Diving deep: zebrafish models in motor neuron degeneration research.

In the dynamic landscape of biomedical science, the pursuit of effective treatments for motor neuron disorders like hereditary spastic paraplegia (HSP), amyotrophic lateral sclerosis (ALS), and spinal muscular atrophy (SMA) remains a key priority. Central to this endeavor is the development of robust animal models, with the zebrafish emerging as a prime candidate. Exhibiting embryonic transparency, a swift life cycle, and significant genetic and neuroanatomical congruencies with humans, zebrafish offer substantial potential for research. Despite the difference in locomotion-zebrafish undulate while humans use limbs, the zebrafish presents relevant phenotypic parallels to human motor control disorders, providing valuable insights into neurodegenerative diseases. This review explores the zebrafish's inherent traits and how they facilitate profound insights into the complex behavioral and cellular phenotypes associated with these disorders. Furthermore, we examine recent advancements in high-throughput drug screening using the zebrafish model, a promising avenue for identifying therapeutically potent compounds.

Personalized drug screening using patient-derived organoid and its clinical relevance in gastric cancer.

The efficacy of chemotherapy varies significantly among patients with gastric cancer (GC), and there is currently no effective strategy to predict chemotherapeutic outcomes. In this study, we successfully establish 57 GC patient-derived organoids (PDOs) from 73 patients with GC (78%). These organoids retain histological characteristics of their corresponding primary GC tissues. GC PDOs show varied responses to different chemotherapeutics. Through RNA sequencing, the upregulation of tumor suppression genes/pathways is identified in 5-fluorouracil (FU)- or oxaliplatin-sensitive organoids, whereas genes/pathways associated with proliferation and invasion are enriched in chemotherapy-resistant organoids. Gene expression biomarker panels, which could distinguish sensitive and resistant patients to 5-FU and oxaliplatin (area under the dose-response curve [AUC] >0.8), are identified. Moreover, the drug-response results in PDOs are validated in patient-derived organoids-based xenograft (PDOX) mice and are consistent with the actual clinical response in 91.7% (11/12) of patients with GC. Assessing chemosensitivity in PDOs can be utilized as a valuable tool for screening chemotherapeutic drugs in patients with GC.

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.

Dual-driven AND molecular logic gates for label-free and sensitive ratiometric fluorescence sensing and inhibitors screening.

Due to the complexity of regulatory networks of disease-related biomarkers, developing simple, sensitive, and accurate methods has remained challenging for precise diagnosis. Herein, an "AND" logic gates DNA molecular machine (LGDM) was constructed, which was powered by the catalytic hairpin assembly (CHA). It was coupled with dual-emission CdTe quantum dots (QDs)-based cation exchange reaction (CER) for label-free, sensitive, and ratiometric fluorescence detection of APE1 and miRNA biomarkers. Benefiting from synergistic signal amplification strategies and a ratiometric fluorometric output mode, this LGDM enables accurate logic computing with robust and significant output signals from weak inputs. It offers improved sensitivity and selectivity even in cell extracts. Using dual-emission spectra CdTe QDs, with a ratiometric signal output mode, ensured good stability and effectively prevented false-positive signals from intrinsic biological interferences compared to the approach relying on a single signal output mode, which enabled the LGDM to achieve rapid, efficient, and accurate natural drug screening against APE1 inhibitors in vitro and cells. The developed method provides impetus to streamline research related to miRNA and APE1, offering significant promise for widespread application in drug development and clinical analysis.

Gastric Cancer Assembloids Derived from Patient-Derived Xenografts: A Preclinical Model for Therapeutic Drug Screening.

The construction of reliable preclinical models is crucial for understanding the molecular mechanisms involved in gastric cancer and for advancing precision medicine. Currently, existing in vitro tumor models often do not accurately replicate the human gastric cancer environment and are unsuitable for high-throughput therapeutic drug screening. In this study, droplet microfluidic technology is employed to create novel gastric cancer assembloids by encapsulating patient-derived xenograft gastric cancer cells and patient stromal cells in Gelatin methacryloyl (GelMA)-Gelatin-Matrigel microgels. The usage of GelMA-Gelatin-Matrigel composite hydrogel effectively alleviated cell aggregation and sedimentation during the assembly process, allowing for the handling of large volumes of cell-laden hydrogel and the uniform generation of assembloids in a high-throughput manner. Notably, the patient-derived xenograft assembloids exhibited high consistency with primary tumors at both transcriptomic and histological levels, and can be efficiently scaled up for preclinical drug screening efforts. Furthermore, the drug screening results clearly demonstrated that the in vitro assembloid model closely mirrored in vivo drug responses. Thus, these findings suggest that gastric cancer assembloids, which effectively replicate the in vivo tumor microenvironment, show promise for enabling more precise high-throughput drug screening and predicting the clinical outcomes of various drugs.

Using the refractive index of latent fingerprints for the quantification and characterisation of sample deposition.

Latent fingerprints (LFPs) are predominantly used for personal identification, but in recent years research has shown their potential for drug screening. Despite this there is no standardised collection method to allow accurate drug test interpretation. We sought to help address this by characterising different variables related to sweat deposition in LFPs as the knowledge is limited. A series of experiments were conducted firstly to validate a novel tool called the Ridgeway (Intelligent Fingerprint Ltd. UK) to quantify the amount of sweat deposited from a LFP using the refractive index (RI). A significant positive correlation was observed between the Ridgeway score (Rs) and LFP mass [r = 0.868, p < 0.01]. The Rs was used as means to investigate optimal sampling to characterise sample deposition for drug screening purposes. It was found with a consistent disposition pressure (300 - 400 g) and surface (glass slide) no significant difference was observed between the left and right index finger [left: p = 0.938; right: p = 0.838]. Significantly higher Rs [p<0.01] were obtained when 10 cumulative LFPs were deposited compared to a single LFP, suggesting a larger sweat quantity. We also wanted to investigate optimal eccrine sweat sampling to confirm drug ingestion over drug contamination of the fingerprint. We found that wearing gloves did not significantly improve mean difference in Rs when compared to no gloves [p = 0.239]. To produce eccrine only LFPs, external contamination (e.g. sebaceous sweat) needs to be removed. Soap with lint free tissue was significantly better for this compared to antibacterial hand gel [p<0.01]. Our findings showed that the Ridgeway tool effectively quantified LFPs at the point of deposition using a refractive index and enabled us to establish conditions for consistent LFP sampling.

A clinically compatible in vitro drug-screening platform identifies therapeutic vulnerabilities in primary cultures of brain metastases.

PURPOSE: Brain metastases represent the most common intracranial tumors in adults and are associated with a poor prognosis. We used a personalized in vitro drug screening approach to characterize individual therapeutic vulnerabilities in brain metastases. METHODS: Short-term cultures of cancer cells isolated from brain metastasis patients were molecularly characterized using next-generation sequencing and functionally evaluated using high-throughput in vitro drug screening to characterize pharmacological treatment sensitivities. RESULTS: Next-generation sequencing identified matched genetic alterations in brain metastasis tissue samples and corresponding short-term cultures, suggesting that short-term cultures of brain metastases are suitable models for recapitulating the genetic profile of brain metastases that may determine their sensitivity to anti-cancer drugs. Employing a high-throughput in vitro drug screening platform, we successfully screened the cultures of five brain metastases for response to 267 anticancer compounds and related drug response to genetic data. Among others, we found that targeted treatment with JAK3, HER2, or FGFR3 inhibitors showed anti-cancer effects in individual brain metastasis cultures. CONCLUSION: Our preclinical study provides a proof-of-concept for combining molecular profiling with in vitro drug screening for predictive evaluation of therapeutic vulnerabilities in brain metastasis patients. This approach could advance the use of patient-derived cancer cells in clinical practice and might eventually facilitate decision-making for personalized drug treatment.

Improving iPSC Differentiation Using a Nanodot Platform.

Differentiation of induced pluripotent stem cells (iPSCs) is an extremely complex process that has proven difficult to study. In this research, we utilized nanotopography to elucidate details regarding iPSC differentiation by developing a nanodot platform consisting of nanodot arrays of increasing diameter. Subjecting iPSCs cultured on the nanodot platform to a cardiomyocyte (CM) differentiation protocol revealed several significant gene expression profiles that were associated with poor differentiation. The observed expression trends were used to select existing small-molecule drugs capable of modulating differentiation efficiency. BRD K98 was repurposed to inhibit CM differentiation, while iPSCs treated with NSC-663284, carmofur, and KPT-330 all exhibited significant increases in not only CM marker expression but also spontaneous beating, suggesting improved CM differentiation. In addition, quantitative polymerase chain reaction was performed to determine the gene regulation responsible for modulating differentiation efficiency. Multiple genes involved in extracellular matrix remodeling were correlated with a CM differentiation efficiency, while genes involved in the cell cycle exhibited contrasting expression trends that warrant further studies. The results suggest that expression profiles determined via short time-series expression miner analysis of nanodot-cultured iPSC differentiation can not only reveal drugs capable of enhancing differentiation efficiency but also highlight crucial sets of genes related to processes such as extracellular matrix remodeling and the cell cycle that can be targeted for further investigation. Our findings confirm that the nanodot platform can be used to reveal complex mechanisms behind iPSC differentiation and could be an indispensable tool for optimizing iPSC technology for clinical applications.

Using the Zebrafish Larval Model of Infection to Investigate Antibiotic Efficacy and Combination Treatments Against Staphylococcus aureus.

There is an increasing need for new treatment regimens to combat antibiotic-resistant strains of bacteria. Staphylococcus aureus is a clinically important, opportunist pathogen that has developed resistance to a range of antibiotics. The zebrafish larval model of systemic disease has been increasingly utilized to elucidate S. aureus virulence mechanisms and host-pathogen interactions. Here, we outline how this model can be used to investigate the effects of different antibiotics alone and in combination against S. aureus.

Multireceptor Analysis for Evaluating the Antidiabetic Efficacy of Karanjin: A Computational Approach.

BACKGROUND: Diabetes mellitus, notably type 2, is a rising global health challenge, prompting the need for effective management strategies. Common medications such as metformin, insulin, repaglinide and sitagliptin can induce side effects like gastrointestinal disturbances, hypoglycemia, weight gain and specific organ risks. Plant-derived therapies like Karanjin from Pongamia pinnata present promising alternatives due to their historical use, holistic health benefits and potentially fewer adverse effects. This study employs in silico analysis to explore Karanjin's interactions with diabetes-associated receptors, aiming to unveil its therapeutic potential while addressing the limitations and side effects associated with conventional medications. METHODOLOGY: The research encompassed the selection of proteins from the Protein Data Bank (PDB), followed by structural refinement processes and optimization. Ligands such as Karanjin and standard drugs were retrieved from PubChem, followed by a comprehensive analysis of their ADMET profiling and pharmacokinetic properties. Protein-ligand interactions were evaluated through molecular docking using AutoDockTools 1.5.7, followed by the analysis of structural stability using coarse-grained simulations with CABS Flex 2.0. Molecular dynamics simulations were performed using Desmond 7.2 and the OPLS4 force field to explore how Karanjin interacts with proteins over 100 nanoseconds, focusing on the dynamics and structural stability. RESULTS: Karanjin, a phytochemical from Pongamia pinnata, shows superior drug candidate potential compared to common medications, offering advantages in efficacy and reduced side effects. It adheres to drug-likeness criteria and exhibits optimal ADMET properties, including moderate solubility, high gastrointestinal absorption and blood-brain barrier penetration. Molecular docking revealed Karanjin's highest binding energy against receptor 3L2M (Pig pancreatic alpha-amylase) at -9.1 kcal/mol, indicating strong efficacy potential. Molecular dynamics simulations confirmed stable ligand-protein complexes with minor fluctuations in RMSD and RMSF, suggesting robust interactions with receptors 3L2M. CONCLUSION: Karanjin demonstrates potential in pharmaceutical expansion for treating metabolic disorders such as diabetes, as supported by computational analysis. Prospects for Karanjin in pharmaceutical development include structural modifications for enhanced efficacy and safety. Nanoencapsulation may improve bioavailability and targeted delivery to pancreatic cells, while combination therapies could optimize treatment outcomes in diabetes management. Clinical trials and experimental studies are crucial to validate its potential as a novel therapeutic agent.

A smart tablet-phone-based high-performance pancreatic cancer cell biosensing system for drug screening.

Exploring more efficient pancreatic cancer drug screening platforms is of significant importance for accelerating the drug development process. In this study, we developed a high-sensitivity bioluminescence system based on smartphones and smart tablets, and constructed a pancreatic cancer drug screening platform (PCDSP) by combining the pancreatic cancer cell sensing model (PCCSM) on the multiwell plates (MTP). A smart tablet was used as the light source and a smartphone as the colorimetric sensing device. The smartphone dynamically controls the color and brightness displayed on the smart tablet to achieve lower LOD and wider detection ranges. We constructed PCCSM for 24 h, 48 h, and 72 h , and performed colorimetric experiments using both PCDSP and a commercial plate reader (CPR). The results showed that the PCDSP had a lower LOD than that of CPR. Moreover, PCDSP even exhibited a lower LOD for 24 h PCCSM testing compared to CPR for 48 h PCCSM testing, effectively shortening the drug evaluation process. Additionally, the PCDSP offers higher portability and efficiency compared with CPR, making it a promising platform for efficient pancreatic cancer drug screening.

Scalable drop-casting construction of light-addressable photoelectrochemical biosensor on laser-induced graphene electrode arrays for high-throughput drug screening.

A drop-casting method for the scalable construction of a solar cell-type light-addressable photoelectrochemical (PEC) sensor on commercial phenol resin (PR) plates is reported. The sensor was fabricated by laser writing of addressable laser-induced graphene (LIG) electrode arrays on PR plates with ring-disc dual-electrode cell configurations using a 405 nm laser machine. Beneficial from the good hydrophilicity of PR-based LIG and the excellent film formation of bismuth sulfide nanorods (Bi2S3 NRs), uniform Bi2S3 photovoltaic films can be reproducibly deposited onto the LIG disc photoanode array via drop casting modification, which show a sensitive photocurrent response toward thiocholine (TCl) when the ring cathode array was coated with Ag/AgCl. An acetylcholinesterase (AChE)-based PEC biosensor was therefore constructed by a similar drop-casting modification method. The resulting biosensor exhibits good sensitivity toward an AChE inhibitor, i.e., galantamine hydrobromide (GH), with a calibration range of 10-300 µM and a detection limit of 7.33 µM (S/N = 3). Moreover, the biosensor possesses good storage stability, which can achieve the high-throughput screening of AChE inhibitor drugs from traditional Chinese medicines (TCMs). The present work thus demonstrates the promising application of LIG technology in constructing light-addressable PEC sensing devices with high performance and low cost.

[Research progress of integrating electrical impedance sensors with microfluidic chips in cell detection].

Cell culture is a fundamental tool for cell-based assays in biological and preclinical research. The measurements of cell culture, including cell count, viability, and metabolic activity, can reflect the conditions of cells under culture conditions. The conventional cell culture and detection methods have problems such as high consumption of reagents and samples, inability to monitor cell status in real time, and difficulty in spatiotemporally adjusting the cell microenvironment. A cell impedance sensor measures changes in the electrical impedance of cells through alternating current, enabling real-time monitoring of impedance changes caused by cell activities such as attachment, growth, proliferation, and migration. Microfluidic chips are praised for reducing complex biological processes, integrating multiple analysis modes, and achieving high automation in detection. Integrating microfluidic chips with cell impedance sensors greatly improves the capability and efficiency of cell-related analysis. This review outlines the application of microfluidic chip-based impedance sensors in 2D and 3D cell systems and summarizes the research progress in application of such sensors in research on cell growth, proliferation, viability, metabolic activity, and drug screening. Finally, this review prospects the future development trends and possible challenges, providing ideas for the development of microfluidic chips integrated with electrical impedance sensors in drug screening.

Drugs, Delirium, and Trauma: Substance Use and Incidence of Delirium After Traumatic Brain Injury.

INTRODUCTION: There is a paucity of data on the effect of preinjury substance (alcohol, drugs) abuse on the risk of delirium in patients with traumatic brain injury (TBI). This study aimed to assess the incidence of delirium among patients with blunt TBI in association with different substances. METHODS: We analyzed the 2020 American College of Surgeons-Trauma Quality Improvement Program. We included all adult (≥18 y) patients with blunt TBI who had a recorded substance (drugs and alcohol) screening. Our primary outcome was the incidence of delirium. RESULTS: A total of 72,901 blunt TBI patients were identified. The mean (standard deviation) age was 56 (20) years and 68.0% were males. The median (interquartile range) injury severity score was 17 (10-25). Among the study population, 23.1% tested positive for drugs (Stimulants: 3.0%; Depressants: 2.9%, hallucinogens: 5.1%, Cannabinoids: 13.4%, TCAs: 0.1%), and 22.8% tested positive for Alcohol. Overall, 1856 (2.5%) experienced delirium. On univariate analysis, patients who developed delirium were more likely to have positive drug screening results. On multivariable regression analyses, positive screen tests for isolated stimulants (adjusted odds ratio [aOR]: 1.340, P = 0.018), tricyclic antidepressants (aOR: 3.107, P = 0.019), and cannabinoids (aOR: 1.326, P ≤ 0.001) were independently associated with higher odds of developing delirium. CONCLUSIONS: Nearly one-fourth of adult patients with blunt TBI had an initial positive substance screening test. Patients with positive results for isolated stimulants, tricyclic antidepressants, and cannabinoids were at a higher risk of developing delirium, whereas this association was not evident with other drugs and alcohol-positive tests. These findings emphasize the need for early drug screening in TBI patients and close monitoring of patients with positive screening tests.

PDCD4 as a marker of mTOR pathway activation and therapeutic target in mycobacterial infections.

Programmed cell death protein 4 (PDCD4) is instrumental in regulating a range of cellular processes such as translation, apoptosis, signal transduction, and inflammatory responses. There is a notable inverse correlation between PDCD4 and the mammalian target of rapamycin (mTOR) pathway, which is integral to cellular growth control. Activation of mTOR is associated with the degradation of PDCD4. Although the role of PDCD4 is well established in oncogenesis and immune response regulation, its function in mycobacterial infections and its interplay with the mTOR pathway necessitate further elucidation. This study investigates the modulation of PDCD4 expression in the context of mycobacterial infections, revealing a consistent pattern of downregulation across diverse mycobacterial species. This observation underscores the potential utility of PDCD4 as a biomarker for assessing mTOR pathway activation during such infections. Building on this finding, we employed a novel approach using PDCD4-based mTOR (Tor)-signal-indicator (TOSI) reporter cells for the high-throughput screening of FDA-approved drugs, focusing on mTOR inhibitors. This methodology facilitated the identification of several agents, inclusive of known mTOR inhibitors, which upregulated PDCD4 expression and concurrently exhibited efficacy in impeding mycobacterial proliferation within macrophages. These results not only reinforce the significance of PDCD4 as a pivotal marker in the understanding of infectious diseases, particularly mycobacterial infections, but also illuminate its potential in the identification of mTOR inhibitors, thereby contributing to the advancement of therapeutic strategies. IMPORTANCE: This study emphasizes the critical role of the mammalian target of rapamycin (mTOR) pathway in macrophage responses to mycobacterial infections, elucidating how mycobacteria activate mTOR, resulting in PDCD4 degradation. The utilization of the (Tor)-signal-indicator (TOSI) vector for real-time monitoring of mTOR activity represents a significant advancement in understanding mTOR regulation during mycobacterial infection. These findings deepen our comprehension of mycobacteria's innate immune mechanisms and introduce PDCD4 as a novel marker for mTOR activity in infectious diseases. Importantly, this research laid the groundwork for high-throughput screening of mTOR inhibitors using FDA-approved drugs, offering the potential for repurposing treatments against mycobacterial infections. The identification of drugs that inhibit mTOR activation opens new avenues for host-directed therapies, marking a significant step forward in combating tuberculosis and other mycobacterial diseases.

Screening of MMP-13 Inhibitors Using a GelMA-Alginate Interpenetrating Network Hydrogel-Based Model Mimicking Cytokine-Induced Key Features of Osteoarthritis In Vitro.

Osteoarthritis (OA) is a chronic joint disease characterized by irreversible cartilage degradation. Current clinical treatment options lack effective pharmaceutical interventions targeting the disease's root causes. MMP (matrix metalloproteinase) inhibitors represent a new approach to slowing OA progression by addressing cartilage degradation mechanisms. However, very few drugs within this class are in preclinical or clinical trial phases. Hydrogel-based 3D in vitro models have shown promise as preclinical testing platforms due to their resemblance to native extracellular matrix (ECM), abundant availability, and ease of use. Metalloproteinase-13 (MMP-13) is thought to be a major contributor to the degradation of articular cartilage in OA by aggressively breaking down type II collagen. This study focused on testing MMP-13 inhibitors using a GelMA-alginate hydrogel-based OA model induced by cytokines interleukin-1 beta (IL-1ß) and tumor necrosis factor alpha (TNF-α). The results demonstrate a significant inhibition of type II collagen breakdown by measuring C2C concentration using ELISA after treatment with MMP-13 inhibitors. However, inconsistencies in human cartilage explant samples led to inconclusive results. Nonetheless, the study highlights the GelMA-alginate hydrogel-based OA model as an alternative to human-sourced cartilage explants for in vitro drug screening.

Real-time label-free three-dimensional invasion assay for anti-metastatic drug screening using impedance sensing.

Tumor metastasis presents a formidable challenge in cancer treatment, necessitating effective tools for anti-cancer drug development. Conventional 2D cell culture methods, while considered the "gold standard" for invasive studies, exhibit limitations in representing cancer hallmarks and phenotypes. This study proposes an innovative approach that combines the advantages of 3D tumor spheroid culture with impedance-based biosensing technologies to establish a high-throughput 3D cell invasion assay for anti-metastasis drug screening through multicellular tumor spheroids. In addition, the xCELLigence device is employed to monitor the time-dependent kinetics of cell behavior, including attachment and invasion out of the 3D matrix. Moreover, an iron chelator (deferoxamine) is employed to monitor the inhibition of epithelial-mesenchymal transition in 3D spheroids across different tumor cell types. The above results indicate that our integrated 3D cell invasion assay with impedance-based sensing could be a promising tool for enhancing the quality of the drug development pipeline by providing a robust platform for predicting the efficacy and safety of anti-metastatic drugs before advancing into preclinical or clinical trials.

Integrated multi-omics analysis and machine learning to refine molecular subtypes, prognosis, and immunotherapy in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) has a malignant characteristic that is highly aggressive and prone to metastasis. There is still a lack of suitable biomarkers to facilitate the refinement of precision-based therapeutic regimens. We used a combination of 10 known clustering algorithms and the omics data from 4 dimensions to identify high-resolution molecular subtypes of LUAD. Subsequently, consensus machine learning-related prognostic signature (CMRS) was developed based on subtypes related genes and an integrated program framework containing 10 machine learning algorithms. The efficiency of CMRS was analyzed from the perspectives of tumor microenvironment, genomic landscape, immunotherapy, drug sensitivity, and single-cell analysis. In terms of results, through multi-omics clustering, we identified 2 comprehensive omics subtypes (CSs) in which CS1 patients had worse survival outcomes, higher aggressiveness, mRNAsi and mutation frequency. Subsequently, we developed CMRS based on 13 key genes up-regulated in CS1. The prognostic predictive efficiency of CMRS was superior to most established LUAD prognostic signatures. CMRS demonstrated a strong correlation with tumor microenvironmental feature variants and genomic instability generation. Regarding clinical performance, patients in the high CMRS group were more likely to benefit from immunotherapy, whereas low CMRS were more likely to benefit from chemotherapy and targeted drug therapy. In addition, we evaluated that drugs such as neratinib, oligomycin A, and others may be candidates for patients in the high CMRS group. Single-cell analysis revealed that CMRS-related genes were mainly expressed in epithelial cells. The novel molecular subtypes identified in this study based on multi-omics data could provide new insights into the stratified treatment of LUAD, while the development of CMRS could serve as a candidate indicator of the degree of benefit of precision therapy and immunotherapy for LUAD.

Exploring the potential of human intestinal organoids: Applications, challenges, and future directions.

The complex and dynamic environment of the gastrointestinal tract shapes one of the fastest renewing tissues in the human body, the intestinal epithelium. Considering the lack of human preclinical studies, reliable models that mimic the intestinal environment are increasingly explored. Patient-derived intestinal organoids are powerful tools that recapitulate in vitro many pathophysiological features of the human intestine. In this review, the possible applications of human intestinal organoids in different research fields are highlighted. From physiologically relevant to intestinal disease modeling, regenerative medicine, and toxicology studies, the potential of intestinal organoids will be here presented and discussed. Despite the remarkable opportunities offered, limitations related to ethical concerns, tissue collection, reproducibility, and methodologies may hinder the full exploitation of this cell-based model into high throughput studies and clinical practice. Currently, distinct approaches can be used to overcome the numerous challenges found along the way and to allow the full implementation of this ground-breaking technology.

Standardized generation of human iPSC-derived hematopoietic organoids and macrophages utilizing a benchtop bioreactor platform under fully defined conditions.

BACKGROUND: There is a significant demand for intermediate-scale bioreactors in academic and industrial institutions to produce cells for various applications in drug screening and/or cell therapy. However, the application of these bioreactors in cultivating hiPSC-derived immune cells and other blood cells is noticeably lacking. To address this gap, we have developed a xeno-free and chemically defined intermediate-scale bioreactor platform, which allows for the generation of standardized human iPSC-derived hematopoietic organoids and subsequent continuous production of macrophages (iPSC-Mac). METHODS: We describe a novel method for intermediate-scale immune cell manufacturing, specifically the continuous production of functionally and phenotypically relevant macrophages that are harvested on weekly basis for multiple weeks. RESULTS: The continuous production of standardized human iPSC-derived macrophages (iPSC-Mac) from 3D hematopoietic organoids also termed hemanoids, is demonstrated. The hemanoids exhibit successive stage-specific embryonic development, recapitulating embryonic hematopoiesis. iPSC-Mac were efficiently and continuously produced from three different iPSC lines and exhibited a consistent and reproducible phenotype, as well as classical functionality and the ability to adapt towards pro- and anti-inflammatory activation stages. Single-cell transcriptomic analysis revealed high macrophage purity. Additionally, we show the ability to use the produced iPSC-Mac as a model for testing immunomodulatory drugs, exemplified by dexamethasone. CONCLUSIONS: The novel method demonstrates an easy-to-use intermediate-scale bioreactor platform that produces prime macrophages from human iPSCs. These macrophages are functionally active and require no downstream maturation steps, rendering them highly desirable for both therapeutic and non-therapeutic applications.