Assessment Of Drug Efficacy Research Articles

Magnetically Controlled Transport of Nanoparticles in Solid Tumor Tissues and Porous Media Using a Tumor-on-a-Chip Format

This study addresses issues in developing spatially controlled magnetic fields for particle guidance, synthesizing biocompatible and chemically stable MNPs and enhancing their specificity to pathological cells through chemical modifications, developing personalized adjustments, and highlighting the potential of tumor-on-a-chip systems, which can simulate tissue environments and assess drug efficacy and dosage in a controlled setting. The research focused on two MNP types, uncoated magnetite nanoparticles (mMNPs) and carboxymethyl dextran coated superparamagnetic nanoparticles (CD-SPIONs), and evaluated their transport properties in microfluidic systems and porous media. The original uncoated mMNPs of bimodal size distribution and the narrow size distribution of the fractions (23 nm and 106 nm by radii) were demonstrated to agglomerate in magnetically driven microfluidic flow, forming a stable stationary web consisting of magnetic fibers within 30 min. CD-SPIONs were demonstrated to migrate in agar gel with the mean pore size equal to or slightly higher than the particle size. The migration velocity was inversely proportional to the size of particles. No compression of the gel was observed under the magnetic field gradient of 40 T/m. In the brain tissue, particles of sizes 220, 350, 820 nm were not penetrating the tissue, while the compression of tissue was observed. The particles of 95 nm size penetrated the tissue at the edge of the sample, and no compression was observed. For all particles, movement through capillary vessels was observed.

Assessment of tuberculosis drug efficacy using preclinical animal models and in vitro predictive techniques

Tuberculosis (TB) killed approximately 1.3 million people in 2022 and remains a leading cause of death from the bacteria Mycobacterium tuberculosis (M.tb); this number of deaths was surpassed only by COVID-19, caused by the SARS-CoV-2 virus. The alarming emergence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) M.tb strains presents an urgent need for effective new treatments. Our study aimed to determine the synergistic effects of antibiotic combinations against M.tb. Using a high-throughput in vitro checkerboard assay, we evaluated the interactions of Bedaquiline (BDQ) and other antibiotics including Capreomycin (CAP), Linezolid (LIN), and Sutezolid (SUT) against M.tb H37Rv. BDQ and CAP demonstrated in vitro enhanced effect, which prompted further investigation in vivo using the murine low dose aerosol (LDA) model. After aerosol challenge with M.tb, C57BL/6 mice were treated with BDQ, CAP, or their combination, starting 28 days post-infection. The antimicrobial treatment lasted four weeks, and the bacterial burden in lung and spleen tissues was assessed at the end of treatment. At 4 weeks post-treatment, a significant reduction in bacterial load was observed within the lungs and spleens of mice given BDQ alone or given as a BDQ/CAP combination compared to the untreated group. In contrast, CAP monotherapy led to an increase in bacterial load within the lung and no significant difference in bacterial burden in the spleen in comparison to the untreated mice. These results were confirmed in the guinea pig model of TB, where both BDQ and the BDQ/CAP combination treatment led to a decrease in bacterial burden in the lung and spleen, whereas CAP had no significant effect on bacterial burden at the 4-week post treatment timepoint. We next determined whether there may be differences in vitro with the BDQ/CAP combination against M.tb lineages 1, 2 and 4. We determined that in vitro enhanced effect was not observed in some representative strains of M.tb lineage 4, indicating variability in drug effectiveness across M.tb lineages. This research underscores the complexity of TB treatment and the critical need for innovative approaches to combat this global health threat.

Microfluidic Technologies in Advancing Cancer Research

This review explores the significant role of microfluidic technologies in advancing cancer research, focusing on the below key areas: droplet-based microfluidics, organ-on-chip systems, paper-based microfluidics, electrokinetic chips, and microfluidic chips for the study of immune response. Droplet-based microfluidics allows precise manipulation of cells and three-dimensional microtissues, enabling high-throughput experiments that reveal insights into cancer cell migration, invasion, and drug resistance. Organ-on-chip systems replicate human organs to assess drug efficacy and toxicity, particularly in the liver, heart, kidney, gut, lung, and brain. Paper-based microfluidics offers an alternative approach to accomplish rapid diagnostics and cell- and tissue-based bioassays. Electrokinetic microfluidic chips offer precise control over cell positioning and behavior, facilitating drug screening and cellular studies. Immune response studies leverage real-time observation of interactions between immune and cancer cells, supporting the development of immunotherapies. These microfluidic advances are paving the way for personalized cancer treatments while addressing challenges of scalability, cost, and clinical integration.

The wound healing of deep partial-thickness burn in Bama miniature pigs is accelerated by a higher dose of hUCMSCs

BackgroundDeep partial-thickness burns have a significant impact on both the physical and mental health of patients. Our previous study demonstrated human Umbilical Cord Mesenchymal stem cells (hUCMSCs) could enhance the healing of severe burns in small animal burn models, such as rats. Furthermore, our team has developed a deep partial-thickness burn model in Bama miniature pigs, which can be utilized for assessing drug efficacy in preclinical trials for wound healing. Therefore, this study further determine the optimal dosage of hUCMSCs in future clinical practice by comparing the efficacy of low-to-high doses of hUCMSCs on deep partial-thickness burn wounds in Bama miniature pigs.Materials and methodsThe male Bama miniature pigs (N = 8, weight: 23–28 kg and length: 71–75 cm) were used to establish deep partial-thickness burn models, which used a continuous pressure of 1 kg and contact times of 35 s by the invented electronic burn instrument at 100℃ to prepare 10 round burn wounds with diameter of 5 cm according to our previous report. And then, 0 × 10^7, 1 × 10^7, 2 × 10^7, 5 × 10^7 and 1 × 10^8 doses of hUCMSCs were respectively injected into burn wounds of their corresponding groups. After treatment for 7, 14 and 21 days, the burned wound tissues were obtained for histological evaluation, including HE staining for histopathological changes, immunohistochemistry for neutrophil (MPO+) infiltration and microvessel (CD31+) quantity, as well as Masson staining for collagen deposition. The levels of inflammatory factors TNF-α, IL-1β, IL-10 and angiogenesis factors angiopoietin-2 (Ang-2), vascular endothelial growth factor (VEGF), as well as collagen type-I/type-III of the wound tissues were quantified by ELISA.ResultsAll of doses hUCMSCs can significantly increase wound healing rate and shorten healing time of the deep partial-thickness burn pigs in a dose-dependent manner. Furthermore, all of doses hUCMSCs can significantly promote epithelialization and decreased inflammatory reaction of wound, including infiltration of inflammatory cells and levels inflammatory factors. Meanwhile, the amounts of microvessel were increased in all of doses hUCMSCs group than those in the burn group. Furthermore, the collagen structure was disordered and partially necrotized, and ratios of collagen type-I and type-III were significantly decreased in burn group (4:1 in normal skin tissue), and those of all hUCMSCs groups were significantly improved in a dose-dependent manner. In a word, 1 × 10^8 dose of hUCMSCs could regenerate the deep partial-thickness burn wounds most efficaciously compared to other dosages groups and the burn group.ConclusionThis regenerative cell therapy study using hUCMSCs demonstrates the best efficacy toward a high dose, that is dose of 1 × 10^8 of hUCMSCs was used as a reference therapeutic dose for treating 20 cm2 deep partial-thickness burns wound in future clinical practice.Graphical abstract

Flavonoids attenuate inflammation of HGF and HBMSC while modulating the osteogenic differentiation based on microfluidic chip

BackgroundWhen inflammation occurs in periodontal tissues, a dynamic cellular crosstalk interacts between gingival fibroblasts and bone marrow mesenchymal stem cells (BMSCs), which plays a crucial role in the biological behaviour and differentiation of the cells. Recently, flavonoids are increasingly recognized for their therapeutic potential in modulating inflammation and osteogenic differentiation. Owing to their varied molecular structures and mechanisms, there are more needs that flavonoid compounds should be identified by extensive screening. However, current drug research mostly relies on static, single-type cell cultures. In this study, an innovative bionic microfluidic chip system tailored for both soft and hard tissues was developed to screen for flavonoids suitable for treating periodontitis.MethodsThis study developed a microfluidic system that bionically simulates the soft and hard structures of periodontal tissues. Live/dead staining, reactive oxygen species (ROS) staining, and RT-qPCR analysis were employed. These techniques evaluated the effects of flavonoid compounds on the levels of inflammatory factors and ROS contents in HGF and HBMSC under LPS stimulation. Additionally, the impact of these compounds on osteogenic induction in HBMSC and the exploration of the underlying mechanisms were assessed.ResultsThe microfluidic chip used in this study features dual chambers separated by a porous membrane, allowing cellular signal communication via bioactive factors secreted by cells in both layers under perfusion. The inflammatory response within the chip under LPS stimulation was lower compared to individual static cultures of HGF and HBMSC. The selected flavonoids-myricetin, catechin, and quercetin-significantly reduced cellular inflammation, decreased ROS levels, and enhanced osteogenic differentiation of BMSCs. Additionally, fisetin, silybin, and icariside II also demonstrated favorable outcomes in reducing inflammation, lowering ROS levels, and promoting osteogenic differentiation through the Wnt/β-catenin pathway.ConclusionsThe bionic microfluidic chip system provides enhanced capabilities for drug screening and evaluation, delivering a more precise assessment of drug efficacy and safety compared to traditional in vitro methods. This study demonstrates the efficacy of flavonoids in influencing osteogenic processes in BMSCs primarily through the Wnt/β-catenin pathway. These results uncover the potential of flavonoids as therapeutic medicine for treating periodontitis, meriting further research and development.Graphical

Enhanced Plaque Stabilization Effects of Alirocumab - Insights From Artificial Intelligence-Aided Optical Coherence Tomography Analysis of the Alirocumab for Thin-Cap Fibroatheroma in Patients With Coronary Artery Disease Estimated by Optical Coherence Tomography (ALTAIR) Study.

Proprotein convertase subtilisin/kexin type 9 inhibitors stabilize vulnerable plaque, reducing cardiovascular events. However, manual optical coherence tomography (OCT) analysis of drug efficacy is challenging because of signal attenuation within lipid plaques. Twenty-four patients with thin-cap fibroatheroma were prospectively enrolled and randomized to receive alirocumab (75 mg every 2 weeks) plus rosuvastatin (10 mg/day) or rosuvastatin (10 mg/day) alone. OCT images at baseline and 36 weeks were analyzed manually and with artificial intelligence (AI)-aided software. AI-aided OCT analysis showed significantly greater percentage changes in the alirocumab+rosuvastatin vs. rosuvastatin-alone group in fibrous cap thickness (FCT; median [interquartile range] 212.3% [140.5-253.5%] vs. 88.6% [63.0-119.6%]; P=0.006) and lipid volume (median [interquartile range] -30.8% [-51.8%, -16.6%] vs. -2.1% [-21.6%, 4.3%]; P=0.015). Interobserver reproducibility for changes in minimum FCT and lipid index was relatively low for manual analysis (interobserver intraclass correlation coefficient [ICC] 0.780 and 0.499, respectively), but high for AI-aided analysis (interobserver ICC 0.999 and 1.000, respectively). Agreements between manual and AI-aided OCT analyses of FCT and the lipid index were acceptable (concordance correlation coefficients 0.859 and 0.833, respectively). AI-aided OCT analysis objectively showed greater plaque stabilization of adding alirocumab to rosuvastatin. Our results highlight the benefits of a fully automated AI-assisted approach for assessing drug efficacy, offering greater objectivity in evaluating serial changes in plaque stability vs. conventional OCT assessment.

Genotyping methods to distinguish Plasmodium falciparum recrudescence from new infection for the assessment of antimalarial drug efficacy: an observational, single-centre, comparison study

Distinguishing Plasmodium falciparum recrudescence from new infections is crucial for the assessment of antimalarial drug efficacy against Pfalciparum. We aimed to compare the efficacy of different genotyping methods to assess their effect on drug efficacy estimates, particularly in patients from high-transmission settings with polyclonal infections. In this head-to-head comparison study, we compared five different genotyping methods currently used: fast capillary electrophoresis (F-CE) using msp1, msp2, and glurp; high-resolution capillary electrophoresis (H-CE) using msp1, msp2, and glurp; H-CE using microsatellites; targeted amplicon deep sequencing (TADS) using single nucleotide polymorphism (SNP)-rich markers; and high-resolution melting (HRM) analysis using msp1 and msp2. We assessed their sensitivity in detecting minority clones in polyclonal infections, their reproducibility, and the genetic diversity of the markers used. Our study used four well characterised Pfalciparum laboratory strains mixed in varying ratios, and 20paired samples collected from an in-vivo clinical trial. The experiments were performed at the Swiss Tropical and Public Health Institute in Basel, Switzerland between May 5, 2020, and Aug 23,2021. H-CE using msp1 and msp2 and TADS revealed the highest sensitivity in detecting minority clones (up to ratios of 1:100 for H-CE and 50:1:1:1 for TADS in the FCB1:HB3 and 3D7:K1:HB3:FCB1 laboratory strain mixtures, respectively), highest reproducibility (intra-assay: 99% and 91% for H-CE and TADS, respectively; inter-assay: 98% and 92% for H-CE and TADS, respectively), and highest genetic diversity in the used markers (up to 36and32unique genotypes in 20paired samples for H-CE using msp2 and TADS using cpmp, respectively). Microsatellites assessed by H-CE had a lower genetic diversity compared with msp1, msp2, and glurp assessed by H-CE and the SNP-rich markers assessed by TADS, with a maximum of 13unique genotypes, and some genotypes having allelic frequencies larger than 30%.Markers used by TADS gave the most consistent results in distinguishing recrudescence from new infection across all methods (in 18of 20pairs of samples vs 15of 20pairs for H-CE). WHO currently recommends replacing glurp with microsatellites. However, in this study, the replacement of glurp with microsatellites did not change the genotyping outcome, probably due to the lower genetic diversity of microsatellites. More studies with large sample sizes are required to identify the most suitablemicrosatellites that could replace glurp. Our study indicates that TADS should be considered the gold standardfor genotyping to distinguish recrudescence from new infection, and that it should be used to validate other methods. Swiss Tropical and Public Health Institute.

The intervention mechanism of Tanshinone IIA in alleviating neuronal injury induced by HMGB1 or TNF-α-mediated microglial activation

Tanshinone IIA (Tan IIA), a neuroprotective natural compound extracted from Salvia miltiorrhiza, is used in stroke treatment. However, elucidating Tan IIA's neuroprotective mechanisms remains challenging due to limitations in assessing drug efficacy and biochemical parameters in clinical studies. This study investigated Tan IIA's impact on neuroinflammatory responses and its neuroprotective mechanisms using HMGB1- or TNF-α-stimulated BV2 microglia in a co-culture system with primary neuron cells. The results indicated that Tan IIA significantly reduced microglial activation induced by TNF-α or HMGB1. Concurrently, Tan IIA disrupted the interactions between HMGB1 and toll-like receptor 4 (TLR4), and between TNF-α and TNF receptor 1 (TNFR1), modulating the HMGB1/TLR4/nuclear factor-kappa B (NF-κB) and TNF-α/TNFR1/NF-κB signaling pathways and related protein expressions. Moreover, co-culture experiments showed that neuronal apoptosis induced by microglial activation was reversed by Tan IIA. In conclusion, Tan IIA provides neuroprotection by modulating signaling pathways in microglia, thus preventing neuronal apoptosis. This study offers new insights into therapeutic targets for ischemic stroke.

Micronutrient availability alters Candida albicans growth and farnesol accumulation: implications for studies using RPMI-1640.

The dimorphic fungus Candida albicans is a major opportunistic pathogen of humans. RPMI-1640 is a chemically defined growth medium commonly used with C. albicans. We identified over 32,000 publications with keywords RPMI and C. albicans. Additionally, Antifungal Susceptibility Testing (AFST) protocols in the United States (CLSI) and Europe (EUCAST) utilize RPMI as a base media to assess drug efficacy against clinical fungal isolates. RPMI contains many nutrients but no added trace metals. We found that the growth characteristics with RPMI were dependent on which MOPS buffer was chosen and the contamination of that buffer by trace levels of Mn(II) and Zn(II). Added Mn(II) was most needed for cell growth while added Zn(II) was most needed for secretion of farnesol and other signaling molecules.

Organoids: development and applications in disease models, drug discovery, precision medicine, and regenerative medicine.

Organoids are miniature, highly accurate representations of organs that capture the structure and unique functions of specific organs. Although the field of organoids has experienced exponential growth, driven by advances in artificial intelligence, gene editing, and bioinstrumentation, a comprehensive and accurate overview of organoid applications remains necessary. This review offers a detailed exploration of the historical origins and characteristics of various organoid types, their applications-including disease modeling, drug toxicity and efficacy assessments, precision medicine, and regenerative medicine-as well as the current challenges and future directions of organoid research. Organoids have proven instrumental in elucidating genetic cell fate in hereditary diseases, infectious diseases, metabolic disorders, and malignancies, as well as in the study of processes such as embryonic development, molecular mechanisms, and host-microbe interactions. Furthermore, the integration of organoid technology with artificial intelligence and microfluidics has significantly advanced large-scale, rapid, and cost-effective drug toxicity and efficacy assessments, thereby propelling progress in precision medicine. Finally, with the advent of high-performance materials, three-dimensional printing technology, and gene editing, organoids are also gaining prominence in the field of regenerative medicine. Our insights and predictions aim to provide valuable guidance to current researchers and to support the continued advancement of this rapidly developing field.

Multi-output prediction of dose–response curves enables drug repositioning and biomarker discovery

Drug response prediction is hampered by uncertainty in the measures of response and selection of doses. In this study, we propose a probabilistic multi-output model to simultaneously predict all dose–responses and uncover their biomarkers. By describing the relationship between genomic features and chemical properties to every response at every dose, our multi-output Gaussian Process (MOGP) models enable assessment of drug efficacy using any dose–response metric. This approach was tested across two drug screening studies and ten cancer types. Kullback-leibler divergence measured the importance of each feature and identified EZH2 gene as a novel biomarker of BRAF inhibitor response. We demonstrate the effectiveness of our MOGP models in accurately predicting dose–responses in different cancer types and when there is a limited number of drug screening experiments for training. Our findings highlight the potential of MOGP models in enhancing drug development pipelines by reducing data requirements and improving precision in dose–response predictions.

Application of Myocardial Salvage Index as a Clinical Endpoint: Assessment Methods and Future Prospects

In patients with acute myocardial infarction (AMI), traditional clinical endpoints used to assess drug efficacy and prognosis include infarct size (IS), incidence of heart failure, and mortality rates. Although these metrics are commonly employed to evaluate outcomes in AMI patients, their utility is limited in small‐scale studies. The introduction of the myocardial salvage index (MSI) reduces variability in assessments across multiple dimensions, thereby enhancing the sensitivity of outcome measures and reducing the required sample size. Moreover, MSI is increasingly utilized to evaluate drug efficacy, prognosis, and risk stratification in AMI patients. Although a variety of methodologies for measuring the MSI are currently available, the incorporation of these methods as clinical endpoints remains limited. In the clinical application of cardioprotective strategies, it is recommended that MSI be evaluated using late gadolinium enhancement measured along the endocardial surface length combined with IS in cardiac magnetic resonance. In dynamic single‐photon emission computed tomography, an assessment of MSI using methods based on abnormalities in myocardial wall thickening combined with perfusion anomalies is advocated. This review comprehensively outlines the principles, advantages, and limitations of different MSI assessment methods and discusses the prospects and challenges of MSI in cardiac protective therapies. Additionally, we summarize recommended strategies for employing MSI as a clinical surrogate endpoint in various clinical scenarios, providing direction for future clinical practice and research.Evidence Level5Technical EfficacyStage 4

Distribution of MRI-derived T2 values as a biomarker for in vivo rapid screening of phenotype severity in mdx mice

Background The pathology in Duchenne muscular dystrophy (DMD) is characterized by degenerating muscle fibers, inflammation, fibro-fatty infiltrate, and edema, and these pathological processes replace normal healthy muscle tissue. The mdx mouse model is one of the most commonly used preclinical models to study DMD. Mounting evidence has emerged illustrating that muscle disease progression varies considerably in mdx mice, with inter-animal differences as well as intra-muscular differences in pathology in individual mdx mice. This variation is important to consider when conducting assessments of drug efficacy and in longitudinal studies. We developed a magnetic resonance imaging (MRI) segmentation and analysis pipeline to rapidly and non-invasively measure the severity of muscle disease in mdx mice. Methods Wildtype and mdx mice were imaged with MRI and T2 maps were obtained axially across the hindlimbs. A neural network was trained to rapidly and semi-automatically segment the muscle tissue, and the distribution of resulting T2 values was analyzed. Interdecile range and Pearson Skew were identified as biomarkers to quickly and accurately estimate muscle disease severity in mice. Results The semiautomated segmentation tool reduced image processing time approximately tenfold. Measures of Pearson skew and interdecile range based on that segmentation were repeatable and reflected muscle disease severity in healthy wildtype and diseased mdx mice based on both qualitative observation of images and correlation with Evans blue dye uptake. Conclusion Use of this rapid, non-invasive, semi-automated MR image segmentation and analysis pipeline has the potential to transform preclinical studies, allowing for pre-screening of dystrophic mice prior to study enrollment to ensure more uniform muscle disease pathology across treatment groups, improving study outcomes.

Developing patient-derived organoids to demonstrate JX24120 inhibits SAMe synthesis in endometrial cancer by targeting MAT2B

Endometrial cancer (EC) is one of the most common gynecologic malignancies, which lacking effective drugs for intractable conditions or patients unsuitable for surgeries. Recently, the patient-derived organoids (PDOs) are found feasible for cancer research and drug discoveries. Here, we have successfully established a panel of PDOs from EC and conducted drug repurposing screening and mechanism analysis for cancer treatment. We confirmed that the regulatory β subunit of methionine adenosyltransferase (MAT2B) is highly correlated with malignant progression in endometrial cancer. Through drug screening on PDOs, we identify JX24120, chlorpromazine derivative, as a specific inhibitor for MAT2B, which directly binds to MAT2B (Kd = 4.724 μM) and inhibits the viability of EC PDOs and canonical cell lines. Correspondingly, gene editing assessment demonstrates that JX24120 suppresses tumor growth depending on the presence of MAT2B in vivo and in vitro. Mechanistically, JX24120 induces inhibition of S-adenosylmethionine (SAMe) synthesis, leading to suppressed mTORC1 signaling, abnormal energy metabolism and protein synthesis, and eventually apoptosis. Taken together, our study offers a novel approach for drug discovery and efficacy assessment by using the PDOs models. These findings suggest that JX24120 may be a potent MAT2B inhibitor and will hopefully serve as a prospective compound for endometrial cancer therapy.

Evaluating the significance of ECSCR in the diagnosis of ulcerative colitis and drug efficacy assessment.

The main challenge in diagnosing and treating ulcerative colitis (UC) has prompted this study to discover useful biomarkers and understand the underlying molecular mechanisms. In this study, transcriptomic data from intestinal mucosal biopsies underwent Robust Rank Aggregation (RRA) analysis to identify differential genes. These genes intersected with UC key genes from Weighted Gene Co-expression Network Analysis (WGCNA). Machine learning identified UC signature genes, aiding predictive model development. Validation involved external data for diagnostic, progression, and drug efficacy assessment, along with ELISA testing of clinical serum samples. RRA integrative analysis identified 251 up-regulated and 211 down-regulated DEGs intersecting with key UC genes in WGCNA, yielding 212 key DEGs. Subsequently, five UC signature biomarkers were identified by machine learning based on the key DEGs-THY1, SLC6A14, ECSCR, FAP, and GPR109B. A logistic regression model incorporating these five genes was constructed. The AUC values for the model set and internal validation data were 0.995 and 0.959, respectively. Mechanistically, activation of the IL-17 signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway in UC was indicated by KEGG and GSVA analyses, which were positively correlated with the signature biomarkers. Additionally, the expression of the signature biomarkers was strongly correlated with various UC types and drug efficacy in different datasets. Notably, ECSCR was found to be upregulated in UC serum and exhibited a positive correlation with neutrophil levels in UC patients. THY1, SLC6A14, ECSCR, FAP, and GPR109B can serve as potential biomarkers of UC and are closely related to signaling pathways associated with UC progression. The discovery of these markers provides valuable information for understanding the molecular mechanisms of UC.

Cryopreservation of human kidney organoids

Recent advances in stem cell research have led to the creation of organoids, miniature replicas of human organs, offering innovative avenues for studying diseases. Kidney organoids, with their ability to replicate complex renal structures, provide a novel platform for investigating kidney diseases and assessing drug efficacy, albeit hindered by labor-intensive generation and batch variations, highlighting the need for tailored cryopreservation methods to enable widespread utilization. Here, we evaluated cryopreservation strategies for kidney organoids by contrasting slow-freezing and vitrification methods. 118 kidney organoids were categorized into five conditions. Control organoids followed standard culture, while two slow-freezing groups used 10% DMSO (SF1) or commercial freezing media (SF2). Vitrification involved V1 (20% DMSO, 20% Ethylene Glycol with sucrose) and V2 (15% DMSO, 15% Ethylene Glycol). Assessment of viability, functionality, and structural integrity post-thawing revealed notable differences. Vitrification, particularly V1, exhibited superior viability (91% for V1, 26% for V2, 79% for SF1, and 83% for SF2 compared to 99.4% in controls). 3D imaging highlighted distinct nephron segments among groups, emphasizing V1’s efficacy in preserving both podocytes and tubules in kidney organoids. Cisplatin-induced injury revealed a significant reduction in regenerative capacities in organoids cryopreserved by flow-freezing methods, while the V1 method did not show statistical significance compared to the unfrozen controls. This study underscores vitrification, especially with high concentrations of cryoprotectants, as an effective approach for maintaining kidney organoid viability and structure during cryopreservation, offering practical approaches for kidney organoid research.

MultiCBlo: Enhancing predictions of compound-induced inhibition of cardiac ion channels with advanced multimodal learning

Predicting compound-induced inhibition of cardiac ion channels is crucial and challenging, significantly impacting cardiac drug efficacy and safety assessments. Despite the development of various computational methods for compound-induced inhibition prediction in cardiac ion channels, their performance remains limited. Most methods struggle to fuse multi-source data, relying solely on specific dataset training, leading to poor accuracy and generalization. We introduce MultiCBlo, a model that fuses multimodal information through a progressive learning approach, designed to predict compound-induced inhibition of cardiac ion channels with high accuracy. MultiCBlo employs progressive multimodal information fusion technology to integrate the compound's SMILES sequence, graph structure, and fingerprint, enhancing its representation. This is the first application of progressive multimodal learning for predicting compound-induced inhibition of cardiac ion channels, to our knowledge. The objective of this study was to predict the compound-induced inhibition of three major cardiac ion channels: hERG, Cav1.2, and Nav1.5. The results indicate that MultiCBlo significantly outperforms current models in predicting compound-induced inhibition of cardiac ion channels. We hope that MultiCBlo will facilitate cardiac drug development and reduce compound toxicity risks. Code and data are accessible at: https://github.com/taowang11/MultiCBlo. The online prediction platform is freely accessible at: https://huggingface.co/spaces/wtttt/PCICB.

Drug Evaluation of Parkinson's Disease Patient-Derived Midbrain Organoids Using Mesoporous Au Nanodot-Patterned 3D Concave Electrode.

Brain organoids are being recognized as valuable tools for drug evaluation in neurodegenerative diseases due to their similarity to the human brain's structure and function. However, a critical challenge is the lack of selective and sensitive electrochemical sensing platforms to detect the response of brain organoids, particularly changes in the neurotransmitter concentration upon drug treatment. This study introduces a 3D concave electrode patterned with a mesoporous Au nanodot for the detection of electrochemical signals of dopamine in response to drugs in brain organoids for the first time. The mesoporous Au nanodot-patterned film was fabricated using laser interference lithography and electrochemical deposition. Then, the film was attached to a polymer-based 3D concave mold to obtain a 3D concave electrode. Midbrain organoids generated from Parkinson's disease (PD) patient-derived iPSCs with gene mutations (named as PD midbrain organoid) or normal midbrain organoids were positioned on the developed 3D concave electrode. The 3D concave electrode showed a 1.4 times higher electrochemical signal of dopamine compared to the bare gold electrode. And the dopamine secreted from normal midbrain organoids or PD midbrain organoids on the 3D concave electrode could be detected electrochemically. After the treatment of PD midbrain organoids with levodopa, the drug for PD, the increase in dopamine level was detected due to the activation of dopaminergic neurons by the drug. The results suggest the potential of the proposed 3D concave electrode combined with brain organoids as a useful tool for assessing drug efficacy. This sensing system can be applied to a variety of organoids for a comprehensive drug evaluation.

Research progress on the application of organoids in gynecological tumors.

Organoids are in vitro 3D models that maintain their own tissue structure and function. They largely overcome the limitations of traditional tumor models and have become a powerful research tool in the field of oncology in recent years. Gynecological malignancies are major diseases that seriously threaten the life and health of women and urgently require the establishment of models with a high degree of similarity to human tumors for clinical studies to formulate individualized treatments. Currently, organoids are widely studied in exploring the mechanisms of gynecological tumor development as a means of drug screening and individualized medicine. Ovarian, endometrial, and cervical cancers as common gynecological malignancies have high morbidity and mortality rates among other gynecological tumors. Therefore, this study reviews the application of modelling, drug efficacy assessment, and drug response prediction for ovarian, endometrial, and cervical cancers, thereby clarifying the mechanisms of tumorigenesis and development, and providing precise treatment options for gynecological oncology patients.

Magneto-optical assessment of Plasmodium parasite growth via hemozoin crystal size

Hemozoin is a natural biomarker formed during the hemoglobin metabolism of Plasmodium parasites, the causative agents of malaria. The rotating-crystal magneto-optical detection (RMOD) has been developed for its rapid and sensitive detection both in cell cultures and patient samples. In the current article we demonstrate that, besides quantifying the overall concentration of hemozoin produced by the parasites, RMOD can also track the size distribution of the hemozoin crystals. We establish the relations between the magneto-optical signal, the mean parasite age and the median crystal size throughout one erythrocytic cycle of Plasmodium falciparum parasites, where the latter two are determined by optical and scanning electron microscopy, respectively. The significant correlation between the magneto-optical signal and the stage distribution of the parasites indicates that the RMOD method can be utilized for species-specific malaria diagnosis and for the quick assessment of drug efficacy.