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Dravet syndrome is a severe genetic epilepsy primarily caused by de novo mutations in a voltage-activated sodium channel gene (SCN1A). Patients face life-threatening seizures that are largely resistant to available anti-seizure medications. Preclinical Dravet syndrome animal models are a valuable tool to identify candidate anti-seizure medications for these patients. Among these, scn1lab mutant zebrafish, exhibiting spontaneous seizure-like activity, are particularly amenable to large-scale drug screening. Thus far, we have screened more than 3000 drug candidates in scn1lab zebrafish mutants, identifying valproate, stiripentol, and fenfluramine e.g. Food and Drug Administration-approved drugs, with clinical application in the Dravet syndrome population. Successful phenotypic screening in scn1lab mutant zebrafish is rigorous and consists of two stages: (i) a locomotion-based assay measuring high-velocity convulsive swim behaviour and (ii) an electrophysiology-based assay, using in vivo local field potential recordings, to quantify electrographic seizure-like events. Historically, nearly 90% of drug candidates fail during translation from preclinical models to the clinic. With such a high failure rate, it becomes necessary to address issues of replication and false positive identification. Leveraging our scn1lab zebrafish assays is one approach to address these problems. Here, we curated a list of nine anti-seizure drug candidates recently identified by other groups using preclinical Dravet syndrome models: 1-Ethyl-2-benzimidazolinone, AA43279, chlorzoxazone, donepezil, lisuride, mifepristone, pargyline, soticlestat and vorinostat. First-stage locomotion-based assays in scn1lab mutant zebrafish identified only 1-Ethyl-2-benzimidazolinone, chlorzoxazone and lisuride. However, second-stage local field potential recording assays did not show significant suppression of spontaneous electrographic seizure activity for any of the nine anti-seizure drug candidates. Surprisingly, soticlestat induced frank electrographic seizure-like discharges in wild-type control zebrafish. Taken together, our results failed to replicate clear anti-seizure efficacy for these drug candidates highlighting a necessity for strict scientific standards in preclinical identification of anti-seizure medications.

A research letter published in the journal Circulation discusses the LMNA Q353R mutation, which is associated with dilated cardiomyopathy. The mutation causes DNA damage accumulation in the heart, leading to premature aging and poor prognosis. The study found that vitamin D2 showed efficacy in reducing DNA damage in patient-specific cardiomyocytes. Another study investigated the mechanism by which the mutation causes DNA damage and found that abnormal localization of the vitamin D receptor leads to reduced DNA repair. The intervention with vitamin D2 can reduce DNA damage and improve cardiac function. This research provides insights into potential treatments for LMNA-mutant cardiomyopathy using vitamin D. [Extracted from the article]

Breast cancer is the most common malignant tumor in women. Due to the high heterogeneity of breast cancer cells, traditional in vitro research models still have major limitations. Therefore, it is urgent to establish an experimental model that can accurately simulate the characteristics of human breast cancer. Breast cancer organoid technology emerged as the times required, that is, to construct tissue analogs with organ characteristics by using a patient's tumor tissue through 3D culture in vitro. Since the breast cancer organoid can fully preserve the histology and genetic characteristics of the original tumor, it provides a reliable model for preclinical drug screening, establishment of breast cancer organoid biobanks, research into the mechanisms of tumor development, and determination of cancer targets. It has promoted personalized treatment for clinical breast cancer patients. This article mainly focuses on recent research progress and applications of organoid technology in breast cancer, discussing the current limitations and prospects of breast cancer organoid technology. [ABSTRACT FROM AUTHOR]

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. 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. 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. 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. [ABSTRACT FROM AUTHOR]

Mitoribosomes are essential for the production of biological energy. The Human Mitoribosomal Small Subunit unit (MRPS) family, responsible for encoding mitochondrial ribosomal small subunits, is actively engaged in protein synthesis within the mitochondria. Intriguingly, MRPS family genes appear to play a role in cancer. A multistep process was employed to establish a risk model associated with MRPS genes, aiming to delineate the immune and pharmacogenomic landscapes in clear cell renal cell carcinoma (ccRCC). MRPScores were computed for individual patients to assess their responsiveness to various treatment modalities and their susceptibility to different therapeutic targets and drugs. While MRPS family genes have been implicated in various cancers as oncogenes, our findings reveal a contrasting tumor suppressor role for MRPS genes in ccRCC. Utilizing an MRPS‐related risk model, we observed its excellent prognostic capability in predicting survival outcomes for ccRCC patients. Remarkably, the subgroup with high MRPS‐related scores (MRPScore) displayed poorer prognosis but exhibited a more robust response to immunotherapy. Through in silico screening of 2183 drug targets and 1646 compounds, we identified two targets (RRM2 and OPRD1) and eight agents (AZ960, carmustine, lasalocid, SGI‐1776, AZD8055_1059, BPD.00008900_1998, MK.8776_2046, and XAV939_1268) with potential therapeutic implications for high‐MRPScore patients. Our study represents the pioneering effort in proposing that molecular classification, diagnosis, and treatment strategies can be formulated based on MRPScores. Indeed, a high MRPScore profile appears to elevate the risk of tumor progression and mortality, potentially through its influence on immune regulation. This suggests that the MRPS‐related risk model holds promise as a prognostic predictor and may offer novel insights into personalized therapeutic strategies. [ABSTRACT FROM AUTHOR]

Since many microfluidic devices have limited drug dose order of gradients and incorporate 2D cell culture, we here present a multi-layered platform with linear and logarithmic gradients with 3D-cell culturing chambers. By employing Hagen–Poiseuille flow resistance equation and the parallel electric schematics, we determined the appropriate channel dimensions to achieve the desired target concentrations (100%, 50%, 20%, 10%, 5%, 2%, 1%, 0%). To validate the gradient formation against theoretical values, we introduced a solution containing fluorescein into the microfluidic chip. Moreover, cell culturing chambers were spaced out laterally for every 9 mm, aligning with the dimensions with the standard plate reader, providing enhanced usability. Vertical layout of the chip minimized the lateral dimension required for housing various components while maintaining a favorable height for imaging. By preventing the need to use external tubing to connect concentration gradient generator and cell culturing chamber modules, our platform holds promise in facilitating the integration of microfluidics into drug evaluation processes. To demonstrate use of this flexible platform, we tested two chemotherapy drugs against human bladder cancer cells (T24) embedded in 3D fibrin gel and evaluated their cell viability and proliferation rate. IC50 values were extracted for cells exposed to varying doses of cisplatin, gemcitabine, and gemcitabine with a fixed cisplatin dose, confirming the enhanced apoptosis of the bladder cancer cells and the advantages of combination chemotherapy. This simple multi-layered device may accelerate screening of anti-cancer drugs for a specific cell type by extracting optimal dosage for two drugs. [ABSTRACT FROM AUTHOR]

Collecting duct carcinoma (CDC) is an aggressive rare subtype of kidney cancer with unmet clinical needs. Little is known about its underlying molecular alterations and etiology, primarily due to its rarity, and lack of preclinical models. This study aims to comprehensively characterize molecular alterations in CDC and identify its therapeutic vulnerabilities. Through whole-exome and transcriptome sequencing, we identified KRAS hotspot mutations (G12A/D/V) in 3/13 (23%) of the patients, in addition to known TP53, NF2 mutations. 3/13 (23%) patients carried a mutational signature (SBS22) caused by aristolochic acid (AA) exposures, known to be more prevalent in Asia, highlighting a geologically specific disease etiology. We further discovered that cell cycle-related pathways were the most predominantly dysregulated pathways. Our drug screening with our newly established CDC preclinical models identified a CDK9 inhibitor LDC000067 that specifically inhibited CDC tumor growth and prolonged survival. Our study not only improved our understanding of oncogenic molecular alterations of Asian CDC, but also identified cell-cycle machinery as a therapeutic vulnerability, laying the foundation for clinical trials to treat patients with such aggressive cancer. Synopsis: Collecting duct carcinoma (CDC) is an aggressive kidney cancer without effective treatment. Our study not only enhanced our scientific understanding of the oncogenic alterations prevalent in Asian CDC, but has also identified cell-cycle machinery as a potential target for therapeutic intervention. Mutations in KRAS hotspot and TP53 were predominantly identified in Asian CDC patients, shedding light on the genetic landscape of this cancer. Aristolochic acid (AA) mutational signature was identified in CDC tumors, providing valuable insights for cancer prevention strategies. Dysregulation of cell-cycle machinery was observed in both Caucasian and Asian CDC patients, indicating similar disease pathobiology. We have established a CDC patient-derived xenograft (PDX) and cell line models to facilitate drug screening and testing. Through our screening efforts, we have identified and validated a CDK9 inhibitor, LDC000067, which specifically inhibited CDC tumor growth and improved overall survival. Collecting duct carcinoma (CDC) is an aggressive kidney cancer without effective treatment. Our study not only enhanced our scientific understanding of the oncogenic alterations prevalent in Asian CDC, but has also identified cell-cycle machinery as a potential target for therapeutic intervention. [ABSTRACT FROM AUTHOR]

Primary liver cancer (PLC) is one of the most common malignant gastrointestinal tumors worldwide. Limited by the shortage of liver transplantation donors and the heterogeneity of tumors, patients with liver cancer lack effective treatment options, which leads to rapid progression and metastasis. Currently, preclinical models of PLC fall short of clinical reality and are limited in their response to disease progression and the effectiveness of drug therapy. Organoids are in vitro three-dimensional cultured preclinical models with a high degree of heterogeneity that preserve the histomorphological and genomic features of primary tumors. Liver cancer organoids have been widely used for drug screening, new target discovery, and precision medicine; thus representing a promising tool to study PLC. Here, we summarize the progress of research on liver cancer organoids and their potential application as disease models. This review provides a comprehensive introduction to this emerging technology and offers new ideas for researchers to explore in the field of precision medicine. [ABSTRACT FROM AUTHOR]

Organoid technology has been developed rapidly in the past decade, which involves the exploration of the mechanism of development, regeneration and various diseases, and intersects among multiple disciplines. Thousands of literature on 3D-culture or organoids have been published in the research areas of cell biology tissue engineering, nanoscience, oncology and so on, resulting in it being challenging for researchers to timely summarize these studies. Bibliometric statistics is a helpfulway to help researchers clarify the above issues efficiently andmanage the whole landscape systematically. In our study, all original articles on organoids were included in the Web of Science database from January 2009 to May 2024, and related information was collected and analyzed using Excel software, "bibliometrix" packages of the R software, VOSviewer and CiteSpace. As results, a total of 6222 papers were included to classify the status quo of the organoids and predict future research areas. Our findings highlight a growing trend in publications related to organoids, with the United States and Netherlands leading in this field. The University of California System, Harvard University, Utrecht University and Utrecht University Medical Center have emerged as pivotal contributors and the key authors in the field include Clevers, H, Beekman, JM and Spence JR. Our results also revealed that the research hotspots and trends of organoids mainly focused on clinical treatment, drug screening, and the application of materials and technologies such as "hydrogel" and "microfluidic technology" in organoids. Next, we had an in-depth interpretation of the development process of organoid research area, including the emergence of technology, the translation from bench to bedsides, the profiles of the most widely studied types of organoids, the application of materials and technologies, and the emerging organoid-immune co-cultures trends. Furthermore,we also discussed the pitfalls, challenges and prospects of organoid technology. In conclusion, this study provides readers straightforward and convenient access to the organoid research field. [ABSTRACT FROM AUTHOR]

Thiosemicarbazones and their metal complexes have been studied for their biological activities against bacteria, cancer cells and protozoa. Short-term in vitro treatment with one gold (III) complex (C3) and its salicyl-thiosemicarbazone ligand (C4) selectively inhibited proliferation of T. gondii. Transmission Electron Microscopy (TEM) detected transient structural alterations in the parasitophorous vacuole membrane and the tachyzoite cytoplasm, but the mitochondrial membrane potential appeared unaffected by these compounds. Proteins potentially interacting with C3 and C4 were identified using differential affinity chromatography coupled with mass spectrometry (DAC-MS). Moreover, long-term in vitro treatment was performed to investigate parasitostatic or parasiticidal activity of the compounds. DAC-MS identified 50 ribosomal proteins binding both compounds, and continuous drug treatments for up to 6 days caused the loss of efficacy. Parasite tolerance to both compounds was, however, rapidly lost in their absence and regained shortly after re-exposure. Proteome analyses of six T. gondii ME49 clones adapted to C3 and C4 compared to the non-adapted wildtype revealed overexpression of ribosomal proteins, of two transmembrane proteins involved in exocytosis and of an alpha/beta hydrolase fold domain-containing protein. Results suggest that C3 and C4 may interfere with protein biosynthesis and that adaptation may be associated with the upregulated expression of tachyzoite transmembrane proteins and transporters, suggesting that the in vitro drug tolerance in T. gondii might be due to reversible, non-drug specific stress-responses mediated by phenotypic plasticity. [ABSTRACT FROM AUTHOR]

Cancer is a leading cause of death worldwide. Around one-third of the total global cancer incidence and mortality are related to gastrointestinal (GI) cancers. Over the past few years, rapid developments have been made in patient-derived organoid (PDO) models for gastrointestinal cancers. By closely mimicking the molecular properties of their parent tumors in vitro, PDOs have emerged as powerful tools in personalized medicine and drug discovery. Here, we review the current literature on the application of PDOs of common gastrointestinal cancers in the optimization of drug treatment strategies in the clinic and their rising importance in pre-clinical drug development. We discuss the advantages and limitations of gastrointestinal cancer PDOs and outline the microfluidics-based strategies that improve the throughput of PDO models in order to extract the maximal benefits in the personalized medicine and drug discovery process. [ABSTRACT FROM AUTHOR]

Computational pharmacogenomics can potentially identify new indications for already approved drugs and pinpoint compounds with similar mechanism-of-action. Here, we used an integrated drug repositioning approach based on transcriptomics data and structure-based virtual screening to identify compounds with gene signatures similar to three known proteasome inhibitors (PIs; bortezomib, MG-132, and MLN-2238). In vitro validation of candidate compounds was then performed to assess proteasomal proteolytic activity, accumulation of ubiquitinated proteins, cell viability, and drug-induced expression in A375 melanoma and MCF7 breast cancer cells. Using this approach, we identified six compounds with PI properties ((-)-kinetin-riboside, manumycin-A, puromycin dihydrochloride, resistomycin, tegaserod maleate, and thapsigargin). Although the docking scores pinpointed their ability to bind to the β5 subunit, our in vitro study revealed that these compounds inhibited the β1, β2, and β5 catalytic sites to some extent. As shown with bortezomib, only manumycin-A, puromycin dihydrochloride, and tegaserod maleate resulted in excessive accumulation of ubiquitinated proteins and elevated HMOX1 expression. Taken together, our integrated drug repositioning approach and subsequent in vitro validation studies identified six compounds demonstrating properties similar to proteasome inhibitors. [ABSTRACT FROM AUTHOR]

Variants (pathogenic) of the LMNA gene are a common cause of familial dilated cardiomyopathy (DCM), which is characterised by early-onset atrioventricular (AV) block, atrial fibrillation and ventricular tachyarrhythmias (VTs), and progressive heart failure. The unstable internal nuclear lamina observed in LMNA-related DCM is a consequence of the disassembly of lamins A and C. This suggests that LMNA variants produce truncated or alternative forms of protein that alter the nuclear structure and the signalling pathway related to cardiac muscle diseases. To date, the pathogenic mechanisms and phenotypes of LMNA-related DCM have been studied using different platforms, such as patient-specific induced pluripotent stem-cell-derived cardiomyocytes (iPSC-CMs) and transgenic mice. In this review, point variants in the LMNA gene that cause autosomal dominantly inherited forms of LMNA-related DCM are summarised. In addition, potential therapeutic targets based on preclinical studies of LMNA variants using transgenic mice and human iPSC-CMs are discussed. They include mitochondria deficiency, variants in nuclear deformation, chromatin remodelling, altered platelet-derived growth factor and ERK1/2-related pathways, and abnormal calcium handling. [ABSTRACT FROM AUTHOR]

Computational approaches for small-molecule drug discovery now regularly scale to the consideration of libraries containing billions of candidate small molecules. One promising approach to increased the speed of evaluating billion-molecule libraries is to develop succinct representations of each molecule that enable the rapid identification of molecules with similar properties. Molecular fingerprints are thought to provide a mechanism for producing such representations. Here, we explore the utility of commonly used fingerprints in the context of predicting similar molecular activity. We show that fingerprint similarity provides little discriminative power between active and inactive molecules for a target protein based on a known active—while they may sometimes provide some enrichment for active molecules in a drug screen, a screened data set will still be dominated by inactive molecules. We also demonstrate that high-similarity actives appear to share a scaffold with the query active, meaning that they could more easily be identified by structural enumeration. Furthermore, even when limited to only active molecules, fingerprint similarity values do not correlate with compound potency. In sum, these results highlight the need for a new wave of molecular representations that will improve the capacity to detect biologically active molecules based on their similarity to other such molecules. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Context: Accurately predicting plasma protein binding rate (PPBR) and oral bioavailability (OBA) helps to better reveal the absorption and distribution of drugs in the human body and subsequent drug design. Although machine learning models have achieved good results in prediction accuracy, they often suffer from insufficient accuracy when dealing with data with irregular topological structures. Methods: In view of this, this study proposes a pharmacokinetic parameter prediction framework based on graph convolutional networks (GCN), which predicts the PPBR and OBA of small molecule drugs. In the framework, GCN is first used to extract spatial feature information on the topological structure of drug molecules, in order to better learn node features and association information between nodes. Then, based on the principle of drug similarity, this study calculates the similarity between small molecule drugs, selects different thresholds to construct datasets, and establishes a prediction model centered on the GCN algorithm. The experimental results show that compared with traditional machine learning prediction models, the prediction model constructed based on the GCN method performs best on PPBR and OBA datasets with an inter-molecular similarity threshold of 0.25, with MAE of 0.155 and 0.167, respectively. In addition, in order to further improve the accuracy of the prediction model, GCN is combined with other algorithms. Compared to using a single GCN method, the distribution of the predicted values obtained by the combined model is highly consistent with the true values. In summary, this work provides a new method for improving the rate of early drug screening in the future. [ABSTRACT FROM AUTHOR]

Drug discovery is a sophisticated process that incorporates scientific innovations and cutting-edge technologies. Compared to traditional bioactivity-based screening methods, encoding and display technologies for combinatorial libraries have recently advanced from proof-of-principle experiments to promising tools for pharmaceutical hit discovery due to their high screening efficiency, throughput, and resource minimization. This review systematically summarizes the development history, typology, and prospective applications of encoding and displayed technologies, including phage display, ribosomal display, mRNA display, yeast cell display, one-bead one-compound, DNA-encoded, peptide nucleic acid-encoded, and new peptide-encoded technologies, and examples of preclinical and clinical translation. We discuss the progress of novel targeted therapeutic agents, covering a spectrum from small-molecule inhibitors and nonpeptidic macrocycles to linear, monocyclic, and bicyclic peptides, in addition to antibodies. We also address the pending challenges and future prospects of drug discovery, including the size of screening libraries, advantages and disadvantages of the technology, clinical translational potential, and market space. This review is intended to establish a comprehensive high-throughput drug discovery strategy for scientific researchers and clinical drug developers. Encoding and display technologies for combinatorial libraries have gained popularity in drug discovery landscapes, attributed to their enhanced screening efficiency, throughput, and contribution to reducing drug discovery timelines and expenditures. [Display omitted] [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AMR) has emerged as a significant threat to public health, particularly in infections caused by critically important Gram-negative bacteria. The development of novel antibiotics has its limitations, and therefore it is crucial to explore alternative strategies to effectively combat infections with resistant pathogens. In this context, the present study investigated the antibacterial potency of 560 compounds against the multidrug-resistant (MDR) strains of Klebsiella pneumoniae and Serratia marcescens. The evaluated compounds were selected from the Pandemic Response Box (PRB) and COVID Box (CB) and subjected to assays to determine the inhibitory concentration (IC), minimum bactericidal concentration (MBC), and biofilm formation. Further, the effects of these compounds on membrane integrity were assessed through protein quantification. Several of the evaluated compounds, including fusidic acid, MMV1580853, and MMV1634399, exhibited a significant reduction in biofilm formation and growth in K. pneumoniae. Trimethoprim exhibited potential against S. marcescens. The IC values of the compounds indicated significant microbial growth inhibition at various concentrations. These findings underscore the potency of the existing antibiotics and novel compounds in combating the MDR strains of bacteria. The importance of reconsidering the known antibiotics and utilizing drug repositioning strategies to address the increasing risk of AMR is highlighted. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) spheroid models are crucial for cancer research, offering more accurate insights into tumour biology and drug responses than traditional 2D cell cultures. However, inconsistent and low-throughput spheroid production has hindered their application in drug screening. Here, we present an automated high-throughput platform for a spheroid selection, fabrication, and sorting system (SFSS) to produce uniform gelatine-encapsulated spheroids (GESs) with high efficiency. SFSS integrates advanced imaging, analysis, photo-triggered fabrication, and microfluidic sorting to precisely control spheroid size, shape, and viability. Our data demonstrate that our SFSS can produce over 50 GESs with consistent size and circularity in 30 min with over 97% sorting accuracy while maintaining cell viability and structural integrity. We demonstrated that the GESs can be used for drug screening and potentially for various assays. Thus, the SFSS could significantly enhance the efficiency of generating uniform spheroids, facilitating their application in drug development to investigate complex biological systems and drug responses in a more physiologically relevant context. [ABSTRACT FROM AUTHOR]

Fluorescence flow cytometry is a powerful instrument to distinguish cells or particles labelled with high-specificity fluorophores. However, traditional flow cytometry is complex, bulky, and inconvenient for users to adjust fluorescence channels. In this paper, we present a modular fluorescence flow cytometry (M-FCM) system in which fluorescence channels can be flexibly arranged. Modules for particle focusing and fluorescence detection were developed. After hydrodynamical focusing, the cells were measured in the detection modules, which were integrated with in situ illumination and fluorescence detection. The signal-to-noise ratio of the detection reached to 33.2 dB. The crosstalk among the fluorescence channels was eliminated. The M-FCM system was applied to evaluate cell viability in drug screening, agreeing well with the commercial cytometry. The modular cytometry presents several outstanding features: flexibility in setting fluorescence channels, cost efficiency, compact construction, ease of operation, and the potential to upgrade for multifunctional measurements. The modular cytometry provides a multifunctional platform for various biophysical measurements, e.g., electrical impedance and refractive-index detection. The proposed work paves an innovative avenue for the multivariate analysis of cellular characteristics. [ABSTRACT FROM AUTHOR]

Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) have emerged as a promising tool for studying cardiac physiology and drug responses. However, their use is largely limited by an immature phenotype and lack of high-throughput analytical methodology. In this study, we developed a high-throughput testing platform utilizing hPSC-CMs to assess the cardiotoxicity and effectiveness of drugs. Following an optimized differentiation and maturation protocol, hPSC-CMs exhibited mature CM morphology, phenotype, and functionality, making them suitable for drug testing applications. We monitored intracellular calcium dynamics using calcium imaging techniques to measure spontaneous calcium oscillations in hPSC-CMs in the presence or absence of test compounds. For the cardiotoxicity test, hPSC-CMs were treated with various compounds, and calcium flux was measured to evaluate their effects on calcium dynamics. We found that cardiotoxic drugs withdrawn due to adverse drug reactions, including encainide, mibefradil, and cetirizine, exhibited toxicity in hPSC-CMs but not in HEK293-hERG cells. Additionally, in the effectiveness test, hPSC-CMs were exposed to ATX-II, a sodium current inducer for mimicking long QT syndrome type 3, followed by exposure to test compounds. The observed changes in calcium dynamics following drug exposure demonstrated the utility of hPSC-CMs as a versatile model system for assessing both cardiotoxicity and drug efficacy. Overall, our findings highlight the potential of hPSC-CMs in advancing drug discovery and development, which offer a physiologically relevant platform for the preclinical screening of novel therapeutics. [ABSTRACT FROM AUTHOR]

In this study, we screened a chemical library to find potent anticancer compounds that are less cytotoxic to non-cancerous cells. This study revealed that pyrazole PTA-1 is a potent anticancer compound. Additionally, we sought to elucidate its mechanism of action (MOA) in triple-negative breast cancer cells. Cytotoxicity was analyzed with the differential nuclear staining assay (DNS). Additional secondary assays were performed to determine the MOA of the compound. The potential MOA of PTA-1 was assessed using whole RNA sequencing, Connectivity Map (CMap) analysis, in silico docking, confocal microscopy, and biochemical assays. PTA-1 is cytotoxic at a low micromolar range in 17 human cancer cell lines, demonstrating less cytotoxicity to non-cancerous human cells, indicating a favorable selective cytotoxicity index (SCI) for the killing of cancer cells. PTA-1 induced phosphatidylserine externalization, caspase-3/7 activation, and DNA fragmentation in triple-negative breast MDA-MB-231 cells, indicating that it induces apoptosis. Additionally, PTA-1 arrests cells in the S and G2/M phases. Furthermore, gene expression analysis revealed that PTA-1 altered the expression of 730 genes at 24 h (198 upregulated and 532 downregulated). A comparison of these gene signatures with those within CMap indicated a profile similar to that of tubulin inhibitors. Subsequent studies revealed that PTA-1 disrupts microtubule organization and inhibits tubulin polymerization. Our results suggest that PTA-1 is a potent drug with cytotoxicity to various cancer cells, induces apoptosis and cell cycle arrest, and inhibits tubulin polymerization, indicating that PTA-1 is an attractive drug for future clinical cancer treatment. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Many drug and therapeutic modalities have emerged over the past few years. However, successful commercialization is dependent on their safety and efficacy evaluations. Several preclinical models are available for drug-screening and safety evaluations, including cellular- and molecular-level models, tissue and organoid models, and animal models. Organoids are three-dimensional cell cultures derived from primary tissues or stem cells that are structurally and functionally similar to the original organs and can self-renew, and they are used to establish various disease models. Human hepatobiliary organoids have been used to study the pathogenesis of diseases, such as hepatitis, liver fibrosis, hepatocellular carcinoma, primary sclerosing cholangitis and biliary tract cancer, as they retain the physiological and histological characteristics of the liver and bile ducts. Here, we review recent research progress in validating drug toxicity, drug screening and personalized therapy for hepatobiliary-related diseases using human hepatobiliary organoid models, discuss the challenges encountered in current research and evaluate the possible solutions. [ABSTRACT FROM AUTHOR]

Endothelial dysfunction is a central contributor to the development of most cardiovascular diseases and is characterised by the reduced synthesis or bioavailability of the vasodilator nitric oxide together with other abnormalities such as inflammation, senescence, and oxidative stress. The use of patient-specific and genome-edited human pluripotent stem cell-derived endothelial cells (hPSC-ECs) has shed novel insights into the role of endothelial dysfunction in cardiovascular diseases with strong genetic components such as genetic cardiomyopathies and pulmonary arterial hypertension. However, their utility in studying complex multifactorial diseases such as atherosclerosis, metabolic syndrome and heart failure poses notable challenges. In this review, we provide an overview of the different methods used to generate and characterise hPSC-ECs before comprehensively assessing their effectiveness in cardiovascular disease modelling and high-throughput drug screening. Furthermore, we explore current obstacles that will need to be overcome to unleash the full potential of hPSC-ECs in facilitating patient-specific precision medicine. Addressing these challenges holds great promise in advancing our understanding of intricate cardiovascular diseases and in tailoring personalised therapeutic strategies. [Display omitted] [ABSTRACT FROM AUTHOR]

• Isogenic CF cell models generated by CRISPR/Cas9 gene editing. • Four cell models each has a specific CFTR mutation of class I, II, III or IV. • Cell models integrated with halide-sensitive fluorescent reporter. • Capable of high-throughput screening of novel CF therapeutics. Cystic fibrosis (CF) is a single-gene disorder that affects the lung, digestive system, and other organs. Mutations in the CF transmembrane conductance regulator (CFTR) gene are classified into several classes based on their pathogenic mechanism and clinical severity. The distinct and heterogeneous clinical behavior of each CF class and the respective CFTR mutations have made the development of a durable therapy for all CF patients extremely challenging. While the FDA-approved drug elexacaftor/tezacaftor/ivacaftor (Trikafta) benefits CF patients carrying at least one F508del mutation in CFTR, it's not effective for many CF patients carrying a variety of other CFTR mutations. To establish a better understanding of CF pathophysiology and aid the development of novel therapeutics for different classes of CF patients, we have created four CF-mutation-specific cell models that recapitulate respectively four distinct CF classes and disease phenotypes, as confirmed by sequencing, CFTR mRNA and protein quantification. The channel function of each cell model was first validated using a well-established FLIPR (Fluorescent Imaging Plate Reader) membrane potential assay and then assessed by the YFP-based functional assay. Integrated with a halide-sensitive fluorescent reporter, these CF cell models can be used for high-throughput drug screening, as demonstrated by a proof-of-concept study using Trikafta. These cell models have the potential to advance CFTR mutation-specific therapies thus addressing the unmet needs of CF patients with rare mutations. [ABSTRACT FROM AUTHOR]

G-protein coupled receptors (GPCRs), crucial in various diseases, are targeted of over 40% of approved drugs. However, the reliable acquisition of experimental GPCRs structures is hindered by their lipid-embedded conformations. Traditional protein–ligand interaction models falter in GPCR–drug interactions, caused by limited and low-quality structures. Generalized models, trained on soluble protein–ligand pairs, are also inadequate. To address these issues, we developed two models, DeepGPCR_BC for binary classification and DeepGPCR_RG for affinity prediction. These models use non-structural GPCR–ligand interaction data, leveraging graph convolutional networks and mol2vec techniques to represent binding pockets and ligands as graphs. This approach significantly speeds up predictions while preserving critical physical–chemical and spatial information. In independent tests, DeepGPCR_BC surpassed Autodock Vina and Schrödinger Dock with an area under the curve of 0.72, accuracy of 0.68 and true positive rate of 0.73, whereas DeepGPCR_RG demonstrated a Pearson correlation of 0.39 and root mean squared error of 1.34. We applied these models to screen drug candidates for GPR35 (Q9HC97), yielding promising results with three (F545-1970, K297-0698, S948-0241) out of eight candidates. Furthermore, we also successfully obtained six active inhibitors for GLP-1R. Our GPCR-specific models pave the way for efficient and accurate large-scale virtual screening, potentially revolutionizing drug discovery in the GPCR field. [ABSTRACT FROM AUTHOR]

In recent years, the rapid emergence of 3D organoid technology has garnered significant attention from researchers. These miniature models accurately replicate the structure and function of human tissues and organs, offering more physiologically relevant platforms for cancer research. These intricate 3D structures not only serve as promising models for studying human cancer, but also significantly contribute to the advancement of various potential applications in the field of cancer research. To date, organoids have been efficiently constructed from both normal and malignant tissues originating from patients. Using such bioengineering platforms, simulations of infections and cancer processes, mutations and carcinogenesis can be achieved, and organoid technology is also expected to facilitate drug testing and personalized therapies. In conclusion, regenerative medicine has the potential to enhance organoid technology and current transplantation treatments by utilizing genetically identical healthy organoids as substitutes for irreversibly deteriorating diseased organs. This review explored the evolution of cancer organoids and emphasized the significant role these models play in fundamental research and the advancement of personalized medicine in oncology. [ABSTRACT FROM AUTHOR]

Organoid-on-a-chip technology emerges as a groundbreaking interdisciplinary innovation of the 21st century, cultivating human cells in three-dimensions ex vivo to form organoids. These organoids replicate human physiological and pathological conditions as well as functions akin to human organs. Integratable with electronic chips, this technology finds extensive applications in drug screening, safety evaluation, personalized medicine, in vitro diagnosis. As a recent avant-grade technological advancement, organoid-on-a-chip demonstrates several benefits over traditional cell-based animal testing methods used for drug screening, such as lower costs, better animal welfare, higher precision, and wider applicability. This positions it at the forefront of future drug screening and safety evaluation methodologies. The use of organoid chips in drug screening encapsulates a plethora of inherent biochemical principles. Incorporating organoid-on-chip related knowledge into university curricula plays a significant role in enabling medical and pharmaceutical students to stay abreast of the forefront in drug development and to grasp biochemical concepts in a more systematic manner. Therefore, this paper begins with the concept of organoid chips, exploring their design, principles, and applications in drug screening, while anticipating their future developments. Simultaneously, it focuses on the multidisciplinary interdisciplinary characteristics of organoid chips in fields, such as cell biology, medicinal chemistry, biochemistry, and electronic information science, analyzing the inherent biochemical principles. In line with this, the paper proposes an 8 lecture-course design for the Biochemistry curriculum, aiming to meet the evolving educational demands for nurturing innovative talents in the pharmaceutical sector. [ABSTRACT FROM AUTHOR]

Background: The SARS‐CoV‐2 pandemic has spurred an unparalleled scientific endeavor to elucidate the virus' structure, infection mechanisms, and pathogenesis. Two‐dimensional culture systems have been instrumental in shedding light on numerous aspects of COVID‐19. However, these in vitro systems lack the physiological complexity to comprehend the infection process and explore treatment options. Three‐dimensional (3D) models have been proposed to fill the gap between 2D cultures and in vivo studies. Specifically, spheroids, composed of lung cell types, have been suggested for studying SARS‐CoV‐2 infection and serving as a drug screening platform. Methods: 3D lung spheroids were prepared by coculturing human alveolar or bronchial epithelial cells with human lung stromal cells. The morphology, size, and ultrastructure of spheroids before and after SARS‐CoV‐2 infection were analyzed using optical and electron microscopy. Immunohistochemistry was used to detect spike protein and, thus, the virus presence in the spheroids. Multiplex analysis elucidated the cytokine release after virus infection. Results: The spheroids were stable and kept their size and morphology after SARS‐CoV‐2 infection despite the presence of multivesicular bodies, endoplasmic reticulum rearrangement, tubular compartment‐enclosed vesicles, and the accumulation of viral particles. The spheroid responded to the infection releasing IL‐6 and IL‐8 cytokines. Conclusion: This study demonstrates that coculture spheroids of epithelial and stromal cells can serve as a cost‐effective infection model for the SARS‐CoV‐2 virus. We suggest using this 3D spheroid as a drug screening platform to explore new treatments related to the cytokines released during virus infection, especially for long COVID treatment. [ABSTRACT FROM AUTHOR]

Traditional drug screening methods typically focus on a single protein target and exhibit limited efficiency due to the multifactorial nature of most diseases, which result from disturbances within complex networks of protein–protein interactions rather than single gene abnormalities. Addressing this limitation requires a comprehensive drug screening strategy. Network medicine is rooted in systems biology and provides a comprehensive framework for understanding disease mechanisms, prevention, and therapeutic innovations. This approach not only explores the associations between various diseases but also quantifies the relationships between disease genes and drug targets within interactome networks, thus facilitating the prediction of drug–disease relationships and enabling the screening of therapeutic drugs for specific complex diseases. An increasing body of research supports the efficiency and utility of network-based strategies in drug screening. This review highlights the transformative potential of network medicine in virtual therapeutic screening for complex diseases, offering novel insights and a robust foundation for future drug discovery endeavors. [ABSTRACT FROM AUTHOR]

Ongoing obstacles in preclinical drug testing have raised significant concerns within the pharmaceutical industry. Recently, utilizing the potential of three‐dimensional (3D) bioprinting offers a solution for creating tissue models for screening of the effectiveness and safety of new drugs. In this study, the anti‐inflammatory potential of garlic extracts is assessed, specifically N‐Benzyl‐N‐methyl‐dodecan‐1‐amine (BMDA), using a 3D bioprinted artificial skin model. Comprehensive physicochemical characterization and immunocytochemical analysis demonstrate that the 3D bioprinted skin model exhibits structures and functions resembling human skin. BMDA treatment in a prepared skin model reveals its capacity to mitigate H2O2‐induced oxidative stress and trigger anti‐inflammatory responses. Notably, BMDA reduces the expression of pro‐inflammatory cytokines and chemokines by downregulating NF‐κB and mitogen‐activated protein kinase inflammatory signaling pathways. In summary, our findings highlight the potential of an artificial skin model as a robust platform for the development of new drugs. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In recent years, with rapid development of technology of regenerative medicine and tissue engineering, brain organoids, as an innovative in vitro model system, have become a hot spot in neuroscience research and drug development. Brain organoids simulate the complex structure and function of the human brain in terms of reproducing key processes of brain development in vitro, providing an unprecedented platform for understanding the mechanisms of neurological diseases and of evaluating drug efficacy and toxicity. This review summarizes the latest research progress in brain organoid technology, particularly its application in drug development and in exploring challenges and orientation of future development.

Primary liver cancer is a leading cause of death worldwide. To create advanced treatments for primary liver cancer, studies have utilized models such as 2D cell culture and in vivo animal models. Recent developments in cancer organoids have created the possibility for 3D in vitro cultures that recapitulates the cancer cell structure and operation as well as the tumor microenvironment (TME). However, before organoids can be directly translated to clinical use, tissue processing and culture medium must be standardized with unified protocols to decrease variability in results. Herein, we present the wide variety of published methodologies used to derive liver cancer organoids from patient tumor tissues. Additionally, we summarize validation methodologies for organoids in terms of marker expression levels with immunohistochemistry as well as the presence of mutations and variants through RNA-sequencing. Primary liver cancer organoids have exciting applications allowing for faster drug testing at a larger scale. Primary liver cancer organoids also assisit in uncovering new mechanisms. Through the coculture of different immune cells and cancer organoids, organoids are now better able to recapitulate the liver cancer TME. In addition, it further aids in the investigation of drug development and drug resistance. Lastly, we posit that the usage of liver cancer organoids in animal models provides researchers a methodology to overcome the current limitations of culture systems.

Abstract Collecting duct carcinoma (CDC) is an aggressive rare subtype of kidney cancer with unmet clinical needs. Little is known about its underlying molecular alterations and etiology, primarily due to its rarity, and lack of preclinical models. This study aims to comprehensively characterize molecular alterations in CDC and identify its therapeutic vulnerabilities. Through whole-exome and transcriptome sequencing, we identified KRAS hotspot mutations (G12A/D/V) in 3/13 (23%) of the patients, in addition to known TP53, NF2 mutations. 3/13 (23%) patients carried a mutational signature (SBS22) caused by aristolochic acid (AA) exposures, known to be more prevalent in Asia, highlighting a geologically specific disease etiology. We further discovered that cell cycle-related pathways were the most predominantly dysregulated pathways. Our drug screening with our newly established CDC preclinical models identified a CDK9 inhibitor LDC000067 that specifically inhibited CDC tumor growth and prolonged survival. Our study not only improved our understanding of oncogenic molecular alterations of Asian CDC, but also identified cell-cycle machinery as a therapeutic vulnerability, laying the foundation for clinical trials to treat patients with such aggressive cancer.

Abstract Primary liver cancer (PLC) is one of the most common malignant gastrointestinal tumors worldwide. Limited by the shortage of liver transplantation donors and the heterogeneity of tumors, patients with liver cancer lack effective treatment options, which leads to rapid progression and metastasis. Currently, preclinical models of PLC fall short of clinical reality and are limited in their response to disease progression and the effectiveness of drug therapy. Organoids are in vitro three-dimensional cultured preclinical models with a high degree of heterogeneity that preserve the histomorphological and genomic features of primary tumors. Liver cancer organoids have been widely used for drug screening, new target discovery, and precision medicine; thus representing a promising tool to study PLC. Here, we summarize the progress of research on liver cancer organoids and their potential application as disease models. This review provides a comprehensive introduction to this emerging technology and offers new ideas for researchers to explore in the field of precision medicine.

Abstract Computational pharmacogenomics can potentially identify new indications for already approved drugs and pinpoint compounds with similar mechanism-of-action. Here, we used an integrated drug repositioning approach based on transcriptomics data and structure-based virtual screening to identify compounds with gene signatures similar to three known proteasome inhibitors (PIs; bortezomib, MG-132, and MLN-2238). In vitro validation of candidate compounds was then performed to assess proteasomal proteolytic activity, accumulation of ubiquitinated proteins, cell viability, and drug-induced expression in A375 melanoma and MCF7 breast cancer cells. Using this approach, we identified six compounds with PI properties ((-)-kinetin-riboside, manumycin-A, puromycin dihydrochloride, resistomycin, tegaserod maleate, and thapsigargin). Although the docking scores pinpointed their ability to bind to the β5 subunit, our in vitro study revealed that these compounds inhibited the β1, β2, and β5 catalytic sites to some extent. As shown with bortezomib, only manumycin-A, puromycin dihydrochloride, and tegaserod maleate resulted in excessive accumulation of ubiquitinated proteins and elevated HMOX1 expression. Taken together, our integrated drug repositioning approach and subsequent in vitro validation studies identified six compounds demonstrating properties similar to proteasome inhibitors.

Drug discovery is a sophisticated process that incorporates scientific innovations and cutting-edge technologies. Compared to traditional bioactivity-based screening methods, encoding and display technologies for combinatorial libraries have recently advanced from proof-of-principle experiments to promising tools for pharmaceutical hit discovery due to their high screening efficiency, throughput, and resource minimization. This review systematically summarizes the development history, typology, and prospective applications of encoding and displayed technologies, including phage display, ribosomal display, mRNA display, yeast cell display, one-bead one-compound, DNA-encoded, peptide nucleic acid-encoded, and new peptide-encoded technologies, and examples of preclinical and clinical translation. We discuss the progress of novel targeted therapeutic agents, covering a spectrum from small-molecule inhibitors and nonpeptidic macrocycles to linear, monocyclic, and bicyclic peptides, in addition to antibodies. We also address the pending challenges and future prospects of drug discovery, including the size of screening libraries, advantages and disadvantages of the technology, clinical translational potential, and market space. This review is intended to establish a comprehensive high-throughput drug discovery strategy for scientific researchers and clinical drug developers.

John D Rodriguez,1,2 Samantha Kerti,3 Adam Hamm,3 George W Ousler,1 Ethan Bensinger,1,2 Sadie Burnham,1,2 Mark B Abelson1,2,4,5 1Ora, Inc, Andover, MA, USA; 2Andover Eye Institute, Andover, MA, USA; 3Statistics and Data Corporation, Tempe, AZ, USA; 4Ophthalmology, Harvard Medical School, Cambridge, MA, USA; 5Mass Eye and Ear, Boston, MA, USACorrespondence: John D Rodriguez, Email jrodriguez@oraclinical.comPurpose: The absence of a standardized diagnostic method for clinical signs of Dry Eye Disease (DED) complicates clinical trials for future treatments. This paper evaluated Lissamine Green (LG) conjunctival staining as a valid, stable and modifiable endpoint for both clinical practice and clinical trials.Methods: Screening and pre-randomization data from two identically designed clinical trials for DED resulted in a pooled dataset of 494 subjects. Inclusion was based on reported symptoms, lissamine green (LG) conjunctival staining, Fluorescein (Fl) corneal and conjunctival staining, and Schirmer’s Test (ST). Outcome measures were assessed based on the modifiability of LG staining to exposure to a Controlled Adverse Environment (CAE®), correlation of LG to Fl staining, relative variation of LG staining scores and Schirmer test scores, and the correlation of LG staining with symptom scores.Results: The modifiability of LG conjunctival staining to environmental exposure was demonstrated, with nasal LG and FL staining displaying the most similar percent change. Nasal LG conjunctival staining scores for subjects with ST scores of less than 8mm were significantly higher than for subjects with ST greater than 8mm. LG staining scores were more consistent (25% change from baseline threshold) than ST scores. Finally, statistically significant correlations were found between LG staining and a number of symptom scores.Conclusion: This evaluation demonstrates the superiority of the utilization of a clinical endpoint focused on ocular surface damage. The reproducibility and modifiability of LG conjunctival staining to controlled adverse environment, coupled with its significant correlation with symptoms, positions it as an exemplary clinical sign endpoint for clinical management and in clinical trials. Our findings advocate for the adoption of LG conjunctival staining as a primary endpoint in both clinical research and drug development, offering a more effective means of identifying and addressing ocular surface damage in the realm of DED.Keywords: dry eye, conjunctiva, stain, lissamine green clinical trials, controlled adverse environment, disease models, drug screening, dry eye disease, efficacy endpoints

[Display omitted] 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. [ABSTRACT FROM AUTHOR]

Pancreatic cancer is a worldwide medical and health problem. Due to its high heterogeneity and malignant phenotype, the 5-year survival rate of pancreatic cancer is only 7.2%, which is a serious threat to human health. The biological mechanism and drug development research of pancreatic cancer often rely on the traditional two-dimensional culture models (cell lines) and patient-derived xenograft models. However, cell lines lack the three-dimensional environment and heterogeneity of the tumor, while xenograft models have the disadvantages of long culture time, low success rate and difficulty in carrying out high-throughput drug screening. There is an urgent need to develop three-dimensional culture models that can highly reflect the characteristics and molecular variation of pancreatic cancer. As a three-dimensional culture model developed in recent years, human-derived pancreatic cancer organoids are multicellular units extracted from tissue samples and embedded in extracellular matrix gels after mechanical and enzymatic digestion, which can reproduce the histological characteristics and organ characteristics of the original patient, and even have the functions of the original organ. With the continuous development and improvement of pancreatic cancer organoids culture system, its simple, economical and stable culture technology has been gradually established, which promotes the application of human pancreatic cancer organoids to high-throughput drug screening, individualized precision treatment and deeper pathogenesis and targeted drug development research. At the same time, human-derived pancreatic cancer organoids are also a novel semi-in vivo model for the study of clinical molecular typing of pancreatic cancer, especially for the study of etiology, molecular characteristics, histomorphology and somatic mutation burden of patients with high mutation rate and high heterogeneity. The construction of human pancreatic cancer organoid biobank with large sample size is a new platform for biology, basic medicine and clinical science oncology research, which provides a reliable resource for the in-depth study of the pathogenesis of pancreatic cancer and the development of treatment strategies. In summary, the research progress of human pancreatic cancer organoids promotes the application of laboratory models that recapitulate the characteristics of clinical patients, improves the connection between basic laboratory research and clinical patients, and provides clinical sources for drug screening, pathogenesis research, individualized treatment strategies and the construction of biobanks. Therefore, this article reviewed the latest research progress of human pancreatic cancer organoids, in order to provide reference for researchers engaged in the research of human pancreatic cancer organoids.

Background and purpose: Colorectal carcinoma (CRC) is a common malignant tumor with incidence and mortality rates second only to gastric cancer and esophageal cancer among digestive system malignancies. Increasing evidence suggests that immune cells play a significant role in the occurrence and development of CRC. The aim of this study was to construct a prognostic model related to immune cell-associated genes to predict the prognosis of CRC patients and enable precise management. Methods: Single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq) data, along with clinical information for colorectal cancer, were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Differential genes of immune cell subtypes were extracted, and genes related to prognosis were screened in TCGA data using Cox regression and LASSO regression, with external validation using GSE39582 and GSE41258. The prognostic model was used to analyze chemotherapy drug sensitivity, assess immunotherapy efficacy, analyze pathways related to risk scores, and perform clinical correlation analysis. Finally, the expression levels of model genes were validated in 10 fresh frozen CRC tissues with post-operative pathological examination and cell lines using real-time fluorescence quantitative polymerase chain reaction (RTFQ-PCR) and immunohistochemistry. All samples were approved by the Fudan University Shanghai Cancer Center Ethics Committee (No. 050432-4-2108*). Results: We defined 16 cell clusters based on the scRNA-seq dataset (GSE161277) and labeled these clusters as different cell types using the R package celldex. Differential analysis of immune cell subtypes yielded 374 differentially expressed genes. Using univariate Cox and LASSO analyses, we constructed a 9-gene risk prognostic model in CRC. This risk model exhibited reliable prognostic prediction performance and played an important role in predicting anti-tumor drug sensitivity, immunotherapy efficacy, potential molecular mechanisms, and clinical characteristics. Patients with high-risk scores had a lower probability of benefiting from immunotherapy. Conclusion: We constructed a 9-gene risk prognostic model based on the heterogeneity of immune cells in the CRC tumor microenvironment, which predicted the survival and treatment outcomes of CRC patients.

Microfluidic is a technology that allows the precise control of fluid in a micro-channel. With its advantages of high throughput and low cost, microfluidic technology has achieved good performance in various fields in recent years. Arthritis is a general term for a variety of joint diseases, which can be clinically manifested as joint pain and swelling, seriously affecting people's physical and mental health. At present, the causes of arthritis disease are still unknown, and existing disease models and treatment methods are still limited, so more treatments need to be developed. Microfluidic organ chip is a cutting-edge technology to build a bionic human organ model, which can reflect the structure and function characteristics of human organs by simulating the physiological environment of tissues and cells in vitro. This paper reviews the application of microfluidic technology in the modeling and treatment of arthritis, hoping to open up a new vision for the study of arthritis.

Objective·To establish various in vitro screening systems for the discovery of peptide inhibitors targeting the interaction between small ubiquitin-like modifier (SUMO)-activating enzyme subunit 1 (SAE1) and subunit 2 (SAE2), as well as to evaluate their advantages, disadvantages, and applicability to this research.Methods·The DNA fragments encoding human SAE1 and SAE2 were cloned into vector pET-28a, respectively, to generate protein SAE1 and SAE2. Purified proteins were used to establish screening assays, including isothermal calorimetry (ITC), fluorescence polarization (FP), surface plasmon resonance (SPR) and a fluorescence assay based on the SAE enzyme activity. The inhibitory activity of peptide candidates in different screening systems was examined, and their performance in terms of sensitivity, robustness, throughput and cost was evaluated.Results·The dissociation constant (Kd) of in vitro SAE1 and SAE2 interaction was determined to be 0.96 μmol/L by ITC, and PEPT7 was identified as the most potent peptide. However, the tracer of FP, which was derived from PEPT7, was not up to snuff due to its low affinity with SAE2. In the SPR assay, the Kd value (=1.13 μmol/L) of SAE1 and SAE2 interaction was in line with the results from ITC. The SAE enzyme activity-based screening assay revealed that HP1B, the most effective peptide, inhibited SAE with an half-maximal inhibitory concentration (IC50) of 15.72 μmol/L. The affinity of HP1B for SAE1 was determined to be 34.4 μmol/L by SPR.Conclusion·Several common screening systems for protein-protein interation (PPI) inhibitors are established and compared. Among them, ITC does not allow for high-throughput screening and it is difficult to accurately evaluate the low-affinity polypeptides with insignificant binding heat. The feasibility of FP relies heavily on the strong affinity between a tracer peptide and the protein target, making it unsuitable for the screening and optimization of low-affinity peptides. SPR is highly sensitive but the cost is high. The SAE enzyme activity-based assay stands out because it is a combination of high sensitivity, robustness, throughput and acceptable cost.

In the field of biomedical research, organoids represent a remarkable advancement that has the potential to revolutionize our approach to studying human diseases even before clinical trials. Organoids are essentially miniature 3D models of specific organs or tissues, enabling scientists to investigate the causes of diseases, test new drugs, and explore personalized medicine within a controlled laboratory setting. Over the past decade, organoid technology has made substantial progress, allowing researchers to create highly detailed environments that closely mimic the human body. These organoids can be generated from various sources, including pluripotent stem cells, specialized tissue cells, and tumor tissue cells. This versatility enables scientists to replicate a wide range of diseases affecting different organ systems, effectively creating disease replicas in a laboratory dish. This exciting capability has provided us with unprecedented insights into the progression of diseases and how we can develop improved treatments. In this paper, we will provide an overview of the progress made in utilizing organoids as preclinical models, aiding our understanding and providing a more effective approach to addressing various human diseases.