Smad2/3， TβRI， and TβRⅡ， key proteins in the TGF-β₁/Smad signaling pathway， was also significantly decreased （P<0.01）. In the TGF-β₁-induced EMT model， compared to the TGF-β₁ group， the cell metastasis ability in the Feiyanning groups was reduced （P<0.01）， and the expression levels of N-cadherin， Zeb1， Snail， and Slug were significantly lower （P<0.01）. The expression levels of p-Smad2/3， Smad2/3， TβRI， and TβRⅡ were also significantly reduced （P<0.01）. In vivo results showed that compared to the model group， the number of lung metastases in the FYN1， FYN2， and SB431542 groups was reduced （P<0.01）， and the range of cell infiltration was narrowed. Immunohistochemical results showed that compared to the model group， the expression of E-cadherin in the FYN1， FYN2， and SB431542 groups was increased （P<0.01）， the expression of N-cadherin decreased （P<0.05， P<0.01）， and the expression of p-Smad2 and p-Smad3， key proteins of the TGF-β₁/Smad pathway， was reduced （P<0.01）. ConclusionFeiyanning inhibits the invasion and metastasis of NSCLC cells and EMT. The mechanism is related to the inhibition of TGF-β₁/Smad signaling pathway.

Artificial intelligence (AI) has emerged as a transformative force in healthcare, with applications spanning diagnostics to drug development. However, its integration into drug regulation remains nascent, with varying degrees of adoption and implementation across different regulatory bodies worldwide. This review aims to provide a comprehensive overview of the current state of AI in drug regulation, encapsulating AI-related policies, initiatives, and its practical application in regulatory agencies globally. It further discusses the challenges and future prospects of AI in this field. The findings reveal that numerous agencies have launched action plans and initiatives to incorporate AI, aiming to streamline regulatory processes and enhance data-driven regulatory decision-making. Moreover, AI's deployment in safety surveillance, workflow optimization, and regulatory science research is expanding, highlighting its increasing impact on drug regulation. Nonetheless, key challenges persist, such as data quality and reliability, technical limitations, talent shortage and the absence of standards. The review concludes that interdisciplinary collaboration is crucial to harness AI's full potential in drug regulation and overcoming its current limitations. In the future, AI may become a pivotal catalyst in drug regulation, promising a new era of enhanced scrutiny, efficiency, and innovation that will benefit public health on a global scale.

Peptide receptor radionuclide therapy (PRRT) with radiolabeled SSTR2 agonists is a treatment option that is highly effective in controlling metastatic and progressive neuroendocrine tumors (NETs). Previous studies have shown that an SSTR2 agonist combined with albumin binding moiety Evans blue (denoted as ¹⁷⁷Lu-EB-TATE) is characterized by a higher tumor uptake and residence time in preclinical models and in patients with metastatic NETs. This study aimed to enhance the in vivo stability, pharmacokinetics, and pharmacodynamics of ¹⁷⁷Lu-EB-TATE by replacing the maleimide-thiol group with a polyethylene glycol chain, resulting in a novel EB conjugated SSTR2-targeting radiopharmaceutical, ¹⁷⁷Lu-LNC1010, for PRRT. In preclinical studies, ¹⁷⁷Lu-LNC1010 exhibited good stability and SSTR2-binding affinity in AR42J tumor cells and enhanced uptake and prolonged retention in AR42J tumor xenografts. Thereafter, we presented the first-in-human dose escalation study of ¹⁷⁷Lu-LNC1010 in patients with advanced/metastatic NETs. ¹⁷⁷Lu-LNC1010 was well-tolerated by all patients, with minor adverse effects, and exhibited significant uptake and prolonged retention in tumor lesions, with higher tumor radiation doses than those of ¹⁷⁷Lu-EB-TATE. Preliminary PRRT efficacy results showed an 83% disease control rate and a 42% overall response rate after two ¹⁷⁷Lu-LNC1010 treatment cycles. These encouraging findings warrant further investigations through multicenter, prospective, and randomized controlled trials.

Gene regulation relies on the precise binding of transcription factors (TFs) at regulatory elements, but simultaneously detecting hundreds of TFs on chromatin is challenging. We developed cFOOT-seq, a cytosine deaminase-based TF footprinting assay, for high-resolution, quantitative genome-wide assessment of TF binding in both open and closed chromatin regions, even with small cell numbers. By utilizing the dsDNA deaminase SsdAtox, cFOOT-seq converts accessible cytosines to uracil while preserving genomic integrity, making it compatible with techniques like ATAC-seq for sensitive and cost-effective detection of TF occupancy at the single-molecule and single-cell level. Our approach enables the delineation of TF footprints, quantification of occupancy, and examination of chromatin influences on TF binding. Notably, cFOOT-seq, combined with FootTrack analysis, enables de novo prediction of TF binding sites and tracking of TF occupancy dynamics. We demonstrate its application in capturing cell type-specific TFs, analyzing TF dynamics during reprogramming, and revealing TF dependencies on chromatin remodelers. Overall, cFOOT-seq represents a robust approach for investigating the genome-wide dynamics of TF occupancy and elucidating the cis-regulatory architecture underlying gene regulation.
Transcription Factors/genetics* ; Humans ; Chromatin/genetics* ; Animals ; Binding Sites ; Mice ; DNA Footprinting/methods*

This paper summarizes Professor WANG Xiuxia's clinical experience in treating hyperprolactinemia using the liver soothing therapy. Professor WANG identifies liver qi stagnation and rebellious chong qi （冲气） as the core pathomechanisms of hyperprolactinemia. Furthermore， liver qi stagnation may transform into fire or lead to pathological changes such as spleen deficiency with phlegm obstruction or kidney deficiency with essence depletion. The treatment strategy centers on soothing the liver， with a modified version of Qinggan Jieyu Decoction （清肝解郁汤） as the base formula. Depending on different syndrome patterns such as liver stagnation transforming into fire， liver stagnation with spleen deficiency， or liver stagnation with kidney deficiency， heat clearing， spleen strengthening， or kidney tonifying herbs are added accordingly. In addition， three paired herb combinations are commonly used for symptom specific treatment， Danggui （Angelica sinensis） with Chuanxiong （Ligusticum chuanxiong）， Zelan （Lycopus lucidus） with Yimucao （Leonurus japonicus） ， and Jiegeng （Platycodon grandiflorus） with Zisu （Perilla frutescens）.