Everything changes but nothing changes: gender stereotypes in the Italian population.

PURPOSE: Gender stereotypes refer to consensual or cultural shared beliefs about the attributes of men and women, influencing society behaviors, interpersonal relationships, education, and workplace. The literature has shown the existence of gender stereotypes on career choices, internalization of roles, and school and social experiences and demonstrates the impact of demographic factors on stereotypes. However, all the studies conducted in Italy available in scientific literature analyzed small sample sizes within specific schools of university settings, with a limited age range. METHODS: To assess the current state of gender stereotypes in Italy, we conducted an online survey from October 2022 to January 2023 on the general population residing in Italy. The questionnaire comprised sociodemographic factors and questions about gender stereotypes, investigating six fields: games, jobs, personality traits, home and family activities, sports, and moral judgments. RESULTS: The study involved 1854 participants, mostly women (70.1%) with an undergraduate or postgraduate degree (57.5%). The statistical and descriptive analyses revealed that gender stereotypes influenced respondents' beliefs, with statistically significant effects observed in most questions when stratifying by age, gender, and degree. Principal component analysis was performed to assess latent variables in different fields, revealing significant main stereotypes in each category. No statistically significant differences between men and women were found for the fields home and family activities, games, and moral judgments, confirming that stereotypes affect both men and women in the same way. CONCLUSIONS: Our results show the persistence of gender stereotypes in any fields investigated, although our cohort is predominantly composed of high educational level women living in the North of Italy. This demonstrates that the long-standing gender stereotypes are prevalent, pernicious, and, unfortunately, internalized at times even by successful women pushbacking and sabotaging them unconsciously.

Looking back and beyond the 2017 diagnostic criteria for hypermobile Ehlers-Danlos syndrome: A retrospective cross-sectional study from an Italian reference center.

The most common conditions with symptomatic joint hypermobility are hypermobile Ehlers-Danlos syndrome (hEDS) and hypermobility spectrum disorders (HSD). Diagnosing these overlapping connective tissue disorders remains challenging due to the lack of established causes and reliable diagnostic tests. hEDS is diagnosed applying the 2017 diagnostic criteria, and patients with symptomatic joint hypermobility but not fulfilling these criteria are labeled as HSD, which is not officially recognized by all healthcare systems. The 2017 criteria were introduced to improve diagnostic specificity but have faced criticism for being too stringent and failing to adequately capture the multisystemic involvement of hEDS. Herein, we retrospectively evaluated 327 patients from 213 families with a prior diagnosis of hypermobility type EDS or joint hypermobility syndrome based on Villefranche and Brighton criteria, to assess the effectiveness of the 2017 criteria in distinguishing between hEDS and HSD and document the frequencies of extra-articular manifestations. Based on our findings, we propose that the 2017 criteria should be made less stringent to include a greater number of patients who are currently encompassed within the HSD category. This will lead to improved diagnostic accuracy and enhanced patient care by properly capturing the diverse range of symptoms and manifestations present within the hEDS/HSD spectrum.

Academic skills in children with cerebral palsy and specific learning disorders.

AIM: To investigate the prevalence and clinical manifestations of reading, writing, and mathematics disorders in children with cerebral palsy (CP). We explored how the clinical profile of these children differed from those with specific learning disorders (SLDs), taking into account several factors, particularly IQ scores, neuropsychological aspects, and the presence of a visual impairment. METHOD: A prospective cross-sectional study was conducted in 42 children with CP (mean age 9 years 8 months; SD = 2 years 2 months) and 60 children with SLDs (mean age 10 years; SD = 1 year 7 months). Clinical characteristics, neuromotor and cognitive profiles, neuropsychological aspects (speech performance, academic skills, visual attention, phonological awareness, working memory), and signs of visual impairment (visual acuity, contrast sensitivity, visual field, oculomotor functions) were assessed. A machine learning approach consisting of a random forest algorithm, where the outcome was the diagnosis and the covariates were the clinical variables collected in the sample, was used for the analyses. RESULTS: About 59% of the children with CP had reading, writing, or mathematics disorders. Children with CP with learning disorders had a low performance IQ, normal phonological awareness, and working memory difficulties, whereas children with SLDs had normal performance IQ, impaired phonological awareness, and mild working memory difficulties. There were no differences in verbal IQ between the two groups. INTERPRETATION: Learning disorders are frequently associated with CP, with different clinical characteristics, compared with SLDs. Assessment of academic skills is mandatory in these children, even if the IQ is normal. At school age, specific interventions to promote academic skills in children with CP could be a major rehabilitative goal.

Mitochondrial Dysfunction in Peripheral Blood Mononuclear Cells as Novel Diagnostic Tools for Non-Alcoholic Fatty Liver Disease: Visualizing Relationships with Known and Potential Disease Biomarkers.

Non-alcoholic fatty liver disease (NAFLD) is a health emergency worldwide due to its high prevalence and the lack of specific therapies. Noninvasive biomarkers supporting NAFLD diagnosis are urgently needed. Liver mitochondrial dysfunction is a central NAFLD pathomechanism that changes throughout disease progression. Blood-cell bioenergetics reflecting mitochondrial organ dysfunction is emerging for its potential applications in diagnostics. We measured real-time mitochondrial respirometry in peripheral blood mononuclear cells (PBMCs), anthropometric parameters, routine blood analytes, and circulating cytokines from a cohort of NAFLD patients (N = 19) and non-NAFLD control subjects (N = 18). PBMC basal respiration, ATP-linked respiration, maximal respiration, and spare respiratory capacity were significantly reduced in NAFLD compared to non-NAFLD cases. Correlation plots were applied to visualize relationships between known or potential NAFLD-related biomarkers, while non-parametric methods were applied to identify which biomarkers are NAFLD predictors. Basal and ATP-linked mitochondrial respiration were negatively correlated with triglycerides and fasting insulin levels and HOMA index. Maximal and spare respiratory capacity were negatively correlated with IL-6 levels. All the mitochondrial respiratory parameters were positively correlated with HDL-cholesterol level and negatively correlated with fatty liver index. We propose including blood cell respirometry in panels of NAFLD diagnostic biomarkers to monitor disease progression and the response to current and novel therapies, including mitochondrial-targeted ones.

NF-κB/c-Rel DNA-binding is reduced in substantia nigra and peripheral blood mononuclear cells of Parkinson's disease patients.

Although Parkinson's disease (PD) key neuropathological hallmarks are well known, the underlying pathogenic mechanisms of the disease still need to be elucidated to identify innovative disease-modifying drugs and specific biomarkers. NF-κB transcription factors are involved in regulating several processes associated with neurodegeneration, such as neuroinflammation and cell death, that could be related to PD pathology. NF-κB/c-Rel deficient (c-rel-/-) mice develop a progressive PD-like phenotype. The c-rel-/- mice present both prodromal and motor symptoms as well as key neuropathological features, including nigrostriatal dopaminergic neurons degeneration, accumulation of pro-apoptotic NF-κB/RelA acetylated at the lysine 310 residue (Ac-RelA(lys310)) and progressive caudo-rostral brain deposition of alpha-synuclein. c-Rel inhibition can exacerbate MPTP-induced neurotoxicity in mice. These findings support the claim that misregulation of c-Rel protein may be implicated in PD pathophysiology. In this study, we aimed at evaluating c-Rel levels and DNA-binding activity in human brains and peripheral blood mononuclear cells (PBMCs) of sporadic PD patients. We analyzed c-Rel protein content and activity in frozen substantia nigra (SN) samples from post-mortem brains of 10 PD patients and 9 age-matched controls as well as in PBMCs from 72 PD patients and 40 age-matched controls. c-Rel DNA-binding was significantly lower and inversely correlated with Ac-RelA(lys310) content in post-mortem SN of sporadic PD cases, when compared to healthy controls. c-Rel DNA-binding activity was also reduced in PBMCs of followed-up PD subjects. The decrease of c-Rel activity in PBMCs from PD patients appeared to be independent from dopaminergic medication or disease progression, as it was evident even in early stage, drug-naïve patients. Remarkably, the levels of c-Rel protein were comparable in PD and control subjects, pointing out a putative role for post-translational modifications of the protein in c-Rel dysfunctions. These findings support that PD is characterized by the loss of NF-κB/c-Rel activity that potentially has a role in PD pathophysiology. Future studies will be aimed at addressing whether the reduction of c-Rel DNA-binding could constitute a novel biomarker for PD.

Hyperactive Akt1 Signaling Increases Tumor Progression and DNA Repair in Embryonal Rhabdomyosarcoma RD Line and Confers Susceptibility to Glycolysis and Mevalonate Pathway Inhibitors.

In pediatric rhabdomyosarcoma (RMS), elevated Akt signaling is associated with increased malignancy. Here, we report that expression of a constitutively active, myristoylated form of Akt1 (myrAkt1) in human RMS RD cells led to hyperactivation of the mammalian target of rapamycin (mTOR)/70-kDa ribosomal protein S6 kinase (p70S6K) pathway, resulting in the loss of both MyoD and myogenic capacity, and an increase of Ki67 expression due to high cell mitosis. MyrAkt1 signaling increased migratory and invasive cell traits, as detected by wound healing, zymography, and xenograft zebrafish assays, and promoted repair of DNA damage after radiotherapy and doxorubicin treatments, as revealed by nuclear detection of phosphorylated H2A histone family member X (γH2AX) through activation of DNA-dependent protein kinase (DNA-PK). Treatment with synthetic inhibitors of phosphatidylinositol-3-kinase (PI3K) and Akt was sufficient to completely revert the aggressive cell phenotype, while the mTOR inhibitor rapamycin failed to block cell dissemination. Furthermore, we found that pronounced Akt1 signaling increased the susceptibility to cell apoptosis after treatments with 2-deoxy-D-glucose (2-DG) and lovastatin, enzymatic inhibitors of hexokinase, and 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGCR), especially in combination with radiotherapy and doxorubicin. In conclusion, these data suggest that restriction of glucose metabolism and the mevalonate pathway, in combination with standard therapy, may increase therapy success in RMS tumors characterized by a dysregulated Akt signaling.

Machine learning for prediction of in-hospital mortality in coronavirus disease 2019 patients: results from an Italian multicenter study.

BACKGROUND: Several risk factors have been identified to predict worse outcomes in patients affected by SARS-CoV-2 infection. Machine learning algorithms represent a novel approach to identifying a prediction model with a good discriminatory capacity to be easily used in clinical practice. The aim of this study was to obtain a risk score for in-hospital mortality in patients with coronavirus disease infection (COVID-19) based on a limited number of features collected at hospital admission. METHODS AND RESULTS: We studied an Italian cohort of consecutive adult Caucasian patients with laboratory-confirmed COVID-19 who were hospitalized in 13 cardiology units during Spring 2020. The Lasso procedure was used to select the most relevant covariates. The dataset was randomly divided into a training set containing 80% of the data, used for estimating the model, and a test set with the remaining 20%. A Random Forest modeled in-hospital mortality with the selected set of covariates: its accuracy was measured by means of the ROC curve, obtaining AUC, sensitivity, specificity and related 95% confidence interval (CI). This model was then compared with the one obtained by the Gradient Boosting Machine (GBM) and with logistic regression. Finally, to understand if each model has the same performance in the training and test set, the two AUCs were compared using the DeLong's test. Among 701 patients enrolled (mean age 67.2 ±â€Š13.2 years, 69.5% male individuals), 165 (23.5%) died during a median hospitalization of 15 (IQR, 9-24) days. Variables selected by the Lasso procedure were: age, oxygen saturation, PaO2/FiO2, creatinine clearance and elevated troponin. Compared with those who survived, deceased patients were older, had a lower blood oxygenation, lower creatinine clearance levels and higher prevalence of elevated troponin (all P < 0.001). The best performance out of the samples was provided by Random Forest with an AUC of 0.78 (95% CI: 0.68-0.88) and a sensitivity of 0.88 (95% CI: 0.58-1.00). Moreover, Random Forest was the unique model that provided similar performance in sample and out of sample (DeLong test P = 0.78). CONCLUSION: In a large COVID-19 population, we showed that a customizable machine learning-based score derived from clinical variables is feasible and effective for the prediction of in-hospital mortality.

The Elephant in the Room: A Cross-Sectional Study on the Stressful Psychological Effects of the COVID-19 Pandemic in Mental Healthcare Workers.

Despite extensive research on COVID-19's impact on healthcare workers, few studies have targeted mental health workers (MHWs) and none have investigated previous traumatic events. We investigated psychological distress in MHWs after the first lockdown in Italy to understand which COVID-19, sociodemographic, and professional variables represented greater effects, and the role of previous trauma. The survey included sociodemographic and professional questions, COVID-19 variables, and the questionnaires Life Events Checklist for DSM-5 (LEC-5), Impact of Event Scale-Revised (IES-R), and Depression Anxiety Stress Scales 21 (DASS-21). On the 271 MHWs who completed the survey (73.1% female; mean age 45.37), we obtained significant effects for contagion fear, experience of patients' death, increased workload, and worse team relationship during the first wave. Nurses were more affected and showed more post-traumatic stress symptoms, assessed by IES-R, and more depressive, anxiety, and stress symptoms, assessed by DASS-21. The strongest risk factors for distress were greater age, professional role, increased workload, worse team relationship, and separation from family members. Previous experience of severe human suffering and unwanted sexual experiences negatively impacted IES-R and DASS-21 scores. Being a psychiatrist or psychologist/psychotherapist and good team relationships were protective factors. Recent but also previous severe stressful events might represent relevant risk factors for distress, reducing resilience skills. Identifying vulnerable factors and professional categories may help in the development of dedicated measures to prevent emotional burden and support psychological health. Highlights: Psychological distress in mental health workers in the COVID-19 pandemic is more frequent in nurses, who experience more depression, anxiety, and post-traumatic stress symptoms. Previous and recent stressful events are risk factors for distress and should guide intervention strategies.

Psychiatric emergencies in migrant adolescents.

BACKGROUND: Stress factors associated with migration may expose minor immigrants to mental health problems. The aim of the study was to describe acute psychiatric problems, in terms of reasons for hospitalization and diagnosis at discharge, in a sample of Italian and Migrant adolescents (both first and second generation). METHODS: We collected data on socio-demographic and clinical-diagnostic characteristics of 423 Italian and Migrant adolescents (mean age: 15 years ± 1.44; range 12-17.91), hospitalized at the Child and Adolescent Neuropsychiatry Unit of the Spedali Civili of Brescia between 2014 and 2019, period prior to the coronavirus disease 19 (COVID-19) pandemic. RESULTS: A reduction in the percentage of hospitalized Italian subjects and an increase of Migrant ones was found among years (p<0.001). Suicidal attempts and psychomotor agitation were the main reasons for hospitalization in both Italian and Migrant groups; in addition, the former presented a higher number of accesses for eating disorders, while the latter for psychotic disorders. Comparing the two groups at discharge, a higher frequency of anxiety disorders (p<0.001), eating disorders (p<0.001), somatic and conversion disorders (p=0.013), and obsessive-compulsive disorder (p=0.022) was detected in the Italian sample; conversely, there was a higher frequency of suicidal attempt (p=0.025), personality disorders (p<0.001), disruptive behavior, impulse control and conduct disorders (p=0.014), and post-traumatic stress disorder (p=0.019) in the Migrant group. CONCLUSIONS: These observations, carried out during a pre-COVID-19 period, provide a starting point for understanding the psychopathology of Migrant adolescents and underline the importance of early diagnosis to guide appropriate interventions.

Synapsin III gene silencing redeems alpha-synuclein transgenic mice from Parkinson's disease-like phenotype.

Fibrillary aggregated α-synuclein (α-syn) deposition in Lewy bodies (LB) characterizes Parkinson's disease (PD) and is believed to trigger dopaminergic synaptic failure and a retrograde terminal-to-cell body neuronal degeneration. We described that the neuronal phosphoprotein synapsin III (Syn III) cooperates with α-syn to regulate dopamine (DA) release and can be found in the insoluble α-syn fibrils composing LB. Moreover, we showed that α-syn aggregates deposition, and the associated onset of synaptic deficits and neuronal degeneration occurring following adeno-associated viral vectors-mediated overexpression of human α-syn in the nigrostriatal system are hindered in Syn III knock out mice. This supports that Syn III facilitates α-syn aggregation. Here, in an interventional experimental design, we found that by inducing the gene silencing of Syn III in human α-syn transgenic mice at PD-like stage with advanced α-syn aggregation and overt striatal synaptic failure, we could lower α-syn aggregates and striatal fibers loss. In parallel, we observed recovery from synaptic vesicles clumping, DA release failure, and motor functions impairment. This supports that Syn III consolidates α-syn aggregates, while its downregulation enables their reduction and redeems the PD-like phenotype. Strategies targeting Syn III could thus constitute a therapeutic option for PD.

Aneurismal subarachnoid hemorrhage during the COVID-19 outbreak in a Hub and Spoke system: observational multicenter cohort study in Lombardy, Italy.

BACKGROUND: Lombardy was the most affected Italian region by the first phase of the COVID-19 pandemic and underwent urgent reorganization for the management of emergencies, including subarachnoid hemorrhage from a ruptured cerebral aneurysm (aSAH). The aim of the study was to define demographics, clinical, and therapeutic features of aSAH during the COVID-19 outbreak and compare these with a historical cohort. METHODS: In this observational multicenter cohort study, patients aged 18 years or older, who were diagnosed with aSAH at the participating centers in Lombardy from March 9 to May 10, 2020, were included (COVID-19 group). In order to minimize bias related to possible SAH seasonality, the control group was composed of patients diagnosed with aSAH from March 9 to May 10 of the three previous years, 2017-2018-2019 (pre-pandemic group). Twenty-three demographic, clinical, and therapeutic features were collected. Statistical analysis was performed. RESULTS: Seventy-two patients during the COVID-19 period and 179 in the control group were enrolled at 14 centers. Only 4 patients were positive for SARS-CoV-2. The "diagnostic delay" was significantly increased (+ 68%) in the COVID-19 group vs. pre-pandemic (1.06 vs. 0.63 days, respectively, p-value = 0.030), while "therapeutic delay" did not differ significantly between the two periods (0.89 vs. 0.74 days, p-value = 0.183). Patients with poor outcome (GOS at discharge from 1 to 3) were higher during the COVID-19 period (54.2%) compared to pre-pandemic (40.2%, p = 0.044). In logistic regression analysis, in which outcome was the dichotomized Glasgow Outcome Scale (GOS), five variables showed p-values < 0.05: age at admission, WFNS grade, treatment (none), days in ICU, and ischemia. CONCLUSIONS: We documented a significantly increased "diagnostic delay" for subarachnoid hemorrhages during the first COVID-19 outbreak in Lombardy. However, despite the dramatic situation that the healthcare system was experiencing, the Lombardy regional reorganization model, which allowed centralization of neurosurgical emergencies such as SAHs, avoided a "therapeutic delay" and led to results overall comparable to the control period.

Magnetic resonance imaging to assess cartilage invasion in recurrent laryngeal carcinoma after transoral laser microsurgery.

Objective: To evaluate the diagnostic performance of magnetic resonance (MR) with surface coils in assessing cartilage invasion in recurrent laryngeal carcinoma after carbon dioxide transoral laser microsurgery (CO2 TOLMS). Methods: Two expert head and neck radiologists assessed cartilage invasion (infiltrated or non-infiltrated) in submucosal recurrences of laryngeal carcinoma after CO2 TOLMS: results were compared with histopathological report after salvage laryngectomy. Results: Thirty patients met the inclusion criteria and 90 cartilages were assessed. Overall sensitivity, specificity, and positive and negative predictive values for cartilage infiltration were 76, 93, 72 and 94%, respectively; for thyroid cartilage, the values were 82, 79, 69 and 88% respectively; for cricoid cartilage, all values were 100%; and for arytenoids, the values were 33, 96, 56 and 93% respectively. Conclusions: MR with surface coils was able to detect most thyroid and cricoid infiltration in the complex setting of post-CO2 TOLMS laryngeal carcinoma recurrence. In particular, the optimal performance in assessing cricoid invasion can be valuable in choosing the most appropriate treatment among total laryngectomy, open partial horizontal laryngectomies and non-surgical strategies.

Early prediction of in-hospital death of COVID-19 patients: a machine-learning model based on age, blood analyses, and chest x-ray score.

An early-warning model to predict in-hospital mortality on admission of COVID-19 patients at an emergency department (ED) was developed and validated using a machine-learning model. In total, 2782 patients were enrolled between March 2020 and December 2020, including 2106 patients (first wave) and 676 patients (second wave) in the COVID-19 outbreak in Italy. The first-wave patients were divided into two groups with 1474 patients used to train the model, and 632 to validate it. The 676 patients in the second wave were used to test the model. Age, 17 blood analytes, and Brescia chest X-ray score were the variables processed using a random forests classification algorithm to build and validate the model. Receiver operating characteristic (ROC) analysis was used to assess the model performances. A web-based death-risk calculator was implemented and integrated within the Laboratory Information System of the hospital. The final score was constructed by age (the most powerful predictor), blood analytes (the strongest predictors were lactate dehydrogenase, D-dimer, neutrophil/lymphocyte ratio, C-reactive protein, lymphocyte %, ferritin std, and monocyte %), and Brescia chest X-ray score (https://bdbiomed.shinyapps.io/covid19score/). The areas under the ROC curve obtained for the three groups (training, validating, and testing) were 0.98, 0.83, and 0.78, respectively. The model predicts in-hospital mortality on the basis of data that can be obtained in a short time, directly at the ED on admission. It functions as a web-based calculator, providing a risk score which is easy to interpret. It can be used in the triage process to support the decision on patient allocation.

The relationship between air pollution and diabetes: A study on the municipalities of the Metropolitan City of Milan.

AIMS: Urbanisation has been linked with an increased risk of developing diabetes mellitus, dramatically worsening the healthcare system's financial burden. Environmental influences are emerging among the causing factors of the urban diabetes epidemic. We evaluated the relationship between air pollution and the prevalence of diabetes in the Municipalities of the Metropolitan City of Milan, comprising more than 3,4 million citizens. METHODS: The prevalence of diabetes in the resident population and the mean annual air concentrations of PM10 and NO2 were retrieved from the municipal Agency for Health Protection and the regional Agency for Ambient Protection datasets. Two linear regression models were estimated to inspect the relationships between the (logit-based transformed) diabetes prevalence and air pollution concentrations, namely: (i) PM10, and (ii) NO2. Both models were adjusted for five control variables, including the qualitative variable year (2011-2018). RESULTS: Both models highlight a statistically significant positive relationship between air pollutants and diabetes prevalence. An increase of one PM10 or NO2 concentrations' unit translates into a rise of 0.81% or 0.41% in diabetes prevalence, respectively. CONCLUSION: Our results contribute to the ongoing research regarding health outcomes of urbanisation dynamics and should be considered in city planning policies.

A Conformation Variant of p53 Combined with Machine Learning Identifies Alzheimer Disease in Preclinical and Prodromal Stages.

Early diagnosis of Alzheimer's disease (AD) is a crucial starting point in disease management. Blood-based biomarkers could represent a considerable advantage in providing AD-risk information in primary care settings. Here, we report new data for a relatively unknown blood-based biomarker that holds promise for AD diagnosis. We evaluate a p53-misfolding conformation recognized by the antibody 2D3A8, also named Unfolded p53 (U-p532D3A8+), in 375 plasma samples derived from InveCe.Ab and PharmaCog/E-ADNI longitudinal studies. A machine learning approach is used to combine U-p532D3A8+ plasma levels with Mini-Mental State Examination (MMSE) and apolipoprotein E epsilon-4 (APOEε4) and is able to predict AD likelihood risk in InveCe.Ab with an overall 86.67% agreement with clinical diagnosis. These algorithms also accurately classify (AUC = 0.92) Aß+-amnestic Mild Cognitive Impairment (aMCI) patients who will develop AD in PharmaCog/E-ADNI, where subjects were stratified according to Cerebrospinal fluid (CSF) AD markers (Aß42 and p-Tau). Results support U-p532D3A8+ plasma level as a promising additional candidate blood-based biomarker for AD.

Anxiety in neurosurgical patients undergoing nonurgent surgery during the COVID-19 pandemic.

OBJECTIVE: The COVID-19 pandemic has forced many countries into lockdown and has led to the postponement of nonurgent neurosurgical procedures. Although stress has been investigated during this pandemic, there are no reports on anxiety in neurosurgical patients undergoing nonurgent surgical procedures. METHODS: Neurosurgical patients admitted to hospitals in eastern Lombardy for nonurgent surgery after the lockdown prospectively completed a pre- and postoperative structured questionnaire. Recorded data included demographics, pathology, time on surgical waiting list, anxiety related to COVID-19, primary pathology and surgery, safety perception during hospital admission before and after surgery, and surgical outcomes. Anxiety was measured with the State-Trait Anxiety Inventory. Descriptive statistics were computed on the different variables and data were stratified according to pathology (oncological vs nononcological). Three different models were used to investigate which variables had the greatest impact on anxiety, oncological patients, and safety perception, respectively. Because the variables (Xs) were of a different nature (qualitative and quantitative), mostly asymmetrical, and related to outcome (Y) by nonlinear relationships, a machine learning approach composed of three steps (1, random forest growing; 2, relative variable importance measure; and 3, partial dependence plots) was chosen. RESULTS: One hundred twenty-three patients from 10 different hospitals were included in the study. None of the patients developed COVID-19 after surgery. State and trait anxiety were reported by 30.3% and 18.9% of patients, respectively. Higher values of state anxiety were documented in oncological compared to nononcological patients (46.7% vs 25%; p = 0.055). Anxiety was strongly associated with worry about primary pathology, surgery, disease worsening, and with stress during waiting time, as expected. Worry about positivity to SARS-CoV-2, however, was the strongest factor associated with anxiety, even though none of the patients were infected. Neuro-oncological disease was associated with state anxiety and with worry about surgery and COVID-19. Increased bed distance and availability of hand sanitizer were associated with a feeling of safety. CONCLUSIONS: These data underline the importance of psychological support, especially for neuro-oncological patients, during a pandemic.

Factors Associated With Surgical Mortality and Complications Among Patients With and Without Coronavirus Disease 2019 (COVID-19) in Italy.

Importance: There are limited data on mortality and complications rates in patients with coronavirus disease 2019 (COVID-19) who undergo surgery. Objective: To evaluate early surgical outcomes of patients with COVID-19 in different subspecialties. Design, Setting, and Participants: This matched cohort study conducted in the general, vascular and thoracic surgery, orthopedic, and neurosurgery units of Spedali Civili Hospital (Brescia, Italy) included patients who underwent surgical treatment from February 23 to April 1, 2020, and had positive test results for COVID-19 either before or within 1 week after surgery. Gynecological and minor surgical procedures were excluded. Patients with COVID-19 were matched with patients without COVID-19 with a 1:2 ratio for sex, age group, American Society of Anesthesiologists score, and comorbidities recorded in the surgical risk calculator of the American College of Surgeons National Surgical Quality Improvement Program. Patients older than 65 years were also matched for the Clinical Frailty Scale score. Exposures: Patients with positive results for COVID-19 and undergoing surgery vs matched surgical patients without infection. Screening for COVID-19 was performed with reverse transcriptase-polymerase chain reaction assay in nasopharyngeal swabs, chest radiography, and/or computed tomography. Diagnosis of COVID-19 was based on positivity of at least 1 of these investigations. Main Outcomes and Measures: The primary end point was early surgical mortality and complications in patients with COVID-19; secondary end points were the modeling of complications to determine the importance of COVID-19 compared with other surgical risk factors. Results: Of 41 patients (of 333 who underwent operation during the same period) who underwent mainly urgent surgery, 33 (80.5%) had positive results for COVID-19 preoperatively and 8 (19.5%) had positive results within 5 days from surgery. Of the 123 patients of the combined cohorts (78 women [63.4%]; mean [SD] age, 76.6 [14.4] years), 30-day mortality was significantly higher for those with COVID-19 compared with control patients without COVID-19 (odds ratio [OR], 9.5; 95% CI, 1.77-96.53). Complications were also significantly higher (OR, 4.98; 95% CI, 1.81-16.07); pulmonary complications were the most common (OR, 35.62; 95% CI, 9.34-205.55), but thrombotic complications were also significantly associated with COVID-19 (OR, 13.2; 95% CI, 1.48-∞). Different models (cumulative link model and classification tree) identified COVID-19 as the main variable associated with complications. Conclusions and Relevance: In this matched cohort study, surgical mortality and complications were higher in patients with COVID-19 compared with patients without COVID-19. These data suggest that, whenever possible, surgery should be postponed in patients with COVID-19.

The impact of integrase inhibitor-based regimens on markers of inflammation among HIV naïve patients.

The use of combination anti-retroviral therapy (cART) correlates with longer and healthier life and with nearly normal life expectancy in people living with HIV. However, cART does not completely restore health. Chronic immune activation and inflammation persist in treated patients and have been described as predictors for clinical events and mortality in HIV-infected patients. Limited information is available on the impact of the various cART regimens on inflammation/immunoactivation. The aim of this work was to explore the impact of elvitegravir, dolutegravir, raltegravir (integrase strand transfer inhibitors, INSTIs) and atazanavir (protease inhibitor, PI) on several soluble markers of immune activation and inflammation during the first year of effective combination anti-retroviral therapy (cART). We conducted an observational retrospective cohort study in HIV-infected cART-naïve patients who initiated an INSTI or atazanavir regimen between March 2015 and February 2016 and a serum sample was available at baseline, 6 and 12 months after initiation. We compared the trend of D-Dimer, TNF- α, IL-2, IL-6, IL-7, IL-10, CCL4/MIP1-ß, CCL5/RANTES, s-CD14, s-CD163, hs-CRP levels among the 4 arms of treatment. Percentage of variation from baseline was also measured for all markers. A total of 36 patients were included. We observed heterogeneous modifications in inflammation markers among arms. In particular, we noted that EVG have significant negative effect on s-CD14, hs-CRP, IL-6 and D-Dimer in respect to other INSTIs and this different effect occurs mainly during the first 6 months of cART. IL-7 values increased in the three arms with INSTIs (significantly only in EGV, 159.8%, p = 0.0003) and decreased significantly in patients on PI (-48.96%; p = 0.04) over the period. In conclusion, our results provide further data on changes of inflammatory marker levels, especially for the new INSTIs. Our data show that among INSTIs, EVG seems to have a worse impact on inflammation.

[Corrigendum] Analysis of a nanoparticle­enriched fraction of plasma reveals miRNA candidates for Down syndrome pathogenesis.

After the publication of the above paper, the authors noted that the names of a couple of the authors listed on the paper were associated with the wrong affliation: Specifically, the eighth and ninth listed authors, Francesca Antonaros and Allison Piovesan, are located at DIMES at the University of Florence (fourth affiliation address), not at CSGI, the Research Center for Colloids and Nanoscience in Florence (third affliation address). Therefore, the author and affiliation details for this paper should have been presented as follows: ALESSANDRO SALVI1, MARIKA VEZZOLI2, SARA BUSATTO1, LUCIA PAOLINI1,3, TERESA FARANDA1, EDOARDO ABENI1, MARIA CARACAUSI4, FRANCESCA ANTONAROS4, ALLISON PIOVESAN4, CHIARA LOCATELLI5, GUIDO COCCHI5,6, GUALTIERO ALVISI7, GIUSEPPINA DE PETRO1, DORIS RICOTTA1, PAOLO BERGESE1,3 and ANNALISA RADEGHIERI1,3. 1Department of Molecular and Translational Medicine, University of Brescia; 2Unit of Biostatistics, Department of Molecular and Translational Medicine, University of Brescia, I­25123 Brescia; 3CSGI, Research Center for Colloids and Nanoscience, Sesto Fiorentino, I­50019 Florence; 4Department of Experimental, Diagnostic and Specialty Medicine (DIMES), Unit of Histology, Embryology and Applied Biology, University of Bologna; 5Neonatology Unit, St. Orsola­Malpighi Polyclinic; 6Department of Medical and Surgical Sciences (DIMEC), University of Bologna, I­40138 Bologna; 7Department of Molecular Medicine, University of Padua, I­35121 Padua, Italy. The authors regret that this error with the author affiliations for Francesca Antonaros and Allison Piovesan was not noticed prior to the publication of their paper, and apologize for any inconvenience caused. [the original article was published in International Journal of Molecular Medicine 43: 2303­2318, 2018; DOI: 10.3892/ijmm.2019.4158].