T1-Mapping Characterization of Two Tumor Types.

T1- mapping is a quantitative method to characterize tissues with MR imaging in a quick and efficient manner. It utilizes the relaxation rate of protons to depict the underlying structures within the imaging frame. While T1-mapping techniques are used with some frequency in areas such as cardiac imaging, their application to understanding malignancies and identify tumor structures has yet to be thoroughly investigated. Utilizing a saturation recovery method to acquire T1-maps for two different tumor models has revealed that longitudinal relaxation mapping is sensitive enough to distinguish between normal and malignant tissue. This is seen even with decreased signal to noise ratios using small voxel sizes to obtain high-resolution images. In both tumor models it was revealed that relaxation mapping recorded significantly different relaxation values between regions encapsulating the tumor, muscle, kidney, or spleen, as well as between the cell lines themselves. This indicates a potential future application of relaxation mapping as a method to fingerprint various stages of tumor development and may prove a useful measure to identify micro-metastases.

Selective targeting of IRAK1 attenuates low molecular weight hyaluronic acid-induced stemness and non-canonical STAT3 activation in epithelial ovarian cancer.

Advanced epithelial ovarian cancer (EOC) survival rates are dishearteningly low, with ~25% surviving beyond 5 years. Evidence suggests that cancer stem cells contribute to acquired chemoresistance and tumor recurrence. Here, we show that IRAK1 is upregulated in EOC tissues, and enhanced expression correlates with poorer overall survival. Moreover, low molecular weight hyaluronic acid, which is abundant in malignant ascites from patients with advanced EOC, induced IRAK1 phosphorylation leading to STAT3 activation and enhanced spheroid formation. Knockdown of IRAK1 impaired tumor growth in peritoneal disease models, and impaired HA-induced spheroid growth and STAT3 phosphorylation. Finally, we determined that TCS2210, a known inducer of neuronal differentiation in mesenchymal stem cells, is a selective inhibitor of IRAK1. TCS2210 significantly inhibited EOC growth in vitro and in vivo both as monotherapy, and in combination with cisplatin. Collectively, these data demonstrate IRAK1 as a druggable target for EOC.

Characterization of a Biochemical Mouse Model of Primary Aldosteronism for Thermal Therapies.

Introduction: Aldosterone-producing adenoma (APA) is the most common cause of endocrine-related hypertension but surgery is not always feasible. Current medical interventions are associated with significant side effects and poor patient compliance. New APA animal models that replicate basic characteristics of APA and give physical and biochemical feedback are needed to test new non-surgical treatment methods, such as image-guided thermal ablation. Methods: A model of APA was developed in nude mice using HAC15 cells, a human adrenal carcinoma cell line. Tumor growth, aldosterone production, and sensitivity to angiotensin II were characterized in the model. The utility of the model was validated via treatment with microwave ablation and characterization of the resulting physical and biochemical changes in the tumor. Results: The APA model showed rapid and relatively homogeneous growth. The tumors produced aldosterone and steroid precursors in response to angiotensin II challenge, and plasma aldosterone levels were significantly higher in tumor bearing mice two hours after challenge verses non-tumor bearing mice. The model was useful for testing microwave ablation therapy, reducing aldosterone production by 80% in treated mice. Conclusion: The HAC15 model is a useful tumor model to study and develop localized treatment methods for APA.

Region-Specific Brain Volume Changes Emerge in Adolescence in the Valproic Acid Model of Autism and Parallel Human Findings.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social and communication deficits, cognitive dysfunction, and stereotyped repetitive behaviors. Regional volume changes are commonly observed in individuals with ASD. To examine volumetric dysregulation across adolescence, the valproic acid (VPA) model was used to induce ASD-like phenotypes in rats. Regional volumes were obtained via magnetic resonance imaging (MRI) at either postnatal day 28 (P28) or postnatal day 40 (P40), which correspond to early and late adolescence, respectively. Consistent with prior research, VPA animals had reduced total brain volume compared to control animals. A novel outcome was that VPA animals had overgrown right hippocampi at P40. Differences in the pattern of development of the anterior cingulate cortex were also observed in VPA animals. Differences for the posterior cingulate were only observed in males but not females. These results demonstrate differences in region-specific developmental trajectories between control and VPA animals and suggest that the VPA model may capture regional volume changes consistent with human ASD.

Description of an activity-based enzyme biosensor for lung cancer detection.

BACKGROUND: Lung cancer is associated with the greatest cancer mortality as it typically presents with incurable distributed disease. Biomarkers relevant to risk assessment for the detection of lung cancer continue to be a challenge because they are often not detectable during the asymptomatic curable stage of the disease. A solution to population-scale testing for lung cancer will require a combination of performance, scalability, cost-effectiveness, and simplicity. METHODS: One solution is to measure the activity of serum available enzymes that contribute to the transformation process rather than counting biomarkers. Protease enzymes modify the environment during tumor growth and present an attractive target for detection. An activity based sensor platform sensitive to active protease enzymes is presented. A panel of 18 sensors was used to measure 750 sera samples from participants at increased risk for lung cancer with or without the disease. RESULTS: A machine learning approach is applied to generate algorithms that detect 90% of cancer patients overall with a specificity of 82% including 90% sensitivity in Stage I when disease intervention is most effective and detection more challenging. CONCLUSION: This approach is promising as a scalable, clinically useful platform to help detect patients who have lung cancer using a simple blood sample. The performance and cost profile is being pursued in studies as a platform for population wide screening.

Lung cancer is responsible for more deaths worldwide than all other cancers. It is often detected with the appearance of symptoms when treatment is limited and outcomes for the patient are much worse. While imaging chest scans can detect disease, they are poorly used even in the United States where it is an approved screening method. When cancer is present, protease enzymes are responsible for making space and modifying the lung tissue for the growing tumor. This report describes a panel of 18 sensors that release a fluorescent signal when these enzymes are present in a blood sample. The signal acts like a fingerprint of activity that can be used to identify people with lung cancer. This sensor platform can detect patients with curable lung cancer and could provide a platform for screening very large populations of at-risk individuals.

Serum amyloid A and mitochondrial DNA in extracellular vesicles are novel markers for detecting traumatic brain injury in a mouse model.

This study investigates the potential use of circulating extracellular vesicles' (EVs) DNA and protein content as biomarkers for traumatic brain injury (TBI) in a mouse model. Despite an overall decrease in EVs count during the acute phase, there was an increased presence of exosomes (CD63+ EVs) during acute and an increase in microvesicles derived from microglia/macrophages (CD11b+ EVs) and astrocytes (ACSA-2+ EVs) in post-acute TBI phases, respectively. Notably, mtDNA exhibited an immediate elevation post-injury. Neuronal (NFL) and microglial (Iba1) markers increased in the acute, while the astrocyte marker (GFAP) increased in post-acute TBI phases. Novel protein biomarkers (SAA, Hp, VWF, CFD, CBG) specific to different TBI phases were also identified. Biostatistical modeling and machine learning identified mtDNA and SAA as decisive markers for TBI detection. These findings emphasize the importance of profiling EVs' content and their dynamic release as an innovative diagnostic approach for TBI in liquid biopsies.

Therapeutic potential of combating cancer by restoring wild-type p53 through mRNA nanodelivery.

Among the tumor suppressor genes, TP53 is the most frequently mutated in human cancers, and most mutations are missense mutations causing production of mutant p53 (mutp53) proteins. TP53 mutations not only results in loss of function (LOH) as a transcription factor and a tumor suppressor, but also gain wild-type p53 (WTp53)-independent oncogenic functions that enhance cancer metastasis and progression (Yamamoto and Iwakuma, 2018; Zhang et al., 2022). TP53 has extensively been studied as a therapeutic target as well as for drug development and therapies, however with limited success. Achieving targeted therapies for restoration of WTp53 function and depletion or repair of mutant p53 (mutp53) will have far reaching implication in cancer treatment and therapies. This review briefly discusses the role of p53 mutation in cancer and the therapeutic potential of restoring WTp53 through the advances in mRNA nanomedicine.

Repurposing sunscreen as an antibiotic: zinc-activated avobenzone inhibits methicillin-resistant Staphylococcus aureus.

Methicillin-resistant Staphylococcus aureus (MRSA) is a major healthcare concern with associated healthcare costs reaching over ${\$}$1 billion in a single year in the USA. Antibiotic resistance in S. aureus is now observed against last line of defense antibiotics, such as vancomycin, linezolid, and daptomycin. Unfortunately, high throughput drug discovery approaches to identify new antibiotics effective against MRSA have not resulted in much tangible success over the last decades. Previously, we demonstrated the feasibility of an alternative drug discovery approach, the identification of metallo-antibiotics, compounds that gain antibacterial activity only after binding to a transition metal ion and as such are unlikely to be detected in standard drug screens. We now report that avobenzone, the primary active ingredient of most sunscreens, can be activated by zinc to become a potent antibacterial compound against MRSA. Zinc-activated avobenzone (AVB-Zn) potently inhibited a series of clinical MRSA isolates [minimal inhibitory concentration (MIC): 0.62-2.5 µM], without pre-existing resistance and activity without zinc (MIC: >10 µM). AVB-Zn was also active against clinical MRSA isolates that were resistant against the commonly used zinc-salt antibiotic bacitracin. We found AVB-Zn exerted no cytotoxicity on human cell lines and primary cells. Last, we demonstrate AVB-Zn can be deployed therapeutically as lotion preparations, which showed efficacy in a mouse wound model of MRSA infection. AVB-Zn thus demonstrates Zn-activated metallo-antibiotics are a promising avenue for future drug discovery.

Super-resolution reconstruction in ultrahigh-field MRI.

Magnetic resonance imaging (MRI) is a highly significant imaging platform for a variety of medical and research applications. However, the low spatiotemporal resolution of conventional MRI limits its applicability toward rapid acquisition of ultrahigh-resolution scans. Current aims at high-resolution MRI focus on increasing the accuracy of tissue delineation, assessments of structural integrity, and early identification of malignancies. Unfortunately, high-resolution imaging often leads to decreased signal/noise (SNR) and contrast/noise (CNR) ratios and increased time cost, which are unfeasible in many clinical and academic settings, offsetting any potential benefits. In this study, we apply and assess the efficacy of super-resolution reconstruction (SRR) through iterative back-projection utilizing through-plane voxel offsets. SRR allows for high-resolution imaging in condensed time frames. Rat skulls and archerfish samples, typical models in academic settings, were used to demonstrate the impact of SRR on varying sample sizes and applicability for translational and comparative neuroscience. The SNR and CNR increased in samples that did not fully occupy the imaging probe and in instances where the low-resolution data were acquired in three dimensions, while the CNR was found to increase with both 3D and 2D low-resolution data reconstructions when compared with directly acquired high-resolution images. Limitations to the applied SRR algorithm were investigated to determine the maximum ratios between low-resolution inputs and high-resolution reconstructions and the overall cost effectivity of the strategy. Overall, the study revealed that SRR could be used to decrease image acquisition time, increase the CNR in nearly all instances, and increase the SNR in small samples.

Anticancer Activity of Novel Difluorinated Curcumin Analog and Its Inclusion Complex with 2-Hydroxypropyl-ß-Cyclodextrin against Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is the primary reason for cancer-related deaths in the US. Genetic mutations, drug resistance, the involvement of multiple signaling pathways, cancer stem cells (CSCs), and desmoplastic stroma, which hinders drug penetrance, contribute to poor chemotherapeutic efficacy. Hence, there is a need to identify novel drugs with improved delivery to improve treatment outcomes. Curcumin is one such compound that can inhibit multiple signaling pathways and CSCs. However, curcumin's clinical applicability for treating PDAC is limited because of its poor solubility in water and metabolic instability. Hence, we developed a difluorinated curcumin (CDF) analog that accumulates selectively in the pancreas and inhibits PDAC growth in vitro and in vivo. In the present work, we developed its 2-hydroxy-propyl-ß-cyclodextrin (HCD) inclusion complex to increase its water solubility and hydrolytic stability. The CDFHCD inclusion complex was characterized by spectroscopic, thermal, and microscopic techniques. The inclusion complex exhibited increased aqueous solubility, hydrolytic stability, and antiproliferative activity compared to parent CDF. Moreover, CDF and CDFHCD inhibited colony and spheroid formation, and induced cell cycle and apoptosis in PDAC cell lines. Hence, CDFHCD self-assembly is an efficient approach to increase water solubility and anticancer therapeutic efficacy, which now warrants advancement towards a clinical proof of concept in PDAC patients.

In Vitro Measurement and Mathematical Modeling of Thermally-Induced Injury in Pancreatic Cancer Cells.

Thermal therapies are under investigation as part of multi-modality strategies for the treatment of pancreatic cancer. In the present study, we determined the kinetics of thermal injury to pancreatic cancer cells in vitro and evaluated predictive models for thermal injury. Cell viability was measured in two murine pancreatic cancer cell lines (KPC, Pan02) and a normal fibroblast (STO) cell line following in vitro heating in the range 42.5-50 °C for 3-60 min. Based on measured viability data, the kinetic parameters of thermal injury were used to predict the extent of heat-induced damage. Of the three thermal injury models considered in this study, the Arrhenius model with time delay provided the most accurate prediction (root mean square error = 8.48%) for all cell lines. Pan02 and STO cells were the most resistant and susceptible to hyperthermia treatments, respectively. The presented data may contribute to studies investigating the use of thermal therapies as part of pancreatic cancer treatment strategies and inform the design of treatment planning strategies.

Adolescent female valproic acid rats have impaired extra-dimensional shifts of attention and enlarged anterior cingulate cortices.

In order to develop better treatments for autism spectrum disorder (ASD) it is critical to understand the developmental trajectory of the disorder and the accompanying brain changes. This study used the valproic acid (VPA) model to induce ASD-like symptoms in rodents. Prior studies have demonstrated that VPA animals are impaired on executive function tasks, paralleling results in humans with ASD. Here, VPA adolescent female rats were impaired on a set-shifting task and had enlarged frontal cortices compared to control females. The deficits observed in the VPA female rats mirrors results in females with ASD. In addition, adolescent VPA females with enlarged frontal cortices performed the worst across the entire task. These brain changes in adolescence are also found in adolescent humans with ASD. These novel findings highlight the importance of studying the brain at different developmental stages.

Iron-Based Magnetic Nanosystems for Diagnostic Imaging and Drug Delivery: Towards Transformative Biomedical Applications.

The advancement of biomedicine in a socioeconomically sustainable manner while achieving efficient patient-care is imperative to the health and well-being of society. Magnetic systems consisting of iron based nanosized components have gained prominence among researchers in a multitude of biomedical applications. This review focuses on recent trends in the areas of diagnostic imaging and drug delivery that have benefited from iron-incorporated nanosystems, especially in cancer treatment, diagnosis and wound care applications. Discussion on imaging will emphasise on developments in MRI technology and hyperthermia based diagnosis, while advanced material synthesis and targeted, triggered transport will be the focus for drug delivery. Insights onto the challenges in transforming these technologies into day-to-day applications will also be explored with perceptions onto potential for patient-centred healthcare.

Early Detection of Pancreatic Cancers Using Liquid Biopsies and Hierarchical Decision Structure.

OBJECTIVE: Pancreatic cancer (PC) is a silent killer, because its detection is difficult and to date no effective treatment has been developed. In the US, the current 5-year survival rate of 11%. Therefore, PC has to be detected as early as possible. METHODS AND PROCEDURES: In this work, we have combined the use of ultrasensitive nanobiosensors for protease/arginase detection with information fusion based hierarchical decision structure to detect PC at the localized stage by means of a simple Liquid Biopsy. The problem of early-stage detection of pancreatic cancer is modelled as a multi-class classification problem. We propose a Hard Hierarchical Decision Structure (HDS) along with appropriate feature engineering steps to improve the performance of conventional multi-class classification approaches. Further, a Soft Hierarchical Decision Structure (SDS) is developed to additionally provide confidences of predicted labels in the form of class probability values. These frameworks overcome the limitations of existing research studies that employ simple biostatistical tools and do not effectively exploit the information provided by ultrasensitive protease/arginase analyses. RESULTS: The experimental results demonstrate that an overall mean classification accuracy of around 92% is obtained using the proposed approach, as opposed to 75% with conventional multi-class classification approaches. This illustrates that the proposed HDS framework outperforms traditional classification techniques for early-stage PC detection. CONCLUSION: Although this study is only based on 31 pancreatic cancer patients and a healthy control group of 48 human subjects, it has enabled combining Liquid Biopsies and Machine Learning methodologies to reach the goal of earliest PC detection. The provision of both decision labels (via HDS) as well as class probabilities (via SDS) helps clinicians identify instances where statistical model-based predictions lack confidence. This further aids in determining if more tests are required for better diagnosis. Such a strategy makes the output of our decision model more interpretable and can assist with the diagnostic procedure. CLINICAL IMPACT: With further validation, the proposed framework can be employed as a decision support tool for the clinicians to help in detection of pancreatic cancer at early stages.

Liquid Biopsy-Based Biomarkers of Inflammatory Nociception Identified in Male Rats.

Physicians are challenged in treating pain patients due to the lack of quantifiable, objective methods of measuring pain in the clinic; pain sensation is multifaceted and subjective to each individual. There is a critical need for point-of-care quantification of accessible biomarkers to provide objective analyses beyond the subjective pain scales currently employed in clinical care settings. In the present study, we employed an animal model to test the hypothesis that circulating regulators of the inflammatory response directly associate with an objective behavioral response to inflammatory pain. Upon induction of localized paw inflammation, we measured the systemic protein expression of cytokines, and activity levels of matrix metalloproteinases (MMPs) that are known to participate in the inflammatory response at the site of injury and investigated their relationship to the behavioral response across a 24 h period. Intraplantar injection with 1% λ-carrageenan induced a significant increase in paw thickness across this timespan with maximal effects observed at the 8 h timepoint when locomotor activity was also impaired. Expression of the chemokines C-X-C motif chemokine ligand 1 (CXCL1) and C-C motif chemokine ligand 2 (CCL2) positively correlated with paw inflammation and negatively correlated with locomotor activity at 8 h. The ratio of MMP9 to MMP2 activity negatively correlated with paw inflammation at the 8 h timepoint. We postulate that the CXCL1 and CCL2 as well as the ratio of MMP9 to MMP2 activity may serve as predictive biomarkers for the timecourse of inflammation-associated locomotor impairment. These data define opportunities for the future development of a point-of-care device to objectively quantify biomarkers for inflammatory pain states.

Mitochondrial Targeting Peptide-based Nanodelivery for Cancer Treatment.

Mitochondria are important intracellular organelles because of their key roles in cellular metabolism, proliferation, and programmed cell death. The differences in the structure and function of the mitochondria of healthy and cancerous cells have made mitochondria an interesting target for drug delivery. Mitochondrial targeting is an emerging field as the targeted delivery of cytotoxic payloads and antioxidants to the mitochondrial DNA is capable of overcoming multidrug resistance. Mitochondrial targeting is preferred over nuclear targeting because it can take advantage of the distorted metabolism in cancer. The negative membrane potential of the inner and outer mitochondrial membranes, as well as their lipophilicity, are known to be the features that drive the entry of compatible targeting moiety, along with anticancer drug conjugates, towards mitochondria. The design of such drug nanocarrier conjugates is challenging because they need not only to target the specific tumor/cancer site but have to overcome multiple barriers as well, such as the cell membrane and mitochondrial membrane. This review focuses on the use of peptide-based nanocarriers (organic nanostructures such as liposomes, inorganic, carbon-based, and polymers) for mitochondrial targeting of the tumor/cancer. Both in vitro and in vivo key results are reported.

System for delivering microwave ablation to subcutaneous tumors in small-animals under high-field MRI thermometry guidance.

PURPOSE: Bio-effects following thermal treatments are a function of the achieved temperature profile in tissue, which can be estimated across tumor volumes with real-time MRI thermometry (MRIT). Here, we report on expansion of a previously developed small-animal microwave hyperthermia system integrated with MRIT for delivering thermal ablation to subcutaneously implanted tumors in mice. METHODS: Computational models were employed to assess suitability of the 2.45 GHz microwave applicators for delivering ablation to subcutaneous tumor targets in mice. Phantoms and ex-vivo tissues were heated to temperatures in the range 47-67 °C with custom-made microwave applicators for validating MRIT with the proton resonance frequency shift method against fiberoptic thermometry. HAC15 tumors implanted in nude mice (n = 6) were ablated in vivo and monitored with MRIT in multiple planes. One day post ablation, animals were euthanized, and excised tumors were processed for viability assessment. RESULTS: Average absolute error between temperatures from fiberoptic sensors and MRIT was 0.6 °C across all ex-vivo ablations. During in-vivo experiments, tumors with volumes ranging between 5.4-35.9 mm3 (mean 14.2 mm3) were ablated (duration: 103-150 s) to achieve 55 °C at the tumor boundary. Thermal doses ≥240 CEM43 were achieved across 90.7-98.0% of tumor volumes for four cases. Ablations were incomplete for remaining cases, attributed to motion-affected thermometry. Thermal dose-based ablative tumor coverage agreed with viability assessment of excised tumors. CONCLUSIONS: We have developed a system for delivering microwave ablation to subcutaneous tumors in small animals under MRIT guidance and demonstrated its performance in-vivo.

Glyco-nanotechnology: A biomedical perspective.

Glycans govern cellular signaling through glycan-protein and glycan-glycan crosstalk. Disruption in the crosstalk initiates 'rogue' signaling and pathology. Nanomaterials supply platforms for multivalent displays of glycans, mediate 'rogue' signal correction, and provide disease treatment modalities (therapeutics). The decorated glycans also target overexpressed lectins on unhealthy cells and direct metal nanoparticles such as gold, iron oxide, and quantum dots to the site of infection. The nanoparticles inform us about the state of the disease (diagnosis) through their distinct optical, magnetic, and electronic properties. Glyco-nanoparticles can sense disease biomarkers, report changes in protein-glycan interactions, and safeguard quality control (analysis). Here we review the current state of glyco-nanotechnology focusing on diagnosis, therapeutics, and analysis of human diseases. We highlight how glyco-nanotechnology could aid in improving diagnostic methods for the detection of disease biomarkers with magnetic resonance imaging (MRI) and fluorescence imaging (FLI), enhance therapeutics such as anti-adhesive treatment of cancer and vaccines against pneumonia, and advance analysis such as the rapid detection of pharmaceutical heparin contaminant and recombinant SARS-COV-2 spike protein. We illustrate these progressions and outline future potentials of glyco-nanotechnology in advancing human health.

Host T Cell Dedifferentiation Effects Drive HIV-1 Latency Stability.

The development of therapies to eliminate the latent HIV-1 reservoir is hampered by our incomplete understanding of the biomolecular mechanism governing HIV-1 latency. To further complicate matters, recent single-cell RNA sequencing (scRNA-seq) studies reported extensive heterogeneity between latently HIV-1-infected primary T cells, implying that latent HIV-1 infection can persist in greatly differing host cell environments. We show here that transcriptomic heterogeneity is also found between latently infected T cell lines, which allowed us to study the underlying mechanisms of intercell heterogeneity at high signal resolution. Latently infected T cells exhibited a dedifferentiated phenotype, characterized by the loss of T cell-specific markers and gene regulation profiles reminiscent of hematopoietic stem cells (HSC). These changes had functional consequences. As reported for stem cells, latently HIV-1-infected T cells efficiently forced lentiviral superinfections into a latent state and favored glycolysis. As a result, metabolic reprogramming or cell redifferentiation destabilized latent infection. Guided by these findings, data mining of single-cell RNA-seq data of latently HIV-1-infected primary T cells from patients revealed the presence of similar dedifferentiation motifs. More than 20% of the highly detectable genes that were differentially regulated in latently infected cells were associated with hematopoietic lineage development (e.g., HUWE1, IRF4, PRDM1, BATF3, TOX, ID2, IKZF3, and CDK6) or were hematopoietic markers (SRGN; hematopoietic proteoglycan core protein). The data add to evidence that the biomolecular phenotype of latently HIV-1-infected cells differs from that of normal T cells and strategies to address their differential phenotype need to be considered in the design of therapeutic cure interventions. IMPORTANCE HIV-1 persists in a latent reservoir in memory CD4 T cells for the lifetime of a patient. Understanding the biomolecular mechanisms used by the host cells to suppress viral expression will provide essential insights required to develop curative therapeutic interventions. Unfortunately, our current understanding of these control mechanisms is still limited. By studying gene expression profiles, we demonstrated that latently HIV-1-infected T cells have a dedifferentiated T cell phenotype. Software-based data integration allowed the identification of drug targets that would redifferentiate viral host cells and, by extension, destabilize latent HIV-1 infection events. The importance of the presented data lies within the clear demonstration that HIV-1 latency is a host cell phenomenon. As such, therapeutic strategies must first restore proper host cell functionality to accomplish efficient HIV-1 reactivation.

Optical biosensing of markers of mucosal inflammation.

We report the design and adaptation of iron/iron oxide nanoparticle-based optical nanobiosensors for enzymes or cytokine/chemokines that are established biomarkers of lung diseases. These biomarkers comprise ADAM33, granzyme B, MMP-8, neutrophil elastase, arginase, chemokine (C-C motif) ligand 20 and interleukin-6. The synthesis of nanobiosensors for these seven biomarkers, their calibration with commercially available enzymes and cytokines/chemokines, as well as their validation using bronchoalveolar lavage (BAL) obtained from a mouse model of TLR3-mediated inflammation are discussed here. Exhaled Breath Condensate (EBC) is a minimally invasive approach for sampling airway fluid in the diagnosis and management of various lung diseases in humans (e.g., asthma, COPD and viral infections). We report the proof-of-concept of using human EBC in conjunction with nanobiosensors for diagnosis/monitoring airway inflammation. These findings suggest that, with nanosensor technology, human EBC can be utilized as a liquid biopsy to monitor inflammation/remodeling in lung disease.