A perspective view on the nanomotion detection of living organisms and its features

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Cysteine cathepsins proteases are enzymes that play essential physiological roles, but their activity is also associated to different aspects of cancer progression and to the development of other diseases. Therefore, cysteine cathepsins are relevant and pr ...

Heterochromatin loss and genetic instability enhance cancer progression by favoring clonal diversity, yet uncontrolled replicative stress leads to mitotic catastrophe and inflammatory responses that promote immune rejection. KRAB domain-containing zinc fin ...

We developed a rational approach to design peptide-based covalent inhibitors and coupled the inhibitors with antibodies for cell-specific delivery. We used this platform to generate antibody-peptide inhibitor conjugates (APICs) that target a family of prot ...

Microorganisms are a key component in the chain of life. They are essential for agriculture, produce a large proportion of oxygen, and play a central role in the cycle of elements. Microorganisms are widely used in the production of food and alcoholic beve ...

The World Health Organization highlights the urgent need to address the global threat posed by antibiotic-resistant bacteria. Efficient and rapid detection of bacterial response to antibiotics and their virulence state is crucial for the effective treatmen ...

This document contains all the data and the details of the analysis used in the manuscript titled " Control of Ge island coalescence for the formation of nanowires on silicon." https://doi.org/10.1039/D3NH00573A ...

This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “3D printing of customizable transient bioelectronics and sensors”. This work aims to study and demonstrate ...

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by ...

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

The advent of immunotherapy, such as immune checkpoint blockade (ICB) and adoptive transfer of cytotoxic lymphocytes, has transformed the clinical care of cancer. However, a significant proportion of patients are resistant to immunotherapy or experience re ...

The morphology and distribution of nanoscale structures, such as catalytic active nanoparticles and quantum dots on surfaces, have a significant impact on their function. Thus, the capability of monitoring these properties during manufacturing and operatio ...

In a context of escalating public health challenges, including the rise of chronic diseases, the impact of climate change, and the COVID-19 pandemic, certain populations bear a disproportionate burden. As a result, there is an urgent need to develop public ...

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

Microorganisms, encompassing both uni- and multicellular entities, exhibit remarkable diversity as omnipresent life forms in nature. They play a pivotal role by supplying essential components for sustaining biological processes across diverse ecosystems, i ...

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

Traditional cell cultures have long been fundamental to biological research, offering an alternative to animal models burdened by ethical constraints and procedural intricacies, often lacking relevance to human physiology and disease. Moreover, their inabi ...

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

This thesis investigates the magnetic properties of single atoms and molecules adsorbed on thin magnesium oxide decoupling layers, grown on a silver single crystal. To address these systems experimentally, we use a low temperature scanning tunneling micros ...

Ever since the advent of Atomic Force Microscope (AFM) the community of its users is expanding which led to a broad spectrum of applications. Most of these applications require AFM instruments with fast, accurate, and reliable performance. The sensors and ...

Cells of two molecular genetic types of breast cancer-hormone-dependent breast cancer (ZR-75 cell line) and triple-negative breast cancer (BT-20 cell line)-were studied using atomic force microscopy and an optical nanomotion detection method. Using the Pea ...

A perspective view on the nanomotion detection of living organisms and its features

Chattez avec Graph Search

Development of cysteine cathepsin inhibitors combined with cell type-specific delivery for the treatment of B-cell lymphoma and solid tumors

A Cluster of Evolutionarily Recent KRAB Zinc Finger Proteins Protects Cancer Cells from Replicative Stress–Induced Inflammation

Antibody-peptide conjugates for targeted inhibition of cysteine proteases

Reconstruction and analysis of genome-scale metabolic networks in single organisms and microbial communities

Machine learning method for the classification of the state of living organisms' oscillations

Data set for control of Ge island coalescence for the formation of nanowires on silicon

Dataset for '3D printing of customizable transient bioelectronics and sensors'

Data and scripts for the RaFSIP scheme

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Exploration and modulation of mechanical cues for enhanced cancer immunotherapy

Hard x-ray grazing-incidence ptychography: large field-of-view nanostructure imaging with ultra-high surface sensitivity

The role of spatial epidemiology to support public health policies : case studies applied to health promotion, noncommunicable and infectious diseases in the canton of Vaud, Switzerland

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Microfluidic systems for infectious disease diagnostics

Robust machine learning for neuroscientific inference

Accessible and highly observable gastrointestinal organoid model systems for studying host-pathogen interactions

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Magnetism of Single Surface Adsorbed Atoms Studied with Radio-Frequency STM

Data-Driven Methods for Controller Design in Atomic Force Microscopy

Mechanical Properties and Nanomotion of BT-20 and ZR-75 Breast Cancer Cells Studied by Atomic Force Microscopy and Optical Nanomotion Detection Method