Electrochemical Sensors for Heavy Metal Ion Detection in Aqueous Medium: A Systematic Review.

Heavy metal ions (HMIs) are very harmful to the ecosystem when they are present in excess of the recommended limits. They are carcinogenic in nature and can cause serious health issues. So, it is important to detect the metal ions quickly and accurately. The metal ions arsenic (As3+), cadmium (Cd2+), chromium (Cr3+), lead (Pb2+), and mercury (Hg2+) are considered to be very toxic among other metal ions. Standard analytical methods like atomic absorption spectroscopy, atomic fluorescence spectroscopy, and X-ray fluorescence spectroscopy are used to detect HMIs. But these methods necessitate highly technical equipment and lengthy procedures with skilled personnel. So, electrochemical sensing methods are considered to be more advantageous because of their quick analysis with precision and simplicity to operate. They can detect a wide range of heavy metals providing real-time monitoring and are cost-effective and enable multiparametric detection. Various sensing applications necessitate severe regulation regarding the modification of electrode surfaces. Numerous nanomaterials such as graphene, carbon nanotubes, and metal nanoparticles have been extensively explored as interface materials in electrode modifiers. These nanoparticles offer excellent electrical conductivity, distinctive catalytic properties, and high surface area resulting in enhanced electrochemical performance. This review examines different HMI detection methods in an aqueous medium by an electrochemical sensing approach and studies the recent developments in interface materials for altering the electrodes.

Designing optimal prototype filters for maximally decimated Cosine Modulated filter banks with rapid convergence.

An analytic design of a prototype filter for M-channel maximally decimated cosine-modulated Near Perfect Reconstruction (NPR) filter banks is proposed in this work. The prototype filter is created using the least-square (CLS) method with weighted constraints, which is one-dimensional and requires single-parameter optimization. Compared to existing approaches, this suggested method achieves rapid convergence by analytically determining the optimal step size, ensuring the 3 dB cutoff frequency at π/2 M. The simulation results for design examples outperform the techniques in the available literature in terms of amplitude and aliasing distortion, reaching distortion around 2.4489 × 10-4 and 3.4907 × 10-9, respectively. This optimization algorithm's usefulness is further demonstrated with the sub-band coding of ECG signals. Implementing optimal prototype filters has tangible real-world effects, especially in critical sectors like healthcare and communications, improving diagnostics accuracy, data transmission efficiency, and overall performance.

Reconfigurable Metasurface: Enabling Tunable Reflection in 6G Wireless Communications.

With the continuous advancement of technology, there is an increasing need for innovative solutions that can handle complex applications such as haptic communications, Internet of Things for smart cities, automation, and manufacturing. One technology that has received much attention is the phase reconfigurable metasurface for reconfigurable intelligent surfaces (RISs). The RIS demands low-power consumption, simple configuration, angular stability, and polarization insensitivity. The use of phase reconfigurable metasurfaces provides benefits such as low cost, low power consumption, and improved communication coverage and quality. This article introduces a reconfigurable combined-loop metasurface that can effectively manipulate phase reflection. This is achieved by incorporating four PIN diodes between two meta-atoms of a 2 × 2 periodic array within a single-layer metallic structure. By controlling the state of the PIN diodes, which can be switched into 16 different states, the metasurface can achieve various phase reflections. The proposed structure has validated a 32× 32 metasurface through numerical simulations and experiments that exhibit promising results, demonstrating its potential for use in 6G applications.

Underwater Wireless Sensor Networks Performance Comparison Utilizing Telnet and Superframe.

Underwater Wireless Sensor Networks (UWSNs) have recently established themselves as an extremely interesting area of research thanks to the mysterious qualities of the ocean. The UWSN consists of sensor nodes and vehicles working to collect data and complete tasks. The battery capacity of sensor nodes is quite limited, which means that the UWSN network needs to be as efficient as it can possibly be. It is difficult to connect with or update a communication that is taking place underwater due to the high latency in propagation, the dynamic nature of the network, and the likelihood of introducing errors. This makes it difficult to communicate with or update a communication. Cluster-based underwater wireless sensor networks (CB-UWSNs) are proposed in this article. These networks would be deployed via Superframe and Telnet applications. In addition, routing protocols, such as Ad hoc On-demand Distance Vector (AODV), Fisheye State Routing (FSR), Location-Aided Routing 1 (LAR1), Optimized Link State Routing Protocol (OLSR), and Source Tree Adaptive Routing-Least Overhead Routing Approach (STAR-LORA), were evaluated based on the criteria of their energy consumption in a range of various modes of operation with QualNet Simulator using Telnet and Superframe applications. STAR-LORA surpasses the AODV, LAR1, OLSR, and FSR routing protocols in the evaluation report's simulations, with a Receive Energy of 0.1 mWh in a Telnet deployment and 0.021 mWh in a Superframe deployment. The Telnet and Superframe deployments consume 0.05 mWh transmit power, but the Superframe deployment only needs 0.009 mWh. As a result, the simulation results show that the STAR-LORA routing protocol outperforms the alternatives.

Detection of early prostate cancer using a hepsin-targeted imaging agent.

Early detection and diagnosis of prostate cancer is key to designing effective treatment strategies. Microarrays have resulted in the discovery of hepsin (HPN) as a biomarker for detection of prostate cancer. In this study, we explore the development of HPN imaging probes for detection of prostate cancer. We used phage display to isolate HPN binding peptides with 190 + 2.2 nmol/L affinity in monomeric form and high specificity. The identified peptides were able to detect human prostate cancer on tissue microarrays and in cell-based assays. HPN-targeted imaging agents were synthesized by conjugating multiple peptides to fluorescent nanoparticles to further improve avidity through multivalency and to improve pharmacokinetics. When injected into mouse xenograft models, HPN-targeted nanoparticles bound specifically to HPN-expressing LNCaP xenografts compared with non-HPN-expressing PC3 xenografts. HPN imaging may provide a new method for detection of prostate cancer.

Targeted nanoparticles for imaging incipient pancreatic ductal adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) carries an extremely poor prognosis, typically presenting with metastasis at the time of diagnosis and exhibiting profound resistance to existing therapies. The development of molecular markers and imaging probes for incipient PDAC would enable earlier detection and guide the development of interventive therapies. Here we sought to identify novel molecular markers and to test their potential as targeted imaging agents. METHODS AND FINDINGS: Here, a phage display approach was used in a mouse model of PDAC to screen for peptides that specifically bind to cell surface antigens on PDAC cells. These screens yielded a motif that distinguishes PDAC cells from normal pancreatic duct cells in vitro, which, upon proteomics analysis, identified plectin-1 as a novel biomarker of PDAC. To assess their utility for in vivo imaging, the plectin-1 targeted peptides (PTP) were conjugated to magnetofluorescent nanoparticles. In conjunction with intravital confocal microscopy and MRI, these nanoparticles enabled detection of small PDAC and precursor lesions in engineered mouse models. CONCLUSIONS: Our approach exploited a well-defined model of PDAC, enabling rapid identification and validation of PTP. The developed specific imaging probe, along with the discovery of plectin-1 as a novel biomarker, may have clinical utility in the diagnosis and management of PDAC in humans.