The preference for ammonium may be attributed to a hyperpolarized membrane potential via TWIK-1 channels Lanying Pan, Brendan Zhu, Simon L Vu, Antony Stalin, Ashley Winters, Qizhi Gong, Yuan Chen Brain Research, 2026 Urine, which contains ammonium, transmits crucial signals among animals. However, the mechanism underlying signal transmission remains unknown. In our study, we observed that there are significant differences in olfactory preference depending on ammonium concentrations of 0.0004 %, 0.004 %, and 0.04 % between TWIK-1 gene knockout (TWIK-1 −/− ) and wild-type (WT) mice (p < 0.05, n = 6), although there is no significant preference difference between the 4 % concentration groups. These results are consistent with calcium imaging data, which showed an increase in calcium fluorescence only in the olfactory epithelium (OE) of TWIK-1 −/− mice at 4 and 400 µM NH 4 + concentrations, but in both groups at 40 mM NH 4 + . The electrophysiological results indicate an increase in the amplitudes of the inward current that hyperpolarizes the membrane potential at 400 µM NH 4 + , while it depolarizes the membrane potential at higher NH 4 + concentrations. These findings suggest a potential mechanism by which ammonium hyperpolarizes the membrane potential via TWIK-1 channels at low concentrations, making the OE cells more difficult to activate and resulting in the differences in olfactory preference between the two groups.
Editorial: Natural medicines for metabolic diseases – computational and pharmacological approaches, Volume II Antony Stalin, Christudas Sunil, Abd El-Latif Hesham, Savarimuthu Ignacimuthu, Quan Zou, Yansu Wang Frontiers in Pharmacology, 2026 (computational biopharmaceutics and modeling), Pharmaceutical Chemistry, Network Pharmacology Metabolic conditions, including type 2 diabetes mellitus (T2DM), obesity, dyslipidemia, and metabolic dysfunction associated with steatotic liver disease, together with their cardiovascular and renal complications, continue to rise in prevalence and impose a substantial economic burden worldwide. Current estimates indicate that more than 500 million individuals are affected by diabetes globally and is projected to increase markedly by 2045 (Sun et al., 2022). The multi-organ and multi-pathway dysregulation characteristic of these disorders leads to clinical heterogeneity, making it difficult to select treatment targets and resulting in mixed responses.Small molecules extracted from natural products and traditional medicines remain an important source of therapeutics, particularly for pathway-level modulation and rational polypharmacology (Newman and Cragg, 2020;Atanasov et al., 2021). In parallel, systems pharmacology, multi-omics technologies, and data-driven artificial intelligence (AI) methods are transforming the field by bridging phytochemicals, molecular targets, and disease phenotypes, enabling exploration of large chemical spaces and generation of experimentally testable mechanistic hypotheses (Hopkins, 2008;Vamathevan et al., 2019).Together, these advances provide a more tractable and mechanism-based framework for natural product research, from dataset construction and model development to candidate prioritization and biological validation.The Research Topic Natural Medicines for Metabolic Diseases: Computational and Pharmacological Approaches brings together contributions that integrate computational and experimental strategies to accelerate translation. It continues the editorial vision introduced in Volume I of this series (Stalin et al., 2024). Volume II comprises six papers: three original research articles and three review or meta-analytic studies, covering diabetic complications, target discovery, and methodology development. Cautious evidence synthesis also benefits clinical translation. Lin et al. conducted a systematic review and meta-analysis of Qingre Lishi decoction (QRLSD) for T2DM, summarizing data from 18 randomized controlled trials. The analysis reports improvements in fasting and postprandial glucose, HbA1c, lipid profiles, and indices of insulin resistance, without an apparent increase in adverse events. However, substantial heterogeneity among studies and variability in formulations limit the strength of causal inference. The authors appropriately call for large, multicenter trials using standardized preparations and extended follow-up to assess generalizability and long-term benefit.In Volume II, several priorities emerge for the next stage. First, improved data infrastructure is essential: standardized chemical identifiers, harmonized endpoints, curated databases, and transparent preprocessing pipelines are prerequisites for credible AI models and reproducible systems pharmacology. Second, multi-target design should be intentional rather than incidental; multi-objective optimization, uncertainty-aware prioritization, and explicit off-target risk assessment are necessary to balance efficacy, safety, and developability. Third, the most impactful studies will tightly integrate computation and experimentation, translating omics-derived hypotheses into a small number of high-confidence targets for directionality-aware testing and subjecting AIprioritized compounds to prospective evaluation, including early ADMET screening.Finally, openness should be the norm: shared code, datasets, and validation protocols will facilitate independent replication and rapid methodological iteration.Together, the six articles create a cohesive impact by supporting a realistic message: finding natural medicines to treat metabolic disorders is most effective when computational prioritization, inference of systems-level mechanisms, and pharmacological validation are integrated into a single auditable process. The Volume II collection is expected to help increase reproducible, mechanism-based pipelines and accelerate the development of promising natural products into plausible therapeutic candidates.
EnDeep4mC predicts DNA N4-methylcytosine sites using a dual-adaptive feature encoding framework in deep ensembles Shuyu Zhang, Quan Zou, Mengting Niu, Zhibin Lv, Antony Stalin, Ximei Luo Genome Research, 2026 DNA N 4 -methylcytosine (4mC), a key epigenetic modification regulating DNA repair and replication, requires efficient computational detection methods due to experimental limitations. Although machine learning predictors have been proposed, their performance could be enhanced through systematic optimization of feature encoding schemes. Here, we propose EnDeep4mC, a dual-adaptive framework integrating species-specific modeling with ensemble deep learning architectures to systematically optimize feature encoding schemes. Evaluated across six species, EnDeep4mC demonstrates commendable prediction performance and significantly outperforms current state-of-the-art predictors. Cross-species validation confirms its robust transferability from animal to microbe groups. Evolutionary analysis further uncovers the functional differentiation of 4mC sequences in biological evolution: Prokaryotic 4mC relies on stable patterns, whereas eukaryotes achieve regulatory plasticity through dynamic sequence combinations, which provides experimental evidence for species-adaptive encoding strategies.
Editorial: Novel natural therapies for infectious diseases using computational and pharmacological approaches Antony Stalin, Pachaiyappan Saravana Kumar, Claudio Ferrante, Abd El-Latif Hesham, Savarimuthu Ignacimuthu, Ximei Luo Frontiers in Pharmacology, 2026 (computational biopharmaceutics and modeling), Pharmaceutical Chemistry, Network Pharmacology Infectious diseases remain a persistent global public health challenge, driven by antimicrobial resistance (AMR) and the ongoing emergence of novel viral pathogens. Drugresistant bacteria were directly responsible for approximately 1.27 million deaths in 2019, with projections indicating a significant increase in this toll without new therapeutic interventions (Murray et al., 2022). Simultaneously, the rapid mutational dynamics of RNA viruses, including SARS-CoV-2 and influenza, continually generate immune-evasive and drug-resistant variants, necessitating broad-spectrum therapeutics (Dhama et al., 2023;Zhao et al., 2023). In this context, naturally derived products from plants, fungi, and marine organisms have re-emerged as historically validated sources of novel anti-infectives (Newman and Cragg, 2020). The pharmacological potential of natural products stems from their diverse secondary metabolites that target key viral and bacterial enzymes, including proteases, polymerases, and cell wall biosynthesis (Atanasov et al., 2021). The integration of computational methodologies such as molecular docking, MD simulations, machine learning, and network pharmacology with experimental pharmacology has catalyzed a paradigm shift in natural product-based drug discovery, enabling systematic virtual screening, ADMET profiling, and mechanistic hypothesis generation (Lluka and Stokes, 2022;Stalin et al., 2024;Wang et al., 2025).Within this context, the Research Topic "Novel Natural Therapies for Infectious Diseases Using Computational and Pharmacological Approaches" presents six articles, including four original research papers and two reviews, reflecting the breadth of contemporary natural antiinfective discovery.Zheng et al. present a review of traditional Chinese medicine in viral pneumonia, focusing on COVID-19-related mechanisms. Instead of viewing herbal medicine as a collection of remedies, the authors organize the literature by signaling pathways, including PI3K/Akt, NF-κB, JAK/STAT, and mTOR. This pathway-centered approach is valuable because it connects complex formulations to biological processes such as inflammation control, immune regulation, apoptosis, and tissue injury. The review also highlights a methodological direction for the field: natural therapies are more likely to achieve translational value when their effects are described in mechanistic terms that can be compared, tested, and refined. Their data show that plant extracts, especially ethyl acetate fractions, contain bioactive constituents and display measurable activity against bacterial and fungal pathogens; while docking and molecular dynamics simulations support plausible interactions with microbial targets. The strength of this work lies in its integrated workflow: metabolite characterization, biological testing, and in silico interpretation are used together rather than as isolated steps. This design increases the value of exploratory phytochemical studies by making the biological observations more interpretable.At the discovery-platform level, Narsing Rao et al. review omics strategies for obtaining molecules from marine Actinomycetota. The article highlights genome mining, metagenomics, transcriptomics, metabolomics, heterologous expression, and analytical methods as tools for overcoming a problem in natural product research: the repeated rediscovery of known compounds. Their review is relevant to this Research Topic because it expands the discussion from individual herbal interventions to the infrastructure needed for natural product discovery. In doing so, it reinforces a central message of the collection: progress in infectious disease pharmacology will increasingly depend on how well biological resources, computational methods, and validation strategies are integrated.The six articles demonstrate that the discovery of natural therapies for infectious diseases is shifting from single-technique, single-endpoint studies toward more integrated workflows.Several priorities emerge from this collection. First, natural products research in infectious disease requires stronger mechanistic resolution, so that extracts or compounds can be linked to defined pathways, host responses, or microbial targets. Second, computational tools should serve as decision-support systems that improve prioritization and reduce experimental ambiguity, rather than functioning as stand-alone additions. Third, model systems are important: clinically relevant ex vivo models, immune-aware infection models, and omics-guided microbial discovery platforms can enhance translational value. Finally, the field would benefit from improved standardization of phytochemical characterization, endpoint reporting, toxicity assessment, and data sharing, which are necessary for reproducibility and meaningful comparison across studies.Overall, this Research Topic provides a perspective on how natural therapies, when studied with pharmacological rigor and computational support, can contribute to anti-infective discovery. The collection does not claim that natural products will resolve the current burden of infectious disease. Instead, it presents a clearer argument: natural compounds, herbal formulations, and microbially derived metabolites remain therapeutic resources, and their future value will be greatest when discovery is guided by mechanism, informed by data, and validated in relevant systems.
Integrating bulk and single cell sequencing data to identify prognostic biomarkers and drug candidates in HBV associated hepatocellular carcinoma Yanjie Zhong, Antony Stalin, Yu-Shi Dai, Zhiqiang He, Siqi Yang, et al. Scientific Reports, 2025 Hepatitis B virus (HBV) infection is a major driver of hepatocellular carcinoma (HCC), yet the mechanisms by which HBV triggers HCC and how it interacts with the immune system remain largely undefined. In this study, 53 immune-related key genes involved in HBV-associated HCC progression were identified. By analyzing the mean C-index of 101 machine learning models, the optimal model-combining stepwise Cox regression (forward) with RSF-was developed to characterize the immune risk index. Patients in the high-risk group exhibited worse survival outcomes and increased infiltration of immunosuppressive cells. Integrating PPI analysis with machine learning, SPP1, GHR, and ESR1 emerged as promising druggable targets, with SPP1 notably overexpressed in tumors and linked to adverse outcomes. ScRNA-seq analysis revealed SPP1 was predominantly expressed in angio-TAMs, which may impair anti-tumor immunity by limiting T and NK cell infiltration. It also involved in tumor progression via angiogenesis and EMT pathways. Drug prediction and molecular docking identified small molecules such as myricetin and mefloquine that can target the aforementioned key immune genes, thereby modulating the immune landscape of HBV-HCC. Repurposing these established drugs represents a novel therapeutic avenue, offering both efficacy and expedited clinical translation for HBV-HCC.
hERG Channel Blockade and Antagonistic Interactions of Three Steroidal Alkaloids from Fritillaria Species Hui Lu, Tingting Hao, Zixuan Zhang, Chenxin Jiang, Jianwei Xu, Antony Stalin, Wei Zhao Molecules, 2025 The bulb of Fritillaria species called “Bei Mu” is a well-known traditional Chinese medicine. We have reported some potential off-target effects of “Bei Mu” due to peimine’s blockade of hERG (human Ether-a-go-go-Related Gene) channels. This research investigated the modulatory effects of three major alkaloid analogs of “Bei Mu” and their cooperative effects on hERG channels using manual whole-cell patch-clamp techniques. Results showed that peiminine and sipeimine blocked hERG currents with IC50s of 36.8 ± 2.5 μM and 47.6 ± 9.8 μM, which were close to that of peimine (26.1 ± 3.5 μM). Peiminine-induced blockade increased with increasing depolarizing strengths, durations, and frequencies, which suggested a preferential binding to open or inactivated states. The reduced blockade by the less inactivating S631A mutation supported peiminine‘s inactivation preference. Molecular docking and dynamics simulations confirmed the hERG-blocking activities of the three alkaloids and provided further insight into potential mechanisms. We also discovered antagonistic effects of the three alkaloids at nearly all concentrations tested, which might help reduce potential cardiotoxicities. To our knowledge, this is the first study to investigate combination effects of chemicals from one herb on hERG channels. In conclusion, peiminine and sipeimine can block hERG channels in a way similar to peimine, but antagonistic effects exist among them.
Gold Nanoparticles: Clinical Applications Sheikdawood Parveen, T. Sathiyapriya, D. Tharani, S. U. Mohammed Riyaz, Rakshi Anuja Dinesh, Jayashree Shanmugam, K. Rajakumar, Dmitry Zherebtsov, Manikandan Dhayalan, Antony Stalin Engineering Materials, 2023
In silico docking analysis to explore the proapoptotic and anti cell proliferative potential of ferulic acid Indian Journal of Biochemistry and Biophysics, 2016
Novel natural therapies for infectious diseases using computational and pharmacological approaches A Stalin, P Saravana Kumar, C Ferrante, AEL Hesham, S Ignacimuthu, ... Frontiers in Pharmacology 17, 1826975 , 2026 2026
EnDeep4mC predicts DNA N4-methylcytosine sites using a dual-adaptive feature encoding framework in deep ensembles S Zhang, Q Zou, M Niu, Z Lv, A Stalin, X Luo Genome Research 36 (3), 589 , 2026 2026
Natural medicines for metabolic diseases–computational and pharmacological approaches, Volume II A Stalin, C Sunil, AEL Hesham, S Ignacimuthu, Q Zou, Y Wang Frontiers in Pharmacology 17, 1799670 , 2026 2026
Musizin from Rhamnus wightii and Its Derivatives Attenuate Non-Alcoholic Fatty Liver Disease in Palmitate Oleate-Induced HepG2 Hepatocytes TRW Raja, A Stalin, V Duraipandiyan, K Balakrishna, S Ignacimuthu, ... REVISTA BRASILEIRA DE FARMACOGNOSIA-BRAZILIAN JOURNAL OF PHARMACOGNOSY 36 (1) , 2026 2026
Musizin from Rhamnus wightii and Its Derivatives Attenuate Non-Alcoholic Fatty Liver Disease in Palmitate Oleate–Induced HepG2 Hepatocytes TR William Raja, A Stalin, V Duraipandiyan, K Balakrishna, S Ignacimuthu, ... Revista Brasileira de Farmacognosia 36 (1), 21 , 2026 2026
Photoprotective effects of deinoxanthin against UVA-Induced oxidative damage: an integrative computational and cellular analysis K Balamurugan, A Stalin, CS Pawar, NR Prasad Archives of Dermatological Research 318 (1), 57 , 2026 2026
The preference for ammonium may be attributed to a hyperpolarized membrane potential via TWIK-1 channels L Pan, B Zhu, SL Vu, A Stalin, A Winters, Q Gong, Y Chen Brain Research, 150109 , 2025 2025
hERG Channel Blockade and Antagonistic Interactions of Three Steroidal Alkaloids from Fritillaria Species H Lu, T Hao, Z Zhang, C Jiang, J Xu, A Stalin, W Zhao Molecules 30 (19), 3882 , 2025 2025
In silico molecular docking analysis on acetylcholinesterase (AChE) inhibition activity on Aedes aegypti and Culex quinquefasciatus by β-isocostic acid A Yagoo, MCJ Milton, J Vilvest, A Stalin Journal of Asia-Pacific Entomology 28 (3), 102433 , 2025 2025 Citations: 2
Integrating bulk and single cell sequencing data to identify prognostic biomarkers and drug candidates in HBV associated hepatocellular carcinoma Y Zhong, A Stalin, Y Dai, Z He, S Yang, R Zou, A Zhai, F Li, H Hu Scientific Reports 15 (1), 26038 , 2025 2025 Citations: 4
Effects of host age and size on progeny production and different foods on the adult longevity of Spalangia nigroaenea Curtis (Hymenoptera: Pteromalidae) reared on puparia … N Velayudham, I Hari, A Stalin, MK Dharmalingam Jothinathan, ... Biocontrol Science and Technology 35 (7), 740-754 , 2025 2025 Citations: 1
Identifying the DNA methylation preference of transcription factors using ProtBERT and SVM Y Li, Q Zou, Q Dai, A Stalin, X Luo PLOS Computational Biology 21 (5), e1012513 , 2025 2025 Citations: 4
Exploration of the regulatory mechanism of norcantharidin on sine oculis homeobox homolog 4 in colon cancer using transcriptome sequencing and bioinformatic F Zhang, C Wu, J Zhang, Z Huang, A Stalin, Y Zhai, S Liu, J Wu Journal of Traditional Chinese Medical Sciences 12 (2), 259-276 , 2025 2025
Activity of Essential Oils From Pentanema indicum (L.) Y. Ling and Chromolaena odorata (L.) R.M.King & H. Rob Against Three Mosquito Species P Ganesan, J Selvakumaran, S Ignacimuthu, B Aldahmash, A Rady, ... Entomological Research 55 (2), e70016 , 2025 2025 Citations: 1
Enhanced Bioactivity of Streptomycin Bioconjugated Metal Nanoparticles Against Streptomycin Resistant Bacillus Sp N Ramasami, M Dhayalan, M Selvaraj, SUM Riyaz, P Perumal, ... Indian Journal of Microbiology 64 (4), 1787-1804 , 2024 2024 Citations: 2
Anticancer effects of rutin from Fagopyrum tataricum (tartary buckwheat) against osteosarcoma cell line D Soosai, R Ramalingam, E Perumal, K Veeramani, C Pancras, ... Molecular biology reports 51 (1), 312 , 2024 2024 Citations: 19
Antimycobacterial activity of plant compounds against extensively drug resistant (XDR-TB) Mycobacterium tuberculosis D Veeramuthu, I Savarimuthu, IA Khan, HA Alodaini, AA Hatamleh, ... Journal of King Saud University-Science 36 (9), 103351 , 2024 2024 Citations: 8
Exploring the antiviral inhibitory activity of Niloticin against the NS2B/NS3 protease of Dengue virus (DENV2) A Stalin, J Han, AD Reegan, S Ignacimuthu, S Liu, X Yao, Q Zou International Journal of Biological Macromolecules 277, 133791 , 2024 2024 Citations: 5
Herbal medical products Q Zou¹, S Ignacimuthu Herbal Medical Products for Metabolic Diseases-New Integrated … , 2024 2024
Herbal medical products for metabolic diseases-new integrated pharmacological approaches A Stalin, AEL Hesham, A Mishra, Q Zou, S Ignacimuthu Frontiers in Pharmacology 15, 1464176 , 2024 2024 Citations: 4
MOST CITED SCHOLAR PUBLICATIONS
Gallic acid attenuates high-fat diet fed-streptozotocin-induced insulin resistance via partial agonism of PPARγ in experimental type 2 diabetic rats and enhances glucose uptake … GR Gandhi, G Jothi, PJ Antony, K Balakrishna, MG Paulraj, S Ignacimuthu, ... European journal of pharmacology 745, 201-216 , 2014 2014 Citations: 235
Insulin sensitization via partial agonism of PPARγ and glucose uptake through translocation and activation of GLUT4 in PI3K/p-Akt signaling pathway by embelin in type 2 … GR Gandhi, A Stalin, K Balakrishna, S Ignacimuthu, MG Paulraj, R Vishal Biochimica et Biophysica Acta (BBA)-General Subjects 1830 (1), 2243-2255 , 2013 2013 Citations: 138
Wearable flexible electronics based cardiac electrode for researcher mental stress detection system using machine learning models on single lead electrocardiogram signal MB Bin Heyat, F Akhtar, SJ Abbas, M Al-Sarem, A Alqarafi, A Stalin, ... Biosensors 12 (6), 427 , 2022 2022 Citations: 130
Protective effects of Ficus carica leaves on glucose and lipids levels, carbohydrate metabolism enzymes and β-cells in type 2 diabetic rats S Stephen Irudayaraj, S Christudas, S Antony, V Duraipandiyan, ... Pharmaceutical biology 55 (1), 1074-1081 , 2017 2017 Citations: 119
Molecular docking of γ-sitosterol with some targets related to diabetes R Balamurugan, A Stalin, S Ignacimuthu European journal of medicinal chemistry 47, 38-43 , 2012 2012 Citations: 107
Antioxidant, antilipidemic and antidiabetic effects of ficusin with their effects on GLUT4 translocation and PPARγ expression in type 2 diabetic rats SS Irudayaraj, A Stalin, C Sunil, V Duraipandiyan, NA Al-Dhabi, ... Chemico-biological interactions 256, 85-93 , 2016 2016 Citations: 80
Myoinositol ameliorates high-fat diet and streptozotocin-induced diabetes in rats through promoting insulin receptor signaling PJ Antony, GR Gandhi, A Stalin, K Balakrishna, E Toppo, K Sivasankaran, ... Biomedicine & Pharmacotherapy 88, 1098-1113 , 2017 2017 Citations: 73
Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels T cell-related prognostic risk model and tumor immune microenvironment modulation in triple-negative breast … S Guo, X Liu, J Zhang, Z Huang, P Ye, J Shi, A Stalin, C Wu, S Lu, ... Computers in biology and medicine 161, 107066 , 2023 2023 Citations: 69
Hypoglycemic activity of 6-bromoembelin and vilangin in high-fat diet fed-streptozotocin-induced type 2 diabetic rats and molecular docking studies A Stalin, SS Irudayaraj, GR Gandhi, K Balakrishna, S Ignacimuthu, ... Life sciences 153, 100-117 , 2016 2016 Citations: 50
γ-sitosterol a potent hypolipidemic agent: In silico docking analysis JHK Rangachari Balamurugan, Antony Stalin, Adithan Aravinthan Medicinal Chemistry Research 24 (Issue 1), 124-130 , 2014 2014 Citations: 47
Advances in functional lipid nanoparticles: from drug delivery platforms to clinical applications M Dhayalan, W Wang, SUM Riyaz, RA Dinesh, J Shanmugam, ... 3 Biotech 14 (2), 57 , 2024 2024 Citations: 46
A network pharmacology approach to reveal the pharmacological targets and biological mechanism of compound kushen injection for treating pancreatic cancer based on WGCNA and in … C Wu, ZH Huang, ZQ Meng, XT Fan, S Lu, YY Tan, LM You, JQ Huang, ... Chinese Medicine 16 (1), 121 , 2021 2021 Citations: 44
Geranii Herba as a Potential Inhibitor of SARS-CoV-2 Main 3CL pro , Spike RBD, and Regulation of Unfolded Protein Response: An In Silico Approach S Arokiyaraj, A Stalin, BS Kannan, H Shin Antibiotics 9 (12), 863 , 2020 2020 Citations: 44
T cell-related prognostic risk model and tumor immune environment modulation in lung adenocarcinoma based on single-cell and bulk RNA sequencing J Zhang, X Liu, Z Huang, C Wu, F Zhang, A Han, A Stalin, S Lu, S Guo, ... Computers in biology and medicine 152, 106460 , 2023 2023 Citations: 42
Biocontrol and non-target effect of fractions and compound isolated from Streptomyces rimosus on the immature stages of filarial vector Culex quinquefasciatus Say (Diptera … P Ganesan, A Stalin, MG Paulraj, K Balakrishna, S Ignacimuthu, ... Ecotoxicology and environmental safety 161, 120-128 , 2018 2018 Citations: 40
Curative effect of arjunolic acid from Terminalia arjuna in non-alcoholic fatty liver disease models E Toppo, SS Darvin, S Esakkimuthu, K Buvanesvaragurunathan, ... Biomedicine & Pharmacotherapy 107, 979-988 , 2018 2018 Citations: 36
Antihyperlipidemic and hepatoprotective effects of Gardenin A in cellular and high fat diet fed rodent models E Toppo, SS Darvin, S Esakkimuthu, A Stalin, K Balakrishna, ... Chemico-biological interactions 269, 9-17 , 2017 2017 Citations: 35
Polyphenols-rich Cyamopsis tetragonoloba (L.) Taub. beans show hypoglycemic and β-cells protective effects in type 2 diabetic rats GR Gandhi, P Vanlalhruaia, A Stalin, SS Irudayaraj, S Ignacimuthu, ... Food and chemical toxicology 66, 358-365 , 2014 2014 Citations: 34
Data mining combines bioinformatics discover immunoinfiltration-related gene SERPINE1 as a biomarker for diagnosis and prognosis of stomach adenocarcinoma Y Zhai, X Liu, Z Huang, J Zhang, A Stalin, Y Tan, F Zhang, M Chen, R Shi, ... Scientific reports 13 (1), 1373 , 2023 2023 Citations: 33
Structure and pharmacological activities of polysaccharides from Anoectochilus roxburghii (Wall.) Lindl T Wu, S Li, Y Huang, Z He, Y Zheng, A Stalin, Q Shao, D Lin Journal of Functional Foods 87, 104815 , 2021 2021 Citations: 31