Teng Lv

427 total citations
16 papers, 347 citations indexed

About

Teng Lv is a scholar working on Cancer Research, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Teng Lv has authored 16 papers receiving a total of 347 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cancer Research, 7 papers in Molecular Biology and 4 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Teng Lv's work include MicroRNA in disease regulation (4 papers), Endometrial and Cervical Cancer Treatments (3 papers) and Cancer, Lipids, and Metabolism (3 papers). Teng Lv is often cited by papers focused on MicroRNA in disease regulation (4 papers), Endometrial and Cervical Cancer Treatments (3 papers) and Cancer, Lipids, and Metabolism (3 papers). Teng Lv collaborates with scholars based in China. Teng Lv's co-authors include Qin Yao, Shu-Zhen Dai, Lei Wang, Yulong Chen, Juan He, Jing Lv, Ruiyun Tian, Jianxia Li, Xiaomin Yu and Hongyan Li and has published in prestigious journals such as FEBS Letters, Medicine and Biomedicine & Pharmacotherapy.

In The Last Decade

Teng Lv

16 papers receiving 345 citations

Peers

Teng Lv
Chong Guo China
Teng Lv
Citations per year, relative to Teng Lv Teng Lv (= 1×) peers Chong Guo

Countries citing papers authored by Teng Lv

Since Specialization
Citations

This map shows the geographic impact of Teng Lv's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Teng Lv with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Teng Lv more than expected).

Fields of papers citing papers by Teng Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Teng Lv. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Teng Lv. The network helps show where Teng Lv may publish in the future.

Co-authorship network of co-authors of Teng Lv

This figure shows the co-authorship network connecting the top 25 collaborators of Teng Lv. A scholar is included among the top collaborators of Teng Lv based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Teng Lv. Teng Lv is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Zhang, Lili, et al.. (2024). Potential Benefits of Statin Therapy in Reducing Osteoarthritis Risk: A Mendelian Randomization Study. Arthritis Care & Research. 76(9). 1260–1268. 5 indexed citations
2.
Zhu, Xiaoying, et al.. (2023). LRRC superfamily expression in stromal cells predicts the clinical prognosis and platinum resistance of ovarian cancer. BMC Medical Genomics. 16(1). 10–10. 5 indexed citations
4.
Ji, Xiaoyu, Lei Sui, Teng Lv, et al.. (2022). Membranous and nuclear staining of CLDN18 in HPV‐independent and HPV‐associated endocervical adenocarcinomas. Cancer Medicine. 12(2). 1441–1450. 6 indexed citations
5.
Zhao, Xiangzhong, et al.. (2022). Serum Free Fatty Acids and G-Coupled Protein Receptors Are Associated With the Prognosis of Epithelial Ovarian Cancer. Frontiers in Oncology. 12. 777367–777367. 4 indexed citations
6.
Cui, Li, Chunmei Li, Xiangzhong Zhao, et al.. (2022). Serum free fatty acid elevation is related to acute kidney injury in primary nephrotic syndrome. Renal Failure. 44(1). 1237–1243. 6 indexed citations
7.
Ji, Xiaoyu, et al.. (2021). PD‐L1, PARP1, and MMRs as potential therapeutic biomarkers for neuroendocrine cervical cancer. Cancer Medicine. 10(14). 4743–4751. 17 indexed citations
8.
Zhang, Dan, Yijing Chu, Yulong Chen, et al.. (2020). Knockdown of enhancer of rudimentary homolog inhibits proliferation and metastasis in ovarian cancer by regulating epithelial-mesenchymal transition. Biomedicine & Pharmacotherapy. 125. 109974–109974. 11 indexed citations
9.
Liu, Wei, Dan Zhang, Hongxuan Li, et al.. (2020). Good performance of p16/Ki‐67 dual‐stain cytology for detection and post‐treatment surveillance of high‐grade CIN/VAIN in a prospective, cross‐sectional study. Diagnostic Cytopathology. 48(7). 635–644. 9 indexed citations
10.
Han, Lei, et al.. (2019). A high serum-free fatty acid level is associated with cancer. Journal of Cancer Research and Clinical Oncology. 146(3). 705–710. 44 indexed citations
11.
Lv, Teng, et al.. (2018). Expression and prognostic value of lactate dehydrogenase-A and -D subunits in human uterine myoma and uterine sarcoma. Medicine. 97(14). e0268–e0268. 31 indexed citations
12.
Lv, Teng, et al.. (2018). Emodin inhibits TGF-β2 by activating the FOXD3/miR‑199a axis in ovarian cancer cells in�vitro. Oncology Reports. 39(5). 2063–2070. 14 indexed citations
13.
Lv, Teng, et al.. (2018). miRNA-34a decreases ovarian cancer cell proliferation and chemoresistance by targeting HDAC1. Biochemistry and Cell Biology. 96(5). 663–671. 47 indexed citations
14.
Yu, Xiaomin, Yulong Chen, Ruiyun Tian, et al.. (2017). miRNA-21 enhances chemoresistance to cisplatin in epithelial ovarian cancer by negatively regulating PTEN. Oncology Letters. 14(2). 1807–1810. 48 indexed citations
15.
Wang, Lei, et al.. (2017). Effects of neoadjuvant chemotherapy on patients with primary vaginal squamous cell carcinoma. Molecular and Clinical Oncology. 7(3). 395–398. 1 indexed citations
16.
Lv, Teng, et al.. (2014). miR‐342‐3p suppresses proliferation, migration and invasion by targeting FOXM1 in human cervical cancer. FEBS Letters. 588(17). 3298–3307. 97 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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