Nanofilament organization in highly tough fibers based on lamin proteins.

The escalating plastic pollution crisis necessitates sustainable alternatives, and one promising solution involves replacing petroleum-based polymers with fibrous proteins. This study focused on the recombinant production of intracellular fibrous proteins, specifically Caenorhabditis elegans lamin (Ce-lamin). Ce-lamins spontaneously organize within the cell nucleus, forming a network of nanofilaments.

Exploring the Interplay of Dataset Size and Imbalance on CNN Performance in Healthcare: Using X-rays to Identify COVID-19 Patients.

Introduction: Convolutional Neural Network (CNN) systems in healthcare are influenced by unbalanced datasets and varying sizes. This article delves into the impact of dataset size, class imbalance, and their interplay on CNN systems, focusing on the size of the training set versus imbalance-a unique perspective compared to the prevailing literature. Furthermore, it addresses scenarios with more than two classification groups, often overlooked but prevalent in practical settings.

An exact projection pursuit-based algorithm for multivariate two-sample nonparametric testing applicable to retrospective and group sequential studies.

Nonparametric tests for equality of multivariate distributions are frequently desired in research. It is commonly required that test-procedures based on relatively small samples of vectors accurately control the corresponding Type I Error (TIE) rates. Often, in the multivariate testing, extensions of null-distribution-free univariate methods, e.

Significant reduction of the culturing time required for bacterial identification and antibiotic susceptibility determination by infrared spectroscopy.

Rapid testing of bacteria for antibiotic susceptibility is essential for effective treatment and curbing the emergence of multidrug-resistant bacteria. The misuse of antibiotics, coupled with the time-consuming classical testing methods, intensifies the threat of antibiotic resistance, a major global health concern. In this study, employing infrared spectroscopy-based machine learning techniques, we significantly shortened the time required for susceptibility testing to 10 hours, a significant improvement from the 24 hours in our previous studies as well as the conventional methods that typically take at least 48 hours.

Infrared spectroscopy-based machine learning algorithms for rapid detection of Klebsiella pneumoniae isolated directly from patients' urine and determining its susceptibility to antibiotics.

Among the most prevalent and detrimental bacteria causing urinary tract infections (UTIs) is Klebsiella (K.) pneumoniae. A rapid determination of its antibiotic susceptibility can enhance patient treatment and mitigate the spread of resistant strains.

Quick Detection of and in Patients' Urine and Assessing Their Antibiotic Susceptibility Using Infrared Spectroscopy and Machine Learning.

Bacterial resistance to antibiotics is a primary global healthcare concern as it hampers the effectiveness of commonly used antibiotics used to treat infectious diseases. The development of bacterial resistance continues to escalate over time. Rapid identification of the infecting bacterium and determination of its antibiotic susceptibility are crucial for optimal treatment and can save lives in many cases.

Early Detection of Pre-Cancerous and Cancerous Cells Using Raman Spectroscopy-Based Machine Learning.

Cancer is the most common and fatal disease around the globe, with an estimated 19 million newly diagnosed patients and approximately 10 million deaths annually. Patients with cancer struggle daily due to difficult treatments, pain, and financial and social difficulties. Detecting the disease in its early stages is critical in increasing the likelihood of recovery and reducing the financial burden on the patient and society.

Detection of extended-spectrum β-lactamase-producing bacteria isolated directly from urine by infrared spectroscopy and machine learning.

Resistant bacteria have become one of the leading health threats in the last decades. Extended-spectrum β-lactamase (ESBL) producing bacteria, including Escherichia (E.) coli and Klebsiella (K.

Instant detection of extended-spectrum β-lactamase-producing bacteria from the urine of patients using infrared spectroscopy combined with machine learning.

Antibiotics are considered the most effective treatment against bacterial infections. However, most bacteria have already developed resistance to a broad spectrum of commonly used antibiotics, mainly due to their uncontrolled use. Extended-spectrum beta-lactamase (ESBL)-producing bacteria are an essential class of multidrug-resistant (MDR) bacteria.

Fast identification and susceptibility determination of E. coli isolated directly from patients' urine using infrared-spectroscopy and machine learning.

For effective treatment, it is crucial to identify the infecting bacterium at the species level and to determine its antimicrobial susceptibility. This is especially true now, when numerous bacteria have developed multidrug resistance to most commonly used antibiotics. Currently used methods need ∼ 48 h to identify a bacterium and determine its susceptibility to specific antibiotics.

Rapid determination of Proteus mirabilis susceptibility to antibiotics using infrared spectroscopy in tandem with random forest.

Bacterial infections cause serious illnesses that are treated with antibiotics. Currently used methods for detecting bacterial antibiotic susceptibility consume 48-72 h, leading to overuse of antibiotics. Thus, many bacterial species have acquired resistance to a broad range of available antibiotics.

Culture-independent susceptibility determination of isolated directly from patients' urine using FTIR and machine-learning.

One of the most common human bacterial infections is the urinary tract infection (UTI). The main cause of UTI is (.) bacteria (∼75%).

Infra-red spectroscopy combined with machine learning algorithms enables early determination of Pseudomonas aeruginosa's susceptibility to antibiotics.

Pseudomonas (P.) aeruginosa is a bacterium responsible for severe infections that have become a real concern in hospital environments. Nosocomial infections caused by P.

Mechanical Properties of Low-Performance Concrete (LPC) and Shear Capacity of Old Unreinforced LPC Squat Walls.

Low-performance concrete (LPC) is characterized by its low strength and commonly by the presence of large aggregates. This type of concrete was used for construction of load carrying, commonly unreinforced walls in old buildings. The resistance of these buildings with LPC squat walls (of relatively low height-to-length ratio), to in plane horizontal loads, was experimentally investigated in this study.

Determination of Susceptibility to Antibiotics Using Infrared Microscopy.

( is one of the most aggressive multidrug-resistant bacteria associated with human infections, resulting in high mortality and morbidity. We obtained 1190 isolates from different patients with urinary tract infections. The isolates were measured to determine their susceptibility regarding nine specific antibiotics.

Rapid detection of producing extended spectrum β lactamase enzymes by infrared microspectroscopy and machine learning algorithms.

Antimicrobial drugs have played an indispensable role in decreasing morbidity and mortality associated with infectious diseases. However, the resistance of bacteria to a broad spectrum of commonly-used antibiotics has grown to the point of being a global health-care problem. One of the most important classes of multi-drug resistant bacteria is Extended Spectrum Beta-Lactamase-producing (ESBL+) bacteria.

Biomimetic nuclear lamin fibers with remarkable toughness and stiffness.

The native hagfish slime threads, which are made up of two intermediate filament (IF)-like proteins, exhibit mechanical properties comparable to dragline spider silk fiber, the toughest fiber in nature. However, unlike silk, the design of artificial IF-protein-based fibers has been rarely studied, possibly because the unique hierarchical organization of the keratin-like proteins within these threads is challenging to mimic, and consequently, extraordinary fiber mechanics has not been shown in slime threads from recombinant IF-protein-based system. Here, we have reported the synthesis and properties of recombinant type V IF-protein, based on the Caenorhabditis elegans (Ce) lamin gene.

Acoustic Emission Monitoring of High-Strength Concrete Columns Subjected to Compressive Axial Loading.

Acoustic Emission (AE) nondestructive tests have attracted great interest for their use in the determination of structural properties and behavior of reinforced concrete (RC) elements. One of the applications this method can contribute to is in high-strength concrete (HSC) columns. These elements have a great advantage in the lower stories of high-rise buildings.

Are ergonomically designed road signs more easily learned?

Traffic signs are used to control and regulate traffic and create a safe environment for road users. Therefore, it is of great importance to ensure that road signs are easily understood and easily learned, especially by drivers. The current study, conducted in Israel, focused on the ability to learn unfamiliar road signs and on the effect of the compliance of those signs with principles of physical and conceptual compatibility (ergonomic principles for symbol design).

Fast and reliable determination of Escherichia coli susceptibility to antibiotics: Infrared microscopy in tandem with machine learning algorithms.

Antimicrobial drugs have an important role in controlling bacterial infectious diseases. However, the increasing resistance of bacteria to antibiotics has become a global health care problem. Rapid determination of antimicrobial susceptibility of clinical isolates is often crucial for the optimal antimicrobial therapy.

Detection of Extended-Spectrum β-Lactamase-Producing Escherichia coli Using Infrared Microscopy and Machine-Learning Algorithms.

The spread of multidrug resistant bacteria has become a global concern. One of the most important and emergent classes of multidrug-resistant bacteria is extended-spectrum β-lactamase-producing bacteria (ESBL-positive = ESBL). Due to widespread and continuous evolution of ESBL-producing bacteria, they become increasingly resistant to many of the commonly used antibiotics, leading to an increase in the mortality associated with resulting infections.

Expert evaluation of traffic signs: conventional vs. alternative designs.

Traffic sign comprehension is significantly affected by their compliance with ergonomics design principles. Despite the UN Convention, designs vary among countries. The goal of this study was to establish theoretical and methodological bases for evaluating the design of conventional and alternative signs.

A density based empirical likelihood approach for testing bivariate normality.

Sample entropy based tests, methods of sieves and Grenander estimation type procedures are known to be very efficient tools for assessing normality of underlying data distributions, in one-dimensional nonparametric settings. Recently, it has been shown that the density based empirical likelihood (EL) concept extends and standardizes these methods, presenting a powerful approach for approximating optimal parametric likelihood ratio test statistics, in a distribution-free manner. In this paper, we discuss difficulties related to constructing density based EL ratio techniques for testing bivariate normality and propose a solution regarding this problem.

The role of carbonate in electro-catalytic water oxidation by using Ni(1,4,8,11-tetraazacyclotetradecane).

NiL are good electro-catalysts for water oxidation in phosphate or carbonate buffers. The results point out that the active oxidizing agents are L(X)NiOH, where X = POH or COH formed from LNiXvia a mechanism involving an acid catalyzed O-P or O-C bond heterolysis. Carbonate behaves differently from phosphate as it is a non-innocent ligand and it can be oxidized.