Search Results (48)

Oximes have been reported to exhibit useful pharmaceutical properties, including compounds with anticancer, anti-arthritis, antibacterial, and neuroprotective activities. Many oximes are kinase inhibitors and have been shown to inhibit various kinases. Herein, a panel of oxime derivatives of tricyclic isatins was synthesized and evaluated for inhibition of cellular inflammatory responses and binding affinity to several kinases. Compounds 5a and 5d (a.k.a. NS-102), which have an unsubstituted oxime group, inhibited lipopolysaccharide (LPS)-induced nuclear factor-κB/activating protein 1 (NF-κB/AP-1) transcriptional activity in human THP-1Blue monocytic cells and interleukin-6 (IL-6) production in human MonoMac-6 monocytic cells, with IC₅₀ values in the micromolar range. These compounds also inhibited LPS-induced production of several other proinflammatory cytokines, including IL-1α, IL-1β, monocyte chemoattractant protein-1 (MCP-1), and tumor necrosis factor (TNF) in MonoMac-6 cells. Compounds 5a and 5d exhibited nanomolar/submicromolar binding affinity toward several kinase targets. The most potent inhibitor, 5d (3-(hydroxyimino)-5-nitro-1,3,6,7,8,9-hexahydro-2H-benzo[g]indol-2-one), demonstrated high binding affinity for 12 kinases, including DYRK1A, DYRK1B, PIM1, Haspin, HIPK1-3, IRAK1, NEK10, and DAPK1-3. Molecular modeling suggested modes of binding interaction of selected compounds in the DYRK1A and PIM1 catalytic sites that agreed with the experimental binding data. Our results demonstrate that tricyclic isatin oximes could be potential candidates for developing anti-inflammatory drugs with neuroprotective effects for treating neurodegenerative diseases. Full article

The implementation of the Authentication and Key Agreement (AKA) protocol in the Internet of Drones (IoD) is crucial for enhancing the security and reliability of information transmission. However, almost all existing authentication protocols between drones and Ground Station (GS) may suffer from several attacks due to capture attacks. In addition, the authentication between drones requires the participation of GS, which not only increases the amount of computation and transmission but also faces challenges such as impersonation attacks, lack of privacy protection, and perfect forward security. Therefore, we propose a secure and lightweight drone-to-GS (D2G) and D2D AKA protocol with perfect forward secrecy for IoD. Our protocol integrates physical unclonable functions (PUF) symmetrically into GS and drones to protect secret information against capture attacks while ensuring that GS does not store secret information related to drones. Furthermore, the proposed protocol enables direct mutual authentication between drones in a symmetrical manner without GS involvement, improving security and efficiency, particularly in scenarios where drones must collaborate without GS connectivity. Formal security proof using the random oracle model confirms the protocol’s resilience against various attacks. The performance analysis indicates that our scheme improves computational efficiency by an average of 39.44% compared to existing schemes that offer comparable security. Additionally, our approach incurs zero storage overhead during the GS authentication process. This protocol offers a secure and efficient solution for IoD, enhancing both security and scalability. Full article

The aim of the work was to study the effect of additive concentration on changes in the adhesive and cohesive strength of bitumen. To evaluate the effectiveness of modifiers in the composition of binary and triple bitumen systems in relation to mineral fillers of two grades, the method of determination of the adhesive efficiency and thermodynamic calculations of adhesion and cohesion work were used. The following compounds were used as additives: AS-2 synthesized from the oil refining waste and AG-4I (waste sealing liquid). Adhesion–cohesion processes in modified bitumen systems are limited by the wetting effect of crushed stone and the intensity of intermolecular forces in the condensed phase of the binder. In the binary compositions, the addition of modifiers into bitumen significantly improves the cohesive strength and adhesive efficiency in relation to crushed stone. The introduction of AS-2 into bitumen compositions with AG-4I increases adhesion efficiency and thermodynamic work of adhesion in relation to the filler surface. The adhesion efficiency and thermodynamic work of adhesion in the “bitumen-AG-4I-AS-2” system reach their maximum at C_AG-4I = 3.0 g/dm³ and C_AS-2 = 1.5 g/dm³. In these concentration modes, the composition ensures maximum increase in adhesion efficiency (A_KS = 65.18%; A_KA = 48.11%) and the greatest increase in thermodynamic work of adhesion (W_A(KS) = 15.79 mN/m; W_A(KA) = 14.13 mN/m). Full article

The 5G-AKA protocol, a foundational component for 5G network authentication, has been found vulnerable to various security threats, including linkability attacks that compromise user privacy. To address these vulnerabilities, we previously proposed the 5G-AKA-Forward Secrecy (5G-AKA-FS) protocol, which introduces an ephemeral key pair within the home network (HN) to support forward secrecy and prevent linkability attacks. However, a re-evaluation uncovered minor errors in the initial BAN-logic verification and highlighted the need for more rigorous security validation using formal methods. In this paper, we correct the BAN-logic verification and advance the formal security analysis by applying an extended SVO logic, which was adopted as it provides a higher level of verification compared to BAN logic, incorporating a new axiom specifically for forward secrecy. Additionally, we enhance the ProVerif analysis by employing a stronger adversarial model. These refinements in formal verification validate the security and reliability of 5G-AKA-FS, ensuring its resilience against advanced attacks. Our findings offer a comprehensive reference for future security protocol verification in 5G networks Full article

When it comes to the development of 4G and 5G technologies, long-range IoT or machine-to-machine (M2M) communication can be achieved with the help of cellular infrastructure. In non-standalone (NSA) 5G infrastructure, cellular-IoT (C-IoT) devices are attached and authenticated by a 4G core network even if it is connected to a 5G base station. In an NSA-based 5G network, the presence of dual connectivity sometimes raises interoperability and authentication issues due to technological differences between LTE and 5G. An attacker explores these technological differences, introduces the threats, and performs various types of attacks like session hijacking at the interfaces and Man-in-the-Middle (MITM) attacks. With the introduction of these attacks, the attackers exploit the network resources and pinch out various critical information sources. To resolve this issue, the NSA-based C-IoT network must incorporate robust and seamless authentication and authorization mechanisms. This article presents the ML-AKA protocol that is used to enhance interoperability and trust between 4G and 5G networks by using a uniform key-sharing (UKS) mechanism. The proposed ML-AKA protocol is analyzed with the help of the AVISPA tool and validated with the use of Proverif. Further, the proposed protocol is compared with other existing protocols like EPS-AKA and UAKA-D2D, and the outcome shows that the proposed protocol significantly reduces the chances of MITM, DDOS and Spoofing attacks during the interoperability in the NSA-C-IoT network. Full article

The rapid evolution of mobile and optical communication technologies is driving the transition from 5G to 6G networks. This transition inevitably brings about changes in authentication scenarios, as new security demands emerge that go beyond the capabilities of existing frameworks. Therefore, it is necessary to address these evolving requirements and the associated key challenges: ensuring Perfect Forward Secrecy (PFS) to protect communications even if long-term keys are compromised and integrating Post-Quantum Cryptography (PQC) techniques to defend against the threats posed by quantum computing. These are essential for both radio and optical communications, which are foundational elements of future 6G infrastructures. The DMRN Protocol, introduced in 2022, represents a major advancement by offering both PFS and PQC while maintaining compatibility with existing 3rd Generation Partnership Project (3GPP) standards. Given the looming quantum-era challenges, it is imperative to analyze the protocol’s security architecture through formal verification. Accordingly, we formally analyze the DMRN Protocol using SVO logic and ProVerif to assess its effectiveness in mitigating attack vectors, such as malicious or compromised serving networks (SNs) and home network (HN) masquerading. Our research found that the DMRN Protocol has vulnerabilities in key areas such as mutual authentication and key exchange. In light of these findings, our study provides critical insights into the design of secure and quantum-safe authentication protocols for the transition to 6G networks. Furthermore, by identifying the vulnerabilities in and discussing countermeasures to address the DMRN Protocol, this study lays the groundwork for the future standardization of secure 6G Authentication and Key Agreement protocols. Full article

The Internet of Things (IoT) has revolutionized connected devices, with applications in healthcare, data analytics, and smart cities. For time-sensitive applications, 5G wireless networks provide ultra-reliable low-latency communication (URLLC) and fog computing offloads IoT processing. Integrating 5G and fog computing can address cloud computing’s deficiencies, but security challenges remain, especially in Authentication and Key Agreement aspects due to the distributed and dynamic nature of fog computing. This study presents an innovative mutual Authentication and Key Agreement protocol that is specifically tailored to meet the security needs of fog computing in the context of the edge–fog–cloud three-tier architecture, enhanced by the incorporation of the 5G network. This study improves security in the edge–fog–cloud context by introducing a stateless authentication mechanism and conducting a comparative analysis of the proposed protocol with well-known alternatives, such as TLS 1.3, 5G-AKA, and various handover protocols. The suggested approach has a total transmission cost of only 1280 bits in the authentication phase, which is approximately 30% lower than other protocols. In addition, the suggested handover protocol only involves two signaling expenses. The computational cost for handover authentication for the edge user is significantly low, measuring 0.243 ms, which is under 10% of the computing costs of other authentication protocols. Full article

In the current study, the effects of drought stress on the growth and phytochemical profile of Scolymus hispanicus L. (a.k.a. golden thistle) were evaluated. Plants were treated with three irrigation regimes, e.g., plants that received only rainwater (Control; C), deficit irrigation (I1; 50% of field capacity (FC)), and full irrigation (Ι2; 100% of FC). The fresh weight of the rosette of leaves was not negatively impacted by deficit irrigation, whereas root development was severely restrained compared to control and I2 treatments. Drought stress conditions had a positive effect on the nutritional properties of the golden thistle since the treatments of control and deficit irrigation showed the highest content of macronutrients and energy. Oxalic acid was the richest organic acid, especially under the I1 regime. Similarly, α-tocopherol was the only identified vitamin E isoform, whose content was also doubled in I1 treatment. Raffinose, glucose, and sucrose were the most abundant free sugars in amounts that varied among the irrigation treatments, while the total and distinct free sugar content was the highest for the I1 treatment. The most abundant detected fatty acid compounds were α-linolenic acid, followed by palmitic and linoleic acid, with the highest amount being detected in C, I1, and I2 treatments, respectively. Flavonoids were the only class of polyphenols detected in golden thistle leaves, including mostly kaempferol and quercetin derivatives. The greatest antioxidant potency was shown for the control and I1 treatments (for OxHLIA and TBARS methods, respectively). The evaluated leaf samples recorded a varied antimicrobial effect for the different bacterial strains and fungi, whereas no cytotoxic, hepatotoxic, and anti-inflammatory effects against the tested cell lines were recorded. Finally, the mineral content of leaves was significantly affected by the irrigation regime, with Ca, Mg, Cu, and Zn being the highest for the I1 treatment, while the I2 treatment had the highest content of K, Fe, and Mn and the lowest Na content. In conclusion, deficit irrigation showed promising results since it improved the phytochemical content without compromising the fresh weight of leaves, and thus it could be suggested as a sustainable agronomic practice for producing high-added value products without significant constraints in growth development and yield parameters of golden thistle. Full article

5G acts as a highway enabling innovative digital transformation and the Fourth Industrial Revolution in our lives. It is undeniable that the success of such a paradigm shift hinges on robust security measures. Foremost among these is primary authentication, the initial step in securing access to 5G network environments. For the 5G primary authentication, two protocols, namely 5G Authentication and Key Agreement (5G-AKA) and Improved Extensible Authentication Protocol Method for 3rd Generation Authentication and Key Agreement (EAP-AKA′), were proposed and standardized, where the former is for 3GPP devices, and the latter is for non-3GPP devices. Recent scrutiny has unveiled vulnerabilities in the 5G-AKA protocol, exposing it to security breaches, including linkability attacks. Moreover, mobile communication technologies are dramatically evolving while 3GPP has standardized Authentication and Key Management for Applications (AKMA) to reuse the credentials, generated during primary authentication, for 5G network applications. That makes it so significant for 5G-AKA to be improved to support forward secrecy as well as address security attacks. In response, several protocols have been proposed to mitigate these security challenges. In particular, they tried to strengthen security by reusing secret keys negotiated through the Elliptic Curve Integrated Encryption Scheme (ECIES) and countering linkability attacks. However, they still have encountered limitations in completing forward secrecy. Motivated by this, we propose an augmentation to 5G-AKA to achieve forward security and thwart linkability attacks (called 5G-AKA-FS). In 5G-AKA-FS, the home network (HN), instead of using its static ECIES key pair, generates a new ephemeral key pair to facilitate robust session key negotiation, truly realizing forward security. In order to thoroughly and precisely prove that 5G-AKA-FS is secure, formal security verification is performed by applying both BAN Logic and ProVerif. As a result, it is demonstrated that 5G-AKA-FS is valid. Besides, our performance comparison highlights that the communication and computation overheads are intrinsic to 5G-AKA-FS. This comprehensive analysis showcases how the protocol effectively balances between security and efficiency. Full article

Lipids are important modifiers of protein function, particularly as parts of lipoproteins, which transport lipophilic substances and mediate cellular uptake of circulating lipids. As such, lipids are of particular interest as blood biological markers for cardiovascular disease (CVD) as well as for conditions linked to CVD such as atherosclerosis, diabetes mellitus, obesity and dietary states. Notably, lipid research is particularly well developed in the context of CVD because of the relevance and multiple causes and risk factors of CVD. The advent of methods for high-throughput screening of biological molecules has recently resulted in the generation of lipidomic profiles that allow monitoring of lipid compositions in biological samples in an untargeted manner. These and other earlier advances in biomedical research have shaped the knowledge we have about lipids in CVD. To evaluate the knowledge acquired on the multiple biological functions of lipids in CVD and the trends in their research, we collected a dataset of references from the PubMed database of biomedical literature focused on plasma lipids and CVD in human and mouse. Using annotations from these records, we were able to categorize significant associations between lipids and particular types of research approaches, distinguish non-biological lipids used as markers, identify differential research between human and mouse models, and detect the increasingly mechanistic nature of the results in this field. Using known associations between lipids and proteins that metabolize or transport them, we constructed a comprehensive lipid–protein network, which we used to highlight proteins strongly connected to lipids found in the CVD-lipid literature. Our approach points to a series of proteins for which lipid-focused research would bring insights into CVD, including Prostaglandin G/H synthase 2 (PTGS2, a.k.a. COX2) and Acylglycerol kinase (AGK). In this review, we summarize our findings, putting them in a historical perspective of the evolution of lipid research in CVD. Full article

Medical imaging-based biomarkers derived from small objects (e.g., cell nuclei) play a crucial role in medical applications. However, detecting and segmenting small objects (a.k.a. blobs) remains a challenging task. In this research, we propose a novel 3D small blob detector called BlobCUT. BlobCUT is an unpaired image-to-image (I2I) translation model that falls under the Contrastive Unpaired Translation paradigm. It employs a blob synthesis module to generate synthetic 3D blobs with corresponding masks. This is incorporated into the iterative model training as the ground truth. The I2I translation process is designed with two constraints: (1) a convexity consistency constraint that relies on Hessian analysis to preserve the geometric properties and (2) an intensity distribution consistency constraint based on Kullback-Leibler divergence to preserve the intensity distribution of blobs. BlobCUT learns the inherent noise distribution from the target noisy blob images and performs image translation from the noisy domain to the clean domain, effectively functioning as a denoising process to support blob identification. To validate the performance of BlobCUT, we evaluate it on a 3D simulated dataset of blobs and a 3D MRI dataset of mouse kidneys. We conduct a comparative analysis involving six state-of-the-art methods. Our findings reveal that BlobCUT exhibits superior performance and training efficiency, utilizing only 56.6% of the training time required by the state-of-the-art BlobDetGAN. This underscores the effectiveness of BlobCUT in accurately segmenting small blobs while achieving notable gains in training efficiency. Full article

An analytical method was established using high-performance liquid chromatography coupled with diode array and evaporative light scattering detectors (HPLC-DAD-ELSD) with -C₁₈ and -NH₂ column tandem for the simultaneous determination of hydrophobic atractylenolide I, II, III, atractylone and hydrophilic compounds glucose, fructose and sucrose in the dried rhizome of Atractylodes macrocephala Koidz (a natural raw material for health foods, Bai-Zhu aka. in Chinese). The method combines the different separation capabilities of reversed-phase liquid chromatography and hydrophilic interaction liquid chromatography. It can provides a new choice for the simultaneous determination of hydrophilic and hydrophobic compounds in traditional Chinese medicines and health foods. It provided a reference method for the quality control of Bai-Zhu. The results showed that the linear correlation coefficients of the established column tandem chromatographic method were all greater than 0.9990, the relative standard deviation was 0.1–2.8%, and the average recovery was 96.7–103.1%. The contents of atractylenolide I, II, III, atractylone, fructose, glucose, and sucrose in 17 batches of Baizhu were 172.3–759.8 μg/g, 201.4–612.8 μg/g, 160.3–534.2 μg/g, 541.4–8723.1 μg/g, 6.9–89.7 mg/g, 0.7–7.9 mg/g, and 1.2–21.0 mg/g, respectively. Full article

Satellite–ground integrated networks (SGIN) are in line with 6th generation wireless network technology (6G) requirements. However, security and privacy issues are challenging with heterogeneous networks. Specifically, although 5G authentication and key agreement (AKA) protects terminal anonymity, privacy preserving authentication protocols are still important in satellite networks. Meanwhile, 6G will have a large number of nodes with low energy consumption. The balance between security and performance needs to be investigated. Furthermore, 6G networks will likely belong to different operators. How to optimize the repeated authentication during roaming between different networks is also a key issue. To address these challenges, on-demand anonymous access and novel roaming authentication protocols are presented in this paper. Ordinary nodes implement unlinkable authentication by adopting a bilinear pairing-based short group signature algorithm. When low-energy nodes achieve fast authentication by utilizing the proposed lightweight batch authentication protocol, which can protect malicious nodes from DoS attacks. An efficient cross-domain roaming authentication protocol, which allows terminals to quickly connect to different operator networks, is designed to reduce the authentication delay. The security of our scheme is verified through formal and informal security analysis. Finally, the performance analysis results show that our scheme is feasible. Full article

This work aimed at preparing nanomicelles from N-benzyl-N,O-succinyl chitosan (NBSCh) loaded with a curcumin analog, 2,6-bis((3-methoxy-4-hydroxyphenyl) methylene) cyclohexanone, a.k.a. cyqualone (CL), for antineoplastic colon cancer chemotherapy. The CL-loaded NBSCh micelles were spherical and less than 100 nm in size. The entrapment efficiency of CL in the micelles ranged from 13 to 39%. Drug release from pristine CL was less than 20% in PBS at pH 7.4, whereas the release from CL-NBSCh micelles was significantly higher. The release study of CL-NBSCh revealed that around 40% of CL content was released in simulated gastric fluid at pH 1.2; 79 and 85% in simulated intestinal fluids at pH 5.5 and 6.8, respectively; and 75% in simulated colonic fluid at pH 7.4. CL-NBSCh showed considerably high selective cytotoxicity towards mucosal epithelial human colon cancer (HT-29) cells and lower levels of toxicity towards mouse connective tissue fibroblasts (L929). CL-NBSCh was also more cytotoxic than the free CL. Furthermore, compared to free CL, CL-NBSCh micelles were found to be more efficient at arresting cell growth at the G2/M phase, and induced apoptosis earlier in HT-29 cells. Collectively, these results indicate the high prospective potential of CL-loaded NBSCh micelles as an oral therapeutic intervention for colon cancer. Full article

Emerald ash borer (Agrilus planipennis) is an invasive pest that has killed millions of ash trees (Fraxinus spp.) in the USA since its first detection in 2002. Although the current methods for trapping emerald ash borers (e.g., sticky traps and trap trees) and visual ground and aerial surveys are generally effective, they are inefficient for precisely locating and assessing the declining and dead ash trees in large or hard-to-access areas. This study was conducted to develop and evaluate a new tool for safe, efficient, and precise detection and assessment of ash decline and death caused by emerald ash borer by using aerial surveys with unmanned aerial systems (a.k.a., drones) and a deep learning model. Aerial surveys with drones were conducted to obtain 6174 aerial images including ash decline in the deciduous forests in West Virginia and Pennsylvania, USA. The ash trees in each image were manually annotated for training and validating deep learning models. The models were evaluated using the object recognition metrics: mean average precisions (mAP) and two average precisions (AP50 and AP75). Our comprehensive analyses with instance segmentation models showed that Mask2former was the most effective model for detecting declining and dead ash trees with 0.789, 0.617, and 0.542 for AP50, AP75, and mAP, respectively, on the validation dataset. A follow-up in-situ field study conducted in nine locations with various levels of ash decline and death demonstrated that deep learning along with aerial survey using drones could be an innovative tool for rapid, safe, and efficient detection and assessment of ash decline and death in large or hard-to-access areas. Full article