Clinical symptoms and signs are a bridge between biomedicine and traditional medicine [TM]. These can be associated with diseases incl. their diagnosis, pharmacological targets, and the use of specific medications, most importantly in the complex cultural basis of a TM. A clinical symptom phenotype (i.e. clinical symptoms and signs used in TM for diagnosis and treatment is often linked to the appearance of medicinal plants or fungi like their color and chemosensory properties.) is easily overlooked in pharmacological research, both in clinical and preclinical settings. Traditional clinical symptoms and signs are directly related to diagnosis and the subsequent use of specific medications. It remains a complex challenge to interpret a traditional concept and then develop an experimental or clinical protocol.
This research topic aims to promote the solution to the following specific challenges:
• First and foremost, it focuses on assessing how clinical symptoms as expressed in traditional medical systems can be used to define experimental approaches or clinical research.
• Application of new experimental methods and technologies in solving the relationship between clinical phenotypes and medication use.
• Identify potential pharmacological effects or toxic side effects of drugs, as well as their action mechanisms and effective components, based on symptom phenotypes from real-world clinical research.
Specific topics to be addressed include:
• Multiple correlations or causal relationships between symptoms as expressed in a traditional medicine context, (e.g., cold or heat) and the evaluation of pharmacological effects.
• Phenotyping research using empirical approaches, for example through new methods such as online pharmacology, big data, or artificial intelligence in order to understand changes in symptom phenotypes before and after medications have been used.
• Understanding clinical symptoms as defined in traditional medical systems using a combination of data mining approaches and clinical assessments in order to construct diagnostic and predictive models.
• The differences in symptom phenotypes as defined in a traditional medical system between healthy individuals and patients in the context of different biomedical and environmental factors (such as gender, age, and season), as well as quantitative or semi-quantitative methods for understanding different symptom phenotypes.
• The link of traditional concepts on the appearance and phenotype of specific plants, fungi, or animals and their medical uses based on these concepts.
• Approaches using artificial intelligence based on image recognition or 3D short video quantitative analysis of symptom phenotypes, as well as diagnostic models for diseases or functional states (if these are linked to pharmacological interventions).
• Text and data mining of pharmacological knowledge in effective clinical cases and for prescribing medications.
Manuscript types include Original Research and Review articles. Review articles need to provide concise and critical updates on Clinical Symptoms and Signs for Medication and Pharmacology as defined in the context of a TM and their biomedical investigation.
Please note the following:
1) Articles on clinical trials will be accepted for review only if they are randomized, double-blinded, and placebo controlled. Statistical power analysis or a justification of the sample size is mandatory as is a detailed chemical characterization of the study medication (see the ConPhyMP statement).
2) In silico studies like network analyses or docking studies are outside of the journal’s scope unless they are combined with an in vitro or in vivo analysis of the material under investigation.
3) All studies must use a therapeutically realistic dose level and the data must be reported on the basis of the amount of extract administered. Single-dose studies are not accepted unless they focus on a species/compound not yet studied in detail, and can be justified on specific ethical grounds (e.g. the 4R rule - Reduce, refine, replace – responsibility, see the Four Pillars).
4) A detailed chemical profile of the extract and pharmacognostic definition of the botanical drugs used is essential as defined in the ConPhyMP statement 2022 ((Front. Pharmacol. 13:953205).
5) This journal only covers therapies that involve a pharmacological intervention. Physical and other interventions (e.g. acupuncture) are not considered
6) All the manuscripts submitted to this project will be peer-reviewed and need to fully comply with the Four Pillars of Best Practice in Ethnopharmacology
Four Pillars of Best Practice in Ethnopharmacology (you can freely download the full version
here). Importantly, please ascertain that the ethnopharmacological context is clearly described (pillar 3d) and that the material investigated is characterized in detail (
pillars 2 a and b).
