Utilizing a quality of life tool to examine the presence of fatigue in subjects with diabetes mellitus.

Introduction: The prevalence of fatigue in patients with diabetes mellitus (DM) can be as high as 50 %. Physical, mental, and psychosocial components of fatigue negatively impact quality of life (QOL), morbidity and mortality. Several tools have been developed to address fatigue, but none specifically for measuring fatigue in DM. The aim of this study was to assess the impact of diabetes and neuropathy on fatigue using the Norfolk QOL-Fatigue (QOL-F) survey. Methods: 605 adult participants from [Anonymous] were recruited (400 subjects with type 1 or type 2 DM and 205 subjects without diabetes (controls)). All subjects completed the Norfolk QOL-F. Demographics, weight, BMI, and duration of diabetes were obtained. The Norfolk QOL-F, a 35-item validated questionnaire, assesses five domains: subjective fatigue, physical and cognitive fatigue, reduced activities, impaired activities of daily living, and depression. Results: Subjects with DM reported significantly higher fatigue total scores (52.63vs33.89, p < 0.0001) and in all five domains when compared to controls. Patients with DM with neuropathy were significantly more fatigued than those without (59.72vs27.83, p < 0.0001). Fatigue scores in patients with DM without neuropathy were similar to controls (27.83vs33.89, p = NS). In multivariate analysis, age, gender, and presence of neuropathy significantly impacted fatigue scores. Conclusions: The Norfolk QOL-F questionnaire can potentially identify the impact of chronic diseases such as diabetes on fatigue. Assessing the different components of fatigue is important for clinicians in improving disease management and outcomes. Further investigations are needed to confirm these observations in specific cohorts with other comorbidities.

Development of donor specific antibodies after SARS-CoV-2 vaccination in kidney and heart transplant recipients.

This study examined the development of new or changes in donor specific antibodies (DSA) mean-fluorescence intensity (MFI) after SARS-CoV-2 vaccination in 100 kidney and 50 heart transplant recipients. The study was performed when the Center for Disease Control and Prevention (CDC) recommended two doses of Pfizer/BioNTech [BNT162b2] and Moderna [mRNA-1273 SARS-CoV-2] vaccine or 1 dose Johnson & Johnson/Janssen [Ad26.COV2·S] vaccines for full vaccination in transplant recipients. A novel assay bead-based platform for detecting antibodies against 4 domains of the SARS-CoV-2 spike protein to determine vaccine response (SA) and one nucleocapsid protein (NC) to determine prior SARS-CoV-2 infection was utilized. These assays were performed on the multiplex, bead-based platform utilized to assay DSA levels. 61/150 patients (40.7%) had successful vaccination. 18 patients had confirmed SARS-CoV-2 infection based on positive NC assay or previous Covid-19 oropharyngeal swab. 138 patients had no DSA prior to vaccination but 3 heart recipients developed new DSA's. Among 12 patients with known DSA prior to vaccination, 4 developed new DSA's or increased MFI. All 7 patients with new or increased DSA had stable graft function without rejection and had no changes in immunosuppression. All 8 patients with stable post vaccine DSA had stable graft function and immunosuppression was not changed. The presence of DSA before vaccination was associated with subsequent development of increased MFI or new DSA's (p = 0.001). There was no association between pre-vaccine DSA and positive vaccine response (NS). There was no association with successful vaccination or prior SARS-CoV-2 infection and DSA changes (NS).

Simulation of elution profiles in liquid chromatography-I: Gradient elution conditions, and with mismatched injection and mobile phase solvents.

High-performance liquid chromatography (HPLC) simulators are effective method development tools. The goal of the present work was to design and implement a simple algorithm for simulation of liquid chromatographic separations that allows for characterization of the effect of injection solvent mismatch and injection solvent volume overload. The simulations yield full analyte profiles during solute migration and at elution, which enable a thorough physical understanding of the effects of method variables on chromatographic performance. The Craig counter-current distribution model (the plate model) is used as the basis for simulation, where a local retention factor is assigned for each spatial and temporal element within the simulation. The algorithm, which is an adaptation of an approach originally described by Czok and Guiochon (Ref. [10]), is sufficiently flexible to allow the use of either linear (e.g., Linear Solvent Strength Theory) or non-linear models of solute retention (e.g., Neue-Kuss (Ref. [36])). In this study, both types of models were used, one for simulating separations of a homologous series of alkylbenzenes, and the other for separations of selected amphetamines. The simulation program was validated first by comparison of simulated retention times and peak widths for five amphetamines to predictions obtained using linear solvent strength (LSS) theory, and to results from experimental separations of these compounds. The simulated retention times for the amphetamines agreed within 0.02% and 2.5% compared to theory and experiment, respectively. Secondly, the program was evaluated for simulating the case where there is a compositional mismatch between the mobile phase at the column inlet and the injection solvent (i.e., the sample matrix). This work involved alkylbenzenes, and retention time and peak width predictions from simulations were within 1.5 and 6.0% of experimental values, respectively, even without correction for extra-column dispersion. The issues of sample/eluent solvent mismatch and solvent volume overload are especially important when considering the challenges of transferring eluent from the first to the second dimension in comprehensive two-dimensional liquid chromatography.