Potential of laser-induced fluorescence-light detection and ranging for future stand-off virus surveillance

Synergizing Nanomaterials and Artificial Intelligence in Advanced Optical Biosensors for Precision Antimicrobial Resistance Diagnosis

Antimicrobial resistance (AMR) poses a critical global One Health concern, ensuing from unintentional and continuous exposure to antibiotics, as well as challenges in accurate contagion diagnostics. Addressing AMR requires a strategic approach that emphasizes early stage prevention through screening in clinical, environmental, farming, and livestock settings to identify nonvulnerable antimicrobial agents and the associated genes. Conventional AMR diagnostics, like antibiotic susceptibility testing, possess drawbacks, including high costs, time-consuming processes, and significant manpower requirements, underscoring the need for intelligent, prompt, and on-site diagnostic techniques. Nanoenabled artificial intelligence (AI)-supported smart optical biosensors present a potential solution by facilitating rapid point-of-care AMR detection with real-time, sensitive, and portable capabilities. This Review comprehensively explores various types of optical nanobiosensors, such as surface plasmon resonance sensors, whispering-gallery mode sensors, optical coherence tomography, interference reflection imaging sensors, surface-enhanced Raman spectroscopy, fluorescence spectroscopy, microring resonance sensors, and optical tweezer biosensors, for AMR diagnostics. By harnessing the unique advantages of these nanoenabled smart biosensors, a revolutionary paradigm shift in AMR diagnostics can be achieved, characterized by rapid results, high sensitivity, portability, and integration with Internet-of-Things (IoT) technologies. Moreover, nanoenabled optical biosensors enable personalized monitoring and on-site detection, significantly reducing turnaround time and eliminating the human resources needed for sample preservation and transportation. Their potential for holistic environmental surveillance further enhances monitoring capabilities in diverse settings, leading to improved modern-age healthcare practices and more effective management of antimicrobial treatments. Embracing these advanced diagnostic tools promises to bolster global healthcare capacity to combat AMR and safeguard One Health.

A comprehensive review of microbial contamination in the indoor environment: sources, sampling, health risks, and mitigation strategies

The quality of the indoor environment significantly impacts human health and productivity, especially given the amount of time individuals spend indoors globally. While chemical pollutants have been a focus of indoor air quality research, microbial contaminants also have a significant bearing on indoor air quality. This review provides a comprehensive overview of microbial contamination in built environments, covering sources, sampling strategies, and analysis methods. Microbial contamination has various origins, including human occupants, pets, and the outdoor environment. Sampling strategies for indoor microbial contamination include air, surface, and dust sampling, and various analysis methods are used to assess microbial diversity and complexity in indoor environments. The review also discusses the health risks associated with microbial contaminants, including bacteria, fungi, and viruses, and their products in indoor air, highlighting the need for evidence-based studies that can relate to specific health conditions. The importance of indoor air quality is emphasized from the perspective of the COVID-19 pandemic. A section of the review highlights the knowledge gap related to microbiological burden in indoor environments in developing countries, using India as a representative example. Finally, potential mitigation strategies to improve microbiological indoor air quality are briefly reviewed.

Next-generation nanophotonic-enabled biosensors for intelligent diagnosis of SARS-CoV-2 variants

Constantly mutating SARS-CoV-2 is a global concern resulting in COVID-19 infectious waves from time to time in different regions, challenging present-day diagnostics and therapeutics. Early-stage point-of-care diagnostic (POC) biosensors are a crucial vector for the timely management of morbidity and mortalities caused due to COVID-19. The state-of-the-art SARS-CoV-2 biosensors depend upon developing a single platform for its diverse variants/biomarkers, enabling precise detection and monitoring. Nanophotonic-enabled biosensors have emerged as 'one platform' to diagnose COVID-19, addressing the concern of constant viral mutation. This review assesses the evolution of current and future variants of the SARS-CoV-2 and critically summarizes the current state of biosensor approaches for detecting SARS-CoV-2 variants/biomarkers employing nanophotonic-enabled diagnostics. It discusses the integration of modern-age technologies, including artificial intelligence, machine learning and 5G communication with nanophotonic biosensors for intelligent COVID-19 monitoring and management. It also highlights the challenges and potential opportunities for developing intelligent biosensors for diagnosing future SARS-CoV-2 variants. This review will guide future research and development on nano-enabled intelligent photonic-biosensor strategies for early-stage diagnosing of highly infectious diseases to prevent repeated outbreaks and save associated human mortalities.

Green-synthesized silver nanoparticle coating on paper for antibacterial and antiviral applications

The use of active packaging has attracted considerable attention over recent years to prevent and decrease the risk of bacterial and viral infection. Thus, this work aims to develop active packaging using a paper coated with green-synthesized silver nanoparticles (AgNPs). Effects of different silver nitrate (AgNO3) concentrations, viz. 50, 100, 150, and 200 mM (AgNPs-50, AgNPs-100, AgNPs-150, and AgNPs-200, respectively), on green synthesis of AgNPs and coated paper properties were investigated. A bio-reducing agent from mangosteen peel extract (ex-Garcinia mangostana (GM)) and citric acid as a crosslinking agent for a starch/polyvinyl alcohol matrix were also used in the synthetic process. The presence of AgNPs, ex-GM, and citric acid indicated the required synergistic antibacterial activities for gram-positive and gram-negative bacteria. The paper coated with AgNPs-150 showed complete inactivation of virus within 1 min. Water resistance and tensile strength of paper improved when being coated with AgNPs-150. The tensile strength of the coated paper was found to be in the same range as that of a common packaging paper. Result revealed that the obtained paper coated with AgNPs was proven to be effective in antibacterial and antiviral activities; hence, it could be used as an active packaging material for items that require manual handling by a number of people.

Initial experimental multi-wavelength EEM (Excitation Emission Matrix) fluorescence lidar detection and classification of atmospheric pollen with potential applications toward real-time bioaerosols monitoring

Fluorescence has the potential to identify the types of substances associated with aerosols. To demonstrate its usefulness in environmental studies, we investigated the use of Excitation-Emission-Matrix (EEM) fluorescence in lidar bioaerosol monitoring. First, the EEM fluorescence of cedar, ragweed, and apple pollens as typical bioaerosols found around our surroundings were measured using a commercial fluorescence spectrometer. We found that the patterns of fluorescence changed depending on the pollen type and excitation wavelength and it meant that studying these EEM fluorescence patterns was a good parameter for identifying pollen types. Then, we setup a simple EEM fluorescence lidar to confirm the usefulness in lidar bioaerosol monitoring. The lidar consisted of three laser diodes and one light emitting diode with output at 520 nm, 445 nm, 405 nm and 325 nm, respectively, an ultra violet camera lens as a receiver, and a fluorescence spectrum detection unit. Comparing the lidar simulation results with the EEM fluorescence dataset supported the possibility of performing bioaerosol monitoring using the EEM fluorescence lidar. Based on the results and the current technology, a feasible design of a bioaerosol detection EEM fluorescence lidar is proposed for future rel-time remote sensing and mapping of atmospheric bioaerosols.

Collection of excitation-emission-matrix fluorescence of aerosol-candidate-substances and its application to fluorescence lidar monitoring

Fluorescence lidars have the potential to identify aerosols, but it seems that the basic data of the fluorescence spectrum of various aerosols appear to be inadequate for practical use in application of fluorescence lidar monitoring. We collected the fluorescence spectrum data of 61 powders with different substances as pseudo-aerosols and organized them as EEM (Excitation-Emission-Matrix) fluorescence data. Our interest was also in the artificial substances that are discarded around our surroundings and become aerosols. Four applications of the EEM fluorescence to fluorescence lidars were discussed; designing fluorescence lidars, reconstructing aerosol fluorescence spectrums measured by fluorescence lidar, searching for new substances for fluorescence lidar measurement, and developing a database of EEM fluorescence for identifying aerosol types measured by fluorescence lidar. All EEM fluorescence data and application software were stored in one USB memory and run in the BIOS (Basic Input/Output System) independent of a computer OS (Operating System) for ease of use. Aerosol identification software worked well in general, but we have also talked a bit about improvements.

Red blood cell distribution width as a prognostic biomarker for viral infections: prospects and challenges

Viral diseases remain a significant global health threat, and therefore prioritization of limited healthcare resources is required to effectively manage dangerous viral disease outbreaks. In a pandemic of a newly emerged virus that is yet to be well understood, a noninvasive host-derived prognostic biomarker is invaluable for risk prediction. Red blood cell distribution width (RDW), an index of red blood cell size disorder (anisocytosis), is a potential predictive biomarker for severity of many diseases. In view of the need to prioritize resources during response to outbreaks, this review highlights the prospects and challenges of RDW as a prognostic biomarker for viral infections, with a focus on hepatitis and COVID-19, and provides an outlook to improve the prognostic performance of RDW for risk prediction in viral diseases.

Therapeutic approaches for SARS-CoV-2 infection

Therapeutic approaches to COVID-19 treatment require appropriate inhibitors to target crucial proteins of SARS-CoV-2 replication machinery. It's been approximately 12 months since the pandemic started, yet no known specific drugs are available. However, research progresses with time in terms of high throughput virtual screening (HTVS) and rational design of repurposed, novel synthetic and natural products discovery by understanding the viral life cycle, immuno-pathological and clinical outcomes in patients based on host's nutritional, metabolic, and lifestyle status. Further, complementary and alternative medicine (CAM) approaches have also improved resiliency and immune responses. In this article, we summarize all the therapeutic antiviral strategies for COVID-19 drug discovery including computer aided virtual screening, repurposed drugs, immunomodulators, vaccines, plasma therapy, various adjunct therapies, and phage technology to unravel insightful mechanistic pathways of targeting SARS-CoV-2 and host's intrinsic, innate immunity at multiple checkpoints that aid in the containment of the disease.

Detection of COVID-19 Virus on Surfaces Using Photonics: Challenges and Perspectives

The propagation of viruses has become a global threat as proven through the coronavirus disease (COVID-19) pandemic. Therefore, the quick detection of viral diseases and infections could be necessary. This study aims to develop a framework for virus diagnoses based on integrating photonics technology with artificial intelligence to enhance healthcare in public areas, marketplaces, hospitals, and airfields due to the distinct spectral signatures from lasers' effectiveness in the classification and monitoring of viruses. However, providing insights into the technical aspect also helps researchers identify the possibilities and difficulties in this field. The contents of this study were collected from six authoritative databases: Web of Science, IEEE Xplore, Science Direct, Scopus, PubMed Central, and Google Scholar. This review includes an analysis and summary of laser techniques to diagnose COVID-19 such as fluorescence methods, surface-enhanced Raman scattering, surface plasmon resonance, and integration of Raman scattering with SPR techniques. Finally, we select the best strategies that could potentially be the most effective methods of reducing epidemic spreading and improving healthcare in the environment.

Detection of COVID-19 Virus on Surfaces Using Photonics: Challenges and Perspectives

The propagation of viruses has become a global threat as proven through the coronavirus disease (COVID-19) pandemic. Therefore, the quick detection of viral diseases and infections could be necessary. This study aims to develop a framework for virus diagnoses based on integrating photonics technology with artificial intelligence to enhance healthcare in public areas, marketplaces, hospitals, and airfields due to the distinct spectral signatures from lasers' effectiveness in the classification and monitoring of viruses. However, providing insights into the technical aspect also helps researchers identify the possibilities and difficulties in this field. The contents of this study were collected from six authoritative databases: Web of Science, IEEE Xplore, Science Direct, Scopus, PubMed Central, and Google Scholar. This review includes an analysis and summary of laser techniques to diagnose COVID-19 such as fluorescence methods, surface-enhanced Raman scattering, surface plasmon resonance, and integration of Raman scattering with SPR techniques. Finally, we select the best strategies that could potentially be the most effective methods of reducing epidemic spreading and improving healthcare in the environment.