The protective role of small heat shock proteins in cardiac diseases: key role in atrial fibrillation

Atrial fibrillation (AF) is the most common tachyarrhythmia which is associated with increased morbidity and mortality. AF usually progresses from a self-terminating paroxysmal to persistent disease. It has been recognized that AF progression is driven by structural remodeling of cardiomyocytes, which results in electrical and contractile dysfunction of the atria. We recently showed that structural remodeling is rooted in derailment of proteostasis, i.e., homeostasis of protein production, function, and degradation. Since heat shock proteins (HSPs) play an important role in maintaining a healthy proteostasis, the role of HSPs was investigated in AF. It was found that especially small heat shock protein (HSPB) levels get exhausted in atrial tissue of patients with persistent AF and that genetic or pharmacological induction of HSPB protects against cardiomyocyte remodeling in experimental models for AF. In this review, we provide an overview of HSPBs as a potential therapeutic target for normalizing proteostasis and suppressing the substrates for AF progression in experimental and clinical AF and discuss HSP activators as a promising therapy to prevent AF onset and progression.     

A combination of cross-neutralizing antibodies synergizes to prevent SARS-CoV-2 and SARS-CoV pseudovirus infection

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Barriers to Implementing the DSM-5 Cultural Formulation Interview: A Qualitative Study

The Outline for Cultural Formulation (OCF) in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) marked an attempt to apply anthropological concepts within psychiatry. The OCF has been criticized for not providing guidelines to clinicians. The DSM-5 Cultural Issues Subgroup has since converted the OCF into the Cultural Formulation Interview (CFI) for use by any clinician with any patient in any clinical setting. This paper presents perceived barriers to CFI implementation in clinical practice reported by patients (n = 32) and clinicians (n = 7) at the New York site within the DSM-5 international field trial. We used an implementation fidelity paradigm to code debriefing interviews after each CFI session through deductive content analysis. The most frequent patient threats were lack of differentiation from other treatments, lack of buy-in, ambiguity of design, over-standardization of the CFI, and severity of illness. The most frequent clinician threats were lack of conceptual relevance between intervention and problem, drift from the format, repetition, severity of patient illness, and lack of clinician buy-in. The Subgroup has revised the CFI based on these barriers for final publication in DSM-5. Our findings expand knowledge on the cultural formulation by reporting the CFI’s reception among patients and clinicians.     

Atlantic salmon (Salmo salar) muscle precursor cells differentiate into osteoblasts in vitro: Polyunsaturated fatty acids and hyperthermia influence gene expression and differentiation

The formation and mineralisation of bone are two critical processes in fast-growing Atlantic salmon (Salmo salar). The mechanisms of these processes, however, have not been described in detail. Thus, in vitro systems that allow the study of factors that influence bone formation in farmed Atlantic salmon are highly warranted. We describe here a method by which unspecialised primary cells from salmon white muscle can differentiate to osteoblasts in vitro. We have subsequently used the differentiated cells as a model system to study the effects of two factors that influence bone formation in Atlantic salmon under commercial farming conditions, namely polyunsaturated fatty acids, PUFAs, and temperature. Muscle precursor cells changed their morphology from triangular or spindle-shaped cells to polygonal or cubical cells after 3 weeks in osteogenic medium. In addition, gene expression studies showed that marker genes for osteoblastogenesis; alp, col1a1, osteocalcin, bmp2 and bmp4 increased after 3 weeks of incubation in osteogenic media showing that these cells have differentiated to osteoblasts at this stage. Adding CLA or DHA to the osteoblast media resulted in a reduced PGE₂ production and increased expression of osteocalcin. Further, temperature studies showed that differentiating osteoblasts are highly sensitive to increased incubation temperature at early stages of differentiation. Our studies show that unspecialised precursor cells isolated from salmon muscle tissue can be caused to differentiate to osteoblasts in vitro. Furthermore, this model system appears to be suitable for the study of osteoblast biology in vitro.     

Development and cell phenotypes in primary follicles of foetal sheep lymph nodes

Lymph nodes from sheep foetuses and postnatal lambs were examined to determine the participation of different leucocyte populations in primary follicle formation, with special emphasis on the emergence and subsequent development of follicular dendritic cells during late gestation and early postnatal life. A series of immune and enzyme histochemical markers was used. The first 5′-nucleotidase-positive primary follicles were found at 80 days gestational age (gestation in sheep is 150 days) in superficial cervical lymph nodes. In the last month of gestation the primary follicles possessed follicular dendritic cells, macrophages, dendritic cells, and CD5-positive lymphocytes, in addition to IgM-positive cells. Follicular dendritic cells in primary follicles were found to be ultrastructurally immature. These follicular dendritic cells were characterised by a few, coarse surface projections and many ribosomes attached to the endoplasmic reticulum. A final differentiation to mature follicular dendritic cells was coincident with the postnatal germinal centre reaction. Computer-assisted morphometric analysis demonstrated that the size of 5′-nucleotidase-positive primary follicles in the distal jejunal lymph node, but not in the superficial cervical lymph node, increased significantly during late gestation. It was concluded that stromal cells in primary follicles of foetal sheep lymph nodes were a continuously developing population but that ultrastructural maturity was only achieved in the germinal centres of postnatal lambs.     

Hybrid coating of alginate microbeads based on protein-biopolymer multilayers for encapsulation of probiotics

A hybrid coating based on multilayers of proteins and biopolymers was developed to enhance the protection performance of alginate microbeads against acidic conditions for delivery of probiotics (Lactobacillus rhamnosus GG). Zeta potential measurements and quartz crystal microbalance with dissipation confirmed layer-by-layer deposition of protein-polymer layers. The stability of protein-based coatings during simulated gastric fluid (SGF) treatment was monitored by microscopy. Protein-coated microbeads were partially dismantled, whereas polymer-coated microbeads were intact after a sequential treatment in simulated gastric and intestinal fluids. This suggests that hybrid formulation offers an advantage over the coatings based on biopolymer multilayers in terms of better release of bacteria. Uncoated alginate microbeads completely dissolved and could not protect bacteria after SGF treatment whereas microbeads with hybrid coating showed increased physical stability and a modest decrease of culturability of 3.8 log units. Therefore, this work provides a concept for future protein-based hybrid coatings for bacterial delivery systems.     

Strong Seasonality of Marine Microbial Eukaryotes in a High-Arctic Fjord (Isfjorden,in West Spitsbergen,Norway)

The Adventfjorden time series station (IsA) in Isfjorden, West Spitsbergen, Norway, was sampled frequently from December 2011 to December 2012. The community composition of microbial eukaryotes (size, 0.45 to 10 μm) from a depth of 25 m was determined using 454 sequencing of the 18S V4 region amplified from both DNA and RNA. The compositional changes throughout the year were assessed in relation to in situ fjord environmental conditions. Size fractionation analyses of chlorophyll a showed that the photosynthetic biomass was dominated by small cells (<10 μm) most of the year but that larger cells dominated during the spring and summer. The winter and early-spring communities were more diverse than the spring and summer/autumn communities. Dinophyceae were predominant throughout the year. The Arctic Micromonas ecotype was abundant mostly in the early-bloom and fall periods, whereas heterotrophs, such as marine stramenopiles (MASTs), Picozoa, and the parasitoid marine alveolates (MALVs), displayed higher relative abundance in the winter than in other seasons. Our results emphasize the extreme seasonality of Arctic microbial eukaryotic communities driven by the light regime and nutrient availability but point to the necessity of a thorough knowledge of hydrography for full understanding of their succession and variability.     

Towards precision medicine in diabetes? A critical review of glucotypes

In response to a study previously published in PLOS Biology, this Formal Comment thoroughly examines the concept of ’glucotypes’ with regard to its generalisability, interpretability and relationship to more traditional measures used to describe data from continuous glucose monitoring.

Although the promise of precision medicine has led to advances in the recognition and treatment of rare monogenic forms of diabetes, its impact on prevention and treatment of more common forms of diabetes has been underwhelming [1]. Several approaches to the subclassification of individuals with, or at high risk of, type 2 diabetes have been published recently [2–4]. Hall and colleagues introduced the concept of “glucotypes” in a research article [3] that has received enormous attention in the highest impact scientific journals [5–8], mostly in relation to precision medicine. The authors developed an algorithm to identify patterns of glucose fluctuations based on continuous glucose monitoring (CGM). They named the 3 identified patterns: “low variability,” “moderate variability,” and “severe variability” glucotypes. Each individual was characterised by the proportion of time spent in the 3 glucotypes and was assigned to an overall glucotype based on the highest proportion. They argued that glucotypes provide the advantage of taking into account a more detailed picture of glucose dynamics, in contrast to commonly used single time point or average-based measures, revealing subphenotypes within traditional diagnostic categories of glucose regulation. Even though the study was based on data from only 57 individuals without a prior diabetes diagnosis, others have interpreted the results as indicating that glucotypes might identify individuals at an early stage of glucose dysregulation, suggesting a potential role in diabetes risk stratification and prevention [5]. However, before glucotypes can become “an important tool in early identification of those at risk for type 2 diabetes” [3], the concept requires thorough validation. Therefore, we explore the generalisability and interpretability of glucotypes and their relationship to traditional CGM-based measures.We used data from The Maastricht Study [9] and the PRE-D Trial [10] comprising a total number of 770 diabetes-free individuals with a 7-day CGM registration. We observed that the average proportion of time spent in the low variability glucotype was low both in The Maastricht Study (6%) and the PRE-D Trial (4%), compared to 20% in the original study. A reason for the difference may be that our study populations were on average 11 to 12 years older and that the PRE-D Trial (n = 116) included only overweight and obese individuals with prediabetes. In The Maastricht Study, the median (Q1 to Q3) body mass index was 25.9 kg/m² (23.4 to 28.7), and 72% had normal glucose tolerance. As a logical consequence, the severe glucotype was most common in the PRE-D Trial (55%). Regardless, our data show that the initial estimates of the different glucotype prevalences do not necessarily generalise to other populations, especially in age groups at increased risk of type 2 diabetes.Hall and colleagues described glucotypes as a new measure of glucose variability, a clinically relevant metric of glycaemic patterns [3]. In the figures accompanying the original publication, the low variability pattern was characterised by both the lowest mean glucose level and variation, while the severe pattern had both the highest mean glucose level and variation. As such, these examples did not give an intuition whether glucotypes were predominantly driven by glucose variability or by mean glucose levels. We therefore present 3 examples from the PRE-D Trial (Fig 1). The first 2 profiles are very similar with regard to glucose variability. Thus, the driver of the most severe glucotype of the second participant is clearly the slightly higher mean glycaemic level. Also, even though the third participant has a much larger variation than the first two, the proportion of time in the severe glucotype is not higher than for the second participant as one would expect from a classical measure of glucose variability. To investigate this further, we assessed the association between glucotypes and classical CGM measures, i.e., the mean CGM glucose level (Fig 2A) and the coefficient of variation (Fig 2B) in The Maastricht Study. The scatterplots show a clear association between the mean CGM glucose and glucotypes. They also suggest that participants with a high proportion of time in the moderate glucotype do not have high variation in glucose. Rather than a biological feature, this may well be a methodological consequence of being assigned to the middle cluster. If large fluctuations were present, glucose levels would reach either low or high values, resulting in a higher proportion of time spent in the low or severe glucotypes, respectively (assuming a strong association between glucotypes and mean CGM glucose). Therefore, we decided to quantify this association using regression analysis where glucotype proportions were the outcomes, and the mean CGM glucose concentration was the independent variable modelled with natural cubic splines (more details on the specification of the models are given in Supporting information S1–S3 Codes). Then, we used the equation estimated in The Maastricht Study to predict glucotypes in the external validation sample (PRE-D Trial, Fig 2C). First, similarly to Hall and colleagues, we assigned individuals to the pattern with the highest proportion of time and then compared the predicted and the observed glucotypes. We found that in 107 out of 116 individuals, the glucotype was predicted correctly when using only the mean CGM glucose value. When considering the glucotypes as continuous proportions of time, the root mean squared errors (RMSEs) were 0.05, 0.09, and 0.07 for the low, moderate, and severe variability glucotypes, respectively, indicating good predictive ability. These results demonstrate that glucotypes either mainly reflect the mean CGM glucose level or do not translate to external datasets (e.g., due to overfitting). To investigate this further, we conducted the same analyses as described for the PRE-D Trial in the original data from Hall and colleagues and found a slightly weaker, but still strong association between mean CGM glucose levels and glucotypes. Using the regression model from The Maastricht Study, we could correctly predict 79% of the glucotypes, while the RMSEs were 0.11, 0.15, and 0.13.Open in a separate windowFig 1Example CGM profiles of participants in the PRE-D Trial with corresponding proportion of time spent in different glucotypes and conventional measures (mean and CV).CGM, continuous glucose monitoring; CV, coefficient of variation.Open in a separate windowFig 2Observed proportion of time spent in the 3 glucotypes by mean CGM glucose (A) and coefficient of variation (B) in The Maastricht Study, and by mean CGM glucose in the PRE-D Trial (C) alongside predicted proportions based on the regression analysis in The Maastricht Study. CGM, continuous glucose monitoring.Although the transformation of continuous measures into categorical ones is a common procedure in clinical research, assigning individuals to the glucotype with the highest proportion of time runs very much against the “precision” tenet of precision medicine. In line with this, a recent study has demonstrated how simple clinical features outperformed clusters in predicting relevant clinical outcomes [11]. This is especially problematic when a method does not provide clear separation between clusters, which can be quantified by calculating relative entropy [12]. A relative entropy of zero would mean that all individuals spend one-third of the time in each of the 3 glucotypes, while a value of one would indicate that each individual spends the entire time period in only one of the 3 glucotypes. In the original cohort of Hall and colleagues [3], we calculated a relative entropy of 0.24 indicating that cluster separation is far from optimal and together with the previous results question the claim that the glucotype is really a “more comprehensive measure of the pattern of glucose excursions than the standard laboratory tests in current use” [3].In conclusion, we demonstrate in 2 large, external datasets, that the assessment of glucotypes does not offer more novel insights than the mean CGM glucose, highlighting the importance of large development datasets and external validation for data-driven algorithms. As CGM is becoming more widely used in large clinical studies also among individuals without diabetes, glucose patterns derived from CGMs will be an important focus area in future diabetes research. However, it is important that scientific scrutiny precedes the introduction of emerging tools with a promise of identifying individuals at high risk of type 2 diabetes and its late complications at an earlier stage of disease progression, especially in an observational setting. Furthermore, future efforts towards precision medicine for diabetes prevention and treatment should go beyond the glucocentric approach we have seen so far. We know that hyperglycaemia is a late feature of diabetes development and that patients benefit most from a multifactorial treatment approach [13]. A multifactorial approach, with relevance to the aetiology of micro- and macrovascular complications, may also yield a more clinically useful risk stratification of nondiabetic individuals [14]. Even so, if we aim for precision medicine, we should aim to retain as much precision as possible at every step of the process, by treating determinants and outcomes as continuous measures if possible and by retaining information on the uncertainty of any hard classification such as cluster membership.