Introduction: A significant proportion of severe asthma patients require oral corticosteroids (OCS) to maintain symptom control. Prolonged OCS predisposes patients to hypothalamicpituitary-adrenal axis suppression which can be lifethreatening. Biologic therapies are effective steroid-sparing options suitable for select severe asthma patients. We evaluated steroid tapering outcomes and adrenal function during biologic therapy in a tertiary severe asthma clinic. Results: A total of 43 patients were included. Median age was 66 years (interquartile range [IQR] 60–74), and 65% were male. Mepolizumab was the most used (17 patients), followed by benralizumab (15), tezepelumab (6), dupilumab (4), and omalizumab (1). Median baseline prednisolone dose was 10 mg (IQR 5–10). Median lowest dose achieved was 3 mg (IQR 0–3), sustained for at least 4 weeks in 90.7% of patients. Median reduction in prednisolone dose was 5 mg (IQR 5–7.25). In all, 42% of patients successfully discontinued maintenance steroids. Adrenal function was assessed using morning serum cortisol (n = 37) and/or SST (n = 28). Evidence of adrenal insufficiency was identified in 19 patients (44%), including 15 patients with failed SST and four with low morning cortisol suggestive of adrenal suppression. Morning serum cortisol was indeterminate in four patients. A total of 17 patients were referred to endocrinology. During steroid tapering, 11 asthma-related hospital admissions and eight emergency department presentations occurred, involving 10 patients. Conclusion Biologics facilitate the reduction of the OCS burden in severe asthma. Tertiary adrenal suppression is common during steroid tapering and requires prompt biochemical assessment and endocrinology referral. Structured monitoring of adrenal function is essential during biologicfacilitated steroid tapering in routine clinical practice.
Biological Products ; Steroids ; Asthma

OBJECTIVE: To assess the impact of long-term biologic therapy on metabolic biochemical parameters in moderate to severe plaque psoriasis patients. METHODS: The study included patients over 18 years old who had been treated by biological agents for at least 24 weeks for moderate to severe plaque psoriasis from Novermber 2015 to January 2024. According to the biological agents the patients used, they were divided into three groups: interleukin-17 (IL-17) inhibitor group, IL-23 and IL-12/23 inhibitor group and tumor necrosis factor-α (TNF-α) inhibitor group. The metabolic biochemical parameters of each group were evaluated and compared before and after the administration of the biologic therapies. RESULTS: A total of 174 patients with moderate to severe plaque psoriasis were included in the long-term treatment with biologics, including 127 males (73.00%), 47 females (27.00%), with a median age of 38.00 (31.50, 49.00) years and a median duration of psoriasis of 12.00 (10.00, 20.00) years. The median duration of biologic treatment was 61.00 (49.00, 96.25) weeks, ranging from 26 to 301 weeks. There were 101 patients in the IL-17 inhibitor group, 38 patients in the IL-23 and IL-12/23 inhibitor group, and 35 patients in the TNF-α inhibitor group. After long-term treatment with IL-17 inhibitors, no statistically significant changes were observed in body weight, body mass index (BMI), alanine aminotransferase (ALT), aspartate aminotransferase (AST), fasting glucose (GLU), total cholesterol (TC), triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C) compared with baseline measurements (P>0.05). However, low-density lipoprotein cholesterol (LDL-C) levels were significantly reduced [(2.90±0.75) mmol/L vs. (3.05±0.79) mmol/L, t=－2.100, P=0.038], while uric acid (UA) levels showed a significant increase [(401.13±99.13) μmol/L vs. (364.94±91.11) μmol/L, t=5.215, P < 0.001]. The group with normal UA levels before treatment showed a significant increase after long-term application of biological agents compared with before treatment [(370.69± 89.59) μmol/L vs. (324.66±64.50) μmol/L, t=5.856, P < 0.001]. Following long-term application of IL-23 and IL-12/23 inhibitors, no statistically significant differences were observed in body weight, BMI, ALT, AST, GLU, TC, TG, HDL-C and UA levels when compared with baseline measurements (P> 0.05). However, LDL-C levels exhibited a significant reduction from baseline [(2.85±0.74) mmol/L vs. (3.12±0.68) mmol/L, t=－2.082, P=0.045]. After long-term treatment with TNF-α inhibitor, there were no significant differences in body weight, BMI, ALT, AST, GLU, TC, TG, HDL-C, LDL-C and UA compared with baseline measurements (P>0.05). CONCLUSION Long-term application of IL-17 inhibitors in moderate to severe plaque psoriasis patients may result in elevated uric acid levels, particularly in patients with normal uric acid levels before treatment. The long-term use of IL-17 inhibitors, IL-23 inhibitors or IL-12/23 inhibitors might reduce LDL-C levels.
Humans ; Psoriasis/blood* ; Male ; Female ; Adult ; Middle Aged ; Interleukin-17/antagonists & inhibitors* ; Interleukin-23/antagonists & inhibitors* ; Tumor Necrosis Factor-alpha/antagonists & inhibitors* ; Interleukin-12/antagonists & inhibitors* ; Biological Therapy ; Biological Products/therapeutic use* ; Triglycerides/blood* ; Cholesterol, LDL/blood* ; Cholesterol, HDL/blood*

Chronic obstructive pulmonary disease (COPD) currently lacks effective treatments to halt disease progression, making the search for preventive and therapeutic drugs a pressing issue. Natural products, with their accessibility, affordability, and low toxicity, offer promising avenues. Investigating the pharmacological effects and related signaling mechanisms of active components from natural products on COPD animal models induced by various triggers has become an important focus. In animal models induced by cigarette smoke, cigarette smoke combined with lipopolysaccharide (LPS), air pollution, elastase, bacterial or viral infections, the active compounds of natural products, such as flavonoids, terpenoids, and phenolics, can exert anti-inflammatory, antioxidant, mucus-regulating, and airway remodeling-inhibiting effects through key signaling pathways including nuclear factor-erythroid 2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1), nuclear factor-kappa B (NF-κB), and mitogen-activated protein kinase (MAPK). These findings not only provide a theoretical basis for the clinical diagnosis and treatment of COPD but also point to new directions for future scientific research.
Pulmonary Disease, Chronic Obstructive/etiology* ; Animals ; Disease Models, Animal ; Biological Products/pharmacology* ; Humans ; NF-kappa B/metabolism* ; Flavonoids/pharmacology* ; Signal Transduction/drug effects* ; Anti-Inflammatory Agents/pharmacology* ; Heme Oxygenase-1/metabolism* ; Terpenes/pharmacology* ; Antioxidants/pharmacology* ; NF-E2-Related Factor 2/metabolism* ; Smoke/adverse effects* ; Phenols/therapeutic use*

Artificial intelligence (AI) has emerged as a transformative technology in accelerating drug discovery and development within natural medicines research. Natural medicines, characterized by their complex chemical compositions and multifaceted pharmacological mechanisms, demonstrate widespread application in treating diverse diseases. However, research and development face significant challenges, including component complexity, extraction difficulties, and efficacy validation. AI technology, particularly through deep learning (DL) and machine learning (ML) approaches, enables efficient analysis of extensive datasets, facilitating drug screening, component analysis, and pharmacological mechanism elucidation. The implementation of AI technology demonstrates considerable potential in virtual screening, compound optimization, and synthetic pathway design, thereby enhancing natural medicines' bioavailability and safety profiles. Nevertheless, current applications encounter limitations regarding data quality, model interpretability, and ethical considerations. As AI technologies continue to evolve, natural medicines research and development will achieve greater efficiency and precision, advancing both personalized medicine and contemporary drug development approaches.
Biological Products/pharmacology* ; Artificial Intelligence ; Humans ; Drug Discovery/methods* ; Machine Learning ; Deep Learning

Natural product-based drug combinations (NPDCs) present distinctive advantages in treating complex diseases. While high-throughput screening (HTS) and conventional computational methods have partially accelerated synergistic drug combination discovery, their applications remain constrained by experimental data fragmentation, high costs, and extensive combinatorial space. Recent developments in artificial intelligence (AI), encompassing traditional machine learning and deep learning algorithms, have been extensively applied in NPDC identification. Through the integration of multi-source heterogeneous data and autonomous feature extraction, prediction accuracy has markedly improved, offering a robust technical approach for novel NPDC discovery. This review comprehensively examines recent advances in AI-driven NPDC prediction, presents relevant data resources and algorithmic frameworks, and evaluates current limitations and future prospects. AI methodologies are anticipated to substantially expedite NPDC discovery and inform experimental validation.
Artificial Intelligence ; Biological Products/chemistry* ; Humans ; Drug Combinations ; Drug Discovery/methods* ; Machine Learning ; Algorithms

Stroke is the second leading cause of disability and mortality worldwide, imposing a substantial socioeconomic burden on individuals and healthcare systems. Annually, approximately 14 million people experience stroke, with ischemic stroke comprising nearly 85% of cases, of which 10% to 20% involve large vessel occlusions. Currently, recombinant tissue plasminogen activator (tPA) remains the only approved pharmacological intervention. However, its utility is limited due to a narrow therapeutic window and low recanalization rates, making it applicable to only a minority of patients. Therefore, there is an urgent need for novel therapeutic strategies, including pharmacological advancements and combinatory treatments. Small-molecule natural medicines, particularly those derived from traditional Chinese herbs, have demonstrated significant therapeutic potential in ischemic stroke management. These compounds exert multiple neuroprotective effects, such as antioxidation, anti-inflammatory action, and inhibition of apoptosis, all of which are critical in mitigating stroke-induced cerebral damage. This review comprehensively examines the pathophysiology of acute ischemic stroke (AIS) and highlights the recent progress in the development of small-molecule natural medicines as promising therapeutic agents for cerebral ischemic stroke.
Humans ; Ischemic Stroke/physiopathology* ; Animals ; Neuroprotective Agents/therapeutic use* ; Drugs, Chinese Herbal/chemistry* ; Biological Products/therapeutic use* ; Stroke/drug therapy*

Natural medicines (NMs) demonstrate distinct advantages in the clinical management of chronic diseases. Recent years have seen growing recognition of the gut microbiota's role in the efficacy and synergy of NMs, providing new impetus for elucidating the material basis and mechanisms of NMs and their path toward modernization. A fundamental question that has emerged is how NM-microbiota interactions integrate into the multi-target holistic mechanisms of NMs, the answer to which may also illuminate new avenues for drug discovery. Metabolic regulation via small-molecule metabolites has been increasingly implicated in host-microbe interaction. This review presents an integral metabolic perspective on NMs-microbiota interaction in host health and disease. It highlights the emerging understanding of gut microbiota-related metabolic signals implicated in NM components' local and systemic actions. Additionally, it discusses key issues and prospects related to drug development and the translational study of NMs.
Gastrointestinal Microbiome/drug effects* ; Humans ; Biological Products/metabolism* ; Animals

Plant-derived natural products have long been a vital source for developing therapeutic drugs. Wedelolactone (WDL), a coumestan isolated from Eclipta prostrata, Wedelia calendulacea, Wedelia chinensis, and Sphagneticola trilobata, demonstrates a broad spectrum of therapeutic potential, including anticancer, anti-inflammatory, anti-obesity, anti-myotoxic, antimicrobial, anti-diabetic, and tissue-protective activities. This review synthesizes information on the isolation, total synthesis, pharmacological activity, underlying mechanisms, and pharmacokinetic properties of WDL. Additionally, it offers insights into potential clinical applications and future drug discovery avenues utilizing WDL or its derivatives, either independently or in combination with other pharmaceuticals.
Coumarins/isolation & purification* ; Humans ; Animals ; Biological Products/chemical synthesis* ; Molecular Structure ; Plant Extracts/chemical synthesis* ; Wedelia/chemistry* ; Eclipta/chemistry*

Ribosomally synthesized and post-translationally modified peptides (RiPPs) constitute a vast and diverse family of bioactive peptides. These peptides, synthesized by ribosomes and subsequently modified by various tailoring enzymes, possess a wide chemical space. Among these modifications, radical S-adenosylmethionine (rSAM) enzymes employ unique radical chemistry to introduce a variety of novel peptide structures, which are crucial for their activity. This review examines the major types of modifications in RiPPs catalyzed by rSAM enzymes, incorporating recent advancements in protein structure analysis techniques and computational methods. Additionally, it elucidates the diverse catalytic mechanisms and substrate selectivity of these enzymes through an analysis of the latest crystal structures.
Protein Processing, Post-Translational ; S-Adenosylmethionine/chemistry* ; Ribosomes/metabolism* ; Peptides/metabolism* ; Biological Products/metabolism* ; Humans

Natural products (NPs) have long held a significant position in various fields such as medicine, food, agriculture, and materials. The chemical space covered by NPs is extensive but often underexplored. Therefore, high-throughput and efficient methodologies for the annotation and discovery of NPs are desired to address the complexity and diversity of NP-based systems. Mass spectrometry (MS) has emerged as a powerful platform for the annotation and discovery of NPs. MS databases provide vital support for the structural characterization of NPs by integrating extensive mass spectral data and sample information. Additionally, the released annotation methodologies, based on a variety of informatics tools, continuously improve the ability to annotate the structure and properties of compounds. This review examines the current mainstream databases and annotation methodologies, focusing on their advantages and limitations. Prospects for future technological advancements are then discussed in terms of novel applications and research objectives. Through a systematic overview, this review aims to provide valuable insights and a reference for MS-based NPs annotation, thereby promoting the discovery of novel natural entities.
Biological Products/chemistry* ; Mass Spectrometry/methods* ; Databases, Factual ; Drug Discovery/methods* ; Humans