Aptamer 学术简报 — infectious_disease — 2026-06-21
自动生成 by RBTX Aptamer Tracker v0.1。 子主题 infectious_disease:近 14 天 5 篇命中(aptamer 池 166 篇)。
评分公式:composite = 0.45×log(IF) + 0.35×log(cites_velocity) + 0.10×social + 0.10×recency_bonus;满分 100。
#1 [17.2] Aptamer modified NPA hollow nanozymes with intrinsic peroxidase-like activity for colorimetric sensing of H1N1.
- Journal: Analytica chimica acta (IF 5.4)
- Date: 2026-06-08 · Citations: 3 · 0.23 cites/day
- Authors: Wang J, Zhang S, Wang Q et al. (9 authors)
- DOI: 10.1016/j.aca.2026.345189 · PMID: 41934996
- Score components: IF 8.1 · velocity 22.5 · recency 56.7
A colorimetric sensor based on aptamer-functionalized nanozyme probes was successfully developed for the sensitive and specific detection of influenza A (H1N1) virus. In this study, trimetallic nickel-palladium-gold hollow nanozymes (NPA) with excellent peroxidase (POD)-like activity were used as catalytic probes. Compared to the horseradish per...
#2 [11.3] Amino Acid-Programmed Biomineralization for Radical-Proximal Enzyme-MOF Interfaces in Electrochemiluminescent Influenza Hemagglutinin Sensing.
- Journal: Analytical chemistry (IF 6.7)
- Date: 2026-06-13 · Citations: 0
- Authors: Li YX, Dai YX, Wu Y et al. (8 authors)
- DOI: 10.1021/acs.analchem.6c02318 · PMID: 42287620
- Score components: IF 8.9 · recency 73.3
Electrochemiluminescent (ECL) biosensing is fundamentally limited by inefficient coupling between catalytic radical generation and luminophore excitation. Here, we report an amino acid-programmed biomineralization strategy for constructing radical-proximal enzyme-MOF interfaces under mild aqueous conditions. Serine reconfigures zirconium precurs...
#3 [9.3] Geometric Deep Learning Reveals Ligandable and Cryptic RNA Binding Small Molecule Pockets (SMARTPocket)
- Journal: bioRxiv (Cold Spring Harbor Laboratory) (IF ?)
- Date: 2026-06-19 · Citations: 0
- Authors: Riddhish H. Thakare, Amirhossein Taghavi, Jielei Wang et al. (7 authors)
- DOI: 10.64898/2026.06.18.732920
- Score components: recency 93.3
RNAs are important therapeutic targets, however identifying ligandable small-molecule binding pockets remains a major barrier to RNA-targeted drug discovery. Here, SMARTPocket, an atomic-level geometric deep learning framework for predicting RNA-small molecule binding pockets directly from three-dimensional structure is introduced. SMARTPocket r...
#4 [8.0] An AutocatalyticMolecular Sensor Enables Rapid, Sensitive,and One-Pot Detection of Nucleic Acids
- Journal: Figshare (IF ?)
- Date: 2026-06-15 · Citations: 0
- Authors: Xue Li (285380), Zhihao Xu (89017), Xiaowei Ma (113432) et al. (13 authors)
- DOI: 10.1021/acsnano.6c06154.s001
- Score components: recency 80.0
Circulating nucleic acids are emerging disease markers whose clinical applications are hindered by the lack of rapid, sensitive, convenient, and cost-effective detection assays. Inspired by the natural replication of virus, here, we developed a biomimetic one-step, one-pot, isothermal detection assay named RAPID to realize rapid and sensitive de...
#5 [6.3] Sennoside A and Ceftazidime Inhibit Nucleocapsid RNA Binding Across SARS-CoV-2, SARS-CoV, and MERS-CoV
- Journal: bioRxiv (Cold Spring Harbor Laboratory) (IF ?)
- Date: 2026-06-10 · Citations: 0
- Authors: Shweta Singh, Gagan D. Gupta
- DOI: 10.64898/2026.06.09.731089
- Score components: recency 63.3
SARS-CoV, MERS-CoV, and SARS-CoV-2 exemplify the persistent threat posed by coronaviruses, with their capacity for zoonotic spill over, rapid transmission, and high mortality, and thus underscores the urgent need for broad-spectrum antiviral strategies. The nucleocapsid (N) protein, essential for RNA binding, genome packaging, and viral replicat...
Methodology
- 数据源:PubMed (esearch + esummary), OpenAlex (concept C2776201186 + DOI 反查 citations), bioRxiv (preprints)
- 去重:按 DOI 跨源合并
- IF:硬编码 top 50 期刊 JCR 2024 IF(
config.JOURNAL_IF) - Citation velocity:OpenAlex
cited_by_count/ 发表天数 - Social:Reddit r/science + r/biotech + HN(DOI/title 关键词搜)
- 窗口:近 14 天发表;超出 30 天 recency_bonus = 0
- 每天:建议 8-9am 跑
python run.py collect && python run.py score && python run.py report