Novel drug candidates against antibiotic-resistant microorganisms: A review.

Antibiotic resistance is fast spreading globally, leading to treatment failures and adverse clinical outcomes. This review focuses on the resistance mechanisms of the top five threatening pathogens identified by the World Health Organization's global priority pathogens list: carbapenem-resistant , carbapenem-resistant , carbapenem-resistant, extended-spectrum beta-lactamase (ESBL)-producing , vancomycin-resistant and methicillin, vancomycin-resistant . Several novel drug candidates have shown promising results from and studies, as well as clinical trials.

Distance-Based Detection of Cough, Wheeze, and Breath Sounds on Wearable Devices.

Smart wearable sensors are essential for continuous health-monitoring applications and detection accuracy of symptoms and energy efficiency of processing algorithms are key challenges for such devices. While several machine-learning-based algorithms for the detection of abnormal breath sounds are reported in literature, they are either too computationally expensive to implement into a wearable device or inaccurate in multi-class detection. In this paper, a kernel-like minimum distance classifier (K-MDC) for acoustic signal processing in wearable devices was proposed.

Optical Potential-Well Array for High-Selectivity, Massive Trapping and Sorting at Nanoscale.

Optical tweezers are versatile tools capable of sorting microparticles, yet formidable challenges are present in the separation of nanoparticles smaller than 200 nm. The difficulties arise from the controversy on the requirement of a tightly focused light spot in order to create strong optical forces while a large area is kept for the sorting. To overcome this problem, we create a near-field potential well array with connected tiny hotspots in a large scale.

Regulation of lipid droplets in live preadipocytes using optical diffraction tomography and Raman spectroscopy.

Lipid droplets have gained strong interest in recent years to comprehend how they function and coordinate with other parts of the cell. However, it remains challenging to study the regulation of lipid droplets in live preadipocytes using conventional microscopic techniques. In this paper, we study the effects of fatty acid stimulation and cell starvation on lipid droplets using optical diffraction tomography and Raman spectroscopy by measuring size, refractive index, volume, dry mass and degree of unsaturation.

Author Correction: Sculpting nanoparticle dynamics for single-bacteria-level screening and direct binding-efficiency measurement.

The original version of this Article omitted the author Kuan Wang, who is from the 'College of Biomedical Engineering, Taipei Medical University, Taipei 11031, Taiwan' and 'Nanyang Environment & Water Research Institute, Nanyang Technological University, Singapore 637141, Singapore.'Also, the author S.H.

Automatic System for Obstructive Sleep Apnea Events Detection Using Convolutional Neural Network.

Obstructive Sleep Apnea (OSA) is characterized by repetitive episodes of airflow reduction (hypopnea) or cessation (apnea), which, as a prevalent sleep disorder, can cause people to stop breathing for 10 to 30 seconds at a time and lead to serious problems such as daytime fatigue, impaired memory, and depression. This work intends to explore automatic detection of OSA events with 1-second annotation based on blood oxygen saturation, oronasal airflow, and ribcage and abdomen movements. Deep Learning (DL) technology, specifically, Convolutional Neural Network (CNN), is employed as a feature detector to learn the characteristics of the highorder correlation among visible data and corresponding labels.

An mRMR-SVM Approach for Opto-Fluidic Microorganism Classification.

The detection of microorganisms is important in numerous applications such as water quality monitoring, blood analysis, and food testing. The conventional detection methods are tedious and labour-intensive. Establish methods involve culturing, counting and identification of the pathogen by an experienced technician which typically can take several days.

Obstructive Sleep Apnea Detection Using Difference in Feature and Modified Minimum Distance Classifier.

The current gold standard of Obstructive Sleep Apnea (OSA) diagnosis involves the use of a Polysomnography (PSG) system which requires the patient to stay in the hospital for overnight recording. The process is uncomfortable for the patient and it disturbs the patient's sleep pattern. On the other hand, it is well known that some acoustic features of the snoring sounds are good indicators of the presence of OSA, and a variety of acoustic OSA detection algorithms have been reported in the literature.

Classification of non-tumorous skin pigmentation disorders using voting based probabilistic linear discriminant analysis.

Non-tumorous skin pigmentation disorders can have a huge negative emotional impact on patients. The correct diagnosis of these disorders is essential for proper treatments to be instituted. In this paper, we present a computerized method for classifying five non-tumorous skin pigmentation disorders (i.

Sculpting nanoparticle dynamics for single-bacteria-level screening and direct binding-efficiency measurement.

Particle trapping and binding in optical potential wells provide a versatile platform for various biomedical applications. However, implementation systems to study multi-particle contact interactions in an optical lattice remain rare. By configuring an optofluidic lattice, we demonstrate the precise control of particle interactions and functions such as controlling aggregation and multi-hopping.

Nanometer-precision linear sorting with synchronized optofluidic dual barriers.

The past two decades have witnessed the revolutionary development of optical trapping of nanoparticles, most of which deal with trapping stiffness larger than 10 N/m. In this conventional regime, however, it remains a formidable challenge to sort out sub-50-nm nanoparticles with single-nanometer precision, isolating us from a rich flatland with advanced applications of micromanipulation. With an insightfully established roadmap of damping, the synchronization between optical force and flow drag force can be coordinated to attempt the loosely overdamped realm (stiffness, 10 to 10 N/m), which has been challenging.

Feature extraction techniques for low-power ambulatory wheeze detection wearables.

Presence of wheezes in breathing sounds has been associated with several respiratory and pulmonary diseases. In this paper we present a novel low-complexity wheeze detection method based on frequency contour tracking for automatic wheeze detection. Two hardware friendly variants of the algorithm have also been proposed.

High-resolution and multi-range particle separation by microscopic vibration in an optofluidic chip.

An optofluidic chip is demonstrated in experiments for high-resolution and multi-range particle separation through the optically-induced microscopic vibration effect, where nanoparticles are trapped in loosely overdamped optical potential wells created with combined optical and fluidic constraints. It is the first demonstration of separating single nanoparticles with diameters ranging from 60 to 100 nm with a resolution of 10 nm. Nanoparticles vibrate with an amplitude of 3-7 μm in the loosely overdamped potential wells in the microchannel.

Correction: Optofluidic lens with low spherical and low field curvature aberrations.

Correction for 'Optofluidic lens with low spherical and low field curvature aberrations' by H. T. Zhao et al.

Optofluidic lens with low spherical and low field curvature aberrations.

This paper reports an optofluidic lens with low spherical and low field curvature aberrations through the desired refractive index profile by precisely controlling the mixing between ethylene glycol and deionized water in an optofluidic chip. The experimental results demonstrate that the spherical aberration is reduced to 19.5 μm and the full width at half maximum of the focal point is 7.

Cell refractive index for cell biology and disease diagnosis: past, present and future.

Cell refractive index is a key biophysical parameter, which has been extensively studied. It is correlated with other cell biophysical properties including mechanical, electrical and optical properties, and not only represents the intracellular mass and concentration of a cell, but also provides important insight for various biological models. Measurement techniques developed earlier only measure the effective refractive index of a cell or a cell suspension, providing only limited information on cell refractive index and hence hindering its in-depth analysis and correlation.

An optofluidic imaging system to measure the biophysical signature of single waterborne bacteria.

In this paper, for the first time, an on-chip optofluidic imaging system is innovated to measure the biophysical signatures of single waterborne bacteria, including both their refractive indices and morphologies (size and shape), based on immersion refractometry. The key features of the proposed optofluidic imaging platform include (1) multiple sites for single-bacterium trapping, which enable parallel measurements to achieve higher throughput, and (2) a chaotic micromixer, which enables efficient refractive index variation of the surrounding medium. In the experiments, the distinctive refractive index of Echerichia coli, Shigella flexneri and Vibrio cholera are measured with a high precision of 5 × 10(-3) RIU.

Droplet optofluidic imaging for λ-bacteriophage detection via co-culture with host cell Escherichia coli.

Bacteriophages are considered as attractive indicators for determining drinking water quality since its concentration is strongly correlated with virus concentrations in water samples. Previously, bacteriophage detection was based on a plague assay that required a complicated labelling technique and a time-consuming culture assay. Here, for the first time, a label-free bacteriophage detection is reported by using droplet optofluidic imaging, which uses host-cell-containing microdroplets as reaction carriers for bacteriophage infection due to a higher contact ratio.

A pseudo-planar metasurface for a polarization rotator.

New demonstrations of effective interaction between light and artificially electromagnetic interface, or the metasurface, have stimulated intensive research interests on control of light to realize applications in beam steering, optical imaging and light focusing, etc. Here we reported a new type of planar metasurface of which every individual metamolecule is single metallic layer with stereo structure and the metasurface is name as Pseudo-Planar Metasurface (PPM). The metamolecule of the PPM is a chiral structure and therefore derives significant optical activity.

An intelligent scoring system and its application to cardiac arrest prediction.

Traditional risk score prediction is based on vital signs and clinical assessment. In this paper, we present an intelligent scoring system for the prediction of cardiac arrest within 72 h. The patient population is represented by a set of feature vectors, from which risk scores are derived based on geometric distance calculation and support vector machine.

3D characterization and trend analysis of scents from EEG recordings of repeated scent exposure.

Scent plays an important role in influencing the brain and has been commonly used in psychological research. Much of such research has been conducted without the use of electroencephalography (EEG) to measure the response of the human brain to scent stimulus. Recent studies have involved the use of EEG to perform comparative studies on how different scents can affect brain activity.

Lung water detection using acoustic techniques.

The presence of an excessive amount of water in lung is a sign of pulmonary edema which can be caused by heart failure. The current solutions for lung water detection involve the use of X-ray, CT scan or serum biomarkers, which require bulky and expensive instruments as well as long measurement duration. This paper reports on a study conducted on the use of a different sensing modality to detect the presence of water in lung.

Discrete wavelet transform coefficients for emotion recognition from EEG signals.

In this paper, we propose to use DWT coefficients as features for emotion recognition from EEG signals. Previous feature extraction methods used power spectra density values dervied from Fourier Transform or sub-band energy and entropy derived from Wavelet Transform. These feature extracion methods eliminate temporal information which are essential for analyzing EEG signals.

A novel respiratory rate estimation method for sound-based wearable monitoring systems.

The respiratory rate is a vital sign that can provide important information about the health of a patient, especially that of the respiratory system. The aim of this study is to develop a simple method that can be applied in wearable systems to monitor the respiratory rate automatically and continuously over extended periods of time. In this paper, a novel respiratory rate estimation method is presented to achieve this target.

Probabilistic neural-network structure determination for pattern classification.

Network structure determination is an important issue in pattern classification based on a probabilistic neural network. In this study, a supervised network structure determination algorithm is proposed. The proposed algorithm consists of two parts and runs in an iterative way.