Predictors of depression in older adults with multiple sclerosis

Canada’s growing population of older people with MS (PwMS) has warranted a closer look into factors associated with depression that may interfere with healthy aging. At the same time, researchers, clinicians, and medical professionals treating PwMS with mood disorders have spoken about the difficulty they face when having to determine a diagnosis of depression in this population. This difficulty arises because both MS and depression share various psychological and neurological symptoms (e.g., fatigue, pain, sleep difficulties, psychomotor retardation, and cognitive difficulties). It is also found that these overlapped symptoms vary when completing a self-report measure of depression, versus when medically diagnosed by a psychiatrist. As such, we aim to investigate the personal and disease-related factors that are associated with self-reported depressive symptoms and medically diagnosed depression (i.e. depression diagnosed by a medical professional). Following this, we aim to determine the risk factors for depression in older PwMS. This study used secondary data collected from the original study, the Canadian survey of health, lifestyle, and aging with multiple sclerosis. Data of the original study was collected from 743 Canadians (> 55 years of age and living with MS for >20 years). In this present study, presence of self-reported depressive symptoms was defined as a score of ≥ 8 on the depression component of the Hospital Anxiety and Depression Scale (HADS-D). Presence of medically diagnosed depression was determined by the item that asked participants if they have received a diagnosis of depression by their medical professional. Logistic regression was used to identify variables that predicted depression. Self-reported depressive symptoms were found in 30.5% of the population, while medically diagnosed depression was found in 25.7%. 11.7% of PwMS had both self-identified depressive symptoms and were diagnosed with depression by their medical professional. Low social support, high perceived disability, and additional comorbid physical conditions were independent predictors of depression in older PwMS in our cohort. Depression is prevalent in older PwMS. Clinicians should be cognizant of the overlap of symptoms between MS and depression and should employ possible ways to minimize over-diagnosing or underdiagnosing depression in this population. Identifying risk factors for depression is imperative because at-risk individuals may be thoroughly assessed for depression and will be able to receive treatment more promptly

Interaction of Virstatin with Human Serum Albumin: Spectroscopic Analysis and Molecular Modeling

Virstatin is a small molecule that inhibits Vibrio cholerae virulence regulation, the causative agent for cholera. Here we report the interaction of virstatin with human serum albumin (HSA) using various biophysical methods. The drug binding was monitored using different isomeric forms of HSA (N form ∼pH 7.2, B form ∼pH 9.0 and F form ∼pH 3.5) by absorption and fluorescence spectroscopy. There is a considerable quenching of the intrinsic fluorescence of HSA on binding the drug. The distance (r) between donor (Trp214 in HSA) and acceptor (virstatin), obtained from Forster-type fluorescence resonance energy transfer (FRET), was found to be 3.05 nm. The ITC data revealed that the binding was an enthalpy-driven process and the binding constants Ka for N and B isomers were found to be 6.09×105 M−1 and 4.47×105 M−1, respectively. The conformational changes of HSA due to the interaction with the drug were investigated from circular dichroism (CD) and Fourier Transform Infrared (FTIR) spectroscopy. For 1∶1 molar ratio of the protein and the drug the far-UV CD spectra showed an increase in α- helicity for all the conformers of HSA, and the protein is stabilized against urea and thermal unfolding. Molecular docking studies revealed possible residues involved in the protein-drug interaction and indicated that virstatin binds to Site I (subdomain IIA), also known as the warfarin binding site

Structural studies on Vibrio cholerae ToxR periplasmic and cytoplasmic domains

The transcription activator ToxR controls the expression of cholera toxin, pilus colonization factor and outer membrane protein in Vibrio cholerae. It binds to the 5'-TTTTGAT-3' tandemly repeated DNA sequence in the cholera toxin promoter region. ToxR is a membrane protein having distinct periplasmic and cytoplasmic domains. The two domains have been cloned, over-expressed and purified for structural studies. The cytoplasmic domain is more compact than the periplasmic domain. The periplasmic domain exists as dimer due to the presence of an interchain disulfide linkage, while the cytoplasmic domain is monomeric in solution implying the importance of the disulfide bond to homodimerize the native ToxR. By replacing one of the cysteines C293 with alanine, using site-directed mutagenesis, a C293A mutant was created at the periplasmic domain to elucidate the role of cysteine in dimerization of ToxR

Unpacking systemic, cascading, and compound risks: A case based analysis of Asia Pacific

The Sendai Framework for Disaster Risk Reduction aims to reduce disaster risk and loss by prioritizing activities that promote a better understanding of disaster risk. It prioritizes activities such as understanding disaster risk and its dimensions, with a focus on preventing the creation of new risks, reducing existing ones, and preparing for residual risks. The concept of systemic, cascading, and compound risks is becoming increasingly important in disaster risk management. However, there is a lack of understanding about these terms and how they overlap and differ in real-world applications. The COVID-19 pandemic has highlighted the evolving and underlying risk patterns in our interconnected society, making it crucial to bridge this gap.The paper explores the existing literature on systemic, cascading, and compound risks, using a secondary literature review and content analysis. It provides a conceptual overview of the three risks and supports the review with an analysis of 40 case studies in the Asia Pacific region. The analysis focuses on the hazards, underlying vulnerabilities, impacted systems, and the complex interconnections between them. Based on the findings, the authors provide recommendations for the management of systemic, cascading, and compound risks in the future

Fluorescence quenching spectra of bis-ANS bound HSA in absence (top) and presence (the arrow indicating curves obtained with increasing concentration) of virstatin in phosphate buffer pH 7.2; [HSA] = 7.5 µM, [bis-ANS] = 5.0 µM and [virstatin] = 0.1 to 5.0 µM (with 10 increments of 0.1 µM, followed by another 5 of 1 µM).

<p>Fluorescence quenching spectra of bis-ANS bound HSA in absence (top) and presence (the arrow indicating curves obtained with increasing concentration) of virstatin in phosphate buffer pH 7.2; [HSA] = 7.5 µM, [bis-ANS] = 5.0 µM and [virstatin] = 0.1 to 5.0 µM (with 10 increments of 0.1 µM, followed by another 5 of 1 µM).</p

ITC data for the titration of (a) the N and (b) the B forms of HSA with virstatin.

<p>Flow of heat with time during the injection of the drug and the heat evolved per mole of added drug for each injection, shown at the top and the bottom, respectively.</p

Change in accessibilities of residues at binding sites I and II on binding different ligands.

a<p>Values for warfarin binding at Site I and ibuprofen binding at Site II are from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037468#pone.0037468-Varshney1" target="_blank">[53]</a>.</p>b<p>ΔASA = ASA(isolated) – ASA(complex), where ASA is the accessible surface area of a given residue. Only values >10 Ų are reported.</p

Urea induced unfolding of (a) N, (b) B and (c) F isomers of HSA in the absence (solid symbols) and the presence (open symbols) of virstain.

<p>The spectra overlaid along with the best-fit curves assuming a two-state model. F₃₄₀ and F₃₅₀ in the y-axis correspond to the fluorescence intensities at the respective wavelengths.</p

Secondary structural content of HSA upon interaction with virstatin in different molar ratios.

<p>Data were deconvoluted using CDNN software (<a href="http://bioinformatik.biochemtech.uni-halle.de/cdnn" target="_blank">http://bioinformatik.biochemtech.uni-halle.de/cdnn</a>).</p