Editorial: Chronic autoimmune arthritis, infections and vaccines

The link between autoimmunity and infection continues to represent an intriguing immunologic conundrum for scientist and a frequent clinical challenge for patients and physicians. Patients with chronic autoimmune arthritis indeed have an increased risk of infections, mainly due to the dysregulation of their immune system and the use of immunosuppressive therapy. Infections in these patients are more frequent, have a more severe clinical course, eventually with prolonged viral persistence, compared to the general population and represent a frequent cause of death. Besides, infections can trigger autoimmune diseases via different immunologic mechanisms such as molecular mimicry, epitope spreading, by-stander activation and can also induce disease relapses. SARS-CoV-2 infection represents a dramatic example of this complex connection. It is known, indeed, that different autoimmune manifestations can complicate SARS-CoV-2 infection such as uncontrolled host-immune response leading to life-threatening condition known as cytokine release syndrome, or autoimmune hemolytic anemia, immune thrombocytopenic purpura, Guillain-Barre syndrome, and the detection of different autoantibodies. This Research Topic includes seventeen contributions, fifteen original articles and two review articles, providing several new insights into the efficacy and safety of SARS-CoV-2 vaccine in autoimmune patients, immunologic biomarkers for diagnosis and therapeutic outcome of autoimmune arthritis

An anatomy-based lumped parameter model of cerebrospinal venous circulation: can an extracranial anatomical change impact intracranial hemodynamics?

Background The relationship between extracranial venous system abnormalities and central nervous system disorders has been recently theorized. In this paper we delve into this hypothesis by modeling the venous drainage in brain and spinal column areas and simulating the intracranial flow changes due to extracranial morphological stenoses. Methods A lumped parameter model of the cerebro-spinal venous drainage was created based on anatomical knowledge and vessels diameters and lengths taken from literature. Each vein was modeled as a hydraulic resistance, calculated through Poiseuille’s law. The inputs of the model were arterial flow rates of the intracranial, vertebral and lumbar districts. The effects of the obstruction of the main venous outflows were simulated. A database comprising 112 Multiple Sclerosis patients (Male/Female = 42/70; median age ± standard deviation = 43.7 ± 10.5 years) was retrospectively analyzed. Results The flow rate of the main veins estimated with the model was similar to the measures of 21 healthy controls (Male/Female = 10/11; mean age ± standard deviation = 31 ± 11 years), obtained with a 1.5 T Magnetic Resonance scanner. The intracranial reflux topography predicted with the model in cases of internal jugular vein diameter reduction was similar to those observed in the patients with internal jugular vein obstacles. Conclusions The proposed model can predict physiological and pathological behaviors with good fidelity. Despite the simplifications introduced in cerebrospinal venous circulation modeling, the key anatomical feature of the lumped parameter model allowed for a detailed analysis of the consequences of extracranial venous impairments on intracranial pressure and hemodynamics

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer’s dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis

Sexual function and quality of life in patients affected by deep infiltrating endometriosis: current evidence and future perspectives

Endometriosis is one of the most common gynecological diseases and has an incidence of approximately 6%-10% in women of reproductive age. Deep infiltrating endometriosis (DIE) is considered the most aggressive form of endometriosis and is defined as a lesion that penetrates for more than 5 mm under the peritoneal surface. It has been demonstrated that DIE is associated with pelvic pain symptoms, and the intensity of pain is correlated with the depth of infiltration. Other symptoms are dysmenorrhea, deep dyspareunia, and painful defecation and urination. These symptoms are strongly associated with a significant reduction of the quality of life and a marked impairment of sexual function in the affected women. Therefore, a multidisciplinary approach and psychological support for women affected by DIE appear mandatory in order to reduce the impact of the disease on quality of life and sexual function as much as possible

...and the winner is...A national contest on Clean Care

Background Patient safety and HAI prevention and control should be a pillar of the professional level of competency starting from the first approach to health care organizations (undergraduate level). It should be based also on active involvement of the students. The 10th anniversary of the adoption of Clean Care is Safer Care project in Italy provided the opportunity to the Universities members of the GISIO-SItI Study Group on HAI to try new ways to encourage students' creativity. Aim To actively involve students in Nursing, Medical Degree, Other HealthCare Professionals in a creative contest on hand hygiene in order to increase their awareness both of this topic and more in general of HAI. Methods The Universities members of the GISIO network promoted at local level a contest after previously defining aim, methods and framework for evaluating the results. Students were invited to prepare by May 5 th , 2016 products such as videos, posters, presentations, leaflets, screensavers. The best works will represent their University in a national contest to be held on November 18 th. Conclusion Given the encouraging achievements, the steering group is considering whether to extend the participation in the next future. References ………………… Results More than 600 students from 9 Italian Universities and 38 from Albania were involved. 105 projects were presented for evaluation. A local committee judged according to a common framework on the following items: scientific accuracy, creativity, products' technical quality, usefulness for campaigning. 5 videos, 2 manifestos, 1 presentation, 1 poster, 1 leaflet won at local level. A national committee will be in charge to apply the same criteria to the national contest

The effects of processing and mastication on almond lipid bioaccessibility using novel methods of in vitro digestion modelling and micro-structural analysis.

A number of studies have demonstrated that consuming almonds increases satiety but does not result in weight gain, despite their high energy and lipid content. To understand the mechanism of almond digestion, in the present study, we investigated the bioaccessibility of lipids from masticated almonds during in vitro simulated human digestion, and determined the associated changes in cell-wall composition and cellular microstructure. The influence of processing on lipid release was assessed by using natural raw almonds (NA) and roasted almonds (RA). Masticated samples from four healthy adults (two females, two males) were exposed to a dynamic gastric model of digestion followed by simulated duodenal digestion. Between 7·8 and 11·1 % of the total lipid was released as a result of mastication, with no significant differences between the NA and RA samples. Significant digestion occurred during the in vitro gastric phase (16·4 and 15·9 %) and the in vitro duodenal phase (32·2 and 32·7 %) for the NA and RA samples, respectively. Roasting produced a smaller average particle size distribution post-mastication; however, this was not significant in terms of lipid release. Light microscopy showed major changes that occurred in the distribution of lipid in all cells after the roasting process. Further changes were observed in the surface cells of almond fragments and in fractured cells after exposure to the duodenal environment. Almond cell walls prevented lipid release from intact cells, providing a mechanism for incomplete nutrient absorption in the gut. The composition of almond cell walls was not affected by processing or simulated digestion