Denfivontinib activates effector T-cells through NLRP3-inflammasome, yielding potent anticancer effects by combination with pembrolizumab.

Various combination therapies have been investigated to overcome the limitations of using immune checkpoint inhibitors. However, determining the optimal combination therapy remains challenging. To overcome the therapeutical limitation, we conducted a translational research to elucidate the mechanisms by which AXL inhibition enhances the anti-tumor effects when combined with anti-PD-1 antibody therapy.

Charge-trap synaptic device with polycrystalline silicon channel for low power in-memory computing.

Processing-in-memory (PIM) is gaining tremendous research and commercial interest because of its potential to replace the von Neumann bottleneck in current computing architectures. In this study, we implemented a PIM hardware architecture (circuit) based on the charge-trap flash (CTF) as a synaptic device. The PIM circuit with a CT memory performed exceedingly well by reducing the inference energy in the synapse array.

Anti-VEGF treatment outcome prediction based on optical coherence tomography images in neovascular age-related macular degeneration using a deep neural network.

Age-related macular degeneration (AMD) is a major cause of blindness in developed countries, and the number of affected patients is increasing worldwide. Intravitreal injections of anti-vascular endothelial growth factor (VEGF) are the standard therapy for neovascular AMD (nAMD), and optical coherence tomography (OCT) is a crucial tool for evaluating the anatomical condition of the macula. However, OCT has limitations in accurately predicting the degree of functional and morphological improvement following intravitreal injections.

Wall Shear Stress (WSS) Analysis in Atherosclerosis in Partial Ligated Apolipoprotein E Knockout Mouse Model through Computational Fluid Dynamics (CFD).

Atherosclerosis involves an inflammatory response due to plaque formation within the arteries, which can lead to ischemic stroke and heart disease. It is one of the leading causes of death worldwide, with various contributing factors such as hyperlipidemia, hypertension, obesity, diabetes, and smoking. Wall shear stress (WSS) is also known as a contributing factor of the formation of atherosclerotic plaques.

On-Chip Annealing Using Embedded Micro-Heater for Highly Sensitive and Selective Gas Detection.

The demand for gas sensing systems that enable fast and precise gas recognition is growing rapidly. However, substantial challenges arise from the complex fabrication process of sensor arrays, time-consuming data transmission to an external processor, and high energy consumption in multi-stage data processing. In this study, a gas sensing system using on-chip annealing for fast and power-efficient gas detection is proposed.

CD81 and CD82 expressing tumor-infiltrating lymphocytes in the NSCLC tumor microenvironment play a crucial role in T-cell activation and cytokine production.

Introduction: To understand the immune system within the tumor microenvironment (TME) of non-small cell lung cancer (NSCLC), it is crucial to elucidate the characteristics of molecules associated with T cell activation.

Methods: We conducted an in-depth analysis using single-cell RNA sequencing data obtained from tissue samples of 19 NSCLC patients. T cells were classified based on the Tumor Proportion Score (TPS) within the tumor region, and molecular markers associated with activation and exhaustion were analyzed in T cells from high TPS areas.

Prediction of neovascular age-related macular degeneration recurrence using optical coherence tomography images with a deep neural network.

Neovascular age-related macular degeneration (nAMD) can result in blindness if left untreated, and patients often require repeated anti-vascular endothelial growth factor injections. Although, the treat-and-extend method is becoming popular to reduce vision loss attributed to recurrence, it may pose a risk of overtreatment. This study aimed to develop a deep learning model based on DenseNet201 to predict nAMD recurrence within 3 months after confirming dry-up 1 month following three loading injections in treatment-naïve patients.

Biogenic species synthesized silver nanoparticles with catalytic, sensing, antimicrobial, and antioxidant properties.

Salvia (Lamiaceae family) is used as a brain tonic to improve cognitive function. The species including and are locally used to cure hepatitis, cough, tumours, hemorrhoids, diarrhoea, common cold, flu, and asthma. To the best of authors' knowledge, no previous study has been conducted on synthesis of and silver nanoparticles (SPAgNPs and SMAgNPs).

Developing and Evaluating an AI-Based Computer-Aided Diagnosis System for Retinal Disease: Diagnostic Study for Central Serous Chorioretinopathy.

Background: Although previous research has made substantial progress in developing high-performance artificial intelligence (AI)-based computer-aided diagnosis (AI-CAD) systems in various medical domains, little attention has been paid to developing and evaluating AI-CAD system in ophthalmology, particularly for diagnosing retinal diseases using optical coherence tomography (OCT) images.

Objective: This diagnostic study aimed to determine the usefulness of a proposed AI-CAD system in assisting ophthalmologists with the diagnosis of central serous chorioretinopathy (CSC), which is known to be difficult to diagnose, using OCT images.

Methods: For the training and evaluation of the proposed deep learning model, 1693 OCT images were collected and annotated.

Fe-Catalyzed C-H Alkenylation of Dialkyl Anilines with Disulfonylethenes.

The oxidative alkenylation reaction of α-aminoalkyl C(sp)-H bonds has been investigated with ()-1,2-bis(sulfonyl)ethenes. The catalytic process of iron-polypyridyl complexes drives the single-electron oxidation of dialkyl anilines, resulting in the formation of α-aminoalkyl radical species. Subsequent cascades of radical addition and elimination reactions ensue, ultimately leading to the generation of sulfonylated allylic amine products.

Polo-like Kinase 4: A Multifaceted Marker Linking Tumor Aggressiveness and Unfavorable Prognosis, and Insights into Therapeutic Strategies.

(1) Background: This study investigated whether polo-like kinase 4 (PLK4) is a suitable therapeutic target or biomarker for lung adenocarcinoma (LUAD). (2) Methods: We acquired LUAD data from The Cancer Genome Atlas (TCGA) database through the UCSC Xena data portal. Gene expression, clinical, survival, and mutation data from multiple samples were analyzed.

Prediction of Visual Acuity in Pathologic Myopia with Myopic Choroidal Neovascularization Treated with Anti-Vascular Endothelial Growth Factor Using a Deep Neural Network Based on Optical Coherence Tomography Images.

Myopic choroidal neovascularization (mCNV) is a common cause of vision loss in patients with pathological myopia. However, predicting the visual prognosis of patients with mCNV remains challenging. This study aimed to develop an artificial intelligence (AI) model to predict visual acuity (VA) in patients with mCNV.

Iron Catalysis of C(sp)-H Azidation Using a Heteroarene Radical Cation Strategy.

The Fe(phen) catalysis of the benzylic C(sp)-H azidation of indoles has been investigated. The Fe(III) complex can selectively oxidize indoles to form arene radical cations, which are transformed into benzylic C(sp) radical intermediates. This strategy exhibits a difference in reactivity between -heteroarenes and benzene, which is difficult to achieve via direct hydrogen abstraction approaches.

Detecting Macular Disease Based on Optical Coherence Tomography Using a Deep Convolutional Network.

Neovascular age-related macular degeneration (nAMD) and central serous chorioretinopathy (CSC) are two of the most common macular diseases. This study proposes a convolutional neural network (CNN)-based deep learning model for classifying the subtypes of nAMD (polypoidal choroidal vasculopathy, retinal angiomatous proliferation, and typical nAMD) and CSC (chronic CSC and acute CSC) and healthy individuals using single spectral-domain optical coherence tomography (SD-OCT) images. The proposed model was trained and tested using 6063 SD-OCT images from 521 patients and 47 healthy participants.

Carbon Nanotube and Its Derived Nanomaterials Based High Performance Biosensing Platform.

After the COVID-19 pandemic, the development of an accurate diagnosis and monitoring of diseases became a more important issue. In order to fabricate high-performance and sensitive biosensors, many researchers and scientists have used many kinds of nanomaterials such as metal nanoparticles (NPs), metal oxide NPs, quantum dots (QDs), and carbon nanomaterials including graphene and carbon nanotubes (CNTs). Among them, CNTs have been considered important biosensing channel candidates due to their excellent physical properties such as high electrical conductivity, strong mechanical properties, plasmonic properties, and so on.

Magnetofluoro-Immunosensing Platform Based on Binary Nanoparticle-Decorated Graphene for Detection of Cancer Cell-Derived Exosomes.

Multi-functionalized carbon nanomaterials have attracted interest owing to their excellent synergic properties, such as plasmon resonance energy transfer and surface-enhanced Raman scattering. Particularly, nanoparticle (NP)-decorated graphene (GRP) has been applied in various fields. In this study, silver NP (AgNP)- and magnetic iron oxide NP (IONP)-decorated GRP were prepared and utilized as biosensing platforms.

Exosome-based drug delivery systems and their therapeutic applications.

In the past few decades, scientists have actively worked on developing effective drug delivery systems (DDSs) as means to control life-threatening diseases and challenging illnesses. In order to develop such DDSs, nanobiotechnological strategies have been introduced, and many nanomaterial-based DDS platforms have been proposed. Among these nanomaterials, DDSs based on exosomes and hybrids of exosomes have been focused upon and developed due to their low toxicity, high bioactivity, and biocompatibility.

Classifying neovascular age-related macular degeneration with a deep convolutional neural network based on optical coherence tomography images.

Neovascular age-related macular degeneration (nAMD) is among the main causes of visual impairment worldwide. We built a deep learning model to distinguish the subtypes of nAMD using spectral domain optical coherence tomography (SD-OCT) images. Data from SD-OCT images of nAMD (polypoidal choroidal vasculopathy, retinal angiomatous proliferation, and typical nAMD) and normal healthy patients were analyzed using a convolutional neural network (CNN).

Assessing central serous chorioretinopathy with deep learning and multiple optical coherence tomography images.

Central serous chorioretinopathy (CSC) is one of the most common macular diseases that can reduce the quality of life of patients. This study aimed to build a deep learning-based classification model using multiple spectral domain optical coherence tomography (SD-OCT) images together to diagnose CSC. Our proposed system contains two modules: single-image prediction (SIP) and a final decision (FD) classifier.