目的采用文献计量学方法探讨药物的生殖与发育毒性研究热点和发展趋势。方法从Web of Science核心集中收集2009—2023年相关文献数据并利用CiteSpace,VOSviewer等工具进行可视化分析。结果共有1962篇文献纳入研究,这些文献多聚焦于药理...目的采用文献计量学方法探讨药物的生殖与发育毒性研究热点和发展趋势。方法从Web of Science核心集中收集2009—2023年相关文献数据并利用CiteSpace,VOSviewer等工具进行可视化分析。结果共有1962篇文献纳入研究,这些文献多聚焦于药理学和毒理学领域,但对公共卫生、环境科学等领域的研究存在欠缺。近15年发文量总体呈上升趋势,至2021年达到高峰。在101个国家/地区中,美国的发文量最多且来自美国的哈佛大学被认为是最高生产力的机构,但其国际交流合作的深度与广度仍待拓展。Werler MM是同时拥有最高发文量和被引频次的作者。在766个期刊中,Reproductive Toxicology以85篇发文量位居第1位。关键词和文献分析表明沙利度胺、抗甲状腺药(ATD)、抗癫痫药(AED)等是高频研究药物,毒性机制聚焦于氧化应激、DNA损伤、细胞凋亡等。结论药物的生殖和发育毒性研究面向多学科发展,对公共卫生和环境科学等研究薄弱领域应加强关注。目前的研究重点聚焦于ATD、AED在内的多种药物毒性探索和毒理机制研究。未来应加强多学科交叉应用,积极探寻有效的抗氧化策略和减少DNA损伤及细胞凋亡的措施。展开更多
目的以氨甲环酸注射液和吡拉西坦注射液为代表,考察这两种治疗脑出血的注射剂与复方电解质醋酸钠葡萄糖注射液超说明书配伍的稳定性,为临床安全使用提供科学指导。方法将氨甲环酸注射液或吡拉西坦注射液与复方电解质醋酸钠葡萄糖注射液...目的以氨甲环酸注射液和吡拉西坦注射液为代表,考察这两种治疗脑出血的注射剂与复方电解质醋酸钠葡萄糖注射液超说明书配伍的稳定性,为临床安全使用提供科学指导。方法将氨甲环酸注射液或吡拉西坦注射液与复方电解质醋酸钠葡萄糖注射液配伍后,于0、1、2、4 h检测配伍溶液的澄明度、pH值、电导率、不溶性微粒和使用高效液相色谱法测定各自主药成分含量的变化。结果氨甲环酸配伍结果和吡拉西坦配伍结果均表明两种配伍溶液在室温放置4 h内未出现变色、气泡、沉淀、浑浊等明显外观变化;氨甲环酸注射液在配伍后0~4 h pH值、电导率的相对标准偏差(RSD)分别为0.10%、0.49%,吡拉西坦注射液在配伍后0~4 h pH值、电导率RSD分别为0.10%、1.50%;两者不溶性微粒均在《中国药典》规定范围内;氨甲环酸含量0~4 h RSD为1.90%;吡拉西坦含量0~4 h RSD为3.27%。结论氨甲环酸注射液或吡拉西坦注射液与复方电解质醋酸钠葡萄糖注射液配伍4 h内稳定。展开更多
Peptide-based therapeutics hold great promise for the treatment of various diseases;however,their clinical application is often hindered by toxicity challenges.The accurate prediction of peptide toxicity is crucial fo...Peptide-based therapeutics hold great promise for the treatment of various diseases;however,their clinical application is often hindered by toxicity challenges.The accurate prediction of peptide toxicity is crucial for designing safe peptide-based therapeutics.While traditional experimental approaches are time-consuming and expensive,computational methods have emerged as viable alternatives,including similarity-based and machine learning(ML)-/deep learning(DL)-based methods.However,existing methods often struggle with robustness and generalizability.To address these challenges,we propose HyPepTox-Fuse,a novel framework that fuses protein language model(PLM)-based embeddings with conventional descriptors.HyPepTox-Fuse integrates ensemble PLM-based embeddings to achieve richer peptide representations by leveraging a cross-modal multi-head attention mechanism and Transformer architecture.A robust feature ranking and selection pipeline further refines conventional descriptors,thus enhancing prediction performance.Our framework outperforms state-of-the-art methods in cross-validation and independent evaluations,offering a scalable and reliable tool for peptide toxicity prediction.Moreover,we conducted a case study to validate the robustness and generalizability of HyPepTox-Fuse,highlighting its effectiveness in enhancing model performance.Furthermore,the HyPepTox-Fuse server is freely accessible at https://balalab-skku.org/HyPepTox-Fuse/and the source code is publicly available at https://github.com/cbbl-skku-org/HyPepTox-Fuse/.The study thus presents an intuitive platform for predicting peptide toxicity and supports reproducibility through openly available datasets.展开更多
文摘目的采用文献计量学方法探讨药物的生殖与发育毒性研究热点和发展趋势。方法从Web of Science核心集中收集2009—2023年相关文献数据并利用CiteSpace,VOSviewer等工具进行可视化分析。结果共有1962篇文献纳入研究,这些文献多聚焦于药理学和毒理学领域,但对公共卫生、环境科学等领域的研究存在欠缺。近15年发文量总体呈上升趋势,至2021年达到高峰。在101个国家/地区中,美国的发文量最多且来自美国的哈佛大学被认为是最高生产力的机构,但其国际交流合作的深度与广度仍待拓展。Werler MM是同时拥有最高发文量和被引频次的作者。在766个期刊中,Reproductive Toxicology以85篇发文量位居第1位。关键词和文献分析表明沙利度胺、抗甲状腺药(ATD)、抗癫痫药(AED)等是高频研究药物,毒性机制聚焦于氧化应激、DNA损伤、细胞凋亡等。结论药物的生殖和发育毒性研究面向多学科发展,对公共卫生和环境科学等研究薄弱领域应加强关注。目前的研究重点聚焦于ATD、AED在内的多种药物毒性探索和毒理机制研究。未来应加强多学科交叉应用,积极探寻有效的抗氧化策略和减少DNA损伤及细胞凋亡的措施。
文摘目的以氨甲环酸注射液和吡拉西坦注射液为代表,考察这两种治疗脑出血的注射剂与复方电解质醋酸钠葡萄糖注射液超说明书配伍的稳定性,为临床安全使用提供科学指导。方法将氨甲环酸注射液或吡拉西坦注射液与复方电解质醋酸钠葡萄糖注射液配伍后,于0、1、2、4 h检测配伍溶液的澄明度、pH值、电导率、不溶性微粒和使用高效液相色谱法测定各自主药成分含量的变化。结果氨甲环酸配伍结果和吡拉西坦配伍结果均表明两种配伍溶液在室温放置4 h内未出现变色、气泡、沉淀、浑浊等明显外观变化;氨甲环酸注射液在配伍后0~4 h pH值、电导率的相对标准偏差(RSD)分别为0.10%、0.49%,吡拉西坦注射液在配伍后0~4 h pH值、电导率RSD分别为0.10%、1.50%;两者不溶性微粒均在《中国药典》规定范围内;氨甲环酸含量0~4 h RSD为1.90%;吡拉西坦含量0~4 h RSD为3.27%。结论氨甲环酸注射液或吡拉西坦注射液与复方电解质醋酸钠葡萄糖注射液配伍4 h内稳定。
基金supported by the National Research Foundation of Korea(NRF)funded by the Ministry of Science and ICT,Republic of Korea(Grant No.:RS-2024-00344752)supported by the Department of Integrative Biotechnology,Sungkyunkwan University(SKKU)and the BK21 FOUR Project,Republic of Korea.
文摘Peptide-based therapeutics hold great promise for the treatment of various diseases;however,their clinical application is often hindered by toxicity challenges.The accurate prediction of peptide toxicity is crucial for designing safe peptide-based therapeutics.While traditional experimental approaches are time-consuming and expensive,computational methods have emerged as viable alternatives,including similarity-based and machine learning(ML)-/deep learning(DL)-based methods.However,existing methods often struggle with robustness and generalizability.To address these challenges,we propose HyPepTox-Fuse,a novel framework that fuses protein language model(PLM)-based embeddings with conventional descriptors.HyPepTox-Fuse integrates ensemble PLM-based embeddings to achieve richer peptide representations by leveraging a cross-modal multi-head attention mechanism and Transformer architecture.A robust feature ranking and selection pipeline further refines conventional descriptors,thus enhancing prediction performance.Our framework outperforms state-of-the-art methods in cross-validation and independent evaluations,offering a scalable and reliable tool for peptide toxicity prediction.Moreover,we conducted a case study to validate the robustness and generalizability of HyPepTox-Fuse,highlighting its effectiveness in enhancing model performance.Furthermore,the HyPepTox-Fuse server is freely accessible at https://balalab-skku.org/HyPepTox-Fuse/and the source code is publicly available at https://github.com/cbbl-skku-org/HyPepTox-Fuse/.The study thus presents an intuitive platform for predicting peptide toxicity and supports reproducibility through openly available datasets.
