Enhancing Open-World Bacterial Raman Spectra Identification by Feature Regularization for Improved Resilience against Unknown Classes.

The combination of deep learning techniques and Raman spectroscopy shows great potential offering precise and prompt identification of pathogenic bacteria in clinical settings. However, the traditional closed-set classification approaches assume that all test samples belong to one of the known pathogens, and their applicability is limited since the clinical environment is inherently unpredictable and dynamic, unknown, or emerging pathogens may not be included in the available catalogs. We demonstrate that the current state-of-the-art neural networks identifying pathogens through Raman spectra are vulnerable to unknown inputs, resulting in an uncontrollable false positive rate.

New quasiperiodic structures in nematic liquid crystals.

Liquid crystal molecules tend to align with each other, often forming regions of opposite alignment that meet at a boundary-topological defects. These often offer information on configuration of the liquid crystal molecules with competing constraints on their order. Here, we experimentally demonstrate a mechanism to generate topological defects in the form of spatially oscillatory domain walls in nematic liquid crystals.

Super-Resolution Imaging of Neuronal Structures with Structured Illumination Microscopy.

Super-resolution structured illumination microscopy (SR-SIM) is an optical fluorescence microscopy method which is suitable for imaging a wide variety of cells and tissues in biological and biomedical research. Typically, SIM methods use high spatial frequency illumination patterns generated by laser interference. This approach provides high resolution but is limited to thin samples such as cultured cells.

Super-resolution imaging of neuronal structure with structured illumination microscopy.

Super-resolution structured illumination microscopy (SR-SIM) is a method in optical fluorescence microscopy which is suitable for imaging a wide variety of cells and tissues in biological and biomedical research. Typically, SIM methods use high spatial frequency illumination patterns generated by laser interference. This approach provides high resolution but is limited to thin samples such as cultured cells.

Magnetic particle based MRI thermometry at 0.2 T and 3 T.

This study provides insight into the advantages and disadvantages of using ferrite particles embedded in agar gel phantoms as MRI temperature indicators for low-magnetic field scanners. We compare the temperature-dependent intensity of MR images at low-field (0.2 T) to those at high-field (3.

Raman Spectroscopy in Open-World Learning Settings Using the Objectosphere Approach.

Raman spectroscopy, combined with machine learning techniques, holds great promise for many applications as a rapid, sensitive, and label-free identification method. Such approaches perform well when classifying spectra of chemical species that were encountered during the training phase. That is, species that are known to the neural network.

Flexible Multiplane Structured Illumination Microscope with a Four-Camera Detector.

Fluorescence microscopy provides an unparalleled tool for imaging biological samples. However, producing high-quality volumetric images quickly and without excessive complexity remains a challenge. Here, we demonstrate a four-camera structured illumination microscope (SIM) capable of simultaneously imaging multiple focal planes, allowing for the capture of 3D fluorescent images without any axial movement of the sample.

Optimization of laser deposited silver nanoparticle substrates for surface-enhanced raman spectroscopy.

Creating sensitive and reproducible substrates for surface-enhanced Raman spectroscopy (SERS) has been a challenge in recent years. While SERS offers significant benefits over traditional Raman spectroscopy, certain hindrances have limited their commercial use, especially in settings where low limits of detection are necessary. We studied a variety of laser-deposited silver microstructured SERS substrates with different morphology as a means to optimize analyte detection.

Simulating the Self-Assembly and Hysteresis Loops of Ferromagnetic Nanoparticles with Sticking of Ligands.

The agglomeration of ferromagnetic nanoparticles in a fluid is studied using nanoparticle-level Langevin dynamics simulations. The simulations have interdigitation and bridging between ligand coatings included using a computationally-cheap, phenomenological sticking parameter . The interactions between ligand coatings are shown in this preliminary study to be important in determining the shapes of agglomerates that form.

Measurement of sub-zero temperatures in MRI using T temperature sensitive soft silicone materials: Applications for MRI-guided cryosurgery.

Purpose: One standard method, proton resonance frequency shift, for measuring temperature using magnetic resonance imaging (MRI), in MRI-guided surgeries, fails completely below the freezing point of water. Because of this, we have developed a new methodology for monitoring temperature with MRI below freezing. The purpose of this paper is to show that a strong temperature dependence of the nuclear relaxation time T in soft silicone polymers can lead to temperature-dependent changes of MRI intensity acquired with T weighting.

Fast Switching Dual-Frequency Nematic Liquid Crystal Tunable Filters.

We develop tunable optical filters with dual-frequency nematic liquid crystal optical retarders to enable fast switching between the passed wavelengths. The filters are composed of a series of two liquid crystal optical retarders. We select the specific thicknesses of the liquid crystal retarders and use individual biasing schemes to continuously tune the wavelength and bandwidth of the filter.

Fluorescence microscopy datasets for training deep neural networks.

Background: Fluorescence microscopy is an important technique in many areas of biological research. Two factors that limit the usefulness and performance of fluorescence microscopy are photobleaching of fluorescent probes during imaging and, when imaging live cells, phototoxicity caused by light exposure. Recently developed methods in machine learning are able to greatly improve the signal-to-noise ratio of acquired images.

Absorption cross section of gold nanoparticles based on NIR laser heating and thermodynamic calculations.

We present a method for measuring the optical absorption cross section ([Formula: see text]) of gold nanoparticles (GNPs) based on optically heating the solution of GNPs with an 808 nm near-infrared (NIR) laser and measuring the temperature increase of the solution. We rely on the theoretical calculations based on the heat diffusion equations and experimental measurements based on the energy balance equations to measure the [Formula: see text] and the temperature distribution of single GNPs. Several morphologies, including gold nanospheres (GNSs), spherical gold nanoparticle conjugate (AuNPC), which are 20 nm GNSs surface-functionalized with an IR 808 dye, gold nanorods (GNRs), and gold nanourchins (GNUs), were studied.

Exploiting Unique Alignment of Cobalt Ferrite Nanoparticles, Mild Hyperthermia, and Controlled Intrinsic Cobalt Toxicity for Cancer Therapy.

Nanoparticle-based magnetic hyperthermia is a well-known thermal therapy platform studied to treat solid tumors, but its use for monotherapy is limited due to incomplete tumor eradication at hyperthermia temperature (45 °C). It is often combined with chemotherapy for obtaining a more effective therapeutic outcome. Cubic-shaped cobalt ferrite nanoparticles (Co-Fe NCs) serve as magnetic hyperthermia agents and as a cytotoxic agent due to the known cobalt ion toxicity, allowing the achievement of both heat and cytotoxic effects from a single platform.

Artifact-free whole-slide imaging with structured illumination microscopy and Bayesian image reconstruction.

Background: Structured illumination microscopy (SIM) is a method that can be used to image biological samples and can achieve both optical sectioning and super-resolution effects. Optimization of the imaging set-up and data-processing methods results in high-quality images without artifacts due to mosaicking or due to the use of SIM methods. Reconstruction methods based on Bayesian estimation can be used to produce images with a resolution beyond that dictated by the optical system.

Beyond the blocking model to fit nanoparticle ZFC/FC magnetisation curves.

We consider the probability of a magnetic nanoparticle to flip its magnetisation near the blocking temperature, and use this to develop quasi-analytic expressions for the zero-field-cooled and field-cooled magnetisation, which go beyond the usual critical energy barrier approach to the superparamagnetic transition. The particles in the assembly are assumed to have random alignment of easy axes, and to not interact. We consider all particles to be of the same size and then extend the theory to treat polydisperse systems of particles.

Exploration of Fermi-Pasta-Ulam Behavior in a Magnetic System.

We study nonlinear spin motion in one-dimensional magnetic chains. We find significant differences from the classic Fermi-Pasta-Ulam (FPU) problem examining nonlinear elastic motion in a chain. We find that FPU behavior, the transfer of energy among low order eigenmodes, does not occur in magnetic systems with only exchange and external fields, but does exist if a uniaxial anisotropy is also present.

Kinetics of Ion-Capturing/Ion-Releasing Processes in Liquid Crystal Devices Utilizing Contaminated Nanoparticles and Alignment Films.

Various types of nanomaterials and alignment layers are considered major components of the next generation of advanced liquid crystal devices. While the steady-state properties of ion-capturing/ion-releasing processes in liquid crystals doped with nanoparticles and sandwiched between alignment films are relatively well understood, the kinetics of these phenomena remains practically unexplored. In this paper, the time dependence of ion-capturing/ion-releasing processes in liquid crystal cells utilizing contaminated nanoparticles and alignment layers is analyzed.

Static and dynamic electro-optical properties of liquid crystals mediated by ferroelectric polymer films.

This paper reports the electro-optical properties of high resistivity nematic liquid crystals sandwiched between ferroelectric polymer films. Interactions between liquid crystals and the film result in a series of interesting optical and electro-optical features. For example, the visualization of ferroelectric domains by means of liquid crystals has been known for decades.

Development of Ferrite-Based Temperature Sensors for Magnetic Resonance Imaging: A Study of CuZnFeO.

We investigate the use of Cu Zn FeO ferrites (0.60 < < 0.76) as potential sensors for magnetic- resonance-imaging thermometry.

Ferroelectric Nanoparticles in Liquid Crystals: Recent Progress and Current Challenges.

The dispersion of ferroelectric nanomaterials in liquid crystals has recently emerged as a promising way for the design of advanced and tunable electro-optical materials. The goal of this paper is a broad overview of the current technology, basic physical properties, and applications of ferroelectric nanoparticle/liquid crystal colloids. By compiling a great variety of experimental data and discussing it in the framework of existing theoretical models, both scientific and technological challenges of this rapidly developing field of liquid crystal nanoscience are identified.

Biological Contamination of Nanoparticles and Its Manifestation in Optical Absorbance Measurements.

The biological contamination of nanomaterials is a serious problem hampering their widespread use in biomedical products. Existing commercial chromogenic assays for the detection and quantification of biocontaminants such as endotoxin can interfere with nanoparticles thus leading to unreliable data. The results reported in this Letter offer a solution to the aforementioned problems of the nanoparticle interference and correct quantification of biocontaminants by decomposing their optical absorbance into two physically measurable components and analyzing them as a function of the concentration of contaminated nanoparticles.

The formation of linear aggregates in magnetic hyperthermia: implications on specific absorption rate and magnetic anisotropy.

The design and application of magnetic nanoparticles for use as magnetic hyperthermia agents has garnered increasing interest over the past several years. When designing these systems, the fundamentals of particle design play a key role in the observed specific absorption rate (SAR). This includes the particle's core size, polymer brush length, and colloidal arrangement.