Nickel-Titanium peripheral stents: can fracture mechanics shed light on their fatigue failure?

The major concern about Nickel-Titanium (Ni-Ti) stents, which are the gold standard in the treatment of occlusive peripheral disease, is fatigue and the consequent fracture in vivo. Indeed, their failure might be responsible for severe drawbacks, among which is the re-occlusion of the treated artery. Although many phenomenological approaches have been proposed to study this topic, the current literature lacks extensive knowledge on the Ni-Ti local damage mechanisms produced by the cyclic loads that promote crack nucleation and lead to the failure of thin struts, such as those of stents. Moreover, due to the super-elastic property of the alloy, the standard approach for interpreting the fracture of metals might be not accurate for this case. This work aims at increasing awareness of fatigue failure in superelastic Ni-Ti thin struts, such as those of stents. To do so, multi-wire specimens, sharing the same dimensions and thermo-mechanical treatment of the stent struts, were fatigue tested under different strain levels and the number of cycles to failure was recorded for each sample. Numerical simulations corroborated the experimental results to gain information on the local stress and strain fields during the fatigue cycles. A fracture mechanics-based fatigue model adopting the cyclic J-integral was here proposed, giving promising results for the interpretation of such failures

A critical overview of tools for assessing cognition in bipolar disorder

Cognitive deficits are prevalent in bipolar disorder even during the euthymic phase, having a negative impact on global functioning and quality of life. As such, more and more mental health professionals agree that neuropsychological assessment should be considered an essential component of the clinical management of bipolar patients. However, no gold standard tool has been established so far. According to bipolar disorder experts targeting cognition, appropriate cognitive tools should be brief, easy to administer, cost-effective and validated in the target population. In this commentary, we critically appraised the strengths and limitations of the tools most commonly used to assess cognitive functioning in bipolar patients, both for screening and diagnostic purposes

The Enhancement of Special-Use Real Estate Properties: The Case of Hospital Facilities

In the Italian context, public investments for the redevelopment and securing of the National Health Service’s real estate assets are a crucial topic in the context of the National Recovery and Resilience Plan (NRRP) within the Next Generation Italian strategy. The paper proposes the evaluation of alternative scenarios for accessing financing under the NRRP with respect to the criterion of the technically efficient solution, i.e., the solution that minimizes investment costs while respecting time obligations. The methodology proposed refers to the Cost approach with specific reference to the Depreciated Replacement Cost Method (DRC) in order to estimate the market value in different scenarios. The approach is applied to a case study located in the Piedmont Region, where alternatives are compared with respect to both budget constraints and the timeframe for accessing financing. Given the growing concern for urban regeneration and “public city” rearrangement as an answer to the ongoing global changes, making investments in special-use real estate properties has become a central and challenging issue both in the public and private decision domains

Edible Energy: balancing inputs and waste in food supply chain and biofuels from algae

Energy is life. Without it there is no water, there is no nutrition. Man's ability to live, grow, produce wealth is closely linked to the energy availability and use. Fire has been the first energy conversion technology; since that moment, the link between energy and progress has been indissoluble. Nowadays, a much greater energy input into the food supply chain has made a much higher food production possible. This might have an impact on the water availability. Algae are a promising solution for the energy-food-water nexus

Machine learning methods to predict outcomes of pharmacological treatment in psychosis

In recent years, machine learning (ML) has been a promising approach in the research of treatment outcome prediction in psychosis. In this study, we reviewed ML studies using different neuroimaging, neurophysiological, genetic, and clinical features to predict antipsychotic treatment outcomes in patients at different stages of schizophrenia. Literature available on PubMed until March 2022 was reviewed. Overall, 28 studies were included, among them 23 using a single-modality approach and 5 combining data from multiple modalities. The majority of included studies considered structural and functional neuroimaging biomarkers as predictive features used in ML models. Specifically, functional magnetic resonance imaging (fMRI) features contributed to antipsychotic treatment response prediction of psychosis with good accuracies. Additionally, several studies found that ML models based on clinical features might present adequate predictive ability. Importantly, by examining the additive effects of combining features, the predictive value might be improved by applying multimodal ML approaches. However, most of the included studies presented several limitations, such as small sample sizes and a lack of replication tests. Moreover, considerable clinical and analytical heterogeneity among included studies posed a challenge in synthesizing findings and generating robust overall conclusions. Despite the complexity and heterogeneity of methodology, prognostic features, clinical presentation, and treatment approaches, studies included in this review suggest that ML tools may have the potential to predict treatment outcomes of psychosis accurately. Future studies need to focus on refining feature characterization, validating prediction models, and evaluate their translation in real-world clinical practice

A novel approach for the purification and proteomic analysis of pathogenic immunglobulin free light chains from serum

An excess of circulating monoclonal free immunoglobulin light chains (FLC) is common in plasma cell disorders. A subset of FLC, as amyloidogenic ones, possess intrinsic pathogenicity. Because of their complex purification, little is known on the biochemical features of serum FLC, possibly related to their pathogenic spectrum. We developed an immunopurification approach to isolate serum FLC from patients with monoclonal gammopathies, followed by proteomic characterization. Serum monoclonal FLC were detected and quantified by immunofixation and immunonephelometry. Immunoprecipitation was performed by serum incubation with agarose beads covalently linked to polyclonal anti-κ or λ FLC antibodies. Isolated FLC were analyzed by SDS-PAGE, 2D-PAGE, immunoblotting, mass spectrometry (MS). Serum FLC were immunoprecipitated from 15 patients with ALλ amyloidosis (serum λ FLC range: 98-2350mg/L), 5 with ALκ amyloidosis and 1 with κ light chain (LC) myeloma (κ FLC range: 266-2660mg/L), and 3 controls. Monoclonal FLC were the prevalent eluted species in patients. On 2D-PAGE, both λ and κ FLC originated discrete spots with multiple pI isoforms. The nature of eluted FLC and coincidence with the LC sequence from the bone marrow clone was confirmed by MS, which also detected post-translational modifications, including truncation, tryptophan oxidation, cysteinylation, peptide dimerization. Serum FLC were purified in soluble form and adequate amounts for proteomics, which allowed studying primary sequence and detecting post-translational modifications. This method is a novel instrument for studying the molecular bases of FLC pathogenicity, allowing for the first time the punctual biochemical description of the circulating forms

Dysregulation of Astrocytic HMGB1 Signaling in Amyotrophic Lateral Sclerosis

Astrocytes have emerged as critical elements for the maintenance and function of the central nervous system. The expression on their cell membrane of RAGE and TLR4 receptors makes astrocytes susceptible to High-mobility group box 1 (HMGB1), a nuclear protein typically released in the extracellular milieu by living cells experiencing physiological stress conditions or by damaged cells. Here, we show that the interaction of HMGB1 with normal spinal cord astrocytes induces the astrocytic production of neurotrophic factors, particularly brain-derived neurotrophic factor (BDNF) and glial cell line-derived neurotrophic factor (GDNF). Multiple investigations suggest a role for HMGB1 in amyotrophic lateral sclerosis (ALS). Yet, no mechanistic information on the implication of HMGB1 signaling in this disorder is currently available. We demonstrate that non-transgenic and transgenic SOD1WT spinal motor neurons exhibit only a basal nucleus-to-cytoplasm shuttling of the HMGB1 protein. Conversely, in SOD1G93A ALS mouse spinal cords, HMGB1 significantly translocates from the nucleus to the cytoplasm of motor neurons, thereby suggesting that it may be eventually released in the extracellular environment during the progression of the disease. We postulate that extracellular HMGB1 can paracrinally interact with the neighboring astrocytes in an attempt to counteract the neurodegenerative process. Yet, at variance with normal cells, SOD1G93A-expressing astrocytes show impaired capacity to raise BDNF and GDNF levels upon HMGB1 stimulation. Our data suggest that HMGB1 have a potential to promote neuroprotective actions by healthy astrocytes. However, this neurotrophic response is disrupted in ALS astrocytes. This indicates that diseased astroglial cells may exacerbate motor neuron degeneration in ALS because of the loss of their neurosupportive functions

Nucleosomes effectively shield DNA from radiation damage in living cells

Abstract Eukaryotic DNA is organized in nucleosomes, which package DNA and regulate its accessibility to transcription, replication, recombination and repair. Here, we show that in living cells nucleosomes protect DNA from high-energy radiation and reactive oxygen species. We combined sequence-based methods (ATAC-seq and BLISS) to determine the position of both nucleosomes and double strand breaks (DSBs) in the genome of nucleosome-rich malignant mesothelioma cells, and of the same cells partially depleted of nucleosomes. The results were replicated in the human MCF-7 breast carcinoma cell line. We found that, for each genomic sequence, the probability of DSB formation is directly proportional to the fraction of time it is nucleosome-free; DSBs accumulate distal from the nucleosome dyad axis. Nucleosome free regions and promoters of actively transcribed genes are more sensitive to DSB formation, and consequently to mutation. We argue that this may be true for a variety of chemical and physical DNA damaging agents

Personality dimensions and treatment drop-outs among eating disorder patients treated with cognitive behavior therapy

Abstract Premature, unilateral interruption of inpatient treatment of eating disorders (ED) is a key factor limiting success. We evaluated the role of personality dimensions (temperament and character) in predicting drop-out in 145 consecutive ED inpatients (133 females) who entered cognitive behavior therapy. Baseline assessment included anthropometry, the Eating Disorder Examination, the Beck Depression Inventory, the State-Trait Anxiety Inventory, and the Temperament and Character Inventory (TCI). Treatment was based on the new transdiagnostic cognitive behavior theory of ED, adapted for an inpatient setting; it was manual-based and lasted 20 weeks (13, inpatients; 7, residential day hospital). Thirty-four patients (23.4%) discontinued treatment. Drop-outs had a lower level of education, a higher prevalence of separation or divorce in the family, and lower scores on the TCI Persistence scale. After correction for age, gender and bodymass index, scores on the Persistence scale continued to be significantly related to drop-out, and the association was confirmed by KaplanMeier analysis. Eating disorder patients with low Persistence scores are significantly less likely to complete inpatient treatment