Herb-CMap: a multimodal fusion framework for deciphering the mechanisms of action in traditional Chinese medicine using Suhuang antitussive capsule as a case study.

Herbal medicines, particularly traditional Chinese medicines (TCMs), are a rich source of natural products with significant therapeutic potential. However, understanding their mechanisms of action is challenging due to the complexity of their multi-ingredient compositions. We introduced Herb-CMap, a multimodal fusion framework leveraging protein-protein interactions and herb-perturbed gene expression signatures. Utilizing a network-based heat diffusion algorithm, Herb-CMap creates a connectivity map linking herb perturbations to their therapeutic targets, thereby facilitating the prioritization of active ingredients. As a case study, we applied Herb-CMap to Suhuang antitussive capsule (Suhuang), a TCM formula used for treating cough variant asthma (CVA). Using in vivo rat models, our analysis established the transcriptomic signatures of Suhuang and identified its key compounds, such as quercetin and luteolin, and their target genes, including IL17A, PIK3CB, PIK3CD, AKT1, and TNF. These drug-target interactions inhibit the IL-17 signaling pathway and deactivate PI3K, AKT, and NF-κB, effectively reducing lung inflammation and alleviating CVA. The study demonstrates the efficacy of Herb-CMap in elucidating the molecular mechanisms of herbal medicines, offering valuable insights for advancing drug discovery in TCM.

KCNQ Potassium Channels as Targets of Botanical Folk Medicines.

Since prehistory, human species have depended on plants for both food and medicine. Even in countries with ready access to modern medicines, alternative treatments are still highly regarded and commonly used. Unlike modern pharmaceuticals, many botanical medicines are in widespread use despite a lack of safety and efficacy data derived from controlled clinical trials and often unclear mechanisms of action. Contributing to this are the complex and undefined composition and likely multifactorial mechanisms of action and multiple targets of many botanical medicines. Here, we review the newfound importance of the ubiquitous KCNQ subfamily of voltage-gated potassium channels as targets for botanical medicines, including basil, capers, cilantro, lavender, fennel, chamomile, ginger, and Camellia, Sophora, and Mallotus species. We discuss the implications for the traditional use of these plants for disorders such as seizures, hypertension, and diabetes and the molecular mechanisms of plant secondary metabolite effects on KCNQ channels.

Comparative study of the mechanism of natural compounds with similar structures using docking and transcriptome data for improving in silico herbal medicine experimentations.

Natural products have successfully treated several diseases using a multi-component, multi-target mechanism. However, a precise mechanism of action (MOA) has not been identified. Systems pharmacology methods have been used to overcome these challenges. However, there is a limitation as those similar mechanisms of similar components cannot be identified. In this study, comparisons of physicochemical descriptors, molecular docking analysis and RNA-seq analysis were performed to compare the MOA of similar compounds and to confirm the changes observed when similar compounds were mixed and used. Various analyses have confirmed that compounds with similar structures share similar MOA. We propose an advanced method for in silico experiments in herbal medicine research based on the results. Our study has three novel findings. First, an advanced network pharmacology research method was suggested by partially presenting a solution to the difficulty in identifying multi-component mechanisms. Second, a new natural product analysis method was proposed using large-scale molecular docking analysis. Finally, various biological data and analysis methods were used, such as in silico system pharmacology, docking analysis and drug response RNA-seq. The results of this study are meaningful in that they suggest an analysis strategy that can improve existing systems pharmacology research analysis methods by showing that natural product-derived compounds with the same scaffold have the same mechanism.

COIMMR: a computational framework to reveal the contribution of herbal ingredients against human cancer via immune microenvironment and metabolic reprogramming.

Immune evasion and metabolism reprogramming have been regarded as two vital hallmarks of the mechanism of carcinogenesis. Thus, targeting the immune microenvironment and the reprogrammed metabolic processes will aid in developing novel anti-cancer drugs. In recent decades, herbal medicine has been widely utilized to treat cancer through the modulation of the immune microenvironment and reprogrammed metabolic processes. However, labor-based herbal ingredient screening is time consuming, laborious and costly. Luckily, some computational approaches have been proposed to screen candidates for drug discovery rapidly. Yet, it has been challenging to develop methods to screen drug candidates exclusively targeting specific pathways, especially for herbal ingredients which exert anti-cancer effects by multiple targets, multiple pathways and synergistic ways. Meanwhile, currently employed approaches cannot quantify the contribution of the specific pathway to the overall curative effect of herbal ingredients. Hence, to address this problem, this study proposes a new computational framework to infer the contribution of the immune microenvironment and metabolic reprogramming (COIMMR) in herbal ingredients against human cancer and specifically screen herbal ingredients targeting the immune microenvironment and metabolic reprogramming. Finally, COIMMR was applied to identify isoliquiritigenin that specifically regulates the T cells in stomach adenocarcinoma and cephaelin hydrochloride that specifically targets metabolic reprogramming in low-grade glioma. The in silico results were further verified using in vitro experiments. Taken together, our approach opens new possibilities for repositioning drugs targeting immune and metabolic dysfunction in human cancer and provides new insights for drug development in other diseases. COIMMR is available at https://github.com/LYN2323/COIMMR.

TCMFP: a novel herbal formula prediction method based on network target's score integrated with semi-supervised learning genetic algorithms.

Traditional Chinese medicine (TCM) has accumulated thousands years of knowledge in herbal therapy, but the use of herbal formulas is still characterized by reliance on personal experience. Due to the complex mechanism of herbal actions, it is challenging to discover effective herbal formulas for diseases by integrating the traditional experiences and modern pharmacological mechanisms of multi-target interactions. In this study, we propose a herbal formula prediction approach (TCMFP) combined therapy experience of TCM, artificial intelligence and network science algorithms to screen optimal herbal formula for diseases efficiently, which integrates a herb score (Hscore) based on the importance of network targets, a pair score (Pscore) based on empirical learning and herbal formula predictive score (FmapScore) based on intelligent optimization and genetic algorithm. The validity of Hscore, Pscore and FmapScore was verified by functional similarity and network topological evaluation. Moreover, TCMFP was used successfully to generate herbal formulae for three diseases, i.e. the Alzheimer's disease, asthma and atherosclerosis. Functional enrichment and network analysis indicates the efficacy of targets for the predicted optimal herbal formula. The proposed TCMFP may provides a new strategy for the optimization of herbal formula, TCM herbs therapy and drug development.

SGAE-MDA: Exploring the MiRNA-disease associations in herbal medicines based on semi-supervised graph autoencoder.

Research indicates that miRNAs present in herbal medicines are crucial for identifying disease markers, advancing gene therapy, facilitating drug delivery, and so on. These miRNAs maintain stability in the extracellular environment, making them viable tools for disease diagnosis. They can withstand the digestive processes in the gastrointestinal tract, positioning them as potential carriers for specific oral drug delivery. By engineering plants to generate effective, non-toxic miRNA interference sequences, it's possible to broaden their applicability, including the treatment of diseases such as hepatitis C. Consequently, delving into the miRNA-disease associations (MDAs) within herbal medicines holds immense promise for diagnosing and addressing miRNA-related diseases. In our research, we propose the SGAE-MDA model, which harnesses the strengths of a graph autoencoder (GAE) combined with a semi-supervised approach to uncover potential MDAs in herbal medicines more effectively. Leveraging the GAE framework, the SGAE-MDA model exactly integrates the inherent feature vectors of miRNAs and disease nodes with the regulatory data in the miRNA-disease network. Additionally, the proposed semi-supervised learning approach randomly hides the partial structure of the miRNA-disease network, subsequently reconstructing them within the GAE framework. This technique effectively minimizes network noise interference. Through comparison against other leading deep learning models, the results consistently highlighted the superior performance of the proposed SGAE-MDA model. Our code and dataset can be available at: https://github.com/22n9n23/SGAE-MDA.

Bone-Targeted Supramolecular Nanoagonist Assembled by Accurate Ratiometric Herbal-Derived Therapeutics for Osteoporosis Reversal.

Developing novel strategies for defeating osteoporosis has become a world-wide challenge with the aging of the population. In this work, novel supramolecular nanoagonists (NAs), constructed from alkaloids and phenolic acids, emerge as a carrier-free nanotherapy for efficacious osteoporosis treatment. These precision nanoagonists are formed through the self-assembly of berberine (BER) and chlorogenic acid (CGA), utilizing noncovalent electrostatic, π-π, and hydrophobic interactions. This assembly results in a 100% drug loading capacity and stable nanostructure. Furthermore, the resulting weights and proportions of CGA and BER within the NAs are meticulously controlled with strong consistency when the CGA/BER assembly feed ratio is altered from 1:1 to 1:4. As anticipated, our NAs themselves could passively target osteoporotic bone tissues following prolonged blood circulation, modulate Wnt signaling, regulate osteogenic differentiation, and ameliorate bone loss in ovariectomy-induced osteoporotic mice. We hope this work will open a new strategy to design efficient herbal-derived Wnt NAs for dealing with intractable osteoporosis.

Chinese herbal medicine for the treatment of intestinal cancer: preclinical studies and potential clinical applications.

Intestinal cancer (IC) poses a significant global health challenge that drives continuous efforts to explore effective treatment modalities. Conventional treatments for IC are effective, but are associated with several limitations and drawbacks. Chinese herbal medicine (CHM) plays an important role in the overall cancer prevention and therapeutic strategies. Recent years have seen a growing body of research focus on the potential of CHM in IC treatment, showing promising results in managing IC and mitigating the adverse effects of radiotherapy and chemotherapy. This review provides updated information from preclinical research and clinical observation on CHM's role in treatment of IC, offering insights into its comprehensive management and guiding future prevention strategies and clinical practice.

Astragalus membranaceus, Nigella sativa, and Perilla frutescens as Immunomodulators-Molecular Mechanisms and Clinical Effectiveness in Allergic Diseases.

Plants are the source of numerous remedies in modern medicine, and some of them have been studied due to their potential immunomodulatory activity. Astragalus membranaceus Fisch. ex Bunge (A. membranaceus), Nigella sativa L. (N. sativa), and Perilla frutescens (L.) Britton (P. frutescens) are plant species used in traditional medicine for the treatment of various diseases. Their potential to act as immunomodulatory, anti-inflammatory, and anti-allergic agents makes them interesting for investigating their clinical potential in alleviating the symptoms of allergic diseases. Allergy affects a large number of people; according to some sources more than 30% of the world population suffer from some type of allergic reaction, with pollen allergy as the most common type. Treatment is usually pharmacological and may not be completely effective or have side effects. Thus, we are seeking traditional medicine, mostly medicinal plants, with promising potential for alleviating allergy symptoms. A literature overview was conducted employing databases such as Scopus, PubMed, Web of Science, Springer, and Google Scholar. This manuscript summarizes recent in vivo preclinical and clinical studies on three species with immunomodulatory activity, provides a comparison of their anti-allergic effects, and underlines the potential of their application in clinical practice. The obtained results confirmed their efficacy in the in vivo and clinical studies, but also emphasize the problem of phytochemical characterization of the species and difference between tested doses. More clinical trials with standardized protocols (defined active molecules, dosage, side effects) are required to obtain safe and effective herbal drugs.

Phytotherapy-Induced Hepatocytotoxicity: A Case Report.

Herbal and complementary medicine are frequently integrated with conventional medicine. We aim to report a case of severe herbal-induced liver injury (HILI) due to chronic use of green tea and protein shake. We present both clinical and laboratory evidence implicating mitochondrial toxicity and an immune response leading to a hypersensitivity reaction to the products. We have recently treated a 39-year-old man with hepatotoxicity resulting from a combination of a green tea-containing powder and a branched-chain amino acid supplement that was commenced 2 months previously. The hepatotoxicity resolved by stopping the consumption of these products and no other cause was detected. We decided to perform a lymphocyte toxicity assay (LTA) to determine if there was laboratory support for this diagnosis. LTA (% toxicity) represents the response of the mitochondria to toxic injury. To determine the role of the proinflammatory and anti-inflammatory cytokines and chemokines in the patient's reaction, we measured the level of cytokines and chemokine in the media of growing cells, exposed to each product or to a combination of products. The increased cytokines and chemokines are presented as the x-fold elevations from the upper limit of normal (ULN) for matrix metalloproteinase (MMP) (pg/mL × 1.5 ULN) and interleukin (IL)-1ß (pg/mL × 1.8 ULN). Higher elevations were found for interferon (IFN)-ß, IFN-γ, IL-8, IL 13, IL-15 (pg/mL × 2 ULN), regulated upon activation, normal T cell expressed and presumably secreted (RANTES) (pg/mL × 2 ULN), and nuclear factor (NFκB) (pg/mL × 3 ULN). The highest increases were for vascular endothelial factor (VEGF) (pg/mL × 10 ULN), tumor necrosis factor (TNF)-α, and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) (pg/mL × 13 ULN). An examination of cellular markers showed the difference between programmed cell death (apoptosis) and cell death due to necrosis. In our case, cytokeratin-ccK18 (M-30) U/L was within the normal limits, suggesting that apoptosis was normal, while ccK8(M65) U/L was elevated at 1.5 × ULN. This result implies that upon the treatment of the patient's lymphocytes with the products, the mechanism of toxicity is necrosis. In susceptible individuals, the combination of protein and herbal tea produces mitochondrial toxicity and a strong T-lymphocyte-1 response, leading to HILI. There is a need of international reporting of adverse drug reactions by clinicians, laboratories, and pharmaceutical manufacturers to drug regulatory authorities. This requires internationally accepted standard definitions of reactions, as well as criteria for assessment.

Mechanisms of intestinal pharmacokinetic natural product-drug interactions.

The growing co-consumption of botanical natural products with conventional medications has intensified the need to understand potential effects on drug safety and efficacy. This review delves into the intricacies of intestinal pharmacokinetic interactions between botanical natural products and drugs, such as alterations in drug solubility, permeability, transporter activity, and enzyme-mediated metabolism. It emphasizes the importance of understanding how drug solubility, dissolution, and osmolality interplay with botanical constituents in the gastrointestinal tract, potentially altering drug absorption and systemic exposure. Unlike reviews that focus primarily on enzyme and transporter mechanisms, this article highlights the lesser known but equally important mechanisms of interaction. Applying the Biopharmaceutics Drug Disposition Classification System (BDDCS) can serve as a framework for predicting and understanding these interactions. Through a comprehensive examination of specific botanical natural products such as byakkokaninjinto, green tea catechins, goldenseal, spinach extract, and quercetin, we illustrate the diversity of these interactions and their dependence on the physicochemical properties of the drug and the botanical constituents involved. This understanding is vital for healthcare professionals to effectively anticipate and manage potential natural product-drug interactions, ensuring optimal patient therapeutic outcomes. By exploring these emerging mechanisms, we aim to broaden the scope of natural product-drug interaction research and encourage comprehensive studies to better elucidate complex mechanisms.

Analysing potent biomarkers along phytochemicals for breast cancer therapy: an in silico approach.

PURPOSE: This research focused on the identification of herbal compounds as potential anti-cancer drugs, especially for breast cancer, that involved the recognition of Notch downstream targets NOTCH proteins (1-4) specifically expressed in breast tumours as biomarkers for prognosis, along with P53 tumour antigens, that were used as comparisons to check the sensitivity of the herbal bio-compounds. METHODS: After investigating phytochemical candidates, we employed an approach for computer-aided drug design and analysis to find strong breast cancer inhibitors. The present study utilized in silico analyses and protein docking techniques to characterize and rank selected bio-compounds for their efficiency in oncogenic inhibition for use in precise carcinomic cell growth control. RESULTS: Several of the identified phytocompounds found in herbs followed Lipinski's Rule of Five and could be further investigated as potential medicinal molecules. Based on the Vina score obtained after the docking process, the active compound Epigallocatechin gallate in green tea with NOTCH (1-4) and P53 proteins showed promising results for future drug repurposing. The stiffness and binding stability of green tea pharmacological complexes were further elucidated by the molecular dynamic simulations carried out for the highest scoring phytochemical ligand complex. CONCLUSION: The target-ligand complex of green tea active compound Epigallocatechin gallate with NOTCH (1-4) had the potential to become potent anti-breast cancer therapeutic candidates following further research involving wet-lab experiments.

Synthetic consortia of four strains promote Schisandra chinensis growth by regulating soil microbial community and improving soil fertility.

MAIN CONCLUSION: Synthetic consortia performed better in promoting Schisandra chinensis growth than individual strains, and this result provides valuable information for the development of synthetic microbial fertilizers. Schisandra chinensis is an herbal medicine that can treat numerous diseases. However, the excessive reliance on chemical fertilizers during the plantation of S. chinensis has severely restricted the development of the S. chinensis planting industry. Plant growth-promoting rhizobacteria (PGPR) can promote the growth of a wide range of crops, and synthetic consortia of them are frequently superior to those of a single strain. In this study, we compared the effects of four PGPR and their synthetic consortia on S. chinensis growth. The pot experiment showed that compared with the control, synthetic consortia significantly increased the plant height, biomass, and total chlorophyll contents of S. chinensis, and their combined effects were better than those of individual strains. In addition, they improved the rhizosphere soil fertility (e.g., TC and TN contents) and enzyme activities (e.g., soil urease activity) and affected the composition and structure of soil microbial community significantly, including promoting the enrichment of beneficial microorganisms (e.g., Actinobacteria and Verrucomicrobiota) and increasing the relative abundance of Proteobacteria, a dominant bacterial phylum. They also enhanced the synergistic effect between the soil microorganisms. The correlation analysis between soil physicochemical properties and microbiome revealed that soil microorganisms participated in regulating soil fertility and promoting S. chinensis growth. This study may provide a theoretical basis for the development of synthetic microbial fertilizers for S. chinensis.

TMNP: a transcriptome-based multi-scale network pharmacology platform for herbal medicine.

One of the most difficult problems that hinder the development and application of herbal medicine is how to illuminate the global effects of herbs on the human body. Currently, the chemo-centric network pharmacology methodology regards herbs as a mixture of chemical ingredients and constructs the 'herb-compound-target-disease' connections based on bioinformatics methods, to explore the pharmacological effects of herbal medicine. However, this approach is severely affected by the complexity of the herbal composition. Alternatively, gene-expression profiles induced by herbal treatment reflect the overall biological effects of herbs and are suitable for studying the global effects of herbal medicine. Here, we develop an online transcriptome-based multi-scale network pharmacology platform (TMNP) for exploring the global effects of herbal medicine. Firstly, we build specific functional gene signatures for different biological scales from molecular to higher tissue levels. Then, specific algorithms are designed to measure the correlations of transcriptional profiles and types of gene signatures. Finally, TMNP uses pharmacotranscriptomics of herbal medicine as input and builds associations between herbs and different biological scales to explore the multi-scale effects of herb medicine. We applied TMNP to a single herb Astragalus membranaceus and Xuesaitong injection to demonstrate the power to reveal the multi-scale effects of herbal medicine. TMNP integrating herbal medicine and multiple biological scales into the same framework, will greatly extend the conventional network pharmacology model centering on the chemical components, and provide a window for systematically observing the complex interactions between herbal medicine and the human body. TMNP is available at http://www.bcxnfz.top/TMNP.

Identification of potential therapeutic targets and mechanisms of COVID-19 through network analysis and screening of chemicals and herbal ingredients.

After experiencing the COVID-19 pandemic, it is widely acknowledged that a rapid drug repurposing method is highly needed. A series of useful drug repurposing tools have been developed based on data-driven modeling and network pharmacology. Based on the disease module, we identified several hub proteins that play important roles in the onset and development of the COVID-19, which are potential targets for repositioning approved drugs. Moreover, different network distance metrics were applied to quantify the relationship between drug targets and COVID-19 disease targets in the protein-protein-interaction (PPI) network and predict COVID-19 therapeutic effects of bioactive herbal ingredients and chemicals. Furthermore, the tentative mechanisms of candidates were illustrated through molecular docking and gene enrichment analysis. We obtained 15 chemical and 15 herbal ingredient candidates and found that different drugs may play different roles in the process of virus invasion and the onset and development of the COVID-19 disease. Given pandemic outbreaks, our method has an undeniable immense advantage in the feasibility analysis of drug repurposing or drug screening, especially in the analysis of herbal ingredients.

Potential COVID-19 remedies from repurposed drugs and herbal small RNAs.

To date, SARS-CoV-2 has caused millions of deaths, but the choice of treatment is limited. We previously established a platform for identifying Food and Drug Administration (FDA)-approved repurposed drugs for avian influenza A virus infections that could be used for coronavirus disease 2019 (COVID-19) treatment. In this study, we analyzed blood samples from two cohorts of 63 COVID-19 patients, including 19 patients with severe disease. Among the 39 FDA-approved drugs we identified for COVID-19 therapy in both cohorts, 23 drugs were confirmed by literature mining data, including 14 drugs already under COVID-19 clinical trials and 9 drugs reported for COVID-19 treatments, suggesting the remaining 16 FDA-approved drugs may be candidates for COVID-19 therapy. Additionally, we previously reported that herbal small RNAs (sRNAs) could be effective components in traditional Chinese medicine (TCM) for treating COVID-19. Based on the abundance of sRNAs, we screened the 245 TCMs in the Bencao (herbal) sRNA Atlas that we had previously established, and we found that the top 12 TCMs for COVID-19 treatment was consistent across both cohorts. We validated the efficiency of the top 30 sRNAs from each of the top 3 TCMs for COVID-19 treatment in poly(I:C)-stimulated human non-small cell lung cancer cells (A549 cells). In conclusion, our study recommends potential COVID-19 remedies using FDA-approved repurposed drugs and herbal sRNAs from TCMs.

Recent application of direct analysis in real time mass spectrometry in plant materials analysis with emphasis on traditional Chinese herbal medicine.

Direct analysis in real time (DART) represents a new generation of ionization techniques that are used to rapidly ionize small molecules under ambient environments. The combination of DART with various mass spectrometry (MS) instruments allows analyzing multiple plant materials, including traditional Chinese herbal medicines (TCHMs), under simple or no sample treatment conditions. This review discussed the DART principles, including devices, ionization mechanisms, and operation parameters. Typical spectra detected by DART-MS were exhibited and discussed. Numerous applications of DART-MS in the fields of plant material and TCHM analysis were reviewed, including compound identification, biomarker discovery, fingerprinting analysis, and quantification analysis. Besides, modifications and improvements of DART-MS, such as hyphenated application with other separation methods, laser-based desorption techniques, and online sampling configuration, were summarized as well.

Development of a virus-based affinity ultrafiltration method for screening virus-surface-protein-targeted compounds from complex matrixes: Herbal medicines as a case study.

Herbal medicines (HMs) are one of the main sources for the development of lead antiviral compounds. However, due to the complex composition of HMs, the screening of active compounds within these is inefficient and requires a significant time investment. We report a novel and efficient virus-based screening method for antiviral active compounds in HMs. This method involves the centrifugal ultrafiltration of viruses, known as the virus-based affinity ultrafiltration method (VAUM). This method is suitable to identify virus specific active compounds from complex matrices such as HMs. The effectiveness of the VAUM was evaluated using influenza A virus (IAV) H1N1. Using this method, four compounds that bind to the surface protein of H1N1 were identified from dried fruits of Terminalia chebula (TC). Through competitive inhibition assays, the influenza surface protein, neuraminidase (NA), was identified as the target protein of these four TC-derived compounds. Three compounds were identified by high performance liquid chromatography (HPLC) and liquid chromatography/mass spectrometry (LC/MS), and their anti-H1N1 activities were verified by examining the cytopathic effect (CPE) and by performing a virus yield reduction assay. Further mechanistic studies demonstrated that these three compounds directly bind to NA and inhibit its activity. In summary, we describe here a VAUM that we designed, one that can be used to accurately screen antiviral active compounds in HMs and also help improve the efficiency of screening antiviral drugs found in natural products.

Label-free detection of ConA-induced T-lymphocyte activation at single-cell level by microfluidics.

Lymphocyte activation is critical in regulating immune responses. The resulting T-cell proliferation has been implicated in the pathogenesis of a variety of autoimmune diseases, such as SLE and rheumatoid arthritis. ConA (concanavalin A)-induced activation has been widely used in the T lymphocytes model of immune-mediated liver injury, autoimmune hepatitis, and so on. In those works, it usually requires fluorescent labeling or cell staining to confirm whether the cells are transformed successfully after medicine treatment to figure out efficacy/pharmacology. The detection preparation steps are time-consuming and have limitations for further proteomic/genomic identifications. Here, a label-free microfluidic method is established to detect lymphocyte activation degree. The lymphocyte and ConA-activated lymphocyte were investigated by a microfluidic device. According to where single cells in the sample were captured in the designed channel, lymphocyte and ConA-activated samples are differentiated and characterized by population electric field factors, 2.08 × 104 and 2.21 × 104 V/m, respectively. Furthermore, salidroside, a herbal medicine that was documented to promote the transformation, was used to treat lymphocyte cells, and the treated cell population is detected to be 2.67 × 104 V/m. The characterization indicates an increasing trend with the activation degree. The result maintains a high consistency with traditional staining methods with transformed cells of 15.8%, 28.8%, and 48.3% in each cell population. Dielectrophoresis is promising to work as a tool for detecting lymphocyte transformation and medical efficacy detection.

Beyond conventional antibiotics approaches: Global perspectives on alternative therapeutics including herbal prevention, and proactive management strategies in bovine mastitis.

Mastitis, an intramammary inflammation resulting from microbial infectious agents, continues to pose a significant challenge within the dairy sector, adversely affecting animal well-being and leading to substantial economic losses. These losses are attributed to decreased milk production, heightened culling rates, and the expenses related to diagnostics, veterinary care, medication, and labor. Moreover, additional costs emerge due to reduced forthcoming milk yields, compromised reproductive health, and increased susceptibility to various illnesses. Identifying the responsible agents is crucial for disease management and the implementation of antimicrobial treatments. Despite the prevalent use of antibiotic treatment, the pressing need for new therapeutic alternatives to combat bovine mastitis arises from limitations, including low cure rates, rising resistance, and the presence of antibiotic residues in milk. This review explores the potential application of herbal extracts and essential oils known for their antimicrobial properties as alternative options for managing pathogens in mastitis treatment. It examines various treatment methods and management strategies, particularly emphasizing the progress of herbal remedies and natural therapeutics in addressing mastitis, a significant concern in bovine populations and dairy herds.