(Neuro-)endocrinology of epithelial hair follicle stem cells

The hair follicle is a repository of different types of somatic stem cells. However, even though the hair follicle is both a prominent target organ and a potent, non-classical site of production and/or metabolism of numerous polypetide- and steroid hormones, neuropeptides, neurotransmitters and neurotrophins, the (neuro-)endocrine controls of hair follicle epithelial stem cell (HFeSC) biology remain to be systematically explored. Focussing on HFeSCs, we attempt here to offer a "roadmap through terra incognita" by listing key open questions, by exploring endocrinologically relevant HFeSC gene profiling and mouse genomics data, and by sketching several clinically relevant pathways via which systemic and/or locally generated (neuro-)endocrine signals might impact on HFeSC. Exemplarily, we discuss, e.g. the potential roles of glucocorticoid and vitamin D receptors, the hairless gene product, thymic hormones, bone morphogenic proteins (BMPs) and their antagonists, and Skg-3 in HFeSC biology. Furthermore, we elaborate on the potential role of nerve growth factor (NGF) and substance P-dependent neurogenic inflammation in HFeSC damage, and explore how neuroendocrine signals may influence the balance between maintenance and destruction of hair follicle immune privilege, which protects these stem cells and their progeny. These considerations call for a concerted research effort to dissect the (neuro-)endocrinology of HFeSCs much more systematically than before.     

T cell response to the cytomegalovirus major capsid protein (UL86) is dominated by helper cells with a large polyfunctional component and diverse epitope recognition

T cells are crucial in controlling cytomegalovirus (CMV) infection. The CMV major capsid protein (UL86) is frequently recognized by these cells, but the nature of this response has not been explored in detail. In this study, healthy CMV-exposed individuals were examined, and ex vivo peptide stimulation of peripheral blood mononuclear cells and flow-cytometry were used to obtain data, including response prevalence, magnitude, functional profiles, and recognized epitopes. Of 24 subjects, 19 (79%) had a UL86-specific CD4 T cell response rate between 0.03% and 1.4%. This group of individuals exhibited a similar percentage of polyfunctional T cells in their UL86-specific and pp65-specific responses. A total of 8 CD4 T cell epitopes were identified. In contrast, CD8 T cell responses to UL86 were rare and small. UL86 is of interest for monitoring the response to CMV.     

Closely related antibody receptors exploit fundamentally different strategies for steroid recognition

Molecular recognition by the adaptive immune system relies on specific high-affinity antibody receptors that are generated from a restricted set of starting sequences through homologous recombination and somatic mutation. The steroid binding antibody DB3 and the catalytic Diels–Alderase antibody 1E9 derive from the same germ line sequences but exhibit very distinct specificities and functions. However, mutation of only two of the 36 sequence differences in the variable domains, Leu^H47Trp and Arg^H100Trp, converts 1E9 into a high-affinity steroid receptor with a ligand recognition profile similar to DB3. To understand how these changes switch binding specificity and function, we determined the crystal structures of the 1E9 Leu^H47Trp/Arg^H100Trp double mutant (1E9dm) as an unliganded Fab at 2.05 Å resolution and in complex with two configurationally distinct steroids at 2.40 and 2.85 Å. Surprisingly, despite the functional mimicry of DB3, 1E9dm employs a distinct steroid binding mechanism. Extensive structural rearrangements occur in the combining site, where residue H47 acts as a specificity switch and H100 adapts to different ligands. Unlike DB3, 1E9dm does not use alternative binding pockets or different sets of hydrogen-bonding interactions to bind configurationally distinct steroids. Rather, the different steroids are inserted more deeply into the 1E9dm combining site, creating more hydrophobic contacts that energetically compensate for the lack of hydrogen bonds. These findings demonstrate how subtle mutations within an existing molecular scaffold can dramatically modulate the function of immune receptors by inducing unanticipated, but compensating, mechanisms of ligand interaction.     

Accurate estimate of pancreatic T2* values: how to deal with fat infiltration

Purpose

We examined different approaches aimed to deal with the signal fluctuation of pancreatic T2* values due to fat infiltration in order to obtain accurate estimates of iron overload.

Methods

Pancreatic T2* values were assessed in 20 patients (13 females, 37.24 ± 9.12 years) enrolled in the Myocardial Iron Overload in Thalassemia network without and with the application of fat suppression-FS (T2*-NoFS and T2*-FS). T2* values were assessed in three different ways: (1) from the immediate fit (original T2*); (2) discarding the echoes until the achievement of a good visual concordance between the signal and the model (final_vis T2*); (3) eliminating the echoes until the achievement of a fitting error (known) <5% (final_thres T2*).

Results

For the T2*-NoFS sequence the original T2* values were significantly higher than the final_vis T2* values (difference:4.8 ± 6.1 ms; P < 0.0001) and the final_thres T2* values (difference:4.3 ± 6.1 ms; P = 0.006). For the T2*-FS sequence the original T2* values were comparable to final_vis and final_thres T2* values. The original T2*-FS values were significantly different from the original T2*-NoFS values. The final_vis T2*-FS values were comparable to the final_vis T2*-NoFS values and the final_thresh T2*-FS values were comparable to the final_thresh T2*-NoFS values. For both T2*-FS and T2*-NoFS sequences, the final_thres T2* values were not significantly different from the final_vis T2* values and no bias was present.

Conclusions

In the clinical practice, an accurate pancreatic iron overload assessment should be done by applying FS and, when needed, by discarding the TEs until the fitting error goes below 5%.