PRMT5 inhibition has a potent anti-tumor activity against adenoid cystic carcinoma of salivary glands.

Background: Adenoid cystic carcinoma (ACC) is a rare glandular malignancy, commonly originating in salivary glands of the head and neck. Given its protracted growth, ACC is usually diagnosed in advanced stage. Treatment of ACC is limited to surgery and/or adjuvant radiotherapy, which often fails to prevent disease recurrence, and no FDA-approved targeted therapies are currently available.

Nanoplasmonic sensing to study CO and oxygen adsorption and CO oxidation on size-selected Pt clusters.

The adsorption of CO and oxygen and CO oxidation on size-selected Pt clusters were studied by indirect nanoplasmonic sensing (INPS) in the pressure range of 1-100 Pa at = 418 K. CO adsorption was reversible, inducing a blue-shift in the localised surface plasmon resonance (LSPR) response, regardless of the initial CO pressure. We observe a plateau at approximately Δ = -0.

A small-molecule TNIK inhibitor targets fibrosis in preclinical and clinical models.

Idiopathic pulmonary fibrosis (IPF) is an aggressive interstitial lung disease with a high mortality rate. Putative drug targets in IPF have failed to translate into effective therapies at the clinical level. We identify TRAF2- and NCK-interacting kinase (TNIK) as an anti-fibrotic target using a predictive artificial intelligence (AI) approach.

PandaOmics: An AI-Driven Platform for Therapeutic Target and Biomarker Discovery.

PandaOmics is a cloud-based software platform that applies artificial intelligence and bioinformatics techniques to multimodal omics and biomedical text data for therapeutic target and biomarker discovery. PandaOmics generates novel and repurposed therapeutic target and biomarker hypotheses with the desired properties and is available through licensing or collaboration. Targets and biomarkers generated by the platform were previously validated in both and studies.

Defining the progeria phenome.

Progeroid disorders are a heterogenous group of rare and complex hereditary syndromes presenting with pleiotropic phenotypes associated with normal aging. Due to the large variation in clinical presentation the diseases pose a diagnostic challenge for clinicians which consequently restricts medical research. To accommodate the challenge, we compiled a list of known progeroid syndromes and calculated the mean prevalence of their associated phenotypes, defining what we term the 'progeria phenome'.

A comprehensive AI-driven analysis of large-scale omic datasets reveals novel dual-purpose targets for the treatment of cancer and aging.

As aging and tumorigenesis are tightly interconnected biological processes, targeting their common underlying driving pathways may induce dual-purpose anti-aging and anti-cancer effects. Our transcriptomic analyses of 16,740 healthy samples demonstrated tissue-specific age-associated gene expression, with most tumor suppressor genes downregulated during aging. Furthermore, a large-scale pan-cancer analysis of 11 solid tumor types (11,303 cases and 4431 control samples) revealed that many cellular processes, such as protein localization, DNA replication, DNA repair, cell cycle, and RNA metabolism, were upregulated in cancer but downregulated in healthy aging tissues, whereas pathways regulating cellular senescence were upregulated in both aging and cancer.

Biomedical generative pre-trained based transformer language model for age-related disease target discovery.

Target discovery is crucial for the development of innovative therapeutics and diagnostics. However, current approaches often face limitations in efficiency, specificity, and scalability, necessitating the exploration of novel strategies for identifying and validating disease-relevant targets. Advances in natural language processing have provided new avenues for predicting potential therapeutic targets for various diseases.

AI-powered therapeutic target discovery.

Disease modeling and target identification are the most crucial initial steps in drug discovery, and influence the probability of success at every step of drug development. Traditional target identification is a time-consuming process that takes years to decades and usually starts in an academic setting. Given its advantages of analyzing large datasets and intricate biological networks, artificial intelligence (AI) is playing a growing role in modern drug target identification.

Precious1GPT: multimodal transformer-based transfer learning for aging clock development and feature importance analysis for aging and age-related disease target discovery.

Aging is a complex and multifactorial process that increases the risk of various age-related diseases and there are many aging clocks that can accurately predict chronological age, mortality, and health status. These clocks are disconnected and are rarely fit for therapeutic target discovery. In this study, we propose a novel approach to multimodal aging clock we call Precious1GPT utilizing methylation and transcriptomic data for interpretable age prediction and target discovery developed using a transformer-based model and transfer learning for case-control classification.

Design of infrared optical absorber using silver nanorings array made by a top-down process.

This paper presents the numerical simulation and fabrication of a metasurface composed of silver nanorings with a split-ring gap. These nanostructures can exhibit optically-induced magnetic responses with unique possibilities to control absorption at optical frequencies. The absorption coefficient of the silver nanoring was optimized by performing a parametric study with Finite Difference Time Domain (FDTD) simulations.

Identification of dual-purpose therapeutic targets implicated in aging and glioblastoma multiforme using PandaOmics - an AI-enabled biological target discovery platform.

Glioblastoma Multiforme (GBM) is the most aggressive and most common primary malignant brain tumor. The age of GBM patients is considered as one of the disease's negative prognostic factors and the mean age of diagnosis is 62 years. A promising approach to preventing both GBM and aging is to identify new potential therapeutic targets that are associated with both conditions as concurrent drivers.

Fluorescence engineering in metamaterial-assisted super-resolution localization microscope.

Single-molecule localization microscopies have gained much attention for their efficient realization of a sub-diffraction-limit imaging with the resolution down to the 10-nm range. In contrast to conventional localization microscopes, which rely on particular fluorescent probes in specific conditions, metamaterial-assisted super-resolution microscopies can be implemented with any fluorescent dye under general conditions. Here, we present a systematic study of fluorescence engineering in metamaterial assisted localization microscopy by using cyclic group metasurfaces coated with a fluorescent film.

Electrical monitoring of organic crystal phase transition using MoS field effect transistor.

Hybrid van der Waals heterostructures made of 2D materials and organic molecules exploit the high sensitivity of 2D materials to all interfacial modifications and the inherent versatility of the organic compounds. In this study, we are interested in the quinoidal zwitterion/MoS hybrid system in which organic crystals are grown by epitaxy on the MoS surface and reorganize in another polymorph after thermal annealing. By means of field-effect transistor measurements recorded all along the process, atomic force microscopy and density functional theory calculations we demonstrate that the charge transfer between quinoidal zwitterions and MoS strongly depends on the conformation of the molecular film.

AlphaFold accelerates artificial intelligence powered drug discovery: efficient discovery of a novel CDK20 small molecule inhibitor.

The application of artificial intelligence (AI) has been considered a revolutionary change in drug discovery and development. In 2020, the AlphaFold computer program predicted protein structures for the whole human genome, which has been considered a remarkable breakthrough in both AI applications and structural biology. Despite the varying confidence levels, these predicted structures could still significantly contribute to structure-based drug design of novel targets, especially the ones with no or limited structural information.

High-confidence cancer patient stratification through multiomics investigation of DNA repair disorders.

Multiple cancer types have limited targeted therapeutic options, in part due to incomplete understanding of the molecular processes underlying tumorigenesis and significant intra- and inter-tumor heterogeneity. Identification of novel molecular biomarkers stratifying cancer patients with different survival outcomes may provide new opportunities for target discovery and subsequent development of tailored therapies. Here, we applied the artificial intelligence-driven PandaOmics platform ( https://pandaomics.

Identification of Therapeutic Targets for Amyotrophic Lateral Sclerosis Using PandaOmics - An AI-Enabled Biological Target Discovery Platform.

Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disease with ill-defined pathogenesis, calling for urgent developments of new therapeutic regimens. Herein, we applied PandaOmics, an AI-driven target discovery platform, to analyze the expression profiles of central nervous system (CNS) samples (237 cases; 91 controls) from public datasets, and direct iPSC-derived motor neurons (diMNs) (135 cases; 31 controls) from Answer ALS. Seventeen high-confidence and eleven novel therapeutic targets were identified and will be released onto ALS.

Hallmarks of aging-based dual-purpose disease and age-associated targets predicted using PandaOmics AI-powered discovery engine.

Aging biology is a promising and burgeoning research area that can yield dual-purpose pathways and protein targets that may impact multiple diseases, while retarding or possibly even reversing age-associated processes. One widely used approach to classify a multiplicity of mechanisms driving the aging process is the hallmarks of aging. In addition to the classic nine hallmarks of aging, processes such as extracellular matrix stiffness, chronic inflammation and activation of retrotransposons are also often considered, given their strong association with aging.

Effector T cell responses unleashed by regulatory T cell ablation exacerbate oral squamous cell carcinoma.

Immune suppression by CD4FOXP3 regulatory T (Treg) cells and tumor infiltration by CD8 effector T cells represent two major factors impacting response to cancer immunotherapy. Using deconvolution-based transcriptional profiling of human papilloma virus (HPV)-negative oral squamous cell carcinomas (OSCCs) and other solid cancers, we demonstrate that the density of Treg cells does not correlate with that of CD8 T cells in many tumors, revealing polarized clusters enriched for either CD8 T cells or CD4 Treg and conventional T cells. In a mouse model of carcinogen-induced OSCC characterized by CD4 T cell enrichment, late-stage Treg cell ablation triggers increased densities of both CD4 and CD8 effector T cells within oral lesions.

Doublecortin-Like Kinase 1 (DCLK1) Is a Novel NOTCH Pathway Signaling Regulator in Head and Neck Squamous Cell Carcinoma.

Despite recent advancements, the 5 year survival of head and neck squamous cell carcinoma (HNSCC) hovers at 60%. DCLK1 has been shown to regulate epithelial-to-mesenchymal transition as well as serving as a cancer stem cell marker in colon, pancreatic and renal cancer. Although it was reported that DCLK1 is associated with poor prognosis in oropharyngeal cancers, very little is known about the molecular characterization of DCLK1 in HNSCC.

COVIDomic: A multi-modal cloud-based platform for identification of risk factors associated with COVID-19 severity.

Coronavirus disease 2019 (COVID-19) is an acute infection of the respiratory tract that emerged in December 2019 in Wuhan, China. It was quickly established that both the symptoms and the disease severity may vary from one case to another and several strains of SARS-CoV-2 have been identified. To gain a better understanding of the wide variety of SARS-CoV-2 strains and their associated symptoms, thousands of SARS-CoV-2 genomes have been sequenced in dozens of countries.

Ligand Nanocluster Array Enables Artificial-Intelligence-Based Detection of Hidden Features in T-Cell Architecture.

Protein patterning has emerged as a powerful means to interrogate adhering cells. However, the tools to apply a sub-micrometer periodic stimulus and the analysis of the response are still being standardized. We propose a technique combining electron beam lithography and surface functionalization to fabricate nanopatterns compatible with advanced imaging.

CO and O Adsorption and CO Oxidation on Pt Nanoparticles by Indirect Nanoplasmonic Sensing.

We used indirect nanoplasmonic sensing (INPS) coupled with mass spectrometry to study CO and oxygen adsorption as well as CO oxidation, on Pt nanoparticles, in the Torr pressure range. Due to an optimization of the physical parameters of our plasmonic sample, we obtain a highly sensitive probe that can detect gas adsorption of a few hundredths of a monolayer, even with a very low number density of Pt particles. Moreover and for the first time, a similarity is observed between the sign and the evolution of the localized surface plasmon resonance (LSPR) peak shift and the work function measurements for CO and oxygen chemisorption.

Radioprotectors.org: an open database of known and predicted radioprotectors.

The search for radioprotectors is an ambitious goal with many practical applications. Particularly, the improvement of human radioresistance for space is an important task, which comes into view with the recent successes in the space industry. Currently, all radioprotective drugs can be divided into two large groups differing in their effectiveness depending on the type of exposure.

Fabrication of sharp silicon arrays to wound Caenorhabditis elegans.

Understanding how animals respond to injury and how wounds heal remains a challenge. These questions can be addressed using genetically tractable animals, including the nematode Caenorhabditis elegans. Given its small size, the current methods for inflicting wounds in a controlled manner are demanding.