Deep Resequencing of 9 Candidate Genes Identifies a Role for ARAP1 and IGF2BP2 in Modulating Insulin Secretion Adjusted for Insulin Resistance in Obese Southern Europeans

Type 2 diabetes is characterized by impairment in insulin secretion, with an established genetic contribution. We aimed to evaluate common and low-frequency (1–5%) variants in nine genes strongly associated with insulin secretion by targeted sequencing in subjects selected from the extremes of insulin release measured by the disposition index. Collapsing data by gene and/or function, the association between disposition index and nonsense variants were significant, also after adjustment for confounding factors (OR = 0.25, 95% CI = 0.11–0.59, p = 0.001). Evaluating variants individually, three novel variants in ARAP1, IGF2BP2 and GCK, out of eight reaching significance singularly, remained associated after adjustment. Constructing a genetic risk model combining the effects of the three variants, only carriers of the ARAP1 and IGF2BP2 variants were significantly associated with a reduced probability to be in the lower, worst, extreme of insulin secretion (OR = 0.223, 95% CI = 0.105–0.473, p < 0.001). Observing a high number of normal glucose tolerance between carriers, a regression posthoc analysis was performed. Carriers of genetic risk model variants had higher probability to be normoglycemic, also after adjustment (OR = 2.411, 95% CI = 1.136–5.116, p = 0.022). Thus, in our southern European cohort, nonsense variants in all nine candidate genes showed association with better insulin secretion adjusted for insulin resistance, and we established the role of ARAP1 and IGF2BP2 in modulating insulin secretion.     

Active Materials for 3D Printing in Small Animals: Current Modalities and Future Directions for Orthopedic Applications

The successful clinical application of bone tissue engineering requires customized implants based on the receiver’s bone anatomy and defect characteristics. Three-dimensional (3D) printing in small animal orthopedics has recently emerged as a valuable approach in fabricating individualized implants for receiver-specific needs. In veterinary medicine, because of the wide range of dimensions and anatomical variances, receiver-specific diagnosis and therapy are even more critical. The ability to generate 3D anatomical models and customize orthopedic instruments, implants, and scaffolds are advantages of 3D printing in small animal orthopedics. Furthermore, this technology provides veterinary medicine with a powerful tool that improves performance, precision, and cost-effectiveness. Nonetheless, the individualized 3D-printed implants have benefited several complex orthopedic procedures in small animals, including joint replacement surgeries, critical size bone defects, tibial tuberosity advancement, patellar groove replacement, limb-sparing surgeries, and other complex orthopedic procedures. The main purpose of this review is to discuss the application of 3D printing in small animal orthopedics based on already published papers as well as the techniques and materials used to fabricate 3D-printed objects. Finally, the advantages, current limitations, and future directions of 3D printing in small animal orthopedics have been addressed.     

A Comparison of Network-Based Methods for Drug Repurposing along with an Application to Human Complex Diseases

Drug repurposing strategy, proposing a therapeutic switching of already approved drugs with known medical indications to new therapeutic purposes, has been considered as an efficient approach to unveil novel drug candidates with new pharmacological activities, significantly reducing the cost and shortening the time of de novo drug discovery. Meaningful computational approaches for drug repurposing exploit the principles of the emerging field of Network Medicine, according to which human diseases can be interpreted as local perturbations of the human interactome network, where the molecular determinants of each disease (disease genes) are not randomly scattered, but co-localized in highly interconnected subnetworks (disease modules), whose perturbation is linked to the pathophenotype manifestation. By interpreting drug effects as local perturbations of the interactome, for a drug to be on-target effective against a specific disease or to cause off-target adverse effects, its targets should be in the nearby of disease-associated genes. Here, we used the network-based proximity measure to compute the distance between the drug module and the disease module in the human interactome by exploiting five different metrics (minimum, maximum, mean, median, mode), with the aim to compare different frameworks for highlighting putative repurposable drugs to treat complex human diseases, including malignant breast and prostate neoplasms, schizophrenia, and liver cirrhosis. Whilst the standard metric (that is the minimum) for the network-based proximity remained a valid tool for efficiently screening off-label drugs, we observed that the other implemented metrics specifically predicted further interesting drug candidates worthy of investigation for yielding a potentially significant clinical benefit.     

Aquaporins Are One of the Critical Factors in the Disruption of the Skin Barrier in Inflammatory Skin Diseases

The skin is the largest organ of the human body, serving as an effective mechanical barrier between the internal milieu and the external environment. The skin is widely considered the first-line defence of the body, with an essential function in rejecting pathogens and preventing mechanical, chemical, and physical damages. Keratinocytes are the predominant cells of the outer skin layer, the epidermis, which acts as a mechanical and water-permeability barrier. The epidermis is a permanently renewed tissue where undifferentiated keratinocytes located at the basal layer proliferate and migrate to the overlying layers. During this migration process, keratinocytes undertake a differentiation program known as keratinization process. Dysregulation of this differentiation process can result in a series of skin disorders. In this context, aquaporins (AQPs), a family of membrane channel proteins allowing the movement of water and small neutral solutes, are emerging as important players in skin physiology and skin diseases. Here, we review the role of AQPs in skin keratinization, hydration, keratinocytes proliferation, water retention, barrier repair, wound healing, and immune response activation. We also discuss the dysregulated involvement of AQPs in some common inflammatory dermatological diseases characterised by skin barrier disruption.     

Pathogenetic Mechanisms of Hypertension–Brain-Induced Complications: Focus on Molecular Mediators

There is growing evidence that hypertension is the most important vascular risk factor for the development and progression of cardiovascular and cerebrovascular diseases. The brain is an early target of hypertension-induced organ damage and may manifest as stroke, subclinical cerebrovascular abnormalities and cognitive decline. The pathophysiological mechanisms of these harmful effects remain to be completely clarified. Hypertension is well known to alter the structure and function of cerebral blood vessels not only through its haemodynamics effects but also for its relationships with endothelial dysfunction, oxidative stress and inflammation. In the last several years, new possible mechanisms have been suggested to recognize the molecular basis of these pathological events. Accordingly, this review summarizes the factors involved in hypertension-induced brain complications, such as haemodynamic factors, endothelial dysfunction and oxidative stress, inflammation and intervention of innate immune system, with particular regard to the role of Toll-like receptors that have to be considered dominant components of the innate immune system. The complete definition of their prognostic role in the development and progression of hypertensive brain damage will be of great help in the identification of new markers of vascular damage and the implementation of innovative targeted therapeutic strategies.     

Pediatric Brain Tumors: Signatures from the Intact Proteome

The present investigation aimed to explore the intact proteome of tissues of pediatric brain tumors of different WHO grades and localizations, including medulloblastoma, pilocytic astrocytoma, and glioblastoma, in comparison with the available data on ependymoma, to contribute to the understanding of the molecular mechanisms underlying the onset and progression of these pathologies. Tissues have been homogenized in acidic water–acetonitrile solutions containing proteases inhibitors and analyzed by LC–high resolution MS for proteomic characterization and label-free relative quantitation. Tandem MS spectra have been analyzed by either manual inspection or software elaboration, followed by experimental/theoretical MS fragmentation data comparison by bioinformatic tools. Statistically significant differences in protein/peptide levels between the different tumor histotypes have been evaluated by ANOVA test and Tukey’s post-hoc test, considering a p-value > 0.05 as significant. Together with intact protein and peptide chains, in the range of molecular mass of 1.3–22.8 kDa, several naturally occurring fragments from major proteins, peptides, and proteoforms have been also identified, some exhibiting proper biological activities. Protein and peptide sequencing allowed for the identification of different post-translational modifications, with acetylations, oxidations, citrullinations, deamidations, and C-terminal truncations being the most frequently characterized. C-terminal truncations, lacking from two to four amino acid residues, particularly characterizing the β-thymosin peptides and ubiquitin, showed a different modulation in the diverse tumors studied. With respect to the other tumors, medulloblastoma, the most frequent malignant brain tumor of the pediatric age, was characterized by higher levels of thymosin β4 and β10 peptides, the latter and its des-IS form particularly marking this histotype. The distribution pattern of the C-terminal truncated forms was also different in glioblastoma, particularly underlying gender differences, according to the definition of male and female glioblastoma as biologically distinct diseases. Glioblastoma was also distinguished for the peculiar identification of the truncated form of the α-hemoglobin chain, lacking the C-terminal arginine, and exhibiting oxygen-binding and vasoconstrictive properties different from the intact form. The proteomic characterization of the undigested proteome, following the top-down approach, was challenging to originally investigate the post-translational events that differently characterize pediatric brain tumors. This study provides a contribution to elucidate the molecular profiles of the solid tumors most frequently affecting the pediatric age, and which are characterized by different grades of aggressiveness and localization.     

A glucose-specific metric to assess predictors and identify models

In diabetes, the mean square error (MSE) metric is extensively used for assessing glucose prediction methods and identifying glucose models. One limitation of this metric is that, by equally treating errors in hypo-, eu-, and hyperglycemia, it is not able to weight the different clinical impact of errors in these three situations. In this paper, we propose a new cost function, which overcomes this limitation and can be used in place of MSE for several scopes, in particular for assessing the quality of glucose predictors and identifying glucose models. The new metric called glucose-specific MSE (gMSE) modifies MSE with a Clark error grid inspired penalty function, which penalizes overestimation in hypoglycemia and underestimation in hyperglycemia, i.e., the most harmful conditions on a clinical perspective. From a mathematical point of view, gMSE retains sensitivity of MSE and inherits some of its important mathematical features, in particular it has no local minima, simplifying the optimization. This makes it suitable for model identification purposes also. First, the goodness of it is demonstrated by means of three experiments, designed ad hoc to evidence its sensitivity to accuracy, precision, and distortion in glucose predictions. Second, a prediction assessment problem is presented, in which two real prediction profiles are compared. Results show that the MSE chooses the worst clinical situation, while gMSE correctly selects the situation with less clinical risk. Finally, we also demonstrate that models identified minimizing gMSE are more accurate in potentially harmful situations (hypo- and hyperglycemia) than those obtained by MSE.     

Metabolic Syndrome and Male Fertility: Beyond Heart Consequences of a Complex Cardiometabolic Endocrinopathy

Metabolic syndrome (MetS) is a highly prevalent condition among adult males, affecting up to 41% of men in Europe. It is characterized by the association of obesity, hypertension, and atherogenic dyslipidemia, which lead to premature morbidity and mortality due to cardiovascular disease (CVD). Male infertility is another common condition which accounts for about 50% of cases of couple infertility worldwide. Interestingly, male infertility and MetS shares several risk factors (e.g., smoking, ageing, physical inactivity, and excessive alcohol consumption), leading to reactive oxygen species (ROS) production and increased oxidative stress (OS), and resulting in endothelial dysfunction and altered semen quality. Thus, the present narrative review aims to discuss the pathophysiological mechanisms which link male infertility and MetS and to investigate the latest available evidence on the reproductive consequences of MetS.