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Objective: Aberrant activity of androgen receptor (AR) is the primary cause underlying development and progression of prostate cancer (PCa) and castration-resistant PCa (CRPC). Androgen signaling regulates gene transcription and lipid metabolism, facilitating tumor growth and therapy resistance in early and advanced PCa. Although direct AR signaling inhibitors exist, AR expression and function can also be epigenetically regulated. Specifically, lysine (K)-specific demethylases (KDMs), which are often overexpressed in PCa and CRPC phenotypes, regulate the AR transcriptional program. Methods: We investigated LSD1/UTX inhibition, two KDMs, in PCa and CRPC using a multi-omics approach. We first performed a mitochondrial stress test to evaluate respiratory capacity after treatment with MC3324, a dual KDM-inhibitor, and then carried out lipidomic, proteomic, and metabolic analyses. We also investigated mechanical cellular properties with acoustic force spectroscopy. Results: MC3324 induced a global increase in H3K4me2 and H3K27me3 accompanied by significant growth arrest and apoptosis in androgen-responsive and -unresponsive PCa systems. LSD1/UTX inhibition downregulated AR at both transcriptional and non-transcriptional level, showing cancer selectivity, indicating its potential use in resistance to androgen deprivation therapy. Since MC3324 impaired metabolic activity, by modifying the protein and lipid content in PCa and CRPC cell lines. Epigenetic inhibition of LSD1/UTX disrupted mitochondrial ATP production and mediated lipid plasticity, which affected the phosphocholine class, an important structural element for the cell membrane in PCa and CRPC associated with changes in physical and mechanical properties of cancer cells. Conclusions: Our data suggest a network in which epigenetics, hormone signaling, metabolite availability, lipid content, and mechano-metabolic process are closely related. This network may be able to identify additional hotspots for pharmacological intervention and underscores the key role of KDM-mediated epigenetic modulation in PCa and CRPC.

A runway pavement during its useful life is subject to a series of deteriorations because of repeated load cycles and environmental conditions. One of the most common deteriorations is the formation of rutting (surface depression in the wheel path) on the runway surface. Rutting negatively affects aircraft performance during landings and will behave even worse during precipitation or with the existence of fluid contaminations on the surface. This paper aims to develop a model for calculating aircraft braking distance during landing on wet-pavement runways affected by rutting based on dynamic skid resistances generated by tire–fluid–pavement interactions. Intense precipitation, variable rutting depths for a 100 m length step, water film depths (e.g., 1 to 26 mm), and aircraft wheel loads (e.g., 10 to 140 kN) are considered as the boundary conditions of the developed model. The output is a model that can estimate aircraft braking distance as a function of rutting depth and can perform further assessment of the probability of the occurrence of landing overrun. After validating the model with existing methodologies and calibrating it according to the actual landing distance required for each type of aircraft, an Italian airport is simulated using a model with real data regarding the level of service of its pavement surface characteristics.

Background: There is a lack of data regarding patients aged 90 years or older undergoing mechanical thrombectomy and their predictors of futile recanalization. Aims: We sought to evaluate the predictors of futile recanalization in patients ≥ 90 years with large vessel occlusion undergoing mechanical thrombectomy. Methods: This multi-center observational retrospective study included patients ≥ 90 years consecutively treated with mechanical thrombectomy in four thrombectomy capable centers between January 1st, 2016 and 30th March 2023. Futile recanalization was defined as large vessel occlusion patients experiencing a 90-day poor outcome (mRS 3–6) despite successful recanalization (mTICI ≥ 2b) after mechanical thrombectomy. Results: Our cohort included 139 patients ≥ 90 years with acute ischemic stroke due to anterior circulation large vessel occlusion treated with mechanical thrombectomy. One hundred seventeen of one hundred thirty-nine patients ≥ 90 years who achieved successful recanalization were included in the analysis (seventy-six female (64.9%)), of whom thirty-one (26.49%) experienced effective recanalization and eighty-six (73.51%) experienced futile recanalization. Patients with futile recanalization had higher NIHSS on admission (p < 0.001); they were less frequently treated with intravenous thrombolysis (p = 0.048), had more often general anesthesia (p = 0.011), and longer door to groin puncture delay (p = 0.002). Univariable regression analysis showed that use of intravenous thrombolysis (0.29, 95% CI 0.02–0.79, p = 0.034) and site of occlusion distal vs proximal (0.34, 95% CI 0.11–0.97, p = 0.044) were associated with reduced probability of futile recanalization while NIHSS on admission (1.29, 95% CI 1.16–1.45, p < 0.001), NIHSS at 24 h (1.15, 95% CI 1.07–1.25, p = 0.002), type of anesthesia used (4.18, 95% CI 1.57–11.08, p = 0.004), and door to groin puncture time (1.02, 95% CI 1.00–1.05, p = 0.005) were associated with increased probability of futile recanalization. Multivariable regression analysis showed that use of intravenous thrombolysis (0.44, 95% CI 0.09–0.88, p = 0.039) was associated with reduced probability of futile recanalization. Conclusion: Our study seems to suggest that mechanical thrombectomy with intravenous thrombolysis is associated with reduced probability of futile recanalization in a multi-center cohort of patients aged 90 years or older. [ABSTRACT FROM AUTHOR]

This study aims to establish an effective approach for evaluating the safety performance of road infrastructure. Road safety levels are typically quantified using safety performance indicators. However, due to the stochastic nature of accidents, many safety performance indicators cannot adequately and completely describe reality. Therefore, predictive methods based on regression models are widely used. This approach also allows for the identification of latent risk conditions in the infrastructure, even in the absence of accidents. Among available approaches, the Highway Safety Manual (HSM) methodology is chosen for its synthesis of validated highway research and best practices for incorporating safety into both new design and rehabilitation. For this study, a preliminary new version of HSM is used. The application of this method, which combines a predictive model with observed accidents through an empirical Bayesian approach, requires a calibration process that is crucial to tailoring this method to the specific study context. In this research, the predictive model is calibrated for single carriageway roads with one lane per direction across the Italian national network. Following calibration, the safety indicators are evaluated. The results obtained according to different indicators are compared to show the importance of adopting this method to counteract the regression to the mean of observed crashes. In fact, the method, supported by empirical Bayesian analysis, enables the identification of high-risk sections of the road network, selecting more sections that would be neglected by traditional indicators based solely on observed crashes. Finally, a possible approach to prioritizing sites for inspection based both on the excess of crashes and the Safety Potential (SAPO) is proposed. In addition, SAPO is adjusted to local conditions to account for the specific context and the decreasing trend of accidents over the years. [ABSTRACT FROM AUTHOR]

The adhesive properties of tack coats between asphalt pavement layers are crucial for the pavement's structural behavior. This study first involved numerical analyses to compare stress patterns, deformations, and displacements in the pavement structure under various geometric and mechanical conditions. A rational calculation method based on the theory of elastic multilayer systems was used to quantify the impact of layer properties such as thickness, stiffness modulus, and Poisson's ratio on interlayer bonding. Three bonding conditions—Full Friction, Partial Bonding, and Full Debonding—were analyzed to understand the tack coat's effect between the top two layers. The second phase involved characterizing the mechanical behavior of the interface through shear strength tests (Leutner shear test) on both laboratory-prepared specimens and samples from a 10-year-old highway. Specimens were prepared using a Roller Compactor and tested under different interface conditions: hot-on-hot (H/H), residual bitumen 200 g/m2 (RB 200), and residual bitumen 400 g/m2 (RB 400). The tests examined the bonding effects in terms of tangential force and shear displacement at failure, as well as the impact of vehicular traffic on rutting and fatigue failure. Finally, this study investigated the long-term aging effects of the binder on interlayer bonding and sought to correlate the results of numerical calculations with those of the laboratory tests. [ABSTRACT FROM AUTHOR]

In this paper, the effectiveness of reinforcements for flexible pavements is evaluated through an analysis of reflective cracking. Different stiffness and thickness reinforcements are considered for the rehabilitation of an already cracked pavement. The effect of the reinforcement is assessed from two different perspectives: (i) the ability to reduce stresses in the rehabilitated pavement layers, and (ii) the capacity to mitigate the crack propagation from deeper layers. A finite element model (FEM) is adopted to study the stress and strain state of the pavement layers. The pavement model has been properly validated, transitioning from a simply supported beam scheme to an elastic multilayer model. In addition, to represent crack propagation, fracture evolution is analyzed using Linear Elastic Fracture Mechanics (LEFMs) and Paris' law. The effect of different reinforcements on the pavement is then simulated. The results show that the reinforcement performance is strictly dependent on the interlayer thickness and stiffness. In particular, high stiffness reinforcements (geomembranes) show increasing effectiveness with stiffness, both in terms of reflective cracking and stress reduction. Conversely, low stiffness reinforcements (SAMIs) show a variable trend with the stiffness modulus. In fact, extremely low stiffness is effective in slowing down crack propagation but is detrimental to the wearing course's stress condition. However, as the stiffness increases, the likelihood of cracking in the wearing course decreases, though only a small beneficial effect is registered for crack propagation in the base layer. [ABSTRACT FROM AUTHOR]

We propose a novel steplength selection rule in proximal gradient methods for minimizing the sum of a differentiable function plus an $ \def\bigtimes{{\Huge \times}} \def\operatornamewithlimits#1{\mathop{\rm #1}\limits} \ell _1 $ ℓ 1 -norm penalty term. The proposed rule modifies one of the classical Barzilai–Borwein steplength, extending analogous results obtained in the context of gradient projection methods for constrained optimization. We analyse the spectral properties of the Barzilai–Borwein-like steplength when the differentiable part is quadratic, showing that its reciprocal lies in the spectrum of the submatrix of the Hessian that depends on both the nonzero and the nonoptimal zero components of the current iterate, allowing for acceleration effects when the optimal zero components start to be identified. Furthermore, we insert the modified rule into a proximal gradient method with a nonmonotone line search, for which we prove global convergence towards a stationary point. Numerical experiments show the ability of the proposed rule to sweep the spectrum of the reduced Hessian on a series of quadratic $ \ell _1 $ ℓ 1 -regularized problems, as well as its effectiveness in recovering the ground truth in a least squares regularized problem arising in image restoration. [ABSTRACT FROM AUTHOR]

Obstructive sleep apnea (OSA) syndrome is a condition characterized by the presence of repeated complete or partial collapse of the upper airways during sleep associated with episodes of intermittent hypoxia, leading to fragmentation of sleep, sympathetic nervous system activation, and oxidative stress. To date, one of the major aims of research is to find out a simplified non-invasive screening system for this still underdiagnosed disease. The Berlin questionnaire (BQ) is the most widely used questionnaire for OSA and is a beneficial screening tool devised to select subjects with a high likelihood of having OSA. We administered the original ten-question Berlin questionnaire, enriched with a set of questions purposely prepared by our team and completing the socio-demographic, clinical, and anamnestic picture, to a sample of Italian professional nurses in order to investigate the possible impact of OSA disease on healthcare systems. According to the Berlin questionnaire, respondents were categorized as high-risk and low-risk of having OSA. For both risk groups, baseline characteristics, work information, clinical factors, and symptoms were assessed. Anthropometric data, work information, health status, and symptoms were significantly different between OSA high-risk and low-risk groups. Through supervised feature selection and Machine Learning, we also reduced the original BQ to a very limited set of items which seem capable of reproducing the outcome of the full BQ: this reduced group of questions may be useful to determine the risk of sleep apnea in screening cases where questionnaire compilation time must be kept as short as possible.

Developmental dyslexia can be viewed as the result of the effects of single deficits or multiple deficits. This study presents a test of the applicability of a multifactor-interactive model (MFi-M) with a preliminary set of five variables corresponding to different neuropsychological functions involved in the reading process. The model has been tested on a sample of 55 school-age children with developmental dyslexia. The results show that the data fit a model in which each variable contributes to the reading ability in a non-additive but rather interactive way. These findings constitute a preliminary validation of the plausibility of the MFi-M, and encourage further research to add relevant factors and specify their relative weights. It is further discussed how subtype-based intervention approaches can be a suitable and advantageous framework for clinical intervention in a MFi-M perspective.

There is strong evidence that homocysteine is a risk factor not only for cerebrovascular diseases but also for degenerative dementias. A recent consensus statement renewed the importance and the role of high levels of homocysteine in cognitive decline in several forms of degenerative dementia, such as Alzheimer’s disease. Although the molecular mechanisms by which homocysteine causes cell dysfunction are known, both the impact of homocysteine on specific cognitive functions and the relationship between homocysteine level and non-Alzheimer dementias have been poorly investigated. Most of the studies addressing the impact of hyperhomocysteinemia on dementias have not examined the profile of performance across different cognitive domains, and have only relied on screening tests, which provide a very general and coarse-grained picture of the cognitive status of the patients. Yet, trying to understand whether hyperhomocysteinemia is associated with the impairment of specific cognitive functions would be crucial, as it would be, in parallel, learning whether some brain circuits are particularly susceptible to the damage caused by hyperhomocysteinemia. These steps would allow one to (i) understand the actual role of homocysteine in the pathogenesis of cognitive decline and (ii) improve the diagnostic accuracy, differential diagnosis and prognostic implications. This review is aimed at exploring and revising the state of the art of these two strictly related domains. Suggestions for future research are provided.

Because of its anabolic effects on muscle, testosterone is being explored as a function-promoting anabolic therapy for functional limitations associated with aging; however, concerns about testosterone's adverse effects on prostate have inspired efforts to develop strategies that selectively increase muscle mass while sparing the prostate. Testosterone's promyogenic effects are mediated through upregulation of follistatin. We show here that the administration of recombinant follistatin (rFst) increased muscle mass in mice, but had no effect on prostate mass. Consistent with the results of rFst administration, follistatin transgenic mice with constitutively elevated follistatin levels displayed greater muscle mass than controls, but had similar prostate weights. To elucidate signaling pathways regulated differentially by testosterone and rFst in prostate and muscle, we performed microarray analysis of mRNAs from prostate and levator ani of castrated male mice treated with vehicle, testosterone, or rFst. Testosterone and rFst shared the regulation of many transcripts in levator ani; however, in prostate, 593 transcripts in several growth-promoting pathways were differentially expressed after testosterone treatment, while rFst showed a negligible effect with only 9 transcripts differentially expressed. Among pathways that were differentially responsive to testosterone in prostate, we identified ornithine decarboxylase (Odc1), an enzyme in polyamine biosynthesis, as a testosterone-responsive gene that is unresponsive to rFst. Accordingly, we administered testosterone with and without α-difluoromethylornithine (DFMO), an Odc1 inhibitor, to castrated mice. DFMO selectively blocked testosterone's effects on prostate, but did not affect testosterone's anabolic effects on muscle. Co-administration of testosterone and Odc1 inhibitor presents a novel therapeutic strategy for prostate-sparing anabolic therapy.

Wound closure in plant stems (after either fire or mechanical damage) is a complex, multi-scale process that involves the formation of a callous tissue (callus lips) responsible for cell proliferation and overgrowth at the injury edges, resulting in coverage of the scarred tissue. Investigating such phenomena, it is difficult to discriminate between cell-specific growth responses, associated with physiological adaptations, and cell proliferation reactions emerging from specific cambium dynamics due to changes in mechanical constrains. In particular, the effects of cell-cell mechanical interactions on the wound closure process have never been investigated. To understand to what extent callus lip formation depends on the intra-tissue mechanical balance of forces, we built a simplified individual-based model (IBM) of cell division and differentiation in a generic woody tissue. Despite its simplified physiological assumptions, the model was capable to simulate callus hyperproliferation and wound healing as an emergent property of the mechanical interactions between individual cells. The model output suggests that the existence of a scar alone does constrain the growth trajectories of the remaining proliferating cells around the injury, thus resulting in the wound closure, ultimately engulfing the damaged tissue in the growing stem.

To achieve sustainable development in the road sector, the use of Electric Vehicles (EVs) appears as a positive response to transport emissions. Among the available technologies, dynamic charging seems to overcome the main weakness points of EVs, even if it requires that traditional roads (t-roads) be equipped with a system providing electricity for EVs. Thus, so-called electrified roads (e-roads) must be implemented into the urban road networks. Since it is not possible to electrify all roads simultaneously, and also to consider the demand needs of citizens, a selection criterion is essential. This research describes and develops a simple, self-explanatory, repeatable, and adaptable selection criterion aimed at helping city managers in prioritizing the roads of an urban network to be upgraded from t-road to e-road status. This method belongs to the so-called Multicriteria Spatial Decision Support Systems (MC-SDSS)—processes useful for solving spatial problems through the integration of multicriteria analysis (Fuzzy Analytic Hierarchy Process, F-AHP) with a geo-referenced data management and analysis tool (GIS). The developed algorithm is based on several criteria related to the infrastructure/transport, social and environmental areas. The result of the implemented method is a Feasibility Index (FI), able to prioritize the roads most eligible to be upgraded as e-roads, as also verified by its application on the urban area of Milan (Italy).

According to the registered databases of air accidents around the world, landing overruns are the most probable accidents among all runway excursion events. Although new aircraft are enhanced with the latest technologies that improve the maneuvers safety, the frequency of landing overruns are bound to increase because of the ascending growth rate of annual traffic. The principal scope of this paper is to evaluate the functionality of Engineered Materials Arresting System (EMAS) as a mitigation strategy to reduce the possible consequences of landing overrun events and in particular to determine if installing an EMAS can help land-locked airports to meet Federal Aviation Administration (FAA) recommendations in order to upgrade their Runway End Safety Areas (RESAs). In the previous studies, not enough investigations are dedicated to predicting the behavior of the aircraft and its deceleration rate after interfering EMAS and how different materials as arrestor beds would modify aircraft braking distance in RESA. Therefore, secondary objective of this paper is to determine the most optimum height of EMAS slabs, in function of execution costs and accident severity reduction rate. In this regard, a MATLAB®-based numerical code, which simulate the tire-pavement interface, is developed in order to evaluate the functionality of EMAS for aircraft ground maneuvers. Although this code is developed for both dry and wet runway conditions, dry runway’s surface is selected as the boundary condition of this study. It simulates aircraft arresting distance by calculating a dynamic skid resistance between aircraft main gear and runway pavement with a fix time step. The results are plotted as risk contour intervals on the layout of EMAS that is installed at the RESA. In addition, this numerical code is adopted in order to perform a sensitivity analysis on five arresting bed materials, which consist of three low-density concretes with maximum crushing stress thresholds of 172500, 345000 and 930000 Pa, one gravel-based material and one foam aggregate-based mixture. Among all, low-density concrete with the highest crushing strength causes shorter aircraft arresting distance.