A study on fractional tumor-immune interaction model related to lung cancer via generalized Laguerre polynomials.

BACKGROUND: Cancer, a complex and deadly health concern today, is characterized by forming potentially malignant tumors or cancer cells. The dynamic interaction between these cells and their environment is crucial to the disease. Mathematical models can enhance our understanding of these interactions, helping us predict disease progression and treatment strategies. METHODS: In this study, we develop a fractional tumor-immune interaction model specifically for lung cancer (FTIIM-LC). We present some definitions and significant results related to the Caputo operator. We employ the generalized Laguerre polynomials (GLPs) method to find the optimal solution for the FTIIM-LC model. We then conduct a numerical simulation and compare the results of our method with other techniques and real-world data. RESULTS: We propose a FTIIM-LC model in this paper. The approximate solution for the proposed model is derived using a series of expansions in a new set of polynomials, the GLPs. To streamline the process, we integrate Lagrange multipliers, GLPs, and operational matrices of fractional and ordinary derivatives. We conduct a numerical simulation to study the effects of varying fractional orders and achieve the expected theoretical results. CONCLUSION: The findings of this study demonstrate that the optimization methods used can effectively predict and analyze complex phenomena. This innovative approach can also be applied to other nonlinear differential equations, such as the fractional Klein-Gordon equation, fractional diffusion-wave equation, breast cancer model, and fractional optimal control problems.

Printed Silk Microelectrode Arrays for Electrophysiological Recording and Controlled Drug Delivery.

The use of soft and flexible bioelectronic interfaces can enhance the quality for recording cells' electrical activity by ensuring a continuous and intimate contact with the smooth, curving surfaces found in the physiological environment. This work develops soft microelectrode arrays (MEAs) made of silk fibroin (SF) films for recording interfaces that can also serve as a drug delivery system. Inkjet printing is used as a tool to deposit the substrate, conductive electrode, and insulator, as well as a drug-delivery nanocomposite film. This approach is highly versatile, as shown in the fabrication of carbon microelectrodes, sandwiched between a silk substrate and a silk insulator. The technique permits the development of thin-film devices that can be employed for in vitro extracellular recordings of HL-1 cell action potentials. The tuning of SF by applying an electrical stimulus to produce a permeable layer that can be used in on-demand drug delivery systems is also demonstrated. The multifunctional MEA developed here can pave the way for in vitro drug screening by applying time-resolved and localized chemical stimuli.

The scholarly footprint of ChatGPT: a bibliometric analysis of the early outbreak phase.

This paper presents a comprehensive analysis of the scholarly footprint of ChatGPT, an AI language model, using bibliometric and scientometric methods. The study zooms in on the early outbreak phase from when ChatGPT was launched in November 2022 to early June 2023. It aims to understand the evolution of research output, citation patterns, collaborative networks, application domains, and future research directions related to ChatGPT. By retrieving data from the Scopus database, 533 relevant articles were identified for analysis. The findings reveal the prominent publication venues, influential authors, and countries contributing to ChatGPT research. Collaborative networks among researchers and institutions are visualized, highlighting patterns of co-authorship. The application domains of ChatGPT, such as customer support and content generation, are examined. Moreover, the study identifies emerging keywords and potential research areas for future exploration. The methodology employed includes data extraction, bibliometric analysis using various indicators, and visualization techniques such as Sankey diagrams. The analysis provides valuable insights into ChatGPT's early footprint in academia and offers researchers guidance for further advancements. This study stimulates discussions, collaborations, and innovations to enhance ChatGPT's capabilities and impact across domains.

Evaluation of grain yield stability of tritipyrum as a novel cereal in comparison with triticale lines and bread wheat varieties through univariate and multivariate parametric methods.

Salinity is a major abiotic stress affecting cereal production. Thus, tritipyrum (x. Tritipyrum), a potential novel salt-tolerant cereal, was introduced as an appropriate alternative for cereal production. The purposes of this study were to evaluate agronomic traits, yield, and yield stability of eight primary tritipyrum lines, five promising triticale lines, and four bread wheat varieties and to screen a stable yielding line. The experiments were conducted in randomized complete block designs with three replicates in three locations during four growing seasons. Analysis of variance in each environment and Bartlett's test for the variance homogeneity of experimental errors were made. Subsequently, separate experiments were analyzed as a combined experiment. The stability of grain yield was analyzed according to Eberhart and Russell's regression method, environmental variance, Wrick's ecovalance, Shokla's stability variance, AMMI, and Tai methods. Genotype × environment interactions (GEI) and environments were significant for the agronomic traits. Stability analysis revealed that combined primary tritipyrum line (Ka/b)(Cr/b)-5 and triticale 4115, 4108, and M45 lines had good adaptability in all environments. The results of the AMMI3 model and pattern analysis showed that the new cereal, tritipyrum, had the most stable response in various environments. The tritipyrum line (Ka/b)(Cr/b)-5 had the best yield performance and general adaptability. Based on Tai's method, the contribution of spike number to the stability of grain yield over different environments was higher than that of other yield components. Also, tritipyrum lines demonstrated higher stability compared with wheat and triticale. Totally, M45 triticale and tritipyrum (Ka/b)(Cr/b)-5 lines were the most stable genotypes with high grain yield. Complementary agronomic experiments may then release a new grain crop of triticale and a new pasture line of combined primary tritipyrum for grain and forage. Moreover, the combined tritipyrum line can be used in bread wheat breeding programs for producing salt-tolerant wheat cultivars.

High-Aspect-Ratio Nanoelectrodes Enable Long-Term Recordings of Neuronal Signals with Subthreshold Resolution.

The further development of neurochips requires high-density and high-resolution recordings that also allow neuronal signals to be observed over a long period of time. Expanding fields of network neuroscience and neuromorphic engineering demand the multiparallel and direct estimations of synaptic weights, and the key objective is to construct a device that also records subthreshold events. Recently, 3D nanostructures with a high aspect ratio have become a particularly suitable interface between neurons and electronic devices, since the excellent mechanical coupling to the neuronal cell membrane allows very high signal-to-noise ratio recordings. In the light of an increasing demand for a stable, noninvasive and long-term recording at subthreshold resolution, a combination of vertical nanostraws with nanocavities is presented. These structures provide a spontaneous tight coupling with rat cortical neurons, resulting in high amplitude sensitivity and postsynaptic resolution capability, as directly confirmed by combined patch-clamp and microelectrode array measurements.

Optimal Solution of a Fractional HIV/AIDS Epidemic Mathematical Model.

This article presents a fractional mathematical model of the human immunodeficiency virus (HIV)/AIDS spread with a fractional derivative of the Caputo type. The model includes five compartments corresponding to the variables describing the susceptible patients, HIV-infected patients, people with AIDS but not receiving antiretroviral treatment, patients being treated, and individuals who are immune to HIV infection by sexual contact. Moreover, it is assumed that the total population is constant. We construct an optimization technique supported by a class of basis functions, consisting of the generalized shifted Jacobi polynomials (GSJPs). The solution of the fractional HIV/AIDS epidemic model is approximated by means of GSJPs with coefficients and parameters in the matrix form. After calculating and combining the operational matrices with the Lagrange multipliers, we obtain the optimization method. The theorems on the existence, unique, and convergence results of the method are proved. Several illustrative examples show the performance of the proposed method. Mathematics Subject Classification: 97M60; 41A58; 92C42.

Generative Adversarial Network-Based Scheme for Diagnosing Faults in Cyber-Physical Power Systems.

This paper presents a novel diagnostic framework for distributed power systems that is based on using generative adversarial networks for generating artificial knockoffs in the power grid. The proposed framework makes use of the raw data measurements including voltage, frequency, and phase-angle that are collected from each bus in the cyber-physical power systems. The collected measurements are firstly fed into a feature selection module, where multiple state-of-the-art techniques have been used to extract the most informative features from the initial set of available features. The selected features are inputs to a knockoff generation module, where the generative adversarial networks are employed to generate the corresponding knockoffs of the selected features. The generated knockoffs are then fed into a classification module, in which two different classification models are used for the sake of fault diagnosis. Multiple experiments have been designed to investigate the effect of noise, fault resistance value, and sampling rate on the performance of the proposed framework. The effectiveness of the proposed framework is validated through a comprehensive study on the IEEE 118-bus system.

The Use of Big Data via 5G to Alleviate Symptoms of Acute Stress Disorder Caused by Quarantine Measures.

This article investigates the role of Big Data in situations of psychological stress such as during the recent pandemic caused by the COVID-19 health crisis. Quarantine measures, which are necessary to mitigate pandemic risk, are causing severe stress symptoms to the human body including mental health. We highlight the most common impact factors and the uncertainty connected with COVID-19, quarantine measures, and the role of Big Data, namely, how Big Data can help alleviate or mitigate these effects by comparing the status quo of current technology capabilities with the potential effects of an increase of digitalization on mental health. We find that, while Big Data helps in the pre-assessment of potentially endangered persons, it also proves to be an efficient tool in alleviating the negative psychological effects of quarantine. We find evidence of the positive effects of Big Data on human health conditions by assessing the effect of internet use on mental health in 173 countries. We found positive effects in 110 countries with 90 significant results. However, increased use of digital media and exclusive exposure to digital connectivity causes negative long-term effects such as a decline in social empathy, which creates a form of psychological isolation, causing symptoms of acute stress disorder.

Is there a causal relationship between oil prices and tourist arrivals?

This application note investigates the causal relationship between oil price and tourist arrivals to further explain the impact of oil price volatility on tourism-related economic activities. The analysis itself considers the time domain, frequency domain and information theory domain perspectives. Data relating to US and nine European countries are exploited in this paper with causality tests which include time domain, frequency domain, and Convergent Cross Mapping (CCM). The CCM approach is nonparametric and therefore not restricted by assumptions. We contribute to existing research through the successful and introductory application of an advanced method, and via the uncovering of significant causal links from oil prices to tourist arrivals.

Platinum substrate for surface plasmon microscopy at small angles.

Platinum is reported as the main component of the substrate in surface plasmon microscopy of the metal-dielectric interface for small-angle measurements. In the absence of a narrow dip in the angular spectrum of platinum, the refractive index of the dielectric medium or the thickness of a deposited layer is proven deducible from the observed sharp peak, close to the critical angle. The sensitivities of refractive index and thickness measurements using platinum are compared with that of a gold surface plasmon resonance chip. Furthermore, the thickness of a structured layer of (3-Aminopropyl)triethoxysilane on the platinum substrate is measured to be 0.7 nm, demonstrating the high sensitivity of the technique.

Forecasting interest rate volatility of the United Kingdom: evidence from over 150 years of data.

This study examines the very short, short, medium and long-term forecasting ability of different univariate GARCH models of United Kingdom (UK)'s interest rate volatility, using a long span monthly data from May 1836 to June 2018. The main results show the relevance of considering alternative error distributions to the normal distribution when estimating GARCH-type models. Thus, we obtain that the Asymmetric Power ARCH (A-PARCH) models with skew generalized error distribution are the most accurate models when forecasting UK interest rates, while for the short, medium and long-term term forecasting horizons, GARCH models with generalized error distribution for the error term are the most accurate models in forecasting UK's interest rates.

Surface Functionalization of Platinum Electrodes with APTES for Bioelectronic Applications.

The interface between electronic components and biological objects plays a crucial role in the success of bioelectronic devices. Since the electronics typically include different elements such as an insulating substrate in combination with conducting electrodes, an important issue of bioelectronics involves tailoring and optimizing the interface for any envisioned applications. In this paper, we present a method for functionalizing insulating substrates (SiO2) and metallic electrodes (Pt) simultaneously with a stable monolayer of organic molecules ((3-aminopropyl)triethoxysilane (APTES)). This monolayer is characterized by high molecule density, long-term stability, and positive surface net charge and most likely represents a self-assembled monolayer (SAM). It facilitates the conversion of biounfriendly Pt surfaces into biocompatible surfaces, which allows cell growth (neurons) on both functionalized components, SiO2 and Pt, which is comparable to that of reference samples coated with poly-L-lysine (PLL). Moreover, the functionalization greatly improves the electronic cell-chip coupling, thereby enabling the recording of action potential signals of several millivolts at APTES-functionalized Pt electrodes.

A new five-parameter Birnbaum-Saunders distribution for modeling bicoid gene expression data.

An extended version of Birnbaum-Saunders distribution with five parameters is introduced. Theoretical aspects of five-parameter Birnbaum-Saunders distribution and the maximum likelihood estimation of parameters are presented. The reliability and applicability of the proposed distribution is evaluated using both simulation and real-world data namely bicoid gene expression profile. The findings of this research confirm that the newly proposed five-parameter Birnbaum-Saunders distribution can be utilized to describe the distribution of bicoid gene expression profile.

Plasma metabolomic profiling of amino acids and polar lipids in Iranian obese adults.

BACKGROUND: Obesity, widely recognized as a serious health concern, is characterized by profoundly altered metabolism. However, the intermediate metabolites involved in this change remain largely unknown. OBJECTIVE: We conducted targeted metabolomics profiling to identify moieties associated with adult obesity. METHODS: In this case-control study of Iranian adults, 200 obese patients were compared with 100 controls based on 104 metabolites profiled by a targeted metabolomic approach using liquid chromatography coupled to triple quadrupole mass spectrometry (LC-MS/MS). The analysis comprised acylcarnitines, diacyl-phosphatidylcholines (PCaa), acyl-alkyl-phosphatidylcholines (PCae), sphingomyelins (SM), lyso-phospholipids (LPC) and amino acids. We performed multivariable linear regression to identify metabolites associated with obesity, adjusting for age, sex, total energy intake, total physical activity, smoking, and alcohol consumption. The Bonferroni correction was used to adjust for multiple testing. RESULTS: A pattern of 19 metabolites was significantly associated with obesity. Branched chain amino acids, alanine, glutamic acid, proline, tyrosine LPCa C16:1, PCaa C32:1, PCaa C32:2 and PCaa C38:3 were positively, while serine, asparagine, LPCa C18:1, LPCa C18:2, LPCe C18:0, PCae C34:3, PCae C38:4 and PCae C40:6 were negatively associated with obesity (all p < 0.00048). CONCLUSIONS: A metabolomic profile containing 9 amino acids and 10 polar lipids may serve as a potential biomarker of adult obesity. Further studies are warranted to replicate these findings as well as investigate potential changes in this profile after weight reduction.

Noninvasive measurement of the refractive index of cell organelles using surface plasmon resonance microscopy.

The health of a eukaryotic cell depends on the proper functioning of its cell organelles. Characterizing these nanometer- to micrometer-scaled specialized subunits without disturbing the cell is challenging but can also provide valuable insights regarding the state of a cell. We show that objective-based scanning surface plasmon resonance microscopy can be used to analyze the refractive index of cell organelles quantitatively in a noninvasive and label-free manner with a lateral resolution at the diffraction limit.

Risk management, signal processing and econometrics: A new tool for forecasting the risk of disease outbreaks.

This paper takes a novel approach for forecasting the risk of disease emergence by combining risk management, signal processing and econometrics to develop a new forecasting approach. We propose quantifying risk using the Value at Risk criterion and then propose a two staged model based on Multivariate Singular Spectrum Analysis and Quantile Regression (MSSA-QR model). The proposed risk measure (PLVaR) and forecasting model (MSSA-QR) is used to forecast the worst cases of waterborne disease outbreaks in 22 European and North American countries based on socio-economic and environmental indicators. The results show that the proposed method perfectly forecasts the worst case scenario for less common waterborne diseases whilst the forecasting of more common diseases requires more socio-economic and environmental indicators.

Production and First Assessment of Iranian Secondary Tritipyrum Genotypes by GISH and AFLP Markers.

BACKGROUND: Non-Iranian Primary Tritipyrum (2n=6x=42, AABBEbEb) set seed after Triticale (2n=6x=42, AABBRR) and Tritordeum (2n=6x=42, AABBHcHc) but, due to a few undesirable agronomic traits, it cannot fulfil the commercial expectations of farming. OBJECTIVES: To remove these deficiencies, six hexaploid Tritipyrum lines were crossed with four Iranian bread wheat cultivars which led to the production of 107 (F1), 479 (F2), 768 (F3), and 1539 (F4) Iranian Secondary Tritipyrum Genotypes (ISTG) seeds. This study was carried out for selecting the plants potentially carry the 5Eb chromosome/s and are good candidates for salt tolerant by GISH and RFLP markers. MATERIALS AND METHODS: The procedure involved extracting the total DNA content of 209 plants, including non-Iranian primary Tritipyrum lines, Iranian wheat cultivars, Chinese Spring addition, and substitution lines for 5Eb and Iranian secondary Tritipyrum genotypes (ISTG: F1, F2, F3, F4). Genomic in situ Hybridization (GISH) on mitotic spreads of fertile new Iranian secondary Tritipyrum genotypes (ISTG) was carried out to demonstrate the feasibility of single Eb chromosomes. There were three trials of 18 Fragment Length Polymorphism (AFLP) EcoRI/MseI primers to identify the presence of the 5Eb chromosome in 105 ISTG plants, along with four wheat addition lines and substitution lines for the 5Eb chromosome. RESULTS: GISH on mitotic spreads demonstrated the feasibility of producing 75 plants out of 105 fertile new Iranian secondary Tritipyrum genotypes (ISTG) with 0-14 single Eb chromosomes. Among the mentioned markers, only the E36/M59 marker showed 43, 50, 30 and 47 identical bands, respectively, in contrast to 53 expected bands in all plants with the 5Eb chromosome which indicated 21, 33, 9 and 6 out of 75 ISTG plants, respectively, with the 5Eb chromosome. CONCLUSION: This study indicated that 69 ISTG Tritipyrum plants were potentially carry the 5Eb chromosome/s and are good candidates for salt tolerant tests in comparison with Iranian modern bread wheat cultivars.

Spatial gradient of bicoid is well explained by Birnbaum-Saunders distribution.

bicoid is a maternally transcribed gene which plays a pivotal role during the early developmental stage of Drosophila melanogaster by acting as an essential input to the segmentation network. Therefore, fundamental insights into gene cross-regulations of segmentation network expect to be unveiled by presenting an accurate mathematical model for bicoid gene expression profile. In this paper, an extended version of Birnbaum-Saunders with four parameters is introduced and evaluated to describe the spatial gradient of this gene. Theoretical aspects of four-parameter Birnbaum-Saunders and the estimated parameters are presented and thoroughly assessed for different embryos. The reliability and validity of the results are evaluated via both simulation studies and real data sets and thereby adding more confidence and value to the findings of this research.

Nanometer-Resolved Mapping of Cell-Substrate Distances of Contracting Cardiomyocytes Using Surface Plasmon Resonance Microscopy.

It has been shown that quantitative measurements of the cell-substrate distance of steady cells are possible with scanning surface plasmon resonance microscopy setups in combination with an angle resolved analysis. However, the accuracy of the determined cell-substrate distances as well as the capabilities for the investigation of cell dynamics remained limited due to the assumption of a homogeneous refractive index of the cytosol. Strong spatial or temporal deviations between the local refractive index and the average value can result in errors in the calculated cell-substrate distance of around 100 nm, while the average accuracy was determined to 37 nm. Here, we present a combination of acquisition and analysis techniques that enables the measurement of the cell-substrate distance of contractile cells as well as the study of intracellular processes through changes in the refractive index at the diffraction limit. By decoupling the measurement of the cell-substrate distance and the refractive index of the cytoplasm, we could increase the accuracy of the distance measurement on average by a factor of 25 reaching 1.5 nm under ideal conditions. We show a temporal and spatial mapping of changes in the refractive index and the cell-substrate distance which strongly correlate with the action potentials and reconstruct the three-dimensional profile of the basal cell membrane and its dynamics, while we reached an actual measurement accuracy of 2.3 nm.

Bicoid signal extraction: Another powerful approach.

This belief has been widely accepted that Bicoid (Bcd) protein distributes in a concentration gradient that organizes the anterior/posterior axis of the Drosophila embryo. Segment polarity protein provides positional cues for the development of head and thoracic segments. Therefore As a result of its essential role, modeling the Bicoid gradient has been welcomed by many researchers in various scientific fields. In this paper, We present investigation of gene expression profiles by means of Singular Spectrum Decomposition (SSD), an optimizing version of Singular Spectrum Analysis for filtering and extracting the bicoid gene expression signal. The results with strong evidence suggest that the proposed technique is capable of eliminating noise and can be considered as an acceptable method for filtering gene expression.