Investigating changes in blood-cerebrospinal fluid barrier function in a rat model of chronic hypertension using non-invasive magnetic resonance imaging

Chronic hypertension is a major risk factor for the development of neurodegenerative disease, yet the etiology of hypertension-driven neurodegeneration remains poorly understood. Forming a unique interface between the systemic circulation and the brain, the blood-cerebrospinal fluid barrier (BCSFB) at the choroid plexus (CP) has been proposed as a key site of vulnerability to hypertension that may initiate downstream neurodegenerative processes. However, our ability to understand BCSFB’s role in pathological processes has, to date, been restricted by a lack of non-invasive functional measurement techniques. In this work, we apply a novel Blood-Cerebrospinal Fluid Barrier Arterial Spin Labeling (BCSFB-ASL) Magnetic resonance imaging (MRI) approach with the aim of detecting possible derangement of BCSFB function in the Spontaneous Hypertensive Rat (SHR) model using a non-invasive, translational technique. SHRs displayed a 36% reduction in BCSFB-mediated labeled arterial water delivery into ventricular cerebrospinal fluid (CSF), relative to normotensive controls, indicative of down-regulated choroid plexus function. This was concomitant with additional changes in brain fluid biomarkers, namely ventriculomegaly and changes in CSF composition, as measured by T1 lengthening. However, cortical cerebral blood flow (CBF) measurements, an imaging biomarker of cerebrovascular health, revealed no measurable change between the groups. Here, we provide the first demonstration of BCSFB-ASL in the rat brain, enabling non-invasive assessment of BCSFB function in healthy and hypertensive rats. Our data highlights the potential for BCSFB-ASL to serve as a sensitive early biomarker for hypertension-driven neurodegeneration, in addition to investigating the mechanisms relating hypertension to neurodegenerative outcomes

Thermodynamic Additivity of Sequence Variations: An Algorithm for Creating High Affinity Peptides Without Large Libraries or Structural Information

BACKGROUND: There is a significant need for affinity reagents with high target affinity/specificity that can be developed rapidly and inexpensively. Existing affinity reagent development approaches, including protein mutagenesis, directed evolution, and fragment-based design utilize large libraries and/or require structural information thereby adding time and expense. Until now, no systematic approach to affinity reagent development existed that could produce nanomolar affinity from small chemically synthesized peptide libraries without the aid of structural information. METHODOLOGY/PRINCIPAL FINDINGS: Based on the principle of additivity, we have developed an algorithm for generating high affinity peptide ligands. In this algorithm, point-variations in a lead sequence are screened and combined in a systematic manner to achieve additive binding energies. To demonstrate this approach, low-affinity lead peptides for multiple protein targets were identified from sparse random sequence space and optimized to high affinity in just two chemical steps. In one example, a TNF-α binding peptide with K(d) = 90 nM and high target specificity was generated. The changes in binding energy associated with each variation were generally additive upon combining variations, validating the basis of the algorithm. Interestingly, cooperativity between point-variations was not observed, and in a few specific cases, combinations were less than energetically additive. CONCLUSIONS/SIGNIFICANCE: By using this additivity algorithm, peptide ligands with high affinity for protein targets were generated. With this algorithm, one of the highest affinity TNF-α binding peptides reported to date was produced. Most importantly, high affinity was achieved from small, chemically-synthesized libraries without the need for structural information at any time during the process. This is significantly different than protein mutagenesis, directed evolution, or fragment-based design approaches, which rely on large libraries and/or structural guidance. With this algorithm, high affinity/specificity peptide ligands can be developed rapidly, inexpensively, and in an entirely chemical manner

Resilience Among Women with HIV: Impact of Silencing the Self and Socioeconomic Factors

In the U.S., women account for over a quarter of the approximately 50,000 annual new HIV diagnoses and face intersecting and ubiquitous adversities including gender inequities, sexism, poverty, violence, and limited access to quality education and employment. Women are also subjected to prescribed gender roles such as silencing their needs in interpersonal relationships, which may lessen their ability to be resilient and function adaptively following adversity. Previous studies have often highlighted the struggles encountered by women with HIV without focusing on their strengths. The present cross-sectional study investigated the relationships of silencing the self and socioeconomic factors (education, employment, and income) with resilience in a sample of women with HIV. The sample consisted of 85 women with HIV, diverse ethnic/racial groups, aged 24 – 65 enrolled at the Chicago site of the Women’s Interagency HIV Study in the midwestern region of the United States. Measures included the Connor-Davidson Resilience Scale -10 item and the Silencing the Self Scale (STSS). Participants showed high levels of resilience. Women with lower scores on the STSS (lower self-silencing) reported significantly higher resilience compared to women with higher STSS scores. Although employment significantly related to higher resilience, silencing the self tended to predict resilience over and above the contributions of employment, income, and education. Results suggest that intervention and prevention efforts aimed at decreasing silencing the self and increasing employment opportunities may improve resilience

Integrated analysis of anatomical and electrophysiological human intracranial data

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