Wearable sensors provide a convenient method of tracking various biomarkers in non-invasively retrievable biofluids such as sweat and saliva. Patients with chronic diseases such as diabetes would benefit greatly from the wearable sensing systems to continuously monitor levels of analytes such as glucose or ketone, as the information can be used by the patient and the clinical care team to modify lifestyle routines and other interventions. However, it is challenging to create such a sensor because the concentrations in sweat and saliva are usually in the micro molar range, which is 10x lower than in serum. Electroenzymatic sensors are especially suitable for this application because they can proportionally transduce the substrate concentration into measurable electrical signals using an enzyme that is highly specific to the target. In this study beta-hydroxybutyrate (HB) is selected as the target analyte because its monitoring can be useful in prevention of diabetic ketoacidosis. With the aid of a carbon nanotube substrate which allows for stably immobilizing the enzyme and the enzymatic reaction cofactor, we developed a dehydrogenase-based sensor for sensitive and selective HB detection in the saliva matrix. The sensor composition was optimized to improve reversibility, selectivity, and resistance to biofouling. The dehydrogenase-based sensors can be generalized to a variety of biomarkers by simply switching the enzyme, which would open the possibility of exploring various applications.

Many of the mechanisms of antibody-mediated protection occur through secondary interactions with immune effector cells via the antibody’s Fc region. Observing Fc regions in action during an active immune response is difficult. However, using systems serology profiling, we can comprehensively survey a diverse array of antibody features in parallel to quantify their interactions with the rest of the immune system. Previously, we showed tensor factorization was successful at reducing systems serology data into relevant components; however, these linear methods cannot model the nonlinearities displayed by immune system complex interactions. In this study, we introduce a novel approach, mechanistic tensor decomposition (MTD), that incorporates a mechanistic binding model into tensor decomposition. The tensor method reduces the data, while the binding model reflects the nonlinear Fc interactions. After better reducing these data into biologically consistent patterns, we reanalyze two SARS-CoV-2 datasets to validate the decomposition. MTD outperforms the traditional canonical polyadic (CP) tensor decomposition in the extent of data reduction, FcγR binding response prediction, and patient status. We report that under MTD, model interpretation improves through effective data reduction and accurately identifying patterns of binding variation across individual measurements. Thus, we propose that MTD is an effective reduction method for data analysis in systems serology that can uncover novel correlations between antibody features and function. Identifying these features more precisely will help such measurements advance our ability to engineer antibody-medicated protection.

Duchenne muscular dystrophy (DMD) is a debilitating disease that leads to progressive weakening of the muscles, affecting 1 in 5700 males. This X-linked recessive disease is caused by loss of function mutations in the DMD gene that encodes for dystrophin. Dystrophin connects the cytoskeleton to the extracellular matrix, and the loss of this protein leads increased susceptibility to muscle contraction induced sarcolemma damage, which contributes to cardiomyopathy over time. Previous research has determined that transgenic overexpression of sarcospan (SSPN), a small transmembrane protein, improved skeletal muscle pathology and cardiac physiology in the mdx model, a common mouse model for DMD. Overexpression of SSPN improved cardiomyocyte membrane stability and reduced fibrosis. To identify the molecular mechanisms underlying SSPN’s cardioprotective effect, we performed proteomics analysis on 1-year old wild-type, mdx, and mdx:SSPN-TG hearts. Proteomics data showed upregulation of ECM proteins in mdx. Mdx:SSPN-TG hearts present a distinct molecular signature, characterized by reduction of ECM proteins. To validate the proteomics data, we performed immunofluorescence analysis and found that proteomics data were not highly correlative for ECM proteins likely due to the differences in detection methods, which suggests that proteomics may be more sensitive at capturing differences from proteins localized to the ECM. Furthermore, the proteomics data support the reduced fibrosis observed with transgenic expression of SSPN and suggest that restoration of ECM proteins significantly contributes to the cardioprotective effect by SSPN.

Toxoplasma gondii is a member of the phylum Apicomplexa, comprised of obligate intracellular parasites of medical and veterinary importance, such as P. falciparum and N. caninum. Toxoplasma can inhabit mammalian hosts in its asexual stages and undergoes sexual development in Felidae. More than 40 million people in the United States are carriers of the parasite's infective bradyzoite stage. Infection in immunocompromised individuals and pregnant women promotes bradyzoite differentiation into rapidly replicating tachyzoites - causing fatal encephalitis, blindness, fetal brain abnormalities, and abortion. Existing drug treatments are restricted to limiting acute disease, emphasizing the importance of studying T. gondii's cellular biology. Our study examined the role of aurora kinases, TgArk2 and TgArk3, in Toxoplasma replication. We hypothesized that TgArk2 compensates for the loss of TgArk3 by altering its typical localization in the mitotic spindle and intranuclear mitotic structures. To address this inquiry, we created two constructs to endogenously tag TgArk2 at its C-terminus in both wild-type and ΔTgArk3 parasites, followed by selection drug markers. Tagged parasites were cloned using limiting dilution and visualized via immunofluorescence assays (IFA) to assess TgArk2 localization. Additionally, we hypothesized that the absence of both TgArk2 and TgArk3 would result in abnormal parasite cell division and morphological defects compared to wild-type and ΔTgArk3 parasites. Thus, we utilized CRISPR/Cas9 and an auxin-inducible degron conditional knockdown approach, followed by IFAs to visualize morphology. These studies aim to reveal a deeper understanding of the role of aurora kinases in endodyogeny, providing clues toward drug development targeting parasite-specific functions in apicomplexans.

Abnormalities in human cortical development are associated with a wide range of neurological disorders and diseases. However, the complete orchestra of signaling pathways and cellular processes that give rise to proper development are not yet elucidated. Cortical development is contingent upon both intrinsic and extrinsic signals that cue cellular processes and neurobiological programs. At present, the role of the endocrine system as an extrinsic signaller in cortical development is poorly understood. Both gonadal hormones and thyroidal hormones have been shown to influence cell viability and metabolic remodeling, and thyroidal hormones have additionally been found to influence neuronal adhesion, migration, and patterning in animal models and cell cultures. Here, we investigate the influence of estrogen, progesterone, and thyroid hormone (T4) on metabolic properties and cell fate specification in the cortical organoid model. Cortical organoids chronically treated in either high (100nM) or low (30nM) concentrations of estradiol (E2), progesterone (P4), or thyroxine (T4) were harvested at their week 9 and 5 timepoints. Through Seahorse Assays and qPCR for mitochondrial-related genes we expect to see evidence of improved oxidative phosphorylation and downregulated glycolysis. Through immunohistochemistry, we expect to see an increase in mature cell type populations. If these phenotypes are observed, this will illuminate an additional role of the endocrine system in cortical development. This could translate to improving the cortical organoid system by providing a necessary extrinsic signal, and better understanding of how hormonal abnormalities in pregnancy could influence the developing fetal brain.