Review of dohan eherenfest et al. (2009) on “classification of platelet concentrates: from pure platelet-rich plasma (p-prp) to leucocyte- and platelet-rich fibrin (l-prf)”

This classic discusses the original publication of Dohan Eherenfest et al. on "Classification of platelet concentrates: from pure platelet-rich plasma (P-PRP) to leucocyte- and platelet-rich fibrin (L-PRF)", in which the authors propose four categories of platelet concentrates depending on their leukocyte and fibrin content (P-PRP, leucocyte- and platelet-rich plasma (L-PRP), pure platelet-rich fibrin (P-PRF), and L-PRF) to group a "jungle" of products in which the term platelet-rich plasma (PRP) was used indistinctly. They were able to identify common factors such as: (1) the use of anticoagulant and immediate centrifugation of the blood after its collection, (2) most preparation techniques allowed platelet concentrate preparation within an hour, (3) the centrifugation aimed to separate the blood in layers that would allow the extraction of specific fractions, and (4) the product was activated with thrombin or calcium chloride. The reviewed manuscript has been listed among the most cited PRP articles in regenerative medicine, with more than 800 citations, driving the current scientific research and clinical practice by categorizing L-PRP and P-PRP (now, leukocyte-poor PRP). The classification has also opened the door to understanding intrinsic biological mechanisms between the platelets, leukocytes, fibrin, and growth factors, later considered for studying the proliferation and differentiation of cells in different tissues affected by PRP. Since the initial classification of platelet concentrates, several other classification systems have been proposed and published in the current literature, such as the PAW, Mishra, PLRA, DEPA, MARSPILL, etc. These classifications have identified important aspects of PRP that affect the biological composition and, ultimately, the indications and outcomes. To date, there is still a lack of standardization in sample preparation, cohort heterogeneity, and incomplete reporting of sample preparation utilized, leading to a lack of clarity and challenging researchers and clinicians

Renal Tumors of Childhood—A Histopathologic Pattern-Based Diagnostic Approach

Renal tumors comprise approximately 7% of all malignant pediatric tumors. This is a highly heterogeneous group of tumors, each with its own therapeutic management, outcome, and association with germline predispositions. Histopathology is the key in establishing the correct diagnosis, and therefore pathologists with expertise in pediatric oncology are needed for dealing with these rare tumors. While each tumor shows different histologic features, they do have considerable overlap in cell type and histologic pattern, making the diagnosis difficult to establish, if based on routine histology alone. To this end, ancillary techniques, such as immunohistochemistry and molecular analysis, can be of great importance for the correct diagnosis, resulting in appropriate treatment. To use ancillary techniques cost-effectively, we propose a pattern-based approach and provide recommendations to aid in deciding which panel of antibodies, supplemented by molecular characterization of a subset of genes, are required

Economic evaluation of Medically Assisted Reproduction : an educational overview of methods and applications for healthcare professionals

Acknowledgements Medical writing support was provided by Steven Goodrick of in Science Communications, Springer Healthcare Ltd, UK, and was funded by Merck Healthcare KGaA, Darmstadt, GermanyPeer reviewedPostprin

Brain age as a surrogate marker for cognitive performance in multiple sclerosis

Background: Data from neuro-imaging techniques allow us to estimate a brain's age. Brain age is easily interpretable as "how old the brain looks", and could therefore be an attractive communication tool for brain health in clinical practice. This study aimed to investigate its clinical utility by investigating the relationship between brain age and cognitive performance in multiple sclerosis (MS). Methods: A linear regression model was trained to predict age from brain MRI volumetric features and sex in a healthy control dataset (HC_train, n=1673). This model was used to predict brain age in two test sets: HC_test (n=50) and MS_test (n=201). Brain-Predicted Age Difference (BPAD) was calculated as BPAD=brain age minus chronological age. Cognitive performance was assessed by the Symbol Digit Modalities Test (SDMT). Results: Brain age was significantly related to SDMT scores in the MS_test dataset (r=-0.46, p<.001), and contributed uniquely to variance in SDMT beyond chronological age, reflected by a significant correlation between BPAD and SDMT (r=-0.24, p<.001) and a significant weight (-0.25, p=0.002) in a multivariate regression equation with age. Conclusions: Brain age is a candidate biomarker for cognitive dysfunction in MS and an easy to grasp metric for brain health

Physical and mental health comorbidity is common in people with multiple sclerosis: nationally representative cross-sectional population database analysis

&lt;b&gt;Background&lt;/b&gt; Comorbidity in Multiple Sclerosis (MS) is associated with worse health and higher mortality. This study aims to describe clinician recorded comorbidities in people with MS. &lt;p&gt;&lt;/p&gt; &lt;b&gt;Methods&lt;/b&gt; 39 comorbidities in 3826 people with MS aged ≥25 years were compared against 1,268,859 controls. Results were analysed by age, gender, and socioeconomic status, with unadjusted and adjusted Odds Ratios (ORs) calculated using logistic regression. &lt;p&gt;&lt;/p&gt; &lt;b&gt;Results&lt;/b&gt; People with MS were more likely to have one (OR 2.44; 95% CI 2.26-2.64), two (OR 1.49; 95% CI 1.38-1.62), three (OR 1.86; 95% CI 1.69-2.04), four or more (OR 1.61; 95% CI 1.47-1.77) non-MS chronic conditions than controls, and greater mental health comorbidity (OR 2.94; 95% CI 2.75-3.14), which increased as the number of physical comorbidities rose. Cardiovascular conditions, including atrial fibrillation (OR 0.49; 95% CI 0.36-0.67), chronic kidney disease (OR 0.51; 95% CI 0.40-0.65), heart failure (OR 0.62; 95% CI 0.45-0.85), coronary heart disease (OR 0.64; 95% CI 0.52-0.71), and hypertension (OR 0.65; 95% CI 0.59-0.72) were significantly less common in people with MS. &lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusion&lt;/b&gt; People with MS have excess multiple chronic conditions, with associated increased mental health comorbidity. The low recorded cardiovascular comorbidity warrants further investigation

Quantum Experimental Data in Psychology and Economics

We prove a theorem which shows that a collection of experimental data of probabilistic weights related to decisions with respect to situations and their disjunction cannot be modeled within a classical probabilistic weight structure in case the experimental data contain the effect referred to as the 'disjunction effect' in psychology. We identify different experimental situations in psychology, more specifically in concept theory and in decision theory, and in economics (namely situations where Savage's Sure-Thing Principle is violated) where the disjunction effect appears and we point out the common nature of the effect. We analyze how our theorem constitutes a no-go theorem for classical probabilistic weight structures for common experimental data when the disjunction effect is affecting the values of these data. We put forward a simple geometric criterion that reveals the non classicality of the considered probabilistic weights and we illustrate our geometrical criterion by means of experimentally measured membership weights of items with respect to pairs of concepts and their disjunctions. The violation of the classical probabilistic weight structure is very analogous to the violation of the well-known Bell inequalities studied in quantum mechanics. The no-go theorem we prove in the present article with respect to the collection of experimental data we consider has a status analogous to the well known no-go theorems for hidden variable theories in quantum mechanics with respect to experimental data obtained in quantum laboratories. For this reason our analysis puts forward a strong argument in favor of the validity of using a quantum formalism for modeling the considered psychological experimental data as considered in this paper.Comment: 15 pages, 4 figure