Waiting time information in the Italian NHS: A citizen perspective

Public involvement in the management and communication of waiting times is known to support initiatives to reduce waiting times, as well as increase fairness and promote transparency and accountability. In order to improve transparency and communication to citizens, Italy recently updated the National Regulatory Plan for Waiting Lists (2019–2021), which calls for the disclosure of waiting time information on healthcare provider webpages. This study analyses waiting time information for outpatient visits and digital services available on the institutional website pages of 144 public healthcare organisations in nine regions and two autonomous provinces of Italy. Web pages were analysed both in terms of the available information/services, using a grid, and in terms of the quality of the text using an advanced readability assessment tool (READ-IT). This information was complemented and validated by regional healthcare key informants during research-specific workshops. Waiting time information disclosure, digital services and text readability varied both within and between the regional healthcare systems and organisations. The types and characteristics of waiting time information and statistics vary considerably with a negative impact on their use for benchmarking and their readability and usability for booking purposes. Overall, communication weaknesses due to low harmonization and clarity of information can undermine efforts in effectively informing and involving the public through online waiting time data disclosure

Benchmarking and survey of explanation methods for black box models

The rise of sophisticated black-box machine learning models in Artificial Intelligence systems has prompted the need for explanation methods that reveal how these models work in an understandable way to users and decision makers. Unsurprisingly, the state-of-the-art exhibits currently a plethora of explainers providing many different types of explanations. With the aim of providing a compass for researchers and practitioners, this paper proposes a categorization of explanation methods from the perspective of the type of explanation they return, also considering the different input data formats. The paper accounts for the most representative explainers to date, also discussing similarities and discrepancies of returned explanations through their visual appearance. A companion website to the paper is provided as a continuous update to new explainers as they appear. Moreover, a subset of the most robust and widely adopted explainers, are benchmarked with respect to a repertoire of quantitative metrics

A psychological intervention based on cognitive-behavioural therapy reduces psychopathological symptoms that indirectly influence the heart rate via cortisol in hypertensive patients: Preliminary results of a pilot study

ObjectiveThis study aimed at assessing the effectiveness of cognitive-behavioural therapy (CBT) integrated with psychoeducation in a group of hypertensive patients with clinically significant psychopathological symptoms.MethodsOne hundred hypertensive patients completed the Symptom Checklist-90-Revised. Of them, 17 scored above the clinical range (cut-off = 0.75) on the Global Severity Index and were included in the study. Psychological distress was assessed again after the intervention (T1) and 6 months after the end of treatment (T2). In addition, the cortisol dosage and the heart rate (HR) measurement were collected at both T0 and T2. Then, mediation analyses were carried out to calculate whether psychopathological distress might predict HR through elevated serum cortisol levels, at both T0 and T2.ResultsThe psychological intervention (CBT integrated with psychoeducation) reduced most of the psychopathological symptoms (anxiety, depression, somatisations, obsessions and compulsions, hostility, interpersonal sensitivity and paranoid ideation) but not cortisol dosage and HR measurement. However, psychological distress indirectly predicted HR via cortisol at T0 but not at T2.ConclusionThese results suggest and encourage the replicability of data in larger sample sizes and the comparison with a control group. Nevertheless, these results highlight a need for a multidimensional assessment of disorders affecting the mental and physical spheres of patients to support their overall well-being

Stress-Induced Changes of Hippocampal NMDA Receptors: Modulation by Duloxetine Treatment

It is now well established that the glutamatergic system contributes to the pathophysiology of depression. Exposure to stress, a major precipitating factor for depression, enhances glutamate release that can contribute to structural abnormalities observed in the brain of depressed subjects. On the other hand, it has been demonstrated that NMDA antagonists, like ketamine, exert an antidepressant effect at preclinical and clinical levels. On these bases, the purpose of our study was to investigate whether chronic mild stress is associated with specific alterations of the NMDA receptor complex, in adult rats, and to establish whether concomitant antidepressant treatment could normalize such deficits. We found that chronic stress increases the expression of the obligatory GluN1 subunit, as well as of the accessory subunits GluN2A and GluN2B at transcriptional and translational levels, particularly in the ventral hippocampus. Concomitant treatment with the antidepressant duloxetine was able to normalize the increase of glutamatergic receptor subunit expression, and correct the changes in receptor phosphorylation produced by stress exposure. Our data suggest that prolonged stress, a condition that has etiologic relevance for depression, may enhance glutamate activity through post-synaptic mechanisms, by regulating NMDA receptors, and that antidepressants may in part normalize such changes. Our results provide support to the notion that antidepressants may exert their activity in the long-term also via modulation of the glutamatergic synapse

Stable and actionable explanations of black-box models through factual and counterfactual rules

Recent years have witnessed the rise of accurate but obscure classification models that hide the logic of their internal decision processes. Explaining the decision taken by a black-box classifier on a specific input instance is therefore of striking interest. We propose a local rule-based model-agnostic explanation method providing stable and actionable explanations. An explanation consists of a factual logic rule, stating the reasons for the black-box decision, and a set of actionable counterfactual logic rules, proactively suggesting the changes in the instance that lead to a different outcome. Explanations are computed from a decision tree that mimics the behavior of the black-box locally to the instance to explain. The decision tree is obtained through a bagging-like approach that favors stability and fidelity: first, an ensemble of decision trees is learned from neighborhoods of the instance under investigation; then, the ensemble is merged into a single decision tree. Neighbor instances are synthetically generated through a genetic algorithm whose fitness function is driven by the black-box behavior. Experiments show that the proposed method advances the state-of-the-art towards a comprehensive approach that successfully covers stability and actionability of factual and counterfactual explanations

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

Neurodevelopmental Outcome and Neuroimaging of Very Low Birth Weight Infants from an Italian NICU Adopting the Family-Centered Care Model

Background: Improvements in perinatal care have substantially decreased mortality rates among preterm infants, yet their neurodevelopmental outcomes and quality of life persist as a pertinent public health concern. Family-centered care has emerged as a holistic philosophy that promotes effective alliances among patients, families, and healthcare providers to improve the quality of care. Aims: This longitudinal prospective study aims to evaluate the neurodevelopmental outcomes and brain MRI findings in a cohort of preterm newborns admitted to a neonatal intensive care unit (NICU) adopting a family-centered care model. Methods: Very low birth weight (VLBW) infants admitted to the NICU of Modena between 2015 and 2020 were enrolled. Infants who underwent conventional brain magnetic resonance imaging (MRI) at term-equivalent age were included. Neurodevelopmental follow-up was performed until the age of 24 months by a multidisciplinary team using the Amiel-Tison neurological assessment and the Griffiths Mental Developmental Scales (GMDS-R). Neurodevelopmental outcomes were classified as major sequelae (cerebral palsy, DQ ≤ 70, severe sensory impairment), minor sequelae (minor neurological signs such as clumsiness or DQ between 71 and 85), and normal outcomes (no neurological signs and DQ > 85). Risk factors for severe outcomes were assessed. Results: In total, 49 of the 356 infants (13.8%) died before hospital discharge, and 2 were excluded because of congenital disorders. Of the remaining 305 infants, 222 (72.8%) completed the 24 month follow-up and were included in the study. Neurodevelopmental outcomes were classified as normal (n = 173, 77.9%), minor (n = 34, 15.3%), and major sequelae (n = 15, 6.8%). Among 221 infants undergoing brain MRI, 76 (34.4%) had major lesions (intraventricular hemorrhage, hemorrhagic parenchymal infarction, periventricular leukomalacia, and large cerebellar hemorrhage). In the multivariate regression model, the retinopathy of prematurity (OR 1.8; p value 0.016) and periventricular–intraventricular hemorrhage (OR 5.6; p value < 0.004) were associated with major sequelae. Conclusions: We reported low rates of severe neurodevelopmental outcomes in VLBW infants born in an Italian NICU with FCC. Identifying the risk factors for severe outcomes can assist in tailoring and optimizing early interventions on an individual basis, both within the NICU and after discharge

Correction to: Human migration: the big data perspective

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Nirmatrelvir treatment of SARS-CoV-2-infected mice blunts antiviral adaptive immune responses

Alongside vaccines, antiviral drugs are becoming an integral part of our response to the SARS-CoV-2 pandemic. Nirmatrelvir-an orally available inhibitor of the 3-chymotrypsin-like cysteine protease-has been shown to reduce the risk of progression to severe COVID-19. However, the impact of nirmatrelvir treatment on the development of SARS-CoV-2-specific adaptive immune responses is unknown. Here, by using mouse models of SARS-CoV-2 infection, we show that nirmatrelvir administration blunts the development of SARS-CoV-2-specific antibody and T cell responses. Accordingly, upon secondary challenge, nirmatrelvir-treated mice recruited significantly fewer memory T and B cells to the infected lungs and mediastinal lymph nodes, respectively. Together, the data highlight a potential negative impact of nirmatrelvir treatment with important implications for clinical management and might help explain the virological and/or symptomatic relapse after treatment completion reported in some individuals