Purpose/background: Based on a population-pharmacokinetic model, the European Medicines Agency has recently approved a simplified starting strategy of aripiprazole once a month (AOM), injectable and long-acting antipsychotic, with two 400 mg injections and a single oral 20 mg dose of aripiprazole, administered on the same day, instead of 1 injection and 14 daily administrations of concurrent oral aripiprazole. However, to our knowledge, no previous study has reported the safety and tolerability of this regimen in real-world patients. Methods/procedures: We retrospectively reviewed medical records of 133 patients who received the newly approved 2-injection start regimen as part of their standard care in 10 Italian clinical centers. Findings/results: Adverse effects were mild or moderate, with no clinically evident difference from the adverse effects observed in previous trials where AOM was started with a single injection followed by 14 days of orally administered aripiprazole. None of the patients who started AOM after the 2-injection start regimen experienced severe adverse effects or severe adverse effects. Implications/conclusions: The coadministration of 2 injections of 400 mg aripiprazole and 20 mg oral aripiprazole was not associated with safety concerns beyond those reported after a single injection followed by 14 days of orally administered aripiprazole. Our results should be interpreted with caution, due to the limited sample size and to the retrospective design of the study.
Background The relationships between problematic smartphone use and psychological factors have been extensively investigated. However, previous studies generally used variable-centered approaches, which hinder an examination of the heterogeneity of smartphone impact on everyday lives. Objective In the present study, we capitalized on latent profile analysis to identify various classes of smartphone owners based on the impact associated with smartphone use in their daily lives (e.g., unregulated usage, preference for smartphone-mediated social relationships) and to compare these classes in terms of established psychological risk factors for problematic smartphone use. Method We surveyed 934 young adults with validated psychometric questionnaires to assess the impact of smartphones, psychopathological symptoms, self-esteem and impulsivity traits. Results Smartphone users fall into four latent profiles: users with low smartphone impact, users with average smartphone impact, problematic smartphone users, and users favoring online interactions. Individuals distributed in the problematic smartphone user profile were characterized by heightened psychopathological symptoms (stress, anxiety, depression, obsessive-compulsive tendencies) and impulsivity traits. Moreover, users who preferred online interactions exhibited the highest symptoms of social anxiety and the lowest levels of self-esteem. Conclusions These findings further demonstrate the multidimensionality and heterogeneity of the impact of smartphone use, calling for tailored prevention and intervention strategies.
This study draws on the linguistics literature, which recognizes the role of language attributes in shaping individual behaviour. We theorize that weak-future languages (e.g., Chinese), which create the perception that the future is closer temporally to the present than do strong-future languages (e.g., English), favour future-oriented behaviours such as investment in crowdfunding of entrepreneurial ventures. To test this thesis, we use a mixed-method approach, combining an original dataset of crowdfunding investments in 53 countries (Study 1) and a randomized experiment examining the investment behaviour of 77 bilingual (English-Chinese) students (Study 2). We find that natives of countries with weak-future languages engage more actively in crowdfunding of entrepreneurial ventures compared to individuals from countries with strong-future languages. We find that this effect dominates the stable effect of national culture. In other words, perceiving the future as closer means that the future assumes greater psychological importance for weak-future speakers and, therefore, they enact more future-oriented behaviours.
Core-collapse Supernovae (SNe) are one of the most energetic events in the Universe, during which almost all the star's binding energy is released in the form of neutrinos. These particles are direct probes of the processes occurring in the stellar core and provide unique insights into the gravitational collapse. RES-NOVA will revolutionize how we detect neutrinos from astrophysical sources, by deploying the first ton-scale array of cryogenic detectors made from archaeological lead. Pb offers the highest neutrino interaction cross-section via coherent elastic neutrino-nucleus scattering (CEνNS). Such process will enable RES-NOVA to be equally sensitive to all neutrino flavours. For the first time, we propose the use archaeological Pb as sensitive target material in order to achieve an ultra-low background level in the region of interest (O(1 keV)). All these features make possible the deployment of the first cm-scale neutrino telescope for the investigation of astrophysical sources. In this contribution, we will characterize the radiopurity level and the performance of a small-scale proof-of-principle detector of RES-NOVA, consisting in a PbWO4 crystal made from archaeological-Pb operated as cryogenic detector.
The air in the Lombardy region, Italy, is one of the most polluted in Europe because of limited air circulation and high emission levels. There is a large scientific consensus that the agricultural sector has a significant impact on air quality. To support studies quantifying the role of the agricultural and livestock sectors on the Lombardy air quality, this paper presents a harmonised dataset containing daily values of air quality, weather, emissions, livestock, and land and soil use in the years 2016–2021, for the Lombardy region. The daily scale is obtained by averaging hourly data and interpolating other variables. In fact, the pollutant data come from the European Environmental Agency and the Lombardy Regional Environment Protection Agency, weather and emissions data from the European Copernicus programme, livestock data from the Italian zootechnical registry, and land and soil use data from the CORINE Land Cover project. The resulting dataset is designed to be used as is by those using air quality data for research.
Objectives Amyloid light chain (AL)-κ and AL-λ share common histopathologic changes; however, the potential difference in clinical manifestations, histologic findings, and clinical significance between the 2 subtypes remain unclear. Methods In a retrospective study, 94 kidney biopsies for AL amyloidosis were evaluated using the composite scarring injury score (CSIS) and amyloid score (AS). Results were then compared between AL-κ and AL-λ. Results Comparing AS and CSIS between AL-κ and AL-λ, the AS was significantly higher in AL-κ than in AL-λ, with 2 components of AS (capillary wall and vascular amyloid) scoring higher in AL-κ than in AL-λ, while mesangial and interstitial ASs were similar in the 2 cohorts. In addition, the proportion of periodic acid–Schiff strong-staining amyloid in AL-κ was markedly higher than in AL-λ. There was no significant difference in CSIS and its components between the 2 subtypes of AL amyloidosis. Conclusions Overall, AL-κ presents with higher serum creatinine and a higher AS score than AL-λ at biopsy, which may indicate a worse prognosis and be an important reference for clinical management.
Purpose The aim of this study is to investigate the role of [⁶⁸Ga]Ga-PSMA-11 PET radiomics for the prediction of post-surgical International Society of Urological Pathology (PSISUP) grade in primary prostate cancer (PCa). Methods This retrospective study included 47 PCa patients who underwent [⁶⁸Ga]Ga-PSMA-11 PET at IRCCS San Raffaele Scientific Institute before radical prostatectomy. The whole prostate was manually contoured on PET images and 103 image biomarker standardization initiative (IBSI)-compliant radiomic features (RFs) were extracted. Features were then selected using the minimum redundancy maximum relevance algorithm and a combination of the 4 most relevant RFs was used to train 12 radiomics machine learning models for the prediction of PSISUP grade: ISUP ≥ 4 vs ISUP < 4. Machine learning models were validated by means of fivefold repeated cross-validation, and two control models were generated to assess that our findings were not surrogates of spurious associations. Balanced accuracy (bACC) was collected for all generated models and compared with Kruskal–Wallis and Mann–Whitney tests. Sensitivity, specificity, and positive and negative predictive values were also reported to provide a complete overview of models’ performance. The predictions of the best performing model were compared against ISUP grade at biopsy. Results ISUP grade at biopsy was upgraded in 9/47 patients after prostatectomy, resulting in a bACC = 85.9%, SN = 71.9%, SP = 100%, PPV = 100%, and NPV = 62.5%, while the best-performing radiomic model yielded a bACC = 87.6%, SN = 88.6%, SP = 86.7%, PPV = 94%, and NPV = 82.5%. All radiomic models trained with at least 2 RFs (GLSZM—Zone Entropy and Shape—Least Axis Length) outperformed the control models. Conversely, no significant differences were found for radiomic models trained with 2 or more RFs (Mann–Whitney p > 0.05). Conclusion These findings support the role of [⁶⁸Ga]Ga-PSMA-11 PET radiomics for the accurate and non-invasive prediction of PSISUP grade.
Human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (CM) constitute a mixed population of ventricular-, atrial-, nodal-like cells, limiting the reliability for studying chamber-specific disease mechanisms. Previous studies characterised CM phenotype based on action potential (AP) morphology, but the classification criteria were still undefined. Our aim was to use in silico models to develop an automated approach for discriminating the electrophysiological differences between hiPSC-CM. We propose the dynamic clamp (DC) technique with the injection of a specific IK1 current as a tool for deriving nine electrical biomarkers and blindly classifying differentiated CM. An unsupervised learning algorithm was applied to discriminate CM phenotypes and principal component analysis was used to visualise cell clustering. Pharmacological validation was performed by specific ion channel blocker and receptor agonist. The proposed approach improves the translational relevance of the hiPSC-CM model for studying mechanisms underlying inherited or acquired atrial arrhythmias in human CM, and for screening anti-arrhythmic agents.
Abstract Background Less invasive alternatives than early cholecystectomy (EC) for acute calculous cholecystitis (ACC) treatment have been spreading in recent years. We still lack a reliable tool to select high-risk patients who could benefit from these alternatives. Our study aimed to prospectively validate the Chole-risk score in predicting postoperative complications in patients undergoing EC for ACC compared with other preoperative risk prediction models. Method The S.P.Ri.M.A.C.C. study is a World Society of Emergency Surgery prospective multicenter observational study. From 1st September 2021 to 1st September 2022, 1253 consecutive patients admitted in 79 centers were included. The inclusion criteria were a diagnosis of ACC and to be a candidate for EC. A Cochran-Armitage test of the trend was run to determine whether a linear correlation existed between the Chole-risk score and a complicated postoperative course. To assess the accuracy of the analyzed prediction models—POSSUM Physiological Score (PS), modified Frailty Index, Charlson Comorbidity Index, American Society of Anesthesiologist score (ASA), APACHE II score, and ACC severity grade—receiver operating characteristic (ROC) curves were generated. The area under the ROC curve (AUC) was used to compare the diagnostic abilities. Results A 30-day major morbidity of 6.6% and 30-day mortality of 1.1% were found. Chole-risk was validated, but POSSUM PS was the best risk prediction model for a complicated course after EC for ACC (in-hospital mortality: AUC 0.94, p
Low-dimensional copper oxide nanostructures are very promising building blocks for various functional materials targeting high-demanded applications, including energy harvesting and transformation systems, sensing and catalysis. Featuring a very high surface-to-volume ratio and high chemical reactivity, these materials have attracted wide interest from researchers. Currently, extensive research on the fabrication and applications of copper oxide nanostructures ensures the fast progression of this technology. In this article we briefly outline some of the most recent, mostly within the past two years, innovations in well-established fabrication technologies, including oxygen plasma-based methods, self-assembly and electric-field assisted growth, electrospinning and thermal oxidation approaches. Recent progress in several key types of leading-edge applications of CuO nanostructures, mostly for energy, sensing and catalysis, is also reviewed. Besides, we briefly outline and stress novel insights into the effect of various process parameters on the growth of low-dimensional copper oxide nanostructures, such as the heating rate, oxygen flow, and roughness of the substrates. These insights play a key role in establishing links between the structure, properties and performance of the nanomaterials, as well as finding the cost-and-benefit balance for techniques that are capable of fabricating low-dimensional CuO with the desired properties and facilitating their integration into more intricate material architectures and devices without the loss of original properties and function.
Cooperation is one of the most advantageous strategies to have evolved in small-and large-scale human societies, often considered essential to their success or survival. We investigated how cooperation and the mechanisms influencing it change across the lifespan, by assessing cooperative choices from adolescence to old age (12-79 years, N = 382) forcing participants to decide either intuitively or deliberatively through the use of randomised time constraints. As determinants of these choices, we considered participants' level of altruism, their reciprocity expectations, their optimism, their desire to be socially accepted, and their attitude toward risk. We found that intuitive decision-making favours cooperation, but only from age 20 when a shift occurs: whereas in young adults, intuition favours cooperation, in adolescents it is reflection that favours cooperation. Participants' decisions were shown to be rooted in their expectations about other people's cooperative behaviour and influenced by individuals' level of optimism about their own future, revealing that the journey to the cooperative humans we become is shaped by reciprocity expectations and individual predispositions.
Purpose The present study examined the longitudinal trajectories, through hierarchical modeling, of quality of life among patients with head and neck cancer, specifically symptoms burden, during radiotherapy, and in the follow-up period (1, 3, 6, and 12 months after completion of radiotherapy), through the M.D. Anderson Symptom Inventory Head and Neck questionnaire, formed by three factors. Furthermore, analyses were conducted controlling for socio-demographic as well as clinical characteristics. Methods Multi-level mixed-effects linear regression was used to estimate the association between quality of life and time, age, gender, household, educational level, employment status, ECOG performance status, human papilloma virus (HPV) status, surgery, chemotherapy, alcohol intake, and smoking. Results Among the 166 participants, time resulted to be a predictor of all the three questionnaire factors, namely, general and specific related symptoms and interference with daily life. Moreover, regarding symptom interference with daily activities factor, HPV-positive status played a significant role. Considering only HPV-negative patients, only time predicted patients’ quality of life. Differently, among HPV-positive patients, other variables, such as gender, educational level, alcohol use, surgery, age at diagnosis, employment status, and ECOG status, resulted significant. Conclusion It was evident that quality of life of patients with head and neck cancer declined during RT, whereas it slowly improved after ending treatment. Our results clarified the role of some socio-demographic and clinical variables, for instance, HPV, which would allow to develop treatments tailored to each patient.
Background Longitudinal single-cell sequencing experiments of patient-derived models are increasingly employed to investigate cancer evolution. In this context, robust computational methods are needed to properly exploit the mutational profiles of single cells generated via variant calling, in order to reconstruct the evolutionary history of a tumor and characterize the impact of therapeutic strategies, such as the administration of drugs. To this end, we have recently developed the LACE framework for the Longitudinal Analysis of Cancer Evolution. Results The LACE 2.0 release aimed at inferring longitudinal clonal trees enhances the original framework with new key functionalities: an improved data management for preprocessing of standard variant calling data, a reworked inference engine, and direct connection to public databases. Conclusions All of this is accessible through a new and interactive Shiny R graphical interface offering the possibility to apply filters helpful in discriminating relevant or potential driver mutations, set up inferential parameters, and visualize the results. The software is available at: github.com/BIMIB-DISCo/LACE.
Much of Earth’s carbon may have been stripped away from the silicate mantle by dense metallic-iron during core formation. However, at deep magma ocean conditions carbon becomes less siderophile and thus large amounts of it may be stranded instead in the deep mantle. Here, we describe the structure and compaction mechanisms of carbonate glass to deep mantle pressures. Our results, based on non-resonant inelastic X-ray scattering, X-ray diffraction and ab initio calculations, demonstrate a pressure-induced change in hybridization of carbon from sp² to sp³ starting at 40 GPa, due to the conversion of CO3²⁻ groups into CO4⁴⁻ units, which is completed at ~112 GPa. The pressure-induced change of carbon coordination number from three to four increases possibilities for carbon-oxygen interactions with lower mantle silicate melts. sp³ hybridized carbon provides a mechanism for changing the presumed siderophile nature of deep carbon, becoming a possible source for carbon-rich emissions registered at the surface in intra-plate and near-ridge hot spots.
Purpose This study tested the efficacy of digital-health home intervention for people within the Alzheimer’s disease (AD)-continuum. Methods Thirty people within the AD continuum were randomly assigned to a telerehabilitation (ABILITY; 6 males, Mage=78.2 ± 3.95) or treatment as usual (TAU; 8 males, Mage=77.13 ± 6.38), performing cognitive and physical activities at home for six weeks. The ABILITY intervention additionally included a digital platform enabling communication between the hospital and the patient’s home. Efficiency, such as adherence, perceived fit of demands and skills, usability, and effectiveness measures, including neuropsychological level, neuropsychiatric symptoms, and autonomy in daily living, were collected before (T0), after the treatment (T1), and at the 1-year-follow-up (T2). Results The ABILITY program was efficient, with a higher adherence (81% vs. 62%), a higher perceived fit of demands and skills than TAU (p<.05), and a good level of technology usability. In terms of effectiveness, a treatment effect (ABILITY > TAU) emerged on the global cognitive level, especially in language, executive functions, and memory domains. Moreover, a treatment carry-over effect (1-year follow-up) was observed in global cognitive functions (especially language) (ABILITY > TAU), behavioral symptoms, and caregiver distress (TAU > ABILITY). Conclusions Our preliminary findings suggest that ABILITY is a promising eHealth intervention to improve at-home treatment adherence and to preserve cognitive and behavioral abilities.
The main objective of the paper is to identify the logic of the sociological field in the GDR, looking at how it was spatialized in the city of East Berlin. In this regard, I am less interested in providing an overview of the different research streams of the main sociologists operating in the scientific and academic institutes located in Berlin than in reconstructing some crucial dynamics at work there and highlighting their effects at the social and symbolic levels. The underlying idea is that, especially in East Berlin, the sociological knowledge produced was less homogeneous than it has been represented in the existing literature. Without negating the existence of shared aspects characterizing Marxist-Leninist sociology, also superimposed on the political elite, a field analysis enables us to see how the different positions and trajectories of GDR-sociologists had an impact on their approaches to theoretical, epistemological, and methodological questions, and on their understanding and uses of concepts deriving from both Marxist-Leninist and "bourgeois" sociology. In the analysis, I will first compare the social trajectories of two of my interview-partners as paradigmatic of two different sociological habitus depending on their different academic/political socialization, networks, and positions in the field. As a second step, I will present a sketch of the sociological field drawn from 63 curricula of sociologists active in East Berlin in an attempt to pinpoint, on a larger scale, the homologies between the social and symbolic spaces of the field. Thus, the underlying idea is to examine the intersection of the "quasi-structural properties" of the field with its "phenomenological aspects" concerning the "feel for the game." While the two understandings of field are interdependent, it is in the second one that the physical space as a localized social space played a crucial role in defining the material, social, and cultural constraints and opportunities actors faced which, in turn, influenced their practices and choices.
A Composite Indicator (CI) is a useful tool to synthesize information on a multidimensional phenomenon and make policy decisions. Multidimensional phenomena are often modeled by hierarchical latent structures that reconstruct relationships between variables. In this paper, we propose an exploratory, simultaneous model for building a hierarchical CI system to synthesize a multidimensional phenomenon and analyze its several facets. The proposal, called the Ultrametric Composite Indicator (UCI) model, reconstructs the hierarchical relationships among manifest variables detected by the correlation matrix via an extended ultrametric correlation matrix. The latter has the feature of being one-to-one associated with a hierarchy of latent concepts. Furthermore, the proposal introduces a test to unravel relevant dimensions in the hierarchy and retain statistically significant higher-level CIs. A simulation study is illustrated to compare the proposal with other existing methodologies. Finally, the UCI model is applied to study Italian municipalities’ behavior toward waste management and to provide a tool to guide their councils in policy decisions.
This article reviews the current knowledge state on pragmatic and structural language abilities in autism and their potential relation to extralinguistic abilities and autistic traits. The focus is on questions regarding autism language profiles with varying degrees of (selective) impairment and with respect to potential comorbidity of autism and language impairment: Is language impairment in autism the co-occurrence of two distinct conditions (comorbidity), a consequence of autism itself (no comorbidity), or one possible combination from a series of neurodevelopmental properties (dimensional approach)? As for language profiles in autism, three main groups are identified, namely, (i) verbal autistic individuals without structural language impairment, (ii) verbal autistic individuals with structural language impairment, and (iii) minimally verbal autistic individuals. However, this tripartite distinction hides enormous linguistic heterogeneity. Regarding the nature of language impairment in autism, there is currently no model of how language difficulties may interact with autism characteristics and with various extralinguistic cognitive abilities. Building such a model requires carefully designed explorations that address specific aspects of language and extralinguistic cognition. This should lead to a fundamental increase in our understanding of language impairment in autism, thereby paving the way for a substantial contribution to the question of how to best characterize neurodevelopmental disorders.
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