Primary headaches in patients with temporomandibular disorders: Diagnosis and treatment of central sensitization pain

Objectives: Central sensitization (CS) has been found in patients with temporomandibular disorders (TMD), craniofacial pain (CP) and primary headaches, but its clinical implications remain uncertain. The first aim was to provide a synthesis of the current state of knowledge about the link between CS and TMD associated with primary headaches; the second goal was to find methodologies to assess and treat CS in this subgroup of patients.

Methods: A narrative review of the literature was conducted.

Results: CS is described in literature as an aggravating factor in patients with TMD-related primary headaches. Further studies are required to support this assertion.

Conclusions: The importance of excluding chronic neuropathic pain and recognizing CS as the main component using a top-down approach to target the best pharmacological and non-pharmacological treatments is evident. Some useful tools to discriminate patients with CS from others have become available, but more research is required to enable an appropriate diagnosis.     

Multiple system atrophy laryngeal stridor treated with radiofrequency-assisted posterior cordotomy and arytenoidectomy

Clinical Autonomic Research -     

Digital breast tomosynthesis and contrast‐enhanced dual‐energy digital mammography alone and in combination compared to 2D digital synthetized mammography and MR imaging in breast cancer detection and classification

To compare diagnostic performance of contrast‐enhanced dual‐energy digital mammography (CEDM) and digital breast tomosynthesis (DBT) alone and in combination compared to 2D digital mammography (MX) and dynamic contrast‐enhanced MRI (DCE‐MRI) in women with breast lesions. We enrolled 100 consecutive patients with breast lesions (BIRADS 3‐5 at imaging or clinically suspicious). CEDM, DBT, and DCE‐MRI 2D were acquired. Synthetized MX was obtained by DBT. A total of 134 lesions were investigated on 111 breasts of 100 enrolled patients: 53 were histopathologically proven as benign and 81 as malignant. Nonparametric statistics and receiver operating characteristic (ROC) curve were performed. Two‐dimensional synthetized MX showed an area under ROC curve (AUC) of 0.764 (sensitivity 65%, specificity 80%), while AUC was of 0.845 (sensitivity 80%, specificity 82%) for DBT, of 0.879 (sensitivity 82%, specificity 80%) for CEDM, and of 0.892 (sensitivity 91%, specificity 84%) for CE‐MRI. DCE‐MRI determined an AUC of 0.934 (sensitivity 96%, specificity 88%). Combined CEDM with DBT findings, we obtained an AUC of 0.890 (sensitivity 89%, specificity 74%). A difference statistically significant was observed only between DCE‐MRI and CEDM (P = .03). DBT, CEDM, CEDM combined to tomosynthesis, and DCE‐MRI had a high ability to identify multifocal and bilateral lesions with a detection rate of 77%, 85%, 91%, and 95% respectively, while 2D synthetized MX had a detection rate for multifocal lesions of 56%. DBT and CEDM have superior diagnostic accuracy of 2D synthetized MX to identify and classify breast lesions, and CEDM combined with DBT has better diagnostic performance compared with DBT alone. The best results in terms of diagnostic performance were obtained by DCE‐MRI. Dynamic information obtained by time‐intensity curve including entire phase of contrast agent uptake allows a better detection and classification of breast lesions.     

Assessing inter- and intra-individual cognitive variability in patients at risk for cognitive impairment: the case of minimal hepatic encephalopathy

Recent evidence reveals that inter- and intra-individual variability significantly affects cognitive performance in a number of neuropsychological pathologies. We applied a flexible family of statistical models to elucidate the contribution of inter- and intra-individual variables on cognitive functioning in healthy volunteers and patients at risk for hepatic encephalopathy (HE). Sixty-five volunteers (32 patients with cirrhosis and 33 healthy volunteers) were assessed by means of the Inhibitory Control Task (ICT). A Generalized Additive Model for Location, Scale and Shape (GAMLSS) was fitted for jointly modeling the mean and the intra-variability of Reaction Times (RTs) as a function of socio-demographic and task related covariates. Furthermore, a Generalized Linear Mixed Model (GLMM) was fitted for modeling accuracy. When controlling for the covariates, patients without minimal hepatic encephalopathy (MHE) did not differ from patients with MHE in the low-demanding condition, both in terms of RTs and accuracy. Moreover, they showed a significant decline in accuracy compared to the control group. Compared to patients with MHE, patients without MHE showed faster RTs and higher accuracy only in the high-demanding condition. The results revealed that the application of GAMLSS and GLMM models are able to capture subtle cognitive alterations, previously not detected, in patients’ subclinical pathologies.     

Multi-Technique Diagnostic Analysis of Plasters and Mortars from the Church of the Annunciation (Tortorici,Sicily)

Plasters and mortars of the Church of the Annunciation (Tortorici, Sicily) were characterized, for the first time, both at the elemental and molecular levels, by means of portable X-ray fluorescence (XRF) and Raman spectroscopy, to achieve information on the “state of health” of the whole structure. The understanding of their degradation mechanisms and the identification of consequent degradation patterns can define the environmental factors responsible for interpreting the potential pathological forms that can impact the general building vulnerability. In this sense, the results obtained in this article provide relevant information to identify and address both the characterization of building materials and the fundamental causes of their deterioration. At the same time, if coupled with the attempt to supply a chronological order of the major restoration interventions carried out on the investigated site, they provide new insights to calibrate the models for building vulnerability studies.     

Totally robotic soave pull-through procedure for Hirschsprung’s disease: lessons learned from 11 consecutive pediatric patients

Pediatric Surgery International - Since Hirschsprung’s disease (HSCR) already proved to benefit from robotic surgery, we aimed at describing a wider series of patients with this rare disease...     

Metastatic colorectal cancer and type 2 diabetes: prognostic and genetic interactions

The present study was undertaken to analyze prognostic and genetic interactions between type 2 diabetes and metastatic colorectal cancer. Patients’ survival was depicted through the Kaplan–Meier product limit method. Prognostic factors were examined through the Cox proportional‐hazards regression model, and associations between diabetes and clinical‐pathologic variables were evaluated by the χ² test. In total, 203 metastatic colorectal cancer patients were enrolled. Lymph nodes (P = 0.0004) and distant organs (> 2 distant sites, P = 0.0451) were more frequently involved in diabetic patients compared with those without diabetes. Diabetes had an independent statistically significant negative prognostic value for survival. Highly selected patients with cancer and/or diabetes as their only illness(es) were divided into three groups: (a) seven oligo‐metastatic patients without diabetes, (b) 10 poly‐metastatic patients without diabetes, and (c) 12 poly‐metastatic diabetic patients. These groups of patients were genetically characterized through the Illumina NovaSeq 6000 (San Diego, CA, USA) platform and TruSigt™Oncology 500 kit, focusing on genes involved in diabetes and colorectal cancer. Gene variants associated with diabetes and cancer were more frequent in patients in group 3. We found that type 2 diabetes is a negative prognostic factor for survival in colorectal cancer. Diabetes‐associated gene variants could concur with malignancy, providing a rational basis for innovative models of tumor progression and therapy.     

Metformin and Rapamycin Reduce Pancreatic Cancer Growth in Obese Prediabetic Mice by Distinct MicroRNA-Regulated Mechanisms

Metformin treatment is associated with a decreased risk and better prognosis of pancreatic cancer (PC) in patients with type 2 diabetes, but the mechanism of metformin’s PC growth inhibition in the context of a prediabetic state is unknown. We used a Panc02 pancreatic tumor cell transplant model in diet-induced obese (DIO) C57BL/6 mice to compare the effects of metformin and the direct mammalian target of rapamycin (mTOR) inhibitor rapamycin on PC growth, glucose regulation, mTOR pathway signaling, and candidate microRNA (miR) expression. In DIO/prediabetic mice, metformin and rapamycin significantly reduced pancreatic tumor growth and mTOR-related signaling. The rapamycin effects centered on decreased mTOR-regulated growth and survival signaling, including increased expression of let-7b and cell cycle–regulating miRs. Metformin (but not rapamycin) reduced glucose and insulin levels and expression of miR-34a and its direct targets Notch, Slug, and Snail. Metformin also reduced the number and size of Panc02 tumor spheres in vitro and inhibited the expression of Notch in spheroids. Our results suggest that metformin and rapamycin can both inhibit pancreatic tumor growth in obese, prediabetic mice through shared and distinct mechanisms. Metformin and direct mTOR inhibitors, alone or possibly in combination, represent promising intervention strategies for breaking the diabetes-PC link.