The establishment of mouse models is critical for discovering the biological targets of tumorigenesis and cancer development, preclinical trials of targeted drugs, and formulation of personalized therapeutic regimens. Currently, the patient-derived xenograft (PDX) model is considered a reliable animal tumor model because of its ability to retain the characteristics of the primary tumor at the histopathological, molecular, and genetic levels, and to preserve the tumor microenvironment. The application of the PDX model has promoted in-depth research on tumors in recent years, focusing on drug development, tumor target discovery, and precise treatment of patients. However, there are still some common questions. This review introduces the latest research progress and common questions regarding tumors with high mortality rates, focusing on their application in targeted drug screening and the formulation of personalized medical strategies. The challenges faced, improvement methods, and future development of the PDX model in tumor treatment applications are also discussed. This article provides technical guidance and comprehensive expectations for anti-cancer drug screening and clinical personalized therapy.

In this comprehensive review, we delve into the evolution of drug delivery systems in reproductive medicine with a focus on the emerging role of exosomes, a class of extracellular vesicles. Exosomes offer unique advantages in overcoming these challenges due to their inherent biocompatibility, stability, and ability to facilitate targeted delivery. This review provides a detailed examination of exosome biogenesis and their function in cellular communication, setting the stage for understanding their potential as drug delivery vehicles. We explore the mechanisms through which exosomes can be loaded with small molecule drugs and the benefits they offer over synthetic nanoparticles. The review highlights groundbreaking case studies that illustrate the successful application of exosome-mediated drug delivery in reproductive health, including enhancing fertility treatments, supporting gamete and embryo development, and facilitating maternal-fetal communication. This study aims to provide a precise understanding of how exosomal drug delivery can revolutionize treatments for reproductive health disorders, paving the way for future therapeutic applications. Lastly, we touch upon the promising therapeutic implications of exosomal delivery for proteins and genes, offering a window into future treatments for reproductive health disorders.

Bipolar disorder (BD) affects 1% of the global population. BD is a group of chronic psychiatric disorders characterized by recurrent manic or hypomanic episodes that may alternate with depressive episodes. Given the current diagnostic modalities, accurately diagnosing BD, particularly distinguishing it from unipolar depression (UD), is challenging. Biomarkers have emerged as potent instruments for establishing objective diagnostic criteria for BD, and their identification, which reflects the pathophysiological processes of BD, can facilitate the precise diagnosis of the disorder. In this review, the search terms “BD” and “diagnosis” or “biomarker” were used as the key search syntax. In total, 110 studies were included. This review systematically examines the research in the field and summarizes current studies on biomarkers of BD in omics and neuroimaging. We hope that this review will benefit research aimed at establishing objective diagnostic criteria for BD and developing novel therapeutic interventions.

This literature review investigates the mechanisms of resistance to human epidermal growth factor receptor 2 (HER2)-targeted therapies in HER2⁺ breast cancer, a subtype that accounts for approximately 20% of breast cancer cases. Despite the effectiveness of treatments such as trastuzumab and lapatinib, many patients experience either primary or acquired resistance, leading to treatment failure. The review systematically categorizes various resistance mechanisms, including the role of receptor activator of nuclear factor kappaΒ (RANK) expression, which has been shown to activate the nuclear factor kappaB (NF-κB) pathway, promoting cell survival and contributing to resistance. Other mechanisms include the activation of alternative signaling pathways, such as the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) pathway, and the involvement of tumor-associated fibroblasts, which can drive resistance through receptor tyrosine kinase (RTK) activation. Additionally, the review highlights the importance of understanding these mechanisms to inform the development of novel therapeutic strategies. By identifying potential biomarkers and therapeutic targets, the review suggests that combining HER2 inhibitors with agents that target resistance pathways may enhance treatment efficacy and improve patient outcomes. Overall, this review underscores the complexity of HER2⁺ breast cancer treatment and the need for continued research to overcome resistance challenges.

Flavonoids, the key active compounds in Epimedii Folium, have both protective and toxic effects on the liver. Their hepatoprotective effects are associated with reducing lipid accumulation and oxidative stress, which contribute to the management of various liver conditions. In contrast, the mechanisms driving Epimedii Folium-induced hepatotoxicity are less understood but likely involve oxidative stress and pyroptosis. Pharmacokinetic studies, especially on icaritin, indicate that it undergoes isopentenyl dehydrogenation, glycosylation, and glucuronidation in vivo, contributing to its pharmacological effects. However, intermediate metabolites of icaritin may interact with biomolecules, potentially leading to liver toxicity. This review offers a detailed examination of the dual effects of Epimedii Folium flavonoids on liver function, emphasizing recent discoveries in their hepatoprotective and hepatotoxic pathways. We also summarize and discuss the pharmacokinetics of these flavonoids, highlighting how their metabolism affects therapeutic efficacy and toxicity. Lastly, we propose strategies to mitigate liver injury, providing new perspectives on the safe use of Epimedii Folium.

Lysosomal diseases (LDs) are a group of rare inherited disorders belonging to inborn metabolism errors. LDs are characterized by the excessive storage of undegraded substrates, most often due to the enzymatic deficiency resulting from disease-causing gene variants. LDs lead to dysregulated cellular pathways and imbalanced molecular homeostasis and can affect multiple organs and tissues. Despite being rare, LDs account for a significant incidence when considered collectively. Due to complex molecular and genetic fingerprints, considerable challenges in LD management must be overcome. Diagnosis can be significantly delayed due to the broad and nonspecific clinical manifestations and the lack of specific biomarkers. Available treatments fail to fully stop the disease progression and can alter the disease's typical phenotypes with novel manifestations. Therefore, a paradigm shift is crucial to better understand LDs and provide actionable insights. Herein, we comprehensively review the literature to demonstrate that multi-omics approaches are promising for pathophysiology elucidation, biomarker discovery, and precision therapy in LDs. We recommend adopting longitudinal study designs integrated with a multi-omics-empowered framework to facilitate mechanistic delineation, biomarker discovery, and treatment development. Relevant approaches exploring the association between LDs and common neurodegenerative disorders are also discussed, paving a potential path for improved therapeutic development and ultimately improving the patient's quality of life.

Iron is an essential trace element in the human body, crucial in maintaining normal physiological functions. Recent studies have identified iron ions as a significant factor in initiating the ferroptosis process, a novel mode of programmed cell death characterized by iron overload and lipid peroxide accumulation. The iron metabolism pathway is one of the primary mechanisms regulating ferroptosis, as it maintains iron homeostasis within the cell. Numerous studies have demonstrated that abnormalities in iron metabolism can trigger the Fenton reaction, exacerbating oxidative stress, and leading to cell membrane rupture, cellular dysfunction, and damage to tissue structures. Therefore, regulation of iron metabolism represents a key strategy for ameliorating ferroptosis and offers new insights for treating diseases associated with iron metabolism imbalances. This review first summarizes the mechanisms that regulate iron metabolic pathways in ferroptosis and discusses the connections between the pathogenesis of various diseases and iron metabolism. Next, we introduce natural and synthetic small molecule compounds, hormones, proteins, and new nanomaterials that can affect iron metabolism. Finally, we provide an overview of the challenges faced by iron regulators in clinical translation and a summary and outlook on iron metabolism in ferroptosis, aiming to pave the way for future exploration and optimization of iron metabolism regulation strategies.

Brain organoid-on-chip platforms have emerged as groundbreaking tools in neural disease modeling and drug discovery, offering a unique and highly accurate simulation of human organ physiology and function compared with traditional cell culture systems. This technology is a harmonious fusion of organ-on-a-chip and organoid culture technologies, leveraging their strengths to provide the most realistic in vitro replication of the in vivo environment, both physically and biologically. As both technologies continue to advance rapidly, this platform is highly promising in vitro platform for disease modeling. In this review, we summarize the historical developments, recent advancements, limitations, and future prospects of brain organoid-on-chip technology, aiming to illuminate the transformative potential of this platform in advancing our understanding and treatment of neural diseases.

In general, bioassay-guided fractionation and isolation of bioactive constituents from botanical materials frequently ended up with the reward of a single compound. However, botanical materials typically exert their therapeutic actions through multi-pathway effects due to the intrinsic complex nature of chemical constituents. In addition, the content of bioactive compounds in botanical materials is largely dependent on humidity, temperature, soil, especially geographical origins, from which rapid and accurate identification of plant materials is pressingly needed. These long-standing obstacles collectively impede the deep exploitation and application of these versatile natural sources. To address the challenges, a new paradigm integrating biogravimetric analyses and machine learning-driven origin classification (BAMLOC) was developed. The biogravimetric analyses are based on absolute qHNMR quantification and in vivo zebrafish model-assisted activity index calculation, by which bioactive substance groups jointly responsible for the bioactivities in all fractions are pinpointed before any isolation effort. To differentiate origin-different botanical materials varying in the content of bioactive substance groups, principal component analysis, linear discriminant analysis, and hierarchical cluster analysis in conjunction with supervised support vector machine are employed to classify and predict production areas based on the detection of volatile organic compounds by E-nose and gas chromatography-mass spectrometry (GC-MS). Expanding BAMLOC to Codonopsis Radix enables the identification of polyacetylenes and pyrrolidine alkaloids as the bioactive substance group for immune restoration effect and accurately determines the origins of plants. This study advances the toolbox for the discovery of bioactive compounds from complex mixtures and lays a more definitive foundation for the in-depth utilization of botanical materials.

Cardiac troponin I (cTnI), a widely used biomarker for assessing cardiovascular risk, can provide a window for the evaluation of drug-induced myocardial injury. Label-free biosensors are promising candidates for detecting cell secretomes, since they do not require labor-intensive processes. In this work, a label-free electrochemical aptasensor is developed for in situ monitoring of cardiac cell secretomes in cell culture media based on target-induced strand displacement. The aptasensing system contains an aptamer-functionalized signal nanoprobe facing trimetallic metal-organic framework nanosheets and a gold nanoparticle-based detection working electrode modified with DNA nanotetrahedron-based complementary DNA for indirect target detection. The signal nanoprobes (termed CAHA) consisted of copper-based metal-organic frameworks, AuPt nanoparticles, horseradish peroxidase, and an aptamer. When the aptasensor is exposed to cardiac cell secretomes, cTnI competitively binds to the aptamer, resulting in the release of signal nanoprobes from the biorecognition interface and electrochemical signal changes. The aptasensor exhibited rapid response times, a low detection limit of 0.31 pg/mL, and a wide linear range of 0.001–100 ng/mL. We successfully used this aptasensor to measure cTnI concentrations among secreted cardiac markers during antitumor drug treatment. In general, aptasensors can be used to monitor a variety of cardiac biomarkers in the evaluation of cardiotoxicity.

Melanoma is characterized by high malignancy, ranking the third among skin malignancies, and is associated with lack of specific treatment options and poor prognosis. Therefore, the development of effective therapies for melanoma is imperative. A critical challenge in addressing subcutaneous disease lies in overcoming the skin barrier. In this study, we engineered a microneedle (MN) system that integrates chemotherapy, photothermal therapy (PTT), and targeted therapy to enhance anti-tumor efficacy while effectively penetrating the skin barrier. In vitro studies have demonstrated that the MN drug delivery system (DDS) can effectively penetrate the stratum corneum of the skin, deliver therapeutics to subcutaneous tumor sites, and establish a drug reservoir at these locations to exert anti-tumor effects. Cellular experiments indicated that the engineered PTT chemotherapy-targeted MNs can be internalized by tumor cells, exhibiting enhanced cytotoxicity against them. In vivo pharmacological investigations revealed that the combination of PTT and chemotherapy delivered via this MN DDS produced synergistic anti-tumor effects, achieving a tumor inhibition rate of up to 98.15%. This in situ DDS minimizes involvement with other organs, significantly reducing chemotherapy-related side effects. In summary, the PTT chemotherapy-targeted MNs developed in this study demonstrate promising application potential by enhancing anti-tumor efficacy while minimizing adverse effects.

Immune complex deposition is a critical factor in early renal damage associated with lupus nephritis (LN), and targeting plasma cell aggregation offers a promising therapeutic strategy. Ginsenoside compound K (i.e., 20-O-β-d-glucopyranosyl-20(S)-protopanaxadiol) (CK), a derivative of ginsenoside, has indicated significant potential in alleviating renal damage in lupus-prone mice, potentially by modulating B cell dynamics in response to endoplasmic reticulum (ER) stress. In this study, CK (20 or 40 mg/kg) was orally administered to female MRL/lpr mice for 10 weeks. The effects of CK on B cell subpopulations, renal function, and histopathological changes were evaluated. Single-cell ribonucleic acid sequencing was employed to analyze gene expression profile and pseudotime trajectories during B cell-mediated renal injury. Additionally, in vitro B cell assays were conducted to explore the role of the sirtuin-1 (SIRT1)-X-box binding protein 1 (XBP1) axis in ER stress. Our findings demonstrated that CK effectively reduced anti-double stranded DNA (dsDNA) antibody levels, alleviated systemic inflammation, improved renal function, and facilitated the clearance of deposited immune complexes. CK likely suppressed the unfolded protein response (UPR), delaying the differentiation of renal-activated B cells into plasma cells. It promoted B cell-specific SIRT1 activation and inhibited the splicing of XBP1 into its active form, XBP1s. CK also restored ER morphology by interacting with calmodulin (CALM) to maintain ER calcium storage, reinforcing SIRT1 functional integrity and promoting XBP1 deacetylation, thereby limiting plasma cell differentiation. In conclusion, CK mitigates plasma cell accumulation in the renal microenvironment by preventing SIRT1-mediated XBP1 splicing, offering a potential therapeutic approach for LN.

Mesangial cell proliferation is an early pathological indicator of diabetic nephropathy (DN). Growing evidence highlights the pivotal role of paired-related homeobox 1 (Prrx1), a key regulator of cellular proliferation and tissue differentiation, in various disease pathogenesis. Notably, Prrx1 is highly expressed in mesangial cells under DN conditions. Both in vitro and in vivo studies have demonstrated that Prrx1 overexpression promotes mesangial cell proliferation and contributes to renal fibrosis in db/m mice. Conversely, Prrx1 knockdown markedly suppresses hyperglycemia-induced mesangial cell proliferation and mitigates renal fibrosis in db/db mice. Mechanistically, Prrx1 directly interacts with the Yes-associated protein 1 (YAP) promoter, leading to the upregulation of YAP expression. This upregulation promotes mesangial cell proliferation and exacerbates renal fibrosis. These findings emphasize the crucial role of Prrx1 upregulation in high glucose-induced mesangial cell proliferation, ultimately leading to renal fibrosis in DN. Therefore, targeting Prrx1 to downregulate its expression presents a promising therapeutic strategy for treating renal fibrosis associated with DN.

Renal tubular injury has emerged as a critical factor in the progression of diabetic kidney disease (DKD). Given renal tubules' high mitochondrial density and susceptibility to mitochondrial dysregulation and ferroptosis, targeting these pathways could offer therapeutic potential. Metformin (MET), a first-line therapy for type 2 diabetes mellitus (T2DM), exerts reno-protective effects by improving mitochondrial function and attenuating fibrosis; however, its role in regulating ferroptosis in DKD remains unclear. This study aimed to investigate the role of MET in modulating mitophagy and ferroptosis in diabetic kidneys. In diabetic mouse models, MET notably alleviated tubular injury by promoting mitophagy and reducing ferroptosis, as shown by increasing levels of phosphatase and tensin homolog (PTEN)-induced putative kinase 1 (PINK1) and Parkin, while decreased levels of malondialdehyde (MDA) and iron content. Mechanistically, MET downregulated the hypoxia-inducible factor-1alpha (HIF-1α)/myo-inositol oxygenase (MIOX) signaling axis in renal tubular epithelial cells (RTECs), thereby restoring mitophagy and inhibiting ferroptosis. These findings demonstrate that MET mitigates diabetic renal injury by promoting mitophagy and countering ferroptosis via suppressing the HIF-1α/MIOX pathway, highlighting its potential as a therapeutic intervention for halting DKD progression.

Rauvolfia serpentina (L.) Benth. Ex Kurz is a greatly appreciated medicinal plant, well-known for its therapeutic benefits in traditional medicine, particularly in Ayurveda, where the roots and whole plant are used to treat a variety of ailments. However, studies focusing on R. serpentina seeds are relatively scarce. Hence, the present study provides a novel approach by analysing the seed oil of R. serpentina extracted using the supercritical-carbon dioxide-fluid-extraction (SCFE) technique. The research employed advanced analytical methods including gas-chromatography with flame ionization detector (GC-FID), gas-chromatography-tandem mass spectrometry (GC-MS/MS), and high performance thin layer chromatography (HPTLC) to characterise the chemical composition of the extracted oil. Functional moieties were evaluated by Fourier transform infrared spectroscopy (FT-IR), while proton nuclear-magnetic-resonance (¹H NMR) spectroscopy was utilised to identify the phytometabolites as well as to assess the physico-chemical parameters. The anti-microbial potential of the supercritically extracted oil was demonstrated through its activity against Klebsiella pneumoniae. The inhibitory effects on K. pneumoniae were quantified using the broth microdilution method, showing activity at both minimum inhibitory concentrations (MIC₅₀ and MIC₉₀). Furthermore, the oil was found to be non-genotoxic, as demonstrated by the Ames assay, which showed no mutagenic effects against S. typhimurium and E. coli WP2 uvrA. Since previous reports on R. serpentina seeds and their novel contribution in the field of pharmaceutics are rather limited, the present study is of utmost importance. The study may pave the way for future investigations into the therapeutic potentials of R. serpentina seeds.

Opuntia dillenii (Ker Gawl.) Haw., which has long been prized for its therapeutic virtues, has shown promise in treating hyperglycemic conditions. This study investigates the chemical composition and antihyperglycemic capabilities of aqueous extracts from O. dillenii’s pulp and peel, as well as their effects on major carbohydrate metabolism enzymes. Significant changes in the composition of bioactive chemicals between pulp and peel were discovered using high performance liquid chromatography with diode-array detector (HPLC-DAD), with high amounts of p-coumaric acid, flavone, quercetin, and kaempferol. Key compounds included gallic acid, vanillic acid, p-coumaric acid, 3-hydroxy flavone, quercetin, cinnamic acid, kaempferol, and flavone. p-coumaric acid was highest in the pulp (298.71 ± 0.43 mg/100 g) and peel (38.18 ± 1.08 mg/100 g), while flavone was higher in the peel (120.03 ± 0.26 mg/100 g). In vitro enzyme inhibition tests showed that the extracts successfully inhibited pancreatic α-amylase, lipase, and intestine α-glucosidase. Molecular docking experiments confirmed the enzyme-binding affinity of these drugs, demonstrating interactions stronger than the conventional medication acarbose. In vivo testing on healthy and diabetic rats demonstrated the extracts' ability to lower blood glucose levels without harm, even at high doses (up to 3,000 mg/kg). These findings indicate that O. dillenii pulp and peel extracts contain bioactive chemicals with promise as natural antidiabetic drugs, necessitating additional research for therapeutic applications.

The quality of traditional Chinese medicine (TCM) prescriptions (TCMPs) is critical to clinical efficacy; however, evaluating their consistency and identifying sources of variability remain challenging. This study proposes an integrated strategy to assess the quality of 100 widely sold TCMPs. A “one-for-all” chromatographic method was employed to analyze 645 sample batches. This large-scale data collection enabled statistical evaluations, such as hierarchical cluster analysis (HCA) and similarity heatmap, to identify quality inconsistencies. The introduction of a TCM-specific mass spectrometry (MS) database allowed for rapid, automated annotation of chemicals across 100 prescriptions and facilitated the tracing of raw material sources. Results indicate that 19% of prescriptions exhibited chemical inconsistencies, which are associated with high market value, low pricing, and substantial price disparities. The MS database allowed rapid annotation of 761 and 673 compounds in positive and negative modes, respectively, in 100 TCMPs, with 73 prescriptions reported for the first time. The tracing efforts succeeded in identifying >40% of the raw material sources for 51 prescriptions. P93 (Yinianjin (YNJ)) is a case in which the chromatographic profiles from three manufacturers displayed inconsistencies. Analysis using the database traced divergent peaks to Rhei Radix et Rhizoma (RRER). Verification with self-prepared samples confirmed that manufacturers utilized three distinct botanical sources. This integrated strategy provides a scalable framework for quality control in TCMPs.

Computational approaches for predicting drug-target interactions (DTIs) are pivotal in advancing drug discovery. Current methodologies leveraging heterogeneous networks often fall short in fully integrating both local and global network information. To comprehensively consider network information, we propose DHGT-DTI, a novel deep learning-based approach for DTI prediction. Specifically, we capture the local and global structural information of the network from both neighborhood and meta-path perspectives. In the neighborhood perspective, we employ a heterogeneous graph neural network (HGNN), which extends Graph Sample and Aggregate (GraphSAGE) to handle diverse node and edge types, effectively learning local network structures. In the meta-path perspective, we introduce a Graph Transformer with residual connections to model higher-order relationships defined by meta-paths, such as “drug-disease-drug”, and use an attention mechanism to fuse information across multiple meta-paths. The learned features from these dual perspectives are synergistically integrated for DTI prediction via a matrix decomposition method. Furthermore, DHGT-DTI reconstructs not only the DTI network but also auxiliary networks to bolster prediction accuracy. Comprehensive experiments on two benchmark datasets validate the superiority of DHGT-DTI over existing baseline methods. Additionally, case studies on six drugs used to treat Parkinson’s disease not only validate the practical utility of DHGT-DTI but also highlight its broader potential in accelerating drug discovery for other diseases.

Efficient drug response prediction is crucial for reducing drug development costs and time, but current computational models struggle with limited experimental data and out-of-distribution issues between in vitro and in vivo settings. To address this, we introduced drug response prediction meta-learner (metaDRP), a novel few-shot learning model designed to enhance predictive accuracy with limited sample sizes across diverse drug-tissue tasks. metaDRP achieves performance comparable to state-of-the-art models in both genomics of drug sensitivity in cancer (GDSC) drug screening and in vivo datasets, while effectively mitigating out-of-distribution problems, making it reliable for translating findings from controlled environments to clinical applications. Additionally, metaDRP’s inherent interpretability offers reliable insights into drug mechanisms of action, such as elucidating the pathways and molecular targets of drugs like epothilone B and pemetrexed. This work provides a promising approach to overcoming data scarcity and out-of-distribution challenges in drug response prediction, while promoting the integration of few-shot learning in this field.