Cyp6g2 is the major P450 epoxidase responsible for juvenile hormone biosynthesis in Drosophila melanogaster.

BACKGROUND: Juvenile hormones (JH) play crucial role in regulating development and reproduction in insects. The most common form of JH is JH III, derived from MF through epoxidation by CYP15 enzymes. However, in the higher dipterans, such as the fruitfly, Drosophila melanogaster, a bis-epoxide form of JHB3, accounted most of the JH detected. Moreover, these higher dipterans have lost the CYP15 gene from their genomes. As a result, the identity of the P450 epoxidase in the JH biosynthesis pathway in higher dipterans remains unknown. RESULTS: In this study, we show that Cyp6g2 serves as the major JH epoxidase responsible for the biosynthesis of JHB3 and JH III in D. melanogaster. The Cyp6g2 is predominantly expressed in the corpus allatum (CA), concurring with the expression pattern of jhamt, another well-studied gene that is crucial in the last steps of JH biosynthesis. Mutation in Cyp6g2 leads to severe disruptions in larval-pupal metamorphosis and exhibits reproductive deficiencies, exceeding those seen in jhamt mutants. Notably, Cyp6g2-/-::jhamt2 double mutants all died at the pupal stage but could be rescued through the topical application of JH analogs. JH titer analyses revealed that both Cyp6g2-/- mutant and jhamt2 mutant lacking JHB3 and JH III, while overexpression of Cyp6g2 or jhamt caused a significant increase in JHB3 and JH III titer. CONCLUSIONS: These findings collectively established that Cyp6g2 as the major JH epoxidase in the higher dipterans and laid the groundwork for the further understanding of JH biosynthesis. Moreover, these findings pave the way for developing specific Cyp6g2 inhibitors as insect growth regulators or insecticides.

The Prl3d1-Cre mouse line selectively induces the expression of Cre recombinase in parietal trophoblast giant cells.

The placenta plays a pivotal role in the maintenance of normal pregnancy, but how it forms, matures, and performs its function remains poorly understood. Here, we describe a novel mouse line (Prl3d1-iCre) that expresses iCre recombinase under the control of the endogenous prl3d1 promoter. Prl3d1 has been proposed as a marker for distinguishing trophoblast giant cells (TGCs) from other trophoblast cells in the placenta. The in vivo efficiency and specificity of the Cre line were analyzed by interbreeding Prl3d1-iCre mice with B6-G/R reporter mice. Through anatomical studies of the placenta and other tissues of Prl3d1-iCre/+; B6-G/R mouse mice, we found that the tdTomato signal was expressed in parietal trophoblast giant cells (P-TGCs). Thus, we report a mouse line with ectopic Cre expression in P-TGCs, which provides a valuable tool for studying human pathological pregnancies caused by implantation failure or abnormal trophoblast secretion due to aberrant gene regulation.

Metasurface Glass for Wireless Communication and Energy Saving.

With the growing global energy demand and environmental issues, energy saving technologies are becoming increasingly important in the building sector. Conventional windows lack energy saving and thermal insulation capabilities, while Low emissivity glass (Low-e glass) attenuates mobile communication signals while reflecting infrared. Therefore, this paper aims to design a type of windows for the "Sub 6GHz" frequency band of 5G. These windows combine the inherent transparency of traditional glass windows with the energy saving properties of Low-e glass, while also ensuring optimal communication performance within the 5G (Sub 6G) band. The metasurface glass is fabricated and subjected to simulation-guided experiments to evaluate their reliability and practicality. The metasurface glass is rigorously assessed in terms of microwave transmission performance, infrared low emissivity performance, and energy saving and thermal insulation capabilities.

The role of drug efflux and uptake transporters in the plasma pharmacokinetics and tissue disposition of morphine and its main metabolites.

Morphine is a widely used opioid for the treatment of pain. Differences in drug transporter expression and activity may contribute to variability in morphine pharmacokinetics and response. Using appropriate mouse models, we investigated the impact of the efflux transporters ABCB1 and ABCG2 and the OATP uptake transporters on the pharmacokinetics of morphine, morphine-3-glucuronide (M3G), and M6G. Upon subcutaneous administration of morphine, its plasma exposure in Abcb1a/1b-/-;Abcg2-/--, Abcb1a/1b-/-;Abcg2-/-;Oatp1a/1b-/-;Oatp2b1-/- (Bab12), and Oatp1a/1b-/-;Oatp2b1-/- mice was similar to that found in wild-type mice. Forty minutes after dosing, morphine brain accumulation increased by 2-fold when mouse (m)Abcb1 and mAbcg2 were ablated. Relative recovery of morphine in small intestinal content was significantly reduced in all the knockout strains. In the absence of mOatp1a/1b and mOatp2b1, plasma levels of M3G were markedly increased, suggesting a lower elimination rate. Moreover, Oatp-deficient mice displayed reduced hepatic and intestinal M3G accumulation. Mouse Oatps similarly affected plasma and tissue disposition of subcutaneously administered M6G. Human OATP1B1/1B3 transporters modestly contribute to the liver accumulation of M6G. In summary, mAbcb1, in combination with mAbcg2, limits morphine brain penetration and its net intestinal absorption. Variation in ABCB1 activity due to genetic polymorphisms/mutations and/or environmental factors might, therefore, partially affect morphine tissue exposure in patients. The ablation of mOatp1a/1b increases plasma exposure and decreases the liver and small intestinal disposition of M3G and M6G. Since the contribution of human OATP1B1/1B3 to M6G liver uptake was quite modest, the risks of undesirable drug interactions or interindividual variation related to OATP activity are likely negligible.

Terahertz communication: detection and signal processing.

The development of 6 G networks has promoted related research based on terahertz communication. As submillimeter radiation, signal transportation via terahertz waves has several superior properties, including non-ionizing and easy penetration of non-metallic materials. This paper provides an overview of different terahertz detectors based on various mechanisms. Additionally, the detailed fabrication process, structural design, and the improvement strategies are summarized. Following that, it is essential and necessary to prevent the practical signal from noise, and methods such as wavelet transform, UM-MIMO and decoding have been introduced. This paper highlights the detection process of the terahertz wave system and signal processing after the collection of signal data.

Three Novel Rhodamine 6G-Based Colorimetric and Fluorescent pH Switches.

Three rhodamine 6G derivatives (REHA, RETA and REDA) were designed and synthesized by connecting rhodamine 6G and 3-methyl-2-thiophenal with hydrazine hydrate, ethylenediamine and diethylenetriamine, respectively. In CH3CN/H2O (50/50, v/v), the absorbance of REHA, RETA and REDA at 528 nm was suddenly enhanced by 3.2, 3.8 and 7.2 times within the pH range of 3.03-2.31, 3.05-2.32 and 3.06-2.34, respectively, and the solution changed from colorless to pink. Meanwhile, the maximal fluorescence intensity sharply increased by 53.9, 26.6 and 24.9 times in the pH range of 3.86-3.46, 3.88-3.47 and 3.89-3.48, respectively, and the solution changed from dark to bright yellow-green fluorescence. REHA, RETA and REDA can act as highly selective and sensitive colorimetric and fluorescent pH switches with good recyclability and anti-interference ability. The response mechanism of REHA, RETA and REDA to pH was studied by 1H NMR spectroscopy, and their application in indicating small pH changes in dyeing wastewater was investigated.

Synthesis of SiO2@Ag Nanocomposite for Investigating Metal-Enhanced Fluorescence and Surface-Enhanced Raman Spectroscopy.

SiO2@Ag nanocomposite (NC) has been synthesized by the chemical reduction and StÓ§ber method for Metal-enhanced fluorescence (MEF) of Rhodmine 6G (R6G) and Surface-enhanced Raman spectroscopy (SERS) of Malachite green (MG). As-synthesized SiO2@Ag NC indicated SiO2 nanosphere (NS) and Ag nanoparticle (NP) morphologies. The SiO2@Ag NC was high quality with a well-defined crystallite phase with average sizes of 24 nm and 132 nm for Ag NP and SiO2 NC, respectively. By using SiO2@Ag NC, the photoluminescence (PL) intensity of the R6G (at 59.17 ppm) was increased approximately 133 times. The SERS of the MG (at 1.0 ppm) with SiO2@Ag NC as substrate clearly observed vibrational modes in MG dye at 798, 916, 1172, 1394, and 1616 cm-1. As a result, the SERS enhancement factor (EFSERS) at 1172 cm-1 obtained 6.3 × 106. This initial study points to the potential of SiO2@Ag NC as a promising material for MEF and SERS substrates to detect dyes at low concentrations.

Cystic echinococcosis in Cyprus: historical retrospective and finding of 2 Echinococcus granulosus sensu lato species.

The island of Cyprus was a historical endemic area for cystic echinococcosis (CE) in the Mediterranean. During the last decades, Cyprus has been an open-air laboratory and a model for testing and implementing control measures aiming to eliminate CE as a public health problem. Despite control and surveillance measures implemented during last 50 years, molecular characterization of Echinococcus granulosus sensu lato specimens has been never provided. In February 2023, the carcass of a stray dog collected in the Nicosia district was examined by the Veterinary Services and found infected with Echinococcus spp. worms. The worms were sent to the European Union Reference Laboratory (EURLP) for species/genotype identification. The sequences analyses of nad2 and nad5 genes allowed us to identify the tapeworms as Echinococcus canadensis, genotype G7b. In November 2023, a parasitic liver cyst was observed during the post-mortem examination of a mouflon from the same area of the dog's finding. The cyst sample was also referred to EURLP for identification and comparison with tapeworms previously collected from the dog. The sequences analysis of cox1 gene allowed to identify the cyst as E. granulosus sensu stricto, genotype G1. The finding of 2 different species of E. granulosus s.l. in a limited area raises epidemiological questions on the origin of the samples: whether distinct transmission cycles are present or a recent introduction event have occurred. From a public health perspective, it will be essential to conduct further molecular epidemiology studies to clarify the recent transmission dynamics of Echinococcus species in Cyprus.

Modulating temperature for Cu2ZnSnS4 (CZTS) synthesis via hot injection method and studying the photocatalytic efficiencies for the degradation of rhodamine 6G and methylene blue pollutants.

Cu2ZnSnS4 (CZTS) was synthesized following hot injection method and the process was optimized by varying temperature conditions. Four samples at different temperatures viz., 200, 250, 300 and 350 °C were prepared and analyzed using different characterization techniques. Based on the correlation between XRD, Raman and XPS, we conclude that the formation of ZnS and SnS2 occurs at 350 °C but at 200 °C there is no breakdown of the complex as per XRD. According to Raman and XPS analysis, as the temperature rises, the bonds between the metals become weaker, which is visibly seen in Raman and XPS due to the minor peaks of copper sulfide. Scanning electron microscopic analysis confirmed nanometric particles which increase in size with temperature. The photocatalytic evaluation showed that CZTS synthesized at 200 °C performed efficiently in the removal of the two colorants, methylene blue and Rhodamine 6G, achieving 92.80% and 90.65%, respectively. The photocatalytic degradation efficiencies decreased at higher temperatures due to bigger sized CZTS particles as confirmed by SEM results. Computational simulations confirm that CZTS has a highly negative energy -25,764 Ry, confirming its structural stability and higher covalent than ionic character.

Analysis of PDE6G mutations in a patient with retinitis pigmentosa.

BACKGROUND: Mutations in PDE6A and PDE6B are known to cause autosomal recessive RP in humans, On the other hand, mutations in PDE6G are rare but can lead to severe early-onset RP. CASE PRESENTATION: An 8-year-old Chinese boy was referred to our hospital for poor vision issues. Refraction with cycloplegia showed high hyperopia with astigmatism both eyes. Funduscopic examination revealed typical bone spicule-type pigment deposits in the periphery and midperiphery. The patient was given glasses and a whole exome sequencing containing mitochondrial genes was performed. The results of genetic testing showed that there was a heterozygous frameshift mutation and a segment deletion in the proband's PDE6G gene. Analysis of the parental genes showed that frameshift mutation was inherited from the proband's mother and segment deletion from his father. CONCLUSIONS: In this paper, we give a firsthand report that the complex heterozygous mutations of PDE6G gene can causes autosomal recessiveRP (arRP), which expands the understanding of the pathogenic genes of RP.

Multistatic Integrated Sensing and Communication System Based on Macro-Micro Cooperation.

A novel multistatic integrated sensing and communication (ISAC) system based on macro-micro cooperation for the sixth-generation (6G) mobile network is proposed. Instead of using macrosites at both the transmitter and receiver sides, microsites are considered as receivers in cooperative sensing. This system is important since microsites can be deployed more flexibly to reduce their distances to the sensing objects, providing better coverage for sensing service. In this work, we first analyze the deployment problem of microsites, which can be deployed along the radius and azimuth angle to cover macrosite cells. The coverage area of each microsite is derived in terms of its position in the cell. Then, we describe an efficient estimating approach for obtaining the position and velocity of sensing objects in the macrosite cell. By choosing multiple microsites around the targeted sensing area, joint data processing with an efficient optimization method is also provided. Simulation results show that the multistatic ISAC system employing macro-micro cooperation can improve the position and velocity estimation accuracy of objects compared to systems employing macrosite cooperation alone, demonstrating the effectiveness and potential for implementing the proposed system in the 6G mobile network.

A Survey of PAPR Techniques Based on Machine Learning.

Orthogonal Frequency Division Multiplexing (OFDM) is the modulation technology used in Fourth Generation (4G) and Fifth Generation (5G) wireless communication systems, and it will likely be essential to Sixth Generation (6G) wireless communication systems. However, OFDM introduces a high Peak to Average Power Ratio (PAPR) in the time domain due to constructive interference among multiple subcarriers, increasing the complexity and cost of the amplifiers and, consequently, the cost and complexity of 6G networks. Therefore, the development of new solutions to reduce the PAPR in OFDM systems is crucial to 6G networks. The application of Machine Learning (ML) has emerged as a promising avenue for tackling PAPR issues. Along this line, this paper presents a comprehensive review of PAPR optimization techniques with a focus on ML approaches. From this survey, it becomes clear that ML solutions offer customized optimization, effective search space navigation, and real-time adaptability. In light of the demands of evolving 6G networks, integration of ML is a necessity to propel advancements and meet increasing prerequisites. This integration not only presents possibilities for PAPR reduction but also calls for continued exploration to harness its potential and ensure efficient and reliable communication within 6G networks.

Dynamic Bandwidth Slicing in Passive Optical Networks to Empower Federated Learning.

Federated Learning (FL) is a decentralized machine learning method in which individual devices compute local models based on their data. In FL, devices periodically share newly trained updates with the central server, rather than submitting their raw data. The key characteristics of FL, including on-device training and aggregation, make it interesting for many communication domains. Moreover, the potential of new systems facilitating FL in sixth generation (6G) enabled Passive Optical Networks (PON), presents a promising opportunity for integration within this domain. This article focuses on the interaction between FL and PON, exploring approaches for effective bandwidth management, particularly in addressing the complexity introduced by FL traffic. In the PON standard, advanced bandwidth management is proposed by allocating multiple upstream grants utilizing the Dynamic Bandwidth Allocation (DBA) algorithm to be allocated for an Optical Network Unit (ONU). However, there is a lack of research on studying the utilization of multiple grant allocation. In this paper, we address this limitation by introducing a novel DBA approach that efficiently allocates PON bandwidth for FL traffic generation and demonstrates how multiple grants can benefit from the enhanced capacity of implementing PON in carrying out FL flows. Simulations conducted in this study show that the proposed solution outperforms state-of-the-art solutions in several network performance metrics, particularly in reducing upstream delay. This improvement holds great promise for enabling real-time data-intensive services that will be key components of 6G environments. Furthermore, our discussion outlines the potential for the integration of FL and PON as an operational reality capable of supporting 6G networking.

Network Slicing in 6G: A Strategic Framework for IoT in Smart Cities.

The emergence of 6G communication technologies brings both opportunities and challenges for the Internet of Things (IoT) in smart cities. In this paper, we introduce an advanced network slicing framework designed to meet the complex demands of 6G smart cities' IoT deployments. The framework development follows a detailed methodology that encompasses requirement analysis, metric formulation, constraint specification, objective setting, mathematical modeling, configuration optimization, performance evaluation, parameter tuning, and validation of the final design. Our evaluations demonstrate the framework's high efficiency, evidenced by low round-trip time (RTT), minimal packet loss, increased availability, and enhanced throughput. Notably, the framework scales effectively, managing multiple connections simultaneously without compromising resource efficiency. Enhanced security is achieved through robust features such as 256-bit encryption and a high rate of authentication success. The discussion elaborates on these findings, underscoring the framework's impressive performance, scalability, and security capabilities.

Hardware Implementations of a Deep Learning Approach to Optimal Configuration of Reconfigurable Intelligence Surfaces.

Reconfigurable intelligent surfaces (RIS) offer the potential to customize the radio propagation environment for wireless networks, and will be a key element for 6G communications. However, due to the unique constraints in these systems, the optimization problems associated to RIS configuration are challenging to solve. This paper illustrates a new approach to the RIS configuration problem, based on the use of artificial intelligence (AI) and deep learning (DL) algorithms. Concretely, a custom convolutional neural network (CNN) intended for edge computing is presented, and implementations on different representative edge devices are compared, including the use of commercial AI-oriented devices and a field-programmable gate array (FPGA) platform. This FPGA option provides the best performance, with ×20 performance increase over the closest FP32, GPU-accelerated option, and almost ×3 performance advantage when compared with the INT8-quantized, TPU-accelerated implementation. More noticeably, this is achieved even when high-level synthesis (HLS) tools are used and no custom accelerators are developed. At the same time, the inherent reconfigurability of FPGAs opens a new field for their use as enabler hardware in RIS applications.

Blockchain 6G-Based Wireless Network Security Management with Optimization Using Machine Learning Techniques.

6G mobile network technology will set new standards to meet performance goals that are too ambitious for 5G networks to satisfy. The limitations of 5G networks have been apparent with the deployment of more and more 5G networks, which certainly encourages the investigation of 6G networks as the answer for the future. This research includes fundamental privacy and security issues related to 6G technology. Keeping an eye on real-time systems requires secure wireless sensor networks (WSNs). Denial of service (DoS) attacks mark a significant security vulnerability that WSNs face, and they can compromise the system as a whole. This research proposes a novel method in blockchain 6G-based wireless network security management and optimization using a machine learning model. In this research, the deployed 6G wireless sensor network security management is carried out using a blockchain user datagram transport protocol with reinforcement projection regression. Then, the network optimization is completed using artificial democratic cuckoo glowworm remora optimization. The simulation results have been based on various network parameters regarding throughput, energy efficiency, packet delivery ratio, end-end delay, and accuracy. In order to minimise network traffic, it also offers the capacity to determine the optimal node and path selection for data transmission. The proposed technique obtained 97% throughput, 95% energy efficiency, 96% accuracy, 50% end-end delay, and 94% packet delivery ratio.

TransNeural: An Enhanced-Transformer-Based Performance Pre-Validation Model for Split Learning Tasks.

While digital twin networks (DTNs) can potentially estimate network strategy performance in pre-validation environments, they are still in their infancy for split learning (SL) tasks, facing challenges like unknown non-i.i.d. data distributions, inaccurate channel states, and misreported resource availability across devices. To address these challenges, this paper proposes a TransNeural algorithm for DTN pre-validation environment to estimate SL latency and convergence. First, the TransNeural algorithm integrates transformers to efficiently model data similarities between different devices, considering different data distributions and device participate sequence greatly influence SL training convergence. Second, it leverages neural network to automatically establish the complex relationships between SL latency and convergence with data distributions, wireless and computing resources, dataset sizes, and training iterations. Deviations in user reports are also accounted for in the estimation process. Simulations show that the TransNeural algorithm improves latency estimation accuracy by 9.3% and convergence estimation accuracy by 22.4% compared to traditional equation-based methods.

Progressive Pattern Interleaver with Multi-Carrier Modulation Schemes and Iterative Multi-User Detection in IoT 6G Environments with Multipath Channels.

Sixth-generation (6G) wireless networks demand a more efficient implementation of non-orthogonal multiple access (NOMA) schemes for severe multipath fading environments to serve multiple users. Using non-orthogonal multiple access (NOMA) schemes in IoT 6G networks is a promising solution to allow multiple users to share the same spectral and temporal resource, increasing spectral efficiency and improving the network's capacity. In this work, we have evaluated the performance of a novel progressive pattern interleaver (PPI) employed to distinguish the users in interleaved division multiple access (IDMA) schemes, suggested by 3GPP guidelines as a NOMA scheme, with two multi-carrier modulation schemes known as single-carrier frequency-division multiple access (SC-FDMA) and orthogonal frequency-division multiplexing (OFDM), resulting in SC-FDMA-IDMA and OFDM-IDMA schemes. Both schemes are multi-carrier schemes with orthogonal sub-carriers to deal against inter-symbol interference (ISI) and orthogonal interleavers for the simultaneous access of multiple users. It has been suggested through simulation outcomes that PPI performance is adequate with SC-FDMA-IDMA and OFDM-IDMA schemes in terms of bit error rate (BER) under multipath channel conditions. Moreover, regarding bandwidth requirement and the implementation complexity of the transmitted interleaver structure, PPI is superior to the conventional random interleaver (RI).

Integrated Communication, Sensing, and Computation Framework for 6G Networks.

In the sixth generation (6G) era, intelligent machine network (IMN) applications, such as intelligent transportation, require collaborative machines with communication, sensing, and computation (CSC) capabilities. This article proposes an integrated communication, sensing, and computation (ICSAC) framework for 6G to achieve the reciprocity among CSC functions to enhance the reliability and latency of communication, accuracy and timeliness of sensing information acquisition, and privacy and security of computing to realize the IMN applications. Specifically, the sensing and communication functions can merge into unified platforms using the same transmit signals, and the acquired real-time sensing information can be exploited as prior information for intelligent algorithms to enhance the performance of communication networks. This is called the computing-empowered integrated sensing and communications (ISAC) reciprocity. Such reciprocity can further improve the performance of distributed computation with the assistance of networked sensing capability, which is named the sensing-empowered integrated communications and computation (ICAC) reciprocity. The above ISAC and ICAC reciprocities can enhance each other iteratively and finally lead to the ICSAC reciprocity. To achieve these reciprocities, we explore the potential enabling technologies for the ICSAC framework. Finally, we present the evaluation results of crucial enabling technologies to show the feasibility of the ICSAC framework.

Secrecy Performance Enhancement Using Self-Interference Cancellation in Wireless Mutual Broadcast Networks for Proximity-Based Services.

With the increasing demand for data exchange between nearby devices in proximity-based services, enhancing the security of wireless mutual broadcast (WMB) networks is crucial. However, WMB networks are inherently vulnerable to eavesdropping due to the open broadcast nature of their communication. This paper investigates the improvement of secrecy performance in random-access-based WMB (RA-WMB) networks by integrating physical layer security (PLS) techniques with hybrid duplex (HBD) operations under a stochastic geometry framework. The HBD method balances half-duplex (HD) receiving and full-duplex (FD) transceiving, utilizing self-interference cancellation (SIC) to enhance PLS performance. Key operational parameters, including transmission probability (TxPr), friendly jammer density, and conditions for FD operation, are designed to maximize secrecy performance. The analytical and numerical results demonstrate significant improvements in PLS performance, with SIC playing a critical role, particularly in scenarios with dense legitimate nodes, and with TxPr adjusted to balance HD receiving and FD transceiving based on SIC imperfections. The proposed design principles provide a comprehensive framework for enhancing the security of WMB networks, addressing the complex interplay of interference and SIC in various network configurations.