Social capital and collusion: the case of merchant guilds

Merchant guilds have been portrayed as ‘social networks’ that generated beneficial ‘social capital’ by sustaining shared norms, effectively transmitting information, and successfully undertaking collective action. This social capital, it is claimed, benefited society as a whole by enabling rulers to commit to providing a secure trading environment for alien merchants. But was this really the case? We develop a new model of the emergence, rise and eventual decline of European merchant guilds which explores the collusive relationship between rulers and guilds, and calls into question the prevailing positive view of merchant guilds. We then confront the model’s predictions with the available historical data. The empirical evidence strongly support our model and refutes existing theories. Our findings show that merchant guilds used their social capital for socially harmful as well as beneficial ends

K Index in cerebrospinal fluid: a valid tool in multiple sclerosis diagnosis

Detection of oligoclonal IgG bands in cerebrospinal fluid by isoelectrocfocusing and immunodetection is the current gold standard to detect an inflammatory process in the central nervous system. It has been proposed that the presence of free light chains (FLCs) in CSF was associated with recent demyelination activity in MS and might be used as a prognosis marker. Our study’s objective is assessing the diagnostic accuracy of a new highly sensitive latex-enhanced nephelometric assay for k free light chain (kFLC) determination in CSF/serum as an alternative to traditional tests and its clinical application. Methods. kFLCs were measured in CSF/serum pairs from 80 patients by the use of a new highly sensitive latex-enhanced nephelometric automated immunoassay for detection of immunoglobulin FLC. The eighty patients were split into three groups according to the neurological diagnosis. In this study we confirm even more the use of the k Index as a diagnostic aid in multiple sclerosis. Results. kFLC Index seems to be more accurate parameter respect the determination of oligoclonal immunoglobulin bands (OCBs). We recalculate the K Index sensitivity and specificity respect the precedent published result. Two patients previously diagnosed with leukoencephalopathy have gone to group 3 as confirmed the diagnosis of MS. Conclusions. These new data reinforce even more the use of the k Index to diagnose MS in comparison to classical methods and to the reference method, the OCBs

The Science of Stem Cell Biobanking: Investing in the Future

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RNA analysis of consensus sequence splicing mutations: implications for thediagnosis of Wilson disease

Wilson disease (WD) is an autosomal recessive disorder caused by a defective function of the copper-transporting ATP7B protein. This results in progressive copper overload and consequent liver, brain, and kidney damage. Approximately 300 WD-causing mutations have been described to date. Missense mutations are largely prevalent, while splice-site mutations are rarer. Of these, only a minority are detected in splicing consensus sequences. Further, few splicing mutations have been studied at the RNA level. In this study we report the RNA molecular characterization of three consensus splice-site mutations identified by DNA analysis in WD patients. One of them, c.51 + 4 A --> T, resides in the consensus sequence of the donor splice site of intron 1; the second, c. 2121 + 3 A --> G, occurred in position + 3 of intron 7; and the c.2447 + 5 G --> A is localized in the consensus sequence of the donor splice site of intron 9. Analysis revealed predominantly abnormal splicing in the samples carrying mutations compared to the normal controls. These results strongly suggest that consensus sequence splice-site mutations result in disease by interfering with the production of the normal WD protein. Our data contribute to understanding the mutational spectrum that affect splicing and improve our capability in WD diagnosis

Chronic treatment with statins increases the availability of selenium in the antioxidant defence systems of hemodialysis patients.

Project. Oxidative stress (OS) is enhanced in hemodialysis (HD) patients. Lipid peroxidation and oxidative damage to glycids, proteins and nucleic acids are main consequences of OS and are associated to increased cardiovascular risk. Vitamin E and Glutathione Peroxidase (GSH-Px) represent main antioxidant systems in human cells. Selenium (Se), bound to the active sites of GSH-Px, plays a critical role in this antioxidant defense system. Statins are widely used and extensively investigated in the prevention of cardiovascular disease, notably in high-risk subjects. Several studies suggest that statins show antioxidant effects, protecting low-density lipoproteins from oxidation. Aim of our study was to compare serum Se concentration in ESRD patients on maintenance HD and in homogeneous healthy subjects and to investigate whether chronic assumption of statins may interfere with serum Se concentration in HD patients. Procedure. A total of 103 HD patients and 69 healthy subjects were enrolled; HD patients were then divided into patients who were not treated with statins (group A) and patients who assumed statins since six months at least (group B). Serum Se was determined by atomic absorption spectrometry. Results. Serum Se was significantly lower in HD patients of group A compared to healthy subjects (81.65±19.66mcg/L Vs. 96.47±15.62mcg/L, p<0.0040). However, in HD patients who assumed statins serum Se was significantly higher than in HD patients who did not. (111.83±18.82mcg/L Vs. 81.65±19.66mcg/L, p<0.0001). Conclusions. our results suggest that in HD patients chronic assumption of statins is related to a higher availability of active antioxidant agents and to reduced oxidative stress

Delayed diagnosis of coeliac disease increases cancer risk

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The Association of Left Ventricular Hypertrophy with Metabolic Syndrome is Dependent on Body Mass Index in Hypertensive Overweight or Obese Patients

Overweight (Ow) and obesity (Ob) influence blood pressure (BP) and left ventricular hypertrophy (LVH). It is unclear whether the presence of metabolic syndrome (MetS) independently affects echocardiographic parameters in hypertension.380 Ow/Ob essential hypertensive patients (age ≤ 65 years) presenting for referred BP control-related problems. MetS was defined according to NCEP III/ATP with AHA modifications and LVH as LVM/h(2.7) ≥ 49.2 g/m(2.7) in males and ≥ 46.7 g/m(2.7) in females. Treatment intensity score (TIS) was used to control for BP treatment as previously reported.Hypertensive patients with MetS had significantly higher BMI, systolic and mean BP, interventricular septum and relative wall thickness and lower ejection fraction than those without MetS. LVM/h(2.7) was significantly higher in MetS patients (59.14 ± 14.97 vs. 55.33 ± 14.69 g/m(2.7); p = 0.022). Hypertensive patients with MetS had a 2.3-fold higher risk to have LVH/h(2.7) after adjustment for age, SBP and TIS (OR 2.34; 95%CI 1.40-3.92; p = 0.001), but MetS lost its independent relationship with LVH when BMI was included in the model.In Ow/Ob hypertensive patients MetS maintains its role of risk factor for LVH independently of age, SBP, and TIS, resulting in a useful predictor of target organ damage in clinical practice. However, MetS loses its independent relationship when BMI is taken into account, suggesting that the effects on MetS on LV parameters are mainly driven by the degree of adiposity

Accumulation of neutral lipids in peripheral blood mononuclear cells as a distinctive trait of Alzheimer patients and asymptomatic subjects at risk of disease

<p>Abstract</p> <p>Background</p> <p>Alzheimer's disease is the most common progressive neurodegenerative disease. In recent years, numerous progresses in the discovery of novel Alzheimer's disease molecular biomarkers in brain as well as in biological fluids have been made. Among them, those involving lipid metabolism are emerging as potential candidates. In particular, an accumulation of neutral lipids was recently found by us in skin fibroblasts from Alzheimer's disease patients. Therefore, with the aim to assess whether peripheral alterations in cholesterol homeostasis might be relevant in Alzheimer's disease development and progression, in the present study we analyzed lipid metabolism in plasma and peripheral blood mononuclear cells from Alzheimer's disease patients and from their first-degree relatives.</p> <p>Methods</p> <p>Blood samples were obtained from 93 patients with probable Alzheimer's disease and from 91 of their first-degree relatives. As controls we utilized 57, cognitively normal, over-65 year-old volunteers and 113 blood donors aged 21-66 years, respectively. Data are reported as mean ± standard error. Statistical calculations were performed using the statistical analysis software Origin 8.0 version. Data analysis was done using the Student t-test and the Pearson test.</p> <p>Results</p> <p>Data reported here show high neutral lipid levels and increased ACAT-1 protein in about 85% of peripheral blood mononuclear cells freshly isolated (<it>ex vivo</it>) from patients with probable sporadic Alzheimer's disease compared to about 7% of cognitively normal age-matched controls. A significant reduction in high density lipoprotein-cholesterol levels in plasma from Alzheimer's disease blood samples was also observed. Additionally, correlation analyses reveal a negative correlation between high density lipoprotein-cholesterol and cognitive capacity, as determined by Mini Mental State Examination, as well as between high density lipoprotein-cholesterol and neutral lipid accumulation. We observed great variability in the neutral lipid-peripheral blood mononuclear cells data and in plasma lipid analysis of the subjects enrolled as Alzheimer's disease-first-degree relatives. However, about 30% of them tend to display a peripheral metabolic cholesterol pattern similar to that exhibited by Alzheimer's disease patients.</p> <p>Conclusion</p> <p>We suggest that neutral lipid-peripheral blood mononuclear cells and plasma high density lipoprotein-cholesterol determinations might be of interest to outline a distinctive metabolic profile applying to both Alzheimer's disease patients and asymptomatic subjects at higher risk of disease.</p

Predictive Power Estimation Algorithm (PPEA) - A New Algorithm to Reduce Overfitting for Genomic Biomarker Discovery

Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA), which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1) PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2) the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3) using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4) more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses