Biological treatment for bullous pemphigoid

BackgroundBullous pemphigoid (BP) is the most common autoimmune subepidermal bullous disease. Topical or systemic corticosteroids are often used as the first-line treatment. However, long-term corticosteroid use may lead to significant side effects. Therefore, various adjuvant immunosuppressant therapies are used as steroid-sparing agents, with accumulating reports of biological treatments for severely recalcitrant BP.ObjectiveTo describe the clinical and immunological features of a series of patients with recalcitrant BP treated with immunobiological therapies. To assess the efficacy and safety of their therapies.MethodsPatients receiving biological treatment for BP from two centers were assessed. Here, we described the clinical, immunopathological, and immunofluorescence findings of adult patients with BP and analyzed the clinical response and adverse events associated with various biological therapies.ResultsWe identified nine eligible patients treated with rituximab (seven), omalizumab (three), or dupilumab (one). The mean age at diagnosis was 60.4 years, the average BP duration before biologic initiation was 1.9 years, and the average previous treatment failure was 2.11 therapies. The mean follow-up period from the first biological treatment to the last visit was 29.3 months. Satisfactory response, defined as clinical improvement, was achieved in 78% (7) of the patients, and total BP clearance was achieved in 55% (5) of the patients at the last follow-up visit. Additional rituximab courses improved the disease outcomes. No adverse events were reported.ConclusionsEfficient and safe novel therapies can be considered in recalcitrant steroid-dependent BP non-responsive to conventional immunosuppressant therapies

Dendritic tree extraction from noisy maximum intensity projection images in C. elegans

Background: Maximum Intensity Projections (MIP) of neuronal dendritic trees obtained from confocal microscopy are frequently used to study the relationship between tree morphology and mechanosensory function in the model organism C. elegans. Extracting dendritic trees from noisy images remains however a strenuous process that has traditionally relied on manual approaches. Here, we focus on automated and reliable 2D segmentations of dendritic trees following a statistical learning framework. Methods: Our dendritic tree extraction (DTE) method uses small amounts of labelled training data on MIPs to learn noise models of texture-based features from the responses of tree structures and image background. Our strategy lies in evaluating statistical models of noise that account for both the variability generated from the imaging process and from the aggregation of information in the MIP images. These noisy models are then used within a probabilistic, or Bayesian framework to provide a coarse 2D dendritic tree segmentation. Finally, some post-processing is applied to refine the segmentations and provide skeletonized trees using a morphological thinning process. Results: Following a Leave-One-Out Cross Validation (LOOCV) method for an MIP database with available “ground truth” images, we demonstrate that our approach provides significant improvements in tree-structure segmentations over traditional intensity-based methods. Improvements for MIPs under various imaging conditions are both qualitative and quantitative, as measured from Receiver Operator Characteristic (ROC) curves and the yield and error rates in the final segmentations. In a final step, we demonstrate our DTE approach on previously unseen MIP samples including the extraction of skeletonized structures, and compare our method to a state-of-the art dendritic tree tracing software. Conclusions: Overall, our DTE method allows for robust dendritic tree segmentations in noisy MIPs, outperforming traditional intensity-based methods. Such approach provides a useable segmentation framework, ultimately delivering a speed-up for dendritic tree identification on the user end and a reliable first step towards further morphological characterizations of tree arborization

DNAJB6 mutants display toxic gain of function through unregulated interaction with Hsp70 chaperones

Abstract Molecular chaperones are essential cellular components that aid in protein folding and preventing the abnormal aggregation of disease-associated proteins. Mutations in one such chaperone, DNAJB6, were identified in patients with LGMDD1, a dominant autosomal disorder characterized by myofibrillar degeneration and accumulations of aggregated protein within myocytes. The molecular mechanisms through which such mutations cause this dysfunction, however, are not well understood. Here we employ a combination of solution NMR and biochemical assays to investigate the structural and functional changes in LGMDD1 mutants of DNAJB6. Surprisingly, we find that DNAJB6 disease mutants show no reduction in their aggregation-prevention activity in vitro, and instead differ structurally from the WT protein, affecting their interaction with Hsp70 chaperones. While WT DNAJB6 contains a helical element regulating its ability to bind and activate Hsp70, in LGMDD1 disease mutants this regulation is disrupted. These variants can thus recruit and hyperactivate Hsp70 chaperones in an unregulated manner, depleting Hsp70 levels in myocytes, and resulting in the disruption of proteostasis. Interfering with DNAJB6-Hsp70 binding, however, reverses the disease phenotype, suggesting future therapeutic avenues for LGMDD1

FITC-Dextran Release from Cell-Embedded Fibrin Hydrogels

Fibrin hydrogel is a central biological material in tissue engineering and drug delivery applications. As such, fibrin is typically combined with cells and biomolecules targeted to the regenerated tissue. Previous studies have analyzed the release of different molecules from fibrin hydrogels; however, the effect of embedded cells on the release profile has yet to be quantitatively explored. This study focused on the release of Fluorescein isothiocyanate (FITC)-dextran (FD) 250 kDa from fibrin hydrogels, populated with different concentrations of fibroblast or endothelial cells, during a 48-h observation period. The addition of cells to fibrin gels decreased the overall release by a small percentage (by 7–15% for fibroblasts and 6–8% for endothelial cells) relative to acellular gels. The release profile was shown to be modulated by various cellular activities, including gel degradation and physical obstruction to diffusion. Cell-generated forces and matrix deformation (i.e., densification and fiber alignment) were not found to significantly influence the release profiles. This knowledge is expected to improve fibrin integration in tissue engineering and drug delivery applications by enabling predictions and ways to modulate the release profiles of various biomolecules

FITC-Dextran Release from Cell-Embedded Fibrin Hydrogels

Fibrin hydrogel is a central biological material in tissue engineering and drug delivery applications. As such, fibrin is typically combined with cells and biomolecules targeted to the regenerated tissue. Previous studies have analyzed the release of different molecules from fibrin hydrogels; however, the effect of embedded cells on the release profile has yet to be quantitatively explored. This study focused on the release of Fluorescein isothiocyanate (FITC)-dextran (FD) 250 kDa from fibrin hydrogels, populated with different concentrations of fibroblast or endothelial cells, during a 48-h observation period. The addition of cells to fibrin gels decreased the overall release by a small percentage (by 7–15% for fibroblasts and 6–8% for endothelial cells) relative to acellular gels. The release profile was shown to be modulated by various cellular activities, including gel degradation and physical obstruction to diffusion. Cell-generated forces and matrix deformation (i.e., densification and fiber alignment) were not found to significantly influence the release profiles. This knowledge is expected to improve fibrin integration in tissue engineering and drug delivery applications by enabling predictions and ways to modulate the release profiles of various biomolecules

The Glycemic Response to Infant Formulas: A Randomized Clinical Trial

Background: Commercial infant formulas attempt to imitate human milk’s unique composition. However, lactose-free and milk protein-free formulas are often chosen due to medical reasons or personal preferences. The aim of this study was to determine the glycemic and insulinemic indices of a variety of infant formulas. Methods: We conducted a three-arm, randomized, double-blind, crossover study. Participants were 25–40-year-old healthy adults. Three commercial infant formulas (cow’s milk protein-based [“standard”], soy protein-based, and lactose-free) were randomly given to each participant. Glycemic and insulinemic responses were determined and compared between the three formulas. Results: Twenty subjects were enrolled (11 females/9 males, mean age 32.8 ± 2.9 years). No significant difference was found in the glycemic index between the three formulas (21.5, 29.1, and 21.5 for the standard, soy protein-based, and lactose-free formulas, respectively, p = 0.21). However, maximal glucose levels were significantly higher for the soy protein-based formula compared to both the standard and lactose-free formulas (111.5 compared to 101.8 and 105.8 mg/dL, respectively, p = 0.001). Conclusion: Cow’s milk protein-based, soy protein-based, and lactose-free formulas have a similar glycemic index. However, soy protein-based formula produced a significantly higher increase in postprandial glucose levels. The implication and biological significance of these results have yet to be determined

Integration of spatially opposing cues by a single interneuron guides decision-making in C. elegans

Summary: The capacity of animals to respond to hazardous stimuli in their surroundings is crucial for their survival. In mammals, complex evaluations of the environment require large numbers and different subtypes of neurons. The nematode C. elegans avoids hazardous chemicals they encounter by reversing their direction of movement. How does the worms’ compact nervous system process the spatial information and direct motion change? We show here that a single interneuron, AVA, receives glutamatergic excitatory and inhibitory signals from head and tail sensory neurons, respectively. AVA integrates the spatially distinct and opposing cues, whose output instructs the animal’s behavioral decision. We further find that the differential activation of AVA stems from distinct localization of inhibitory and excitatory glutamate-gated receptors along AVA’s process and from different threshold sensitivities of the sensory neurons. Our results thus uncover a cellular mechanism that mediates spatial computation of nociceptive cues for efficient decision-making in C. elegans

Progesterone Increases Bifidobacterium Relative Abundance during Late Pregnancy

Summary: Gestation is accompanied by alterations in the microbial repertoire; however, the mechanisms driving these changes are unknown. Here, we demonstrate a dramatic shift in the gut microbial composition of women and mice during late pregnancy, including an increase in the relative abundance of Bifidobacterium. Using in-vivo-transplanted pellets, we found that progesterone, the principal gestation hormone, affects the microbial community. The effect of progesterone on the richness of several bacteria species, including Bifidobacterium, was also demonstrated in vitro, indicating a direct effect. Altogether, our results delineate a model in which progesterone promotes Bifidobacterium growth during late pregnancy. : Nuriel-Ohayon et al. demonstrate a dramatic shift in the gut microbial composition of women and mice during late pregnancy, including an increase in the relative abundance of Bifidobacterium. Using in vitro and in vivo experiments, they show that supplementation of progesterone affects the microbial communities, including increasing the relative abundance of Bifidobacterium. Keywords: progesterone, Bifidobacterium, pregnancy, gut microbiota, 16S rRNA, microbiom