淀粉直支比定量技术及其在食品领域中的应用

天然淀粉中含有直链和支链两种形式的α-D-葡聚糖,二者的相对含量不仅与淀粉的糊化、老化、凝胶等理化性质和食品功能有关,还决定着淀粉的经济价值。淀粉直支比定量技术在含淀粉的粮谷类作物育种、淀粉的高值化利用以及食品品质保障和创新等领域具有广泛的应用。本文综述了当前食品科学研究和加工制造领域对淀粉直支比定量技术的需求,介绍和对比了各种经典和新型淀粉直支比定量技术的原理、优缺点和适用性,对淀粉直支比定量技术在未来食品领域的潜在应用提出展望。     

Copresence of High-Risk Human Papillomaviruses and Epstein–Barr Virus in Colorectal Cancer: A Tissue Microarray and Molecular Study from Lebanon

Colorectal cancer (CRC) is the third most common cause of cancer-related deaths worldwide. Human papillomaviruses (HPVs) and Epstein–Barr virus (EBV) have been reported to be present in different types of human cancers, including CRCs, where they can play a key role in the onset and/or progression of these cancers. Thus, we herein explored the prevalence of high-risk HPVs and EBV in a cohort of 94 CRC tissue samples and 13 colorectal normal tissues from the Lebanese population using polymerase chain reaction, immunohistochemistry, and tissue microarray methodologies. We found that high-risk HPVs are present in 64%, while EBV is present in 29% of our CRC samples. Additionally, our data showed that high-risk HPV types (16, 18, 35, 58, 51, 45, 52, 31, and 33) are the most frequent in CRC in the Lebanese cohort, respectively. Our data point out that HPVs and EBV are copresent in 28% of the samples. Thus, this study clearly suggests that high-risk HPVs and EBV are present/copresent in CRCs, where they could play an important role in colorectal carcinogenesis. Nevertheless, further investigations using a larger cohort are needed to elucidate the possible cooperation between these oncoviruses in the development of CRC.     

Fog-Sec: Secure end-to-end communication in fog-enabled IoT network using permissioned blockchain system

The technological integration of the Internet of Things (IoT)-Cloud paradigm has enabled intelligent linkages of things, data, processes, and people for efficient decision making without human intervention. However, it poses various challenges for IoT networks that cannot handle large amounts of operation technology (OT) data due to physical storage shortages, excessive latency, higher transfer costs, a lack of context awareness, impractical resiliency, and so on. As a result, the fog network emerged as a new computing model for providing computing capacity closer to IoT edge devices. The IoT-Fog-Cloud network, on the other hand, is more vulnerable to multiple security flaws, such as missing key management problems, inappropriate access control, inadequate software update mechanism, insecure configuration files and default passwords, missing communication security, and secure key exchange algorithms over unsecured channels. Therefore, these networks cannot make good security decisions, which are significantly easier to hack than to defend the fog-enabled IoT environment. This paper proposes the cooperative flow for securing edge devices in fog-enabled IoT networks using a permissioned blockchain system (pBCS). The proposed fog-enabled IoT network provides efficient security solutions for key management issues, communication security, and secure key exchange mechanism using a blockchain system. To secure the fog-based IoT network, we proposed a mechanism for identification and authentication among fog, gateway, and edge nodes that should register with the blockchain network. The fog nodes maintain the blockchain system and hold a shared smart contract for validating edge devices. The participating fog nodes serve as validators and maintain a distributed ledger/blockchain to authenticate and validate the request of the edge nodes. The network services can only be accessed by nodes that have been authenticated against the blockchain system. We implemented the proposed pBCS network using the private Ethereum 2.0 that enables secure device-to-device communication and demonstrated performance metrics such as throughput, transaction delay, block creation response time, communication, and computation overhead using state-of-the-art techniques. Finally, we conducted a security analysis of the communication network to protect the IoT edge devices from unauthorized malicious nodes without data loss.     

Enhancing Parkinson’s Disease Diagnosis Accuracy Through Speech Signal Algorithm Modeling

Parkinson’s disease (PD), one of whose symptoms is dysphonia, is a prevalent neurodegenerative disease. The use of outdated diagnosis techniques, which yield inaccurate and unreliable results, continues to represent an obstacle in early-stage detection and diagnosis for clinical professionals in the medical field. To solve this issue, the study proposes using machine learning and deep learning models to analyze processed speech signals of patients’ voice recordings. Datasets of these processed speech signals were obtained and experimented on by random forest and logistic regression classifiers. Results were highly successful, with 90% accuracy produced by the random forest classifier and 81.5% by the logistic regression classifier. Furthermore, a deep neural network was implemented to investigate if such variation in method could add to the findings. It proved to be effective, as the neural network yielded an accuracy of nearly 92%. Such results suggest that it is possible to accurately diagnose early-stage PD through merely testing patients’ voices. This research calls for a revolutionary diagnostic approach in decision support systems, and is the first step in a market-wide implementation of healthcare software dedicated to the aid of clinicians in early diagnosis of PD.     

Diffusion of chemically reactive species in third grade fluid flow over an exponentially stretching sheet considering magnetic field effects

This article addresses the magnetohydrodynamics (MHD) flow of a third grade fluid over an exponentially stretching sheet.Analysis is carried out in the presence of first order chemical reaction.Both cases of constructive and destructive chemical reactions are reported.Convergent solutions of the resulting differential systems are presented in series forms.Characteristics of various sundry parameters on the velocity,concentration,skin friction and local Sherwood number are analyzed and discussed.     

Furosine induces DNA damage and cell death in selected human cell lines: a strong toxicant to kidney Hek-293 cells

Food Science and Biotechnology - Ne-(2-furoylmethyl)-l-lysine (furosine) is well-known indicator of early stage of Maillard reaction in processed food. Yet the toxicological aspects associated with...     

A Rational Insight into the Effect of Dimethyl Sulfoxide on TNF-α Activity

Direct inhibition of tumor necrosis factor-alpha (TNF-α) action is considered a promising way to prevent or treat TNF-α-associated diseases. The trimeric form of TNF-α binds to its receptor (TNFR) and activates the downstream signaling pathway. The interaction of TNF-α with molecular-grade dimethyl sulfoxide (DMSO) in an equal volumetric ratio renders TNF-α inert, in this state, TNF-α fails to activate TNFR. Here, we aimed to examine the inhibition of TNF-α function by various concentrations of DMSO. Its higher concentration led to stronger attenuation of TNF-α-induced cytokine secretion by fibroblasts, and of their death. We found that this inhibition was mediated by a perturbation in the formation of the functional TNF-α trimer. Molecular dynamics simulations revealed a transient interaction between DMSO molecules and the central hydrophobic cavity of the TNF-α homodimer, indicating that a brief interaction of DMSO with the TNF-α homodimer may disrupt the formation of the functional homotrimer. We also found that the sensitizing effect of actinomycin D on TNF-α-induced cell death depends upon the timing of these treatments and on the cell type. This study will help to select an appropriate concentration of DMSO as a working solvent for the screening of water-insoluble TNF-α inhibitors.     

Green Chemical Synthesis of Silver Nanoparticles and its Catalytic Activity

Silver nanoparticles (Ag(0) NPs) were synthesized by the chemical reduction method, in which ceftriaxone (antibiotic) used as reducing (to convert Ag⁺ to Ag(0)) and capping agent. UV–Visible spectroscopy revealed the first indication of formation of Ag(0) NPs. FT-IR spectroscopy showed the interaction of formation of bonding between antibiotic standard and silver. X-ray powder diffraction powder pattern confirmed the crystalline nature of prepared Ag(0) NPs. These Ag(0) NPs were used as catalyst for three organic hazardous chemicals i.e., 4-nitro-1,3-Phenylene diamine, 6-methyl-2-nitroanilline, 4-methyle-2-nitroanilline. The prepared Ag(0) NPs showed good catalytic activity against these compounds.     

Ultra-fast catalytic reduction of dyes by ionic liquid recoverable and reusable mefenamic acid derived gold nanoparticles

We synthesized mefenamic acid (MA) derived gold nanoparticles (MA-AuNps) in aqueous solution (MA-Au sol). Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM) of the sol at 1, 5, 15 and 60 min showed changes in size and shape of formed AuNps. Fourier Transform Infrared (FTIR) Spectroscopy revealed the interaction between AuNps and MA. Each Au sol exhibited exceptional catalytic activity for the reduction of Methylene Blue (MB), Rose Bengal (RB) and Eosin B (EB) dye individually as well as collectively. However, complete reduction of dye(s) was accomplished by Au sol of 5 min in just 15s. The catalytic performance of Ma-Au sol was far superior to that adsorbed on glass. AuNps were recovered with the help of water insoluble room temperature ionic liquid and reused with enhanced catalytic potential. This finding is a novel, rapid and highly economical alternative for environmental safety against pollution by dyes and extendable for control of other reducible contaminants as well.     

Ultrasound-Assisted Chitosan–Surfactant Nanostructure Assemblies: Towards Maintaining Postharvest Quality of Tomatoes

A novel ultrasound-assisted chitosan–surfactant nanostructure assembly was developed to allow better delivery of chitosan particles into intact fruit tissues for extension of postharvest life. Three solutions of 1 % chitosan–surfactant nanostructure assembly with micelle sizes of 400, 600 and 800 nm were prepared and applied as an edible coating on tomatoes. The fruits were stored at 15?±?2 °C and 70–80 % relative humidity for 20 days. The indicators of tomato ripening, which included loss of firmness, decline of titratable acidity, decline of chlorophyll content and increase in soluble solid content, were delayed in the treated fruits in comparison to the control (p?<?0.05). A delay of approximately 5 days in ripening was observed by evaluating the colour evolution from green to red. The treatment significantly (p?<?0.05) enhanced the phenolic content while maintaining a lower level of respiration in comparison to the control, throughout most of the storage duration. However, weight loss was higher in the treated fruits in comparison to the control. No significant difference in the resultant effects was observed by using chitosan–surfactant nanostructure assemblies of different micelle sizes (p?>?0.05).