A Common Polymorphism in the Promoter of UCP2 Contributes to the Variation in Insulin Secretion in Glucose-Tolerant Subjects

It was reported that the common −866G/A polymorphism in the promoter of the human uncoupling protein-2 (UCP2) gene, which enhances its trascriptional activity, is associated with increased mRNA levels in human adipocytes and reduced risk of obesity. Studies in knockout mice and β-cells indicate that UCP2 may play a role in β-cell function. In this study, we addressed the question of whether the common −866G/A polymorphism in UCP2 gene contributes to the variation of insulin secretion in humans by genotyping 301 nondiabetic subjects who underwent an oral glucose tolerance test. Glucose-stimulated insulin secretion estimated by several indexes of β-cell function was significantly lower in carriers of the −866A/A genotype compared with −866A/G or −866G/G according to the dosage of the A allele (P = 0.002–0.05). To investigate directly whether the UCP2 −866G/A polymorphism affects human islet function, pancreatic islets isolated from two −866G/G homozygous, seven −866G/A heterozygous, and one −866A/A homozygous nondiabetic donors were studied. Islets from −866A/A homozygous had lower insulin secretion in response to glucose stimulation as compared with −866G/G and −866G/A carriers. These results indicate that the common −866G/A polymorphism in the UCP2 gene may contribute to the biological variation of insulin secretion in humans

Hypoglycemia Assessed by Continuous Glucose Monitoring Is Associated with Preclinical Atherosclerosis in Individuals with Impaired Glucose Tolerance

Hypoglycemia is associated with increased risk of cardiovascular adverse clinical outcomes. There is evidence that impaired glucose tolerance (IGT) is associated with cardiovascular morbidity and mortality. Whether IGT individuals have asymptomatic hypoglycemia under real-life conditions that are related to early atherosclerosis is unknown. To this aim, we measured episodes of hypoglycemia during continuous interstitial glucose monitoring (CGM) and evaluated their relationship with early manifestation of vascular atherosclerosis in glucose tolerant and intolerant individuals. An oral glucose tolerance test (OGTT) was performed in 79 non-diabetic subjects. Each individual underwent continuous glucose monitoring for 72 h. Cardiovascular risk factors and ultrasound measurement of carotid intima-media thickness (IMT) were evaluated. IGT individuals had a worse cardiovascular risk profile, including higher IMT, and spent significantly more time in hypoglycemia than glucose-tolerant individuals. IMT was significantly correlated with systolic (r = 0.22; P = 0.05) and diastolic blood pressure (r = 0.28; P = 0.01), total (r = 0.26; P = 0.02) and LDL cholesterol (r = 0.27; P = 0.01), 2-h glucose (r = 0.39; P<0.0001), insulin sensitivity (r = −0.26; P = 0.03), and minutes spent in hypoglycemia (r = 0.45; P<0.0001). In univariate analyses adjusted for gender, minutes spent in hypoglycemia were significantly correlated with age (r = 0.26; P = 0.01), waist circumference (r = 0.33; P = 0.003), 2-h glucose (r = 0.58; P<0.0001), and 2-h insulin (r = 0.27; P = 0.02). In a stepwise multivariate regression analysis, the variables significantly associated with IMT were minutes spent in hypoglycemia (r2 = 0.252; P<0.0001), and ISI index (r2 = 0.089; P = 0.004), accounting for 34.1% of the variation. Episodes of hypoglycemia may be considered as a new potential cardiovascular risk factor for IGT individuals

A Survey on Design Methodologies for Accelerating Deep Learning on Heterogeneous Architectures

In recent years, the field of Deep Learning has seen many disruptive and impactful advancements. Given the increasing complexity of deep neural networks, the need for efficient hardware accelerators has become more and more pressing to design heterogeneous HPC platforms. The design of Deep Learning accelerators requires a multidisciplinary approach, combining expertise from several areas, spanning from computer architecture to approximate computing, computational models, and machine learning algorithms. Several methodologies and tools have been proposed to design accelerators for Deep Learning, including hardware-software co-design approaches, high-level synthesis methods, specific customized compilers, and methodologies for design space exploration, modeling, and simulation. These methodologies aim to maximize the exploitable parallelism and minimize data movement to achieve high performance and energy efficiency. This survey provides a holistic review of the most influential design methodologies and EDA tools proposed in recent years to implement Deep Learning accelerators, offering the reader a wide perspective in this rapidly evolving field. In particular, this work complements the previous survey proposed by the same authors in [203], which focuses on Deep Learning hardware accelerators for heterogeneous HPC platforms

Levofloxacin-induced hemichorea-hemiballism in a patient with previous thalamic infarction

[no abstract available

CIDP, CMT1B, or CMT1B plus CIDP?

Charcot-Marie-Tooth disease type 1 (CMT1) and chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) have distinct clinical and neurophysiological features that result from dysmyelination in CMT1 and macrophage-mediated segmental demyelination in CIDP. CMT1 may occur in genetically isolated cases with atypical presentations that converge phenotypically with CIDP; in rare cases, however, CMT1 may be complicated by superimposed CIDP. We report the case of a patient harboring a de novo heterozygous null mutation of the myelin protein zero (MPZ) gene and affected by subclinical CMT1B who became symptomatic due to superimposed CIDP. Peripheral nerve high-resolution ultrasound (HRUS) aided in establishing the coexistence of CMT1B and CIDP; the diagnosis was further supported by favorable clinical, neurophysiological, and ultrasound responses to immunoglobulin therapy

Hypothalamic-Bulbar MRI hyperintensity in Anti-IgLON5 disease with serum-restricted antibodies: a case report and systematic review of literature

Anti-IgLON5 disease is a rare neurodegenerative tauopathy that displays heterogeneity in clinical spectrum, disease course, cerebrospinal fluid (CSF) findings, and variable response to immunotherapy. Sleep disorders, bulbar dysfunction, and gait abnormalities are common presenting symptoms, and conventional brain MRI scanning is often unrevealing

Towards Chemotactic Supramolecular Nanoparticles: From Autonomous Surface Motion Following Specific Chemical Gradients to Multivalency-Controlled Disassembly

Nature designs chemotactic supramolecular structures that can selectively bind specific groups present on surfaces, autonomously scan them moving along density gradients, and react once a critical concentration is encountered. While such properties are key in many biological functions, these also offer inspirations for designing artificial systems capable of similar bioinspired autonomous behaviors. One approach is to use soft molecular units that self-assemble in aqueous solution generating nanoparticles (NPs) that display specific chemical groups on their surface, enabling for multivalent interactions with complementarily functionalized surfaces. However, a first challenge is to explore the behavior of these assemblies at sufficiently high-resolution to gain insights on the molecular factors controlling their behaviors. Here we show that, coupling coarse-grained molecular models and advanced simulation approaches, it is possible to study the (autonomous or driven) motion of self-assembled NPs on a receptor-grafted surface at submolecular resolution. As an example, we focus on self-assembled NPs composed of facially amphiphilic oligomers. We observe how tuning the multivalent interactions between the NP and the surface allows to control NP binding, its diffusion along chemical surface gradients, and ultimately, the NP reactivity at determined surface group densities. In silico experiments provide physical-chemical insights on key molecular features in the self-assembling units which determine the dynamic behavior and fate of the NPs on the surface: from adhesion, to diffusion, and disassembly. This offers a privileged point of view into the chemotactic properties of supramolecular assemblies, improving our knowledge on how to design new types of materials with bioinspired autonomous behaviors.</p