Ijaz Gul

Rapid rise in antimicrobial-resistant bacteria highlights the urgent need for interventions to combat antimicrobial resistance (AMR). Antimicrobial susceptibility testing (AST) is crucial for antibiotic discovery and efficacy testing. However, existing AST systems are costly and labor-intensive. Herein, we developed an automatic, label-free, and high-throughput AST system called Cage-Based Phase Contrast Microscopy with You Only Look Once-Segment Anything Model (YOLO-SAM) Algorithm Droplets AST (CYSDrop AST) for antibacterial drug analysis. When using this system, the initial bacterial concentration should be controlled at around OD₆₀₀ = 0.05 to maximize the encapsulation of one bacterium per droplet, and facilitate the subsequent statistical analysis. Because of low-cost T-junction microfluidic chips that encapsulate bacteria at single-cell level into picoliter droplets, the per-assay cost is reduced to at least one-third of that of traditional methods. The total sample-to-result time is shortened to 4 h, which includes a 2 h bacterial cultivation step. We used colistin susceptibility testing as a model system. The system determined the colistin susceptibility of E. coli strains within 4 h and achieved 100% categorical agreement with the reference broth microdilution (BMD) method. The core advantage of this method lies in its quantitative analysis of bacterial load, which achieves high consistency (89.6%) with manual annotation, complemented by its near-perfect performance in discriminating between positive and negative droplets (AUC = 0.994, AP = 0.988). Furthermore, we demonstrated its utility by testing colistin resistance in urine samples. This system is particularly valuable for guiding the use of last-line antibiotics and optimizing therapeutic strategies for patients with multidrug-resistant infections.

Bacteriophytochrome-derived near-infrared fluorescent proteins (NIR FPs) provide deep tissue penetration, low autofluorescence, and endogenous biliverdin compatibility, enabling non-invasive visualization of viral processes in living systems. Engineering advances (iRFPs, monomeric miRFPs, photoactivatable PAiRFPs) have improved brightness, stability, and genetic encodability for robust use in mammalian models. These reporters support real-time tracking of infection dynamics and host-virus interactions and power diagnostic platforms including reporter viruses, CRISPR-based assays, and nanotechnology-enhanced biosensors. Multimodal integration with photoacoustic tomography and PET further extends their translational utility. Remaining challenges include brightness/photostability limits and the need for broader translational validation, yet progress in structure-guided mutagenesis, computational/AI-assisted protein design, and hybrid imaging strategies promises to close these gaps. This mini-review synthesizes the design principles, viral imaging/detection use cases, and translational prospects of bacteriophytochrome-derived NIR FPs, highlighting their potential to advance viral surveillance, therapeutic evaluation, and precision diagnostics. Graphical Abstract Engineering of bacteriophytochrome-derived NIR FPs (iRFPs, miRFPs, PAiRFPs) as versatile tools for viral imaging, biosensing, and diagnostics.

The CRISPR/Cas13 nucleases have been widely documented for nucleic acid detection. Understanding the intricacies of CRISPR/Cas13’s reaction components is pivotal for harnessing its full potential for biosensing applications. Herein, we report on the influence of CRISPR/Cas13a reaction components on its trans-cleavage activity and the development of an on-chip total internal reflection fluorescence microscopy (TIRFM)-powered RNA sensing system. We used SARS-CoV-2 synthetic RNA and pseudovirus as a model system. Our results show that optimizing Mg²⁺ concentration, reporter length, and crRNA combination significantly improves the detection sensitivity. Under optimized conditions, we detected 100 fM unamplified SARS-CoV-2 synthetic RNA using a microtiter plate reader. To further improve sensitivity and provide a new amplification-free RNA sensing toolbox, we developed a TIRFM-based amplification-free RNA sensing system. We were able to detect RNA down to 100 aM. Furthermore, the TIRM-based detection system developed in this study is 1000-fold more sensitive than the off-coverslip assay. The possible clinical applicability of the system was demonstrated by detecting SARS-CoV-2 pseudovirus RNA. Our proposed sensing system has the potential to detect any target RNA with slight modifications to the existing setup, providing a universal RNA detection platform. Graphical Abstract

Depression is a multifactorial disease with unknown etiology affecting globally. It’s the second most significant reason for infirmity in 2020, affecting about 50 million people worldwide, with 80% living in developing nations. Recently, a surge in depression research has been witnessed, resulting in a multitude of emerging techniques developed for prediction, evaluation, detection, classification, localization, and treatment. The main purpose of this study is to determine the volume of depression research conducted on different aspects such as genetics, proteins, hormones, oxidative stress, inflammation, mitochondrial dysfunction, and associations with other mental disorders like anxiety and stress using traditional and medical intelligence (medical with AI). In addition, it also designs a comprehensive survey on detection, treatment planning, and genetic predisposition, along with future recommendations. This work is designed through different methods, including a systematic mapping process, literature review, and network visualization. In addition, we also used VOSviewer software and some authentic databases such as Google Scholar, Scopus, PubMed, and Web of Science for data collection, analysis, and designing comprehensive picture of the study. We analyzed 60 articles related to medical intelligence, including 47 from machine learning with 513,767 subjects (mean ± SD = 10,931.212 ± 35,624.372) and 13 from deep learning with 37,917 subjects (mean ± SD = 3159.75 ± 6285.57). Additionally, we also found that stressors impact the brain's cognitive and autonomic functioning, resulting in increased production of catecholamine, decreased cholinergic and glucocorticoid activity, with increased cortisol. These factors lead to chronic inflammation and hinder the brain's normal functioning, leading to depression, anxiety, and cardiovascular disorders. In the brain, reactive oxygen species (ROS) production is increased by IL-6 stimulation and mitochondrial cytochrome c oxidase is inhibited by nitric oxide, a potent inhibitor. Proteins, lipids, oxidative phosphorylation enzymes, and mtDNA are further disposed to oxidative impairment in the mitochondria. Consequently, mitochondrial dysfunction exacerbates oxidative stress, impairs mitochondrial DNA (mtDNA) or deletions of mtDNA, increases intracellular Ca²⁺ levels, changes in fission/fusion and mitochondrial morphology, and lastly leads to neuronal death. This study highlights the multidisciplinary approaches to depression with different aspects using traditional and medical intelligence. It will open a new way for depression research through new emerging technologies.

The global outbreak of the monkeypox virus (MPXV) highlights the need for rapid and cost‐effective MPXV detection tools to effectively monitor and control the monkeypox disease. Herein, we demonstrated a portable CRISPR–Cas‐based system for naked‐eye detection of MPXV. The system harnesses the high selectivity of CRISPR–Cas12 and the isothermal nucleic acid amplification potential of recombinase polymerase amplification. It can detect both the current circulating MPXV clade and the original clades. We reached a limit of detection (LoD) of 22.4 aM (13.5 copies/µl) using a microtiter plate reader, while the visual LoD of the system is 75 aM (45 copies/µl) in a two‐step assay, which is further reduced to 25 aM (15 copies/µl) in a one‐pot system. We compared our results with quantitative polymerase chain reaction and obtained satisfactory consistency. For clinical application, we demonstrated a sensitive and precise visual detection method with attomolar sensitivity and a sample‐to‐answer time of 35 min.

Rapid and cost-effective diagnostic tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are a critical and valuable weapon for the coronavirus disease 2019 (COVID-19) pandemic response. SARS-CoV-2 invasion is primarily mediated by human angiotensin-converting enzyme 2 (hACE2). Recent developments in ACE2-based SARS-CoV-2 detection modalities accentuate the potential of this natural host-virus interaction for developing point-of-care (POC) COVID-19 diagnostic systems. Although research on harnessing ACE2 for SARS-CoV-2 detection is in its infancy, some interesting biosensing devices have been developed, showing the commercial viability of this intriguing new approach. The exquisite performance of the reported ACE2-based COVID-19 biosensors provides opportunities for researchers to develop rapid detection tools suitable for virus detection at points of entry, workplaces, or congregate scenarios in order to effectively implement pandemic control and management plans. However, to be considered as an emerging approach, the rationale for ACE2-based biosensing needs to be critically and comprehensively surveyed and discussed. Herein, we review the recent status of ACE2-based detection methods, the signal transduction principles in ACE2 biosensors and the development trend in the future. We discuss the challenges to development of ACE2-biosensors and delineate prospects for their use, along with recommended solutions and suggestions.

The outbreak of the monkeypox virus (MPXV) in non-endemic countries is an emerging global health threat and may have an economic impact if proactive actions are not taken. As shown by the COVID-19 pandemic, rapid, accurate, and cost-effective virus detection techniques play a pivotal role in disease diagnosis and control. Considering the sudden multicountry MPXV outbreak, a critical evaluation of the MPXV detection approaches would be a timely addition to the endeavors in progress for MPXV control and prevention. Herein, we evaluate the current MPXV detection methods, discuss their pros and cons, and provide recommended solutions to the problems. We review the traditional and emerging nucleic acid detection approaches, immunodiagnostics, whole-particle detection, and imaging-based MPXV detection techniques. The insights provided in this article will help researchers to develop novel techniques for the diagnosis of MPXV.

Rapid and cost-effective diagnostic tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have become a critical and valuable weapon for the coronavirus disease 2019 (COVID-19) pandemic response. SARS-CoV-2 invasion is primarily mediated by human angiotensin-converting enzyme 2 (hACE2). Recent developments in ACE2-based SARS-CoV-2 detection modalities accentuate the potential of this natural host-virus interaction for developing point-of-care (POC) COVID-19 diagnostic tools and devices. Although research on harnessing ACE2 for SARS-CoV-2 detection is in its infancy, some interesting biosensing devices have been developed, showing the commercial viability of this intriguing new approach. The exquisite performance of the reported ACE2-based COVID-19 biosensors provides opportunities for researchers to develop rapid detection tools suitable for testing at points of entry, workplaces, or congregate scenarios in order to effectively implement pandemic control and management plans. However, to be considered as an emerging approach, the rationale for ACE2-based biosensing needs to be critically and comprehensively surveyed and discussed. Herein, we review the current status of ACE2-based detection methods, the signal transduction principles in ACE2 biosensors and the development trend in the future. We discuss the challenges to development of ACE2-biosensors and delineate prospects for their use, along with recommended solutions and suggestions