Deep phenotyping of post-infectious myalgic encephalomyelitis/chronic fatigue syndrome

Post-infectious myalgic encephalomyelitis/chronic fatigue syndrome (PI-ME/CFS) is a disabling disorder, yet the clinical phenotype is poorly defined, the pathophysiology is unknown, and no disease-modifying treatments are available. We used rigorous criteria to recruit PI-ME/CFS participants with matched controls to conduct deep phenotyping. Among the many physical and cognitive complaints, one defining feature of PI-ME/CFS was an alteration of effort preference, rather than physical or central fatigue, due to dysfunction of integrative brain regions potentially associated with central catechol pathway dysregulation, with consequences on autonomic functioning and physical conditioning. Immune profiling suggested chronic antigenic stimulation with increase in naïve and decrease in switched memory B-cells. Alterations in gene expression profiles of peripheral blood mononuclear cells and metabolic pathways were consistent with cellular phenotypic studies and demonstrated differences according to sex. Together these clinical abnormalities and biomarker differences provide unique insight into the underlying pathophysiology of PI-ME/CFS, which may guide future intervention.

Mixed methods system for the assessment of post-exertional malaise in myalgic encephalomyelitis/chronic fatigue syndrome: an exploratory study

Background

A central feature of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is post-exertional malaise (PEM), which is an acute worsening of symptoms after a physical, emotional and/or mental exertion. Dynamic measures of PEM have historically included scaled questionnaires, which have not been validated in ME/CFS. To enhance our understanding of PEM and how best to measure it, we conducted semistructured qualitative interviews (QIs) at the same intervals as visual analogue scale (VAS) measures after a cardiopulmonary exercise test (CPET).

Methods

Ten ME/CFS and nine healthy volunteers participated in a CPET. For each volunteer, PEM symptom VAS (12 symptoms) and semistructured QIs were administered at six timepoints over 72 hours before and after a single CPET. QI data were used to plot the severity of PEM at each time point and identify the self-described most bothersome symptom for each ME/CFS volunteer. Performance of QI and VAS data was compared with each other using Spearman correlations.

Results

Each ME/CFS volunteer had a unique PEM experience, with differences noted in the onset, severity, trajectory over time and most bothersome symptom. No healthy volunteers experienced PEM. QI and VAS fatigue data corresponded well an hour prior to exercise (pre-CPET, r=0.7) but poorly at peak PEM (r=0.28) and with the change from pre-CPET to peak (r=0.20). When the most bothersome symptom identified from QIs was used, these correlations improved (r=0.0.77, 0.42. and 0.54, respectively) and reduced the observed VAS scale ceiling effects.

Conclusion

In this exploratory study, QIs were able to capture changes in PEM severity and symptom quality over time, even when VAS scales failed to do so. Measurement of PEM can be improved by using a quantitative-qualitative mixed model approach.

A Mixed Methods System for the Assessment of Post Exertional Malaise in Encephalomyelitis/Chronic Fatigue Syndrome

Background

A central feature of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is post exertional malaise (PEM), which is an acute worsening of symptoms after a physical, emotional and/or mental exertion. PEM is also a feature of Long COVID. Dynamic measures of PEM have historically included scaled questionnaires which have not been validated in ME/CFS. To enhance our understanding of PEM and how best to measure it, we conducted semi-structured qualitative interviews (QIs) at the same intervals as Visual Analog Scale (VAS) measures after a Cardiopulmonary Exercise Test (CPET).

Methods

Ten ME/CFS and nine healthy volunteers participated in a CPET. For each participant, PEM symptom VAS (7 symptoms) and semi-structured QIs were administered at six timepoints over 72 hours before and after a single CPET. QI data were used to plot the severity of PEM at each time point and identify the self-described most bothersome symptom for each patient. QI data were used to determine the symptom trajectory and peak of PEM. Performance of QI and VAS data were compared to each other using Spearman correlations.

Results

QIs documented that each ME/CFS volunteer had a unique PEM experience, with differences noted in the onset, severity, trajectory over time, and most bothersome symptom. No healthy volunteers experienced PEM. Scaled QI data were able to identify PEM peaks and trajectories, even when VAS scales were unable to do so due to known ceiling and floor effects. QI and VAS fatigue data corresponded well prior to exercise (baseline, r=0.7) but poorly at peak PEM (r=0.28) and with the change from baseline to peak (r=0.20). When the most bothersome symptom identified from QIs was used, these correlations improved (r=.0.77, 0.42. and 0.54 respectively) and reduced the observed VAS scale ceiling and floor effects.

Conclusion

QIs were able to capture changes in PEM severity and symptom quality over time in all the ME/CFS volunteers, even when VAS scales failed to do so. Information collected from QIs also improved the performance of VAS. Measurement of PEM can be improved by using a quantitative-qualitative mixed model approach.

Tuning the structure and solubility of nanojars by peripheral ligand substitution, leading to unprecedented liquid-liquid extraction of the carbonate ion from water into aliphatic solvents

Nanojars, a novel class of neutral anion-incarcerating agents of the general formula [Cu(II)(OH)(pz)]n (Cun; n = 27-31, pz = pyrazolate anion), efficiently sequester various oxoanions with large hydration energies from water. In this work, we explore whether substituents on the pyrazole ligand interfere with nanojar formation, and whether appropriate substituents could be employed to tune the solubility of nanojars in solvents of interest, such as long-chain aliphatic hydrocarbons (solvent of choice for large-scale liquid-liquid extraction processes) and water. To this end, we conducted a comprehensive study using 40 different pyrazole ligands, with one, two or three substituents in their 3-, 4- and 5-positions. The corresponding nanojars are characterized by single-crystal X-ray diffraction and/or electrospray-ionization mass spectrometry (ESI-MS). The results show that Cun-nanojars with various substituents in the pyrazole 4-position, including long chains, phenyl and CF3 groups, can be obtained. Straight chains are also tolerated at the pyrazole 3-position, and favor the Cu30-nanojar. Homoleptic nanojars, however, could not be obtained with phenyl or CF3 groups. Nevertheless, if used in mixture with the parent non-substituted pyrazole, sterically hindered pyrazoles do form heteroleptic nanojars. With 3,5-disubstituted pyrazoles, only heteroleptic nanojars are accessible. The crystal structure of novel nanojars (Bu4N)2[CO3⊂{Cu30(OH)30(3,5-Me2pz)y(pz)30-y}] (y = 14 and 15) is presented. We find that in contrast to the parent nanojar, which is insoluble in aliphatic solvents and water, nanojars with alkyl substituents are soluble in saturated hydrocarbon solvents, whereas nanojars based on novel pyrazoles, functionalized with oligoether chains, are readily soluble in water. Liquid-liquid extraction of carbonate from water under basic pH is presented for the first time.