Search Results (414)

Objective: We evaluated the feasibility of a machine-learning (ML) model based on clinical features and radiomics from [¹⁸F]FDG PET/CT images to differentiate between infected and non-infected intracavitary vascular grafts and endografts (iVGEI). Methods: Three ML models were developed: one based on pre-treatment criteria to diagnose a vascular graft infection (“MAGIC-light features”), another using radiomics features from diagnostic [¹⁸F]FDG-PET scans, and a third combining both datasets. The training set included 92 patients (72 iVGEI-positive, 20 iVGEI-negative), and the external test set included 20 iVGEI-positive and 12 iVGEI-negative patients. The abdominal aorta and iliac arteries in the PET/CT scans were automatically segmented using SEQUOIA and TotalSegmentator and manually adjusted, extracting 96 radiomics features. The best-performing models for the MAGIC-light features and PET-radiomics features were selected from 343 unique models. Most relevant features were combined to test three final models using ROC analysis, accuracy, sensitivity, and specificity. Results: The combined model achieved the highest AUC in the test set (mean ± SD: 0.91 ± 0.02) compared with the MAGIC-light-only model (0.85 ± 0.06) and the PET-radiomics model (0.73 ± 0.03). The combined model also achieved a higher accuracy (0.91 vs. 0.82) than the diagnosis based on all the MAGIC criteria and a comparable sensitivity and specificity (0.70 and 1.00 vs. 0.76 and 0.92, respectively) while providing diagnostic information at the initial presentation. The AUC for the combined model was significantly higher than the PET-radiomics model (p = 0.02 in the bootstrap test), while other comparisons were not statistically significant. Conclusions: This study demonstrated the potential of ML models in supporting diagnostic decision making for iVGEI. A combined model using pre-treatment clinical features and PET-radiomics features showed high diagnostic performance and specificity, potentially reducing overtreatment and enhancing patient outcomes. Full article

Antimicrobial resistance (AMR) has emerged as one of the most pressing global health challenges of our time. Alarming projections of increasing mortality from resistant infections highlight the urgent need for innovative solutions. While many candidates have shown promise in preliminary studies, they often encounter challenges in terms of efficacy and safety during clinical translation. This review examines cutting-edge approaches to combat AMR, with a focus on engineered antimicrobial peptides, functionalized nanoparticles, and advanced genomic therapies, including Clustered Regularly Interspaced Short Palindromic Repeats-associated proteins (CRISPR-Cas systems) and phage therapy. Recent advancements in these fields are critically analyzed, with a focus on their mechanisms of action, therapeutic potential, and current limitations. Emphasis is given to strategies targeting biofilm disruption and quorum sensing interference, which address key mechanisms of resistance. By synthesizing current knowledge, this work provides researchers with a comprehensive framework for developing next-generation antimicrobials, highlighting the most promising approaches for overcoming AMR through rational drug design and targeted therapies. Ultimately, this review aims to bridge the gap between experimental innovation and clinical application, providing valuable insights for developing effective and resistance-proof antimicrobial agents. Full article

Respiratory diseases represent a persistent global health challenge, underscoring the need for intelligent, accurate, and personalized diagnostic and therapeutic systems. Existing methods frequently suffer from limitations in diagnostic precision, lack of individualized treatment, and constrained adaptability to complex clinical scenarios. To address these challenges, our study introduces a modular AI-powered framework that integrates an audio-based disease classification model with simulated molecular biomarker profiles to evaluate the feasibility of future multimodal diagnostic extensions, alongside a synthetic-data-driven prescription recommendation engine. The disease classification model analyzes respiratory sound recordings and accurately distinguishes among eight clinical classes: bronchiectasis, pneumonia, upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), asthma, chronic obstructive pulmonary disease (COPD), bronchiolitis, and healthy respiratory state. The proposed model achieved a classification accuracy of 99.99% on a holdout test set, including 94.2% accuracy on pediatric samples. In parallel, the prescription module provides individualized treatment recommendations comprising drug, dosage, and frequency trained on a carefully constructed synthetic dataset designed to emulate real-world prescribing logic.The model achieved over 99% accuracy in medication prediction tasks, outperforming baseline models such as those discussed in research. Minimal misclassification in the confusion matrix and strong clinician agreement on 200 prescriptions (Cohen’s $\kappa$ = 0.91 [0.87–0.94] for drug selection, 0.78 [0.74–0.81] for dosage, 0.96 [0.93–0.98] for frequency) further affirm the system’s reliability. Adjusted clinician disagreement rates were 2.7% (drug), 6.4% (dosage), and 1.5% (frequency). SHAP analysis identified age and smoking as key predictors, enhancing model explainability. Dosage accuracy was 91.3%, and most disagreements occurred in renal-impaired and pediatric cases. However, our study is presented strictly as a proof-of-concept. The use of synthetic data and the absence of access to real patient records constitute key limitations. A trialed clinical deployment was conducted under a controlled environment with a positive rate of satisfaction from experts and users, but the proposed system must undergo extensive validation with de-identified electronic medical records (EMRs) and regulatory scrutiny before it can be considered for practical application. Nonetheless, the findings offer a promising foundation for the future development of clinically viable AI-assisted respiratory care tools. Full article

Background/Objectives: Nerve injuries cause functional loss and psychosocial issues due to prolonged rehabilitation. Recently, 3D-modeled nerve conduits have been used to aid in surgical planning. This study investigated the impact of 3D-bioprinted PLA, chitosan, alginate, and collagen conduits on nerve regeneration in a rat sciatic nerve crush injury model. Methods: This study, conducted at Kütahya University of Health Sciences, involves 50 rats were divided into four groups: (1) sham-operated controls, (2) sciatic nerve injury without treatment, (3) injury treated with a PLA conduit, and (4) injury treated with 3D-printed tubes composed of chitosan and alginate. The procedures were performed, blood was collected, and the rats were sacrificed after two months. Weekly checks for infection, scar healing, and motor responses were performed. Results: Rats with nerve conduits showed less macroscopic scarring. Weekly assessments of motor nerve recovery showed no movement restrictions in limbs treated with PLA conduits, graft conduits, or conduits bridging retracted nerve stumps, based on responses to stimulus checks. An infection developed in the sciatic nerve and surrounding muscle tissue of one rat with a bio-graft conduit, prompting histopathological examination to investigate its cause. Conclusions: This proof-of-principle study demonstrates the feasibility of using 3D-printed biocompatible nerve conduits for peripheral nerve repair, providing a basis for future, more comprehensive investigations. Full article

Background: In just twenty years, three dangerous human coronaviruses—SARS-CoV, MERS-CoV, and SARS-CoV-2 have exposed critical gaps in early detection of emerging viral threats. Current diagnostics remain pathogen-focused, often missing the earliest phase of infection. A virus-agnostic, host-based diagnostic capable of detecting responses to viral intrusion is urgently needed. Methods: We hypothesized that the lungs act as biomechanical instruments, with infection altering tissue tension, wave propagation, and flow dynamics in ways detectable through subaudible vibroacoustic signals. In a matched case–control study, we enrolled 19 RT-PCR-confirmed COVID-19 inpatients and 16 matched controls across two Johns Hopkins hospitals. Multimodal data were collected, including passive vibroacoustic auscultation, lung ultrasound, peak expiratory flow, and laboratory markers. Machine learning models were trained to identify host-response biosignatures from anterior chest recordings. Results: 19 COVID-19 inpatients and 16 matched controls (mean BMI 32.4 kg/m², mean age 48.6 years) were successfully enrolled to the study. The top-performing, unoptimized, vibroacoustic-only model achieved an AUC of 0.84 (95% CI: 0.67–0.92). The host-covariate optimized model achieved an AUC of 1.0 (95% CI: 0.94–1.0), with 100% sensitivity (95% CI: 82–100%) and 99.6% specificity (95% CI: 85–100%). Vibroacoustic data from the anterior chest alone reliably distinguished COVID-19 cases from controls. Conclusions: This proof-of-concept study demonstrates that passive, noninvasive vibroacoustic biosignatures can detect host response to viral infection in a hospitalized population and supports further testing of this modality in broader populations. These findings support the development of scalable, host-based diagnostics to enable early, agnostic detection of future pandemic threats (ClinicalTrials.gov number: NCT04556149). Full article

Background and Objectives: To evaluate the mRNA vaccine platform for blood-stage Plasmodium parasites, we completed a proof-of-concept study using the P. yoelii mouse model of malaria and two mRNA-based vaccines. Both encoded PyMSP1₁₉ fused to PyMSP8 (PyMSP1/8). One was designed for secretion of the encoded protein (PyMSP1/8-sec); the other encoded membrane-bound antigen (PyMSP1/8-mem). Methods: Secretion of PyMSP1/8-sec and membrane localization of PyMSP1/8-mem were verified in mRNA-transfected cells. As recombinant PyMSP1/8 (rPyMSP1/8) is known to protect mice against lethal P. yoelii 17XL infection, we first compared immunogenicity and efficacy of the PyMSP1/8-sec mRNA vaccine versus the recombinant formulation in outbred mice. Animals were immunized three times followed by challenge with a lethal dose of P. yoelii 17XL-parasitized RBCs (pRBCs). Similar immunization and challenge experiments were conducted to compare PyMSP1/8-sec versus PyMSP1/8-mem mRNA vaccines. Results: Immunogenicity of the PyMSP1/8-sec mRNA vaccine was superior to the recombinant formulation, inducing higher antibody titers against both vaccine components. Following challenge with P. yoelii 17XL pRBCs, all PyMSP1/8-sec-immunized animals survived, with 50% of these showing no detectible pRBCs in circulation (<0.01%). In addition, mean peak parasitemia in PyMSP1/8-sec mRNA-immunized mice was significantly lower than that in the rPyMSP1/8 vaccine group. Both PyMSP1/8-sec and PyMSP1/8-mem were protective against P. yoelii 17XL challenge, with PyMSP1/8-mem immunization providing a significantly higher level of protection than PyMSP1/8-sec immunization considering the number of animals with no detectable pRBCs in circulation and the mean peak parasitemia in animals with detectable parasitemia. Conclusions: mRNA vaccines were highly immunogenic and potently protective against blood-stage malaria, outperforming a similar recombinant-based vaccine. The membrane-bound antigen was more effective at inducing protective antibody responses, highlighting the need to consider antigen localization for mRNA vaccine design. Full article

Hepatitis delta virus (HDV) infection is associated with severe hepatic complications and rapid progression towards liver cirrhosis and hepatocellular carcinoma. Accurate measurement of HDV RNA is critical for monitoring therapeutic responses, especially during treatment with novel therapies such as bulevirtide (BLV). This study compared the analytical performance of two HDV RNA quantification assays, Bosphore (Anatolia) and AltoStar^® (Altona), focusing on their sensitivity, specificity, and potential implications for clinical management. Sixty-one clinical samples from twenty-four patients, including fifteen HDV-infected patients receiving BLV treatment and nine controls, were tested using each assay. Of 30 samples identified as HDV-negative by the Bosphore assay, 17 (56.7%) were HDV-positive with AltoStar^®, demonstrating the superior sensitivity (p < 0.0001) of the latter assay. Quantitative analyses revealed consistently higher viral load measurements with AltoStar^® compared to Bosphore, with a difference of 1.23 Log IU/mL and a moderate correlation (r² = 0.7385) between assays. Each assay demonstrated a high specificity, with no false positives detected among control samples. However, our findings suggest that differences in assay sensitivity could impact the evaluation of virological response, highlighting the risk of false-negative results in chronically HDV-infected patients with low-level viremia. This emphasizes the need for careful assay selection to accurately monitor treatment outcomes. Full article

In this paper, a prey–predator diffusion model with isolation and drug treatment control measures for prey infection is studied. The main objective is to find an optimal control that minimizes the population density of infected prey and the costs of isolation and drug treatment for infected prey. Through analysis, the existence and uniqueness of weak solution, as well as the existence and local uniqueness of optimal controls are proven. The first-order necessary condition is derived, and the feasibility of the theoretical proof is verified through numerical simulations. Full article

Understanding the contribution of human herpesviruses to the aetiology of neurodegenerative diseases is an emerging field of interest. The association of Epstein–Barr virus with multiple sclerosis is the most researched example; however, the definitive proof of causation is still lacking. Alzheimer’s disease (AD) is the most common form of dementia and typically manifests in individuals aged over 65 years; however, it also occurs in a small number of individuals aged less than 65 years. A combination of environmental, genetic, and lifestyle factors is believed to contribute to the development of AD. There have been several reports describing potential associations of infections or reactivations of human alphaherpesviruses with AD. A particular characteristic of human alphaherpesviruses (herpes simplex viruses 1 and 2, varicella zoster virus) is that they are neurotropic and that lifelong infection (latency) is established mainly in the dorsal root and trigeminal ganglia. There have also been reports that suppression of alphaherpesvirus infections through either vaccination or the application of antiviral treatments may be protective against the development of AD. Zoster vaccines and acyclovir may prove to be effective interventions for preventing or limiting the progression of AD. This is particularly relevant as there are currently no available cheap and effective treatments for AD. In this review, the basic virology of human alphaherpesviruses is described followed by their epidemiology and associations with AD. Finally, the prevention and treatment of human alphaherpesviruses are considered in the context of potential applications for the prevention of AD. Full article

Measles, hepatitis C, and COVID-19 are significant human diseases caused by RNA viruses. While vaccines exist to prevent infections, there are a small number of currently available therapeutic agents that can effectively treat these diseases after infection occurs. This study explores a new therapeutic strategy using a small molecule designated polyprenyl immunostimulant (PI) to increase innate immune responses and combat viral infections. Using a multi-disciplinary approach, this study quantifies the effects of PI in mice and THP-1 cells using flow cytometry to identify immune phenotypic markers and mass spectroscopy to monitor the metabolomic profiles of immune cells perturbed by PI treatment. The metabolomic studies identified that sphinganine and ceramide, which are precursors of sphingosine-1-phosphate (S1P), were the common metabolites upregulated in THP-1 and mice blood. Sphingosine-1-phosphate can mediate the trafficking of T cells, whereas ceramide can signal the activation and proliferation of T cells, thereby modulating the mammalian host’s immunity. To demonstrate proof-of-principle, a case study was conducted to examine the benefit of administering PI to improve the outcomes of a feline co-infected with two distinct RNA viruses—feline leukemia virus and feline infectious peritonitis virus. Both viruses produce deadly symptoms that closely resemble RNA viruses that infect humans. The results identify quantifiable cellular and metabolic markers arising from PI treatment that can be used to establish a platform measuring the efficacy of PI in modulating the innate immune system. Full article

A rapid and accurate evaluation of a chemical disinfectant’s bactericidal efficacy is crucial for ensuring effective infection control, preventing the spread of pathogens, and supporting the development of new disinfectant formulations. In this study, we report a rapid, label-free flow cytometry (FCM) protocol for evaluating the bactericidal efficacy of disinfectants. Five commercial disinfectants (alcohols, oxidizing agents, and alkylating agents) were evaluated against type strains recommended by EN 13727+A2 and ten clinical strains. The label-free FCM method allowed the determination of disinfectant efficacy through assessment of scatter light profiles (FSC-H/SSC-H) and count differences. The label-free FCM provided the results in approximately 4 h and showed strong correlation with standard tests (91.4%, sensitivity 0.94 and specificity 0.98) that can take up to 48 h. Our results represent a proof-of-principle that label-free FCM can reliably assess the efficacy of chemical disinfectants, the same day, and substantially faster than the current growth-based methods. Additionally, the study highlights the potential of the FCM method for detecting the occurrence of viable but non-culturable bacteria following treatment with chlorine-based disinfectants. With its speed, accuracy, and capability to identify bacterial injuries at a single-cell level, the FCM method is a powerful tool for assessing the efficacy of new disinfectant formulations. Full article

The potato is the third most important crop in the world, and more than 375 million metric tonnes of potatoes are produced globally on an annual basis. Potato Virus Y (PVY) poses a significant threat to the production of seed potatoes, resulting in economic losses and risks to food security. Current detection methods for PVY typically rely on serological assays for leaves and PCR for tubers; however, these processes are labor-intensive, time-consuming, and not scalable. In this proof-of-concept study, we propose the use of unmanned aerial vehicles (UAVs) integrated with hyperspectral cameras, including a downwelling irradiance sensor, to detect the PVY in commercial growers’ fields. We used a 400–1000 nm visible and near-infrared (Vis-NIR) hyperspectral camera and trained several standard machine learning and deep learning models with optimized hyperparameters on a curated dataset. The performance of the models is promising, with the convolutional neural network (CNN) achieving a recall of 0.831, reliably identifying the PVY-infected plants. Notably, UAV-based imaging maintained performance levels comparable to ground-based methods, supporting its practical viability. The hyperspectral camera captures a wide range of spectral bands, many of which are redundant in identifying the PVY. Our analysis identified five key spectral regions that are informative in identifying the PVY. Two of them are in the visible spectrum, two are in the near-infrared spectrum, and one is in the red-edge spectrum. This research shows that early-season PVY detection is feasible using UAV hyperspectral imaging, offering the potential to minimize economic and yield losses. It also highlights the most relevant spectral regions that carry the distinctive signatures of PVY. This research demonstrates the feasibility of early-season PVY detection using UAV hyperspectral imaging and provides guidance for developing cost-effective multispectral sensors tailored to this task. Full article

The COVID-19 pandemic highlighted the need for new therapeutic strategies to counter emerging pathogenic viruses. Herein, we introduce a novel fusion protein platform that enables antiviral targeting of distinct viral species based on host receptor specificity. Proof-of-concept studies focused on the human coronavirus NL63, which shares specificity for the ACE2 host receptor with the pandemic SARS-CoV and SARS-CoV-2 species. This antiviral fusion protein combines IFN-β with the soluble extracellular domain of ACE2 (IFNβ-ACE2). Both domains retained predicted bioactivities in that the IFN-β domain exhibited potent antiproliferative activity and the ACE2 domain exhibited full binding to the transmembrane SARS-CoV-2 Spike protein. In virus-washed (virus-targeted) and non-washed in vitro infection systems, we showed that the pool of IFNβ-ACE2 targeted to the virion surface had superior antiviral activity against NL63 compared to soluble ACE2, IFN-β, or the unlinked combination of ACE2 and IFN-β. The pool of IFNβ-ACE2 on the virion surface exhibited robust antiviral efficacy based on the preemptive targeting of antiviral IFN-β activity to the proximal site of viral infection. In conclusion, virus-targeted IFN-β places interferon optimally and antecedent to viral infection to constitute a new antiviral strategy. Full article

This study presents a proof-of-concept evaluation of optimized whole-cell biosensors designed for the real-time detection of crop infections. Genetically engineered luminescent bacterial strains were used to detect volatile organic compounds (VOCs) emitted by crops during spoilage. Key factors investigated include bacterial uniformity, nutrient supply, and temperature effects. The results demonstrated that lower temperatures (+4 °C) yielded higher sensor sensitivity and prolonged bacterial viability. A proof-of-concept evaluation was conducted in storage-like conditions, showing effective infection detection in potatoes. These findings underscore the potential of whole-cell-based biosensors for monitoring postharvest production in cold storage environments. Full article

Background: Influenza virus is one of the major respiratory virus infections that is a global health concern. Although there are already approved vaccines, most are administered via the intramuscular route, which is usually painful, leading to vaccine hesitancy. To this end, exploring the non-invasive, transdermal vaccination route using dissolving microneedles would significantly improve vaccine compliance. Research on innovative vaccine delivery systems, such as antigen-loaded PLGA microparticles, has the potential to pave the way for a broader range of vaccine candidates. Methods: In this proof-of-concept study, a combination of the inactivated influenza A H1N1 virus and inactivated influenza A H3N2 virus were encapsulated in a biodegradable poly (lactic-co-glycolic acid) (PLGA) polymeric matrix within microparticles, which enhanced antigen presentation. The antigen PLGA microparticles were prepared separately using a double emulsion (w/o/w), lyophilized, and characterized. Next, the vaccine microparticles were assessed in vitro in dendritic cells (DC 2.4) for immunogenicity. To explore pain-free transdermal vaccination, the vaccine microparticles were loaded into dissolving microneedles and administered in mice (n = 5). Results: Our vaccination study demonstrated that the microneedle-based vaccine elicited strong humoral responses as demonstrated by high antigen-specific IgA, IgG, IgG1, and IgG2a antibodies in serum samples and IgA in lung supernatant. Further, the vaccine also elicited a strong cellular response as evidenced by high levels of CD4+ and CD8a+ T cells in lymphoid organs such as the lymph nodes and spleen. Conclusion: The delivery of influenza vaccine-loaded PLGA microparticles using microneedles would be beneficial to individuals experiencing needle-phobia, as well as the geriatric and pediatric population. Full article