Our aim was to investigate the prevalence and clinical relevance of inherited complement and antibody deficiency states in a large series of patients with various autoimmune rheumatologic diseases (ARD) with juvenile onset. A total number of 117 consecutive patients from 2 tertiary referral hospitals were included in the study. All patients underwent genetic screening for type I C2 deficiency and C4 allotyping. Serum levels of immunoglobulin classes measured systematically throughout their regular medical care were recorded retrospectively. Our cohort of patients included 84 with juvenile idiopathic arthritis (JIA), 21 with systemic lupus erythematosus (SLE), 6 with systemic vasculitis, 2 with juvenile scleroderma, 2 with idiopathic uveitis, 1 with mixed connective tissue disease and 1 with SLE/scleroderma overlap syndrome. We have found 16 patients with evidence of primary immunodeficiency in our series (13.7 %), including 7 with C4 deficiency, 5 with selective IgA deficiency, 3 with C2 deficiency and 2 with unclassified hypogammaglobulinemia (one also presented C4D). Of the 84 patients with JIA, 4 (4.8 %) had a complement deficiency, which was less prevalent than in the SLE cohort (23.8 %), but all of them have exhibited an aggressive disease. Most of our patients with primary antibody deficiencies showed a more complicated and severe disease course and even the co-occurrence of two associated autoimmune diseases (SLE/scleroderma overlap syndrome and SLE/autoimmune hepatitis type 1 overlap). Our findings among others demonstrate that complement and immunoglobulin immunodeficiencies need careful consideration in patients with ARD, as they are common and might contribute to a more severe clinical course of the disease.

The coronavirus 2019 (COVID-19) disease has long-term effects, known as post-COVID conditions (PCC) or long-COVID. Post-COVID-19 syndrome is defined by signs and symptoms that occur during or after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection which persist for more than 12 weeks and cannot be supported by an alternative diagnosis. The cardiovascular damage caused by COVID-19 in the severe forms of the disease is induced by severe systemic inflammation, considered to be one of the causes of myocardial lesions, with increased levels of circulating cytokines and toxic response mediators. We have focused on conditions that can induce long-COVID-19, or multisystem inflammatory syndrome in adults or children (MIS-C/MIS-A), with an emphasis on endocrinological and metabolic disorders. Although described less frequently in children than in adults, long-COVID syndrome should not be confused with MIS-C, which is an acute condition characterized by multisystem involvement and paraclinical evidence of inflammation in a pediatric patient who tested positive for SARS-CoV-2. At the same time, we mention that the MIS-A symptoms remit within a few weeks, while the duration of long-COVID is measured in months. Long-COVID syndrome, along with its complications, MIS-A and MIS-C, represents an important challenge in the medical community. Underlying comorbidities can expose both COVID-19 adult and pediatric patients to a higher risk of negative outcomes not only during, but in the aftermath of the SARS-CoV-2 infection as well.

Food authenticity control represents a constant concern nowadays, and against this background, new means of food fraud detection are developed by research and control laboratories. Among the most accessible analytical methods in this regard, attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy proved to be an effective tool, being rapid, cost-effective, and not requiring solvent use. However, the generated experimental data need to be further processed in an efficient manner in order to be able to accurately assess the authenticity of a certain product. The temptation to pass some more available honey varieties as rarer ones might exist and in order to detect these types of miss labeling, we proposed in this study the development of new recognition models based on supervised chemometric models and artificial intelligence. In this way a comparison between the models’ capabilities constructed based on the association between ATR-IR spectroscopy with partial least squares discriminant analysis (PLS-DA) and support vector machines (SVM), respectively, was performed. The most efficient models for the individual botanical differentiation were developed by applying SVM on the significant spectral markers, determined through a supervised method.

The application of artificial intelligence for the development of recognition models for food and beverages differentiation has benefited from increasing attention in recent years. For this scope, different machine learning (ML) algorithms were used in order to find the most suitable model for a certain purpose. In the present work, three ML algorithms, namely artificial neural networks (ANN), support vector machines (SVM) and k-nearest neighbors (KNN), were applied for constructing honey geographical classification models, and their performance was assessed and compared. A preprocessing step consisting of either a component reduction method or a supervised feature selection technique was applied prior to model development. The most efficient geographical differentiation models were obtained based on ANN, when a subset of features corresponding to the markers having the highest discrimination potential was used as input data. Therefore, when the samples aimed to be classified at an intercountry level, an accuracy of 95% was achieved; namely, 99% of the Romanian samples and 73% of the ones originating from other countries were correctly predicted. Promising results were also obtained for the intracountry honey discrimination; namely, the model built for classifying the Transylvanian samples from the ones produced in other Romanian regions had an 85% accuracy.

Background. ROHHADNET syndrome is a pleiotropic disorder defined by rapid onset of obesity, hypothalamic-pituitary endocrine dysfunctions, alveolar hypoventilation and hypothalamic autonomic dysregulation and neural tumors. Case presentation. We report the case of a 5.8-year-old female patient with rapid onset of obesity and growth arrest, hypercortisolism, hyperprolactinemia, low IGF1, severe hypernatremia (with no signs of diabetes insipidus) and chronic hyperchloremic metabolic acidosis. Additional symptoms included sleep apnea and two episodes of cardiopulmonary arrest after mild sedation. Brain MRI, chest and abdominal enhanced CT scans were all negative. As no tumors were revealed at the time of diagnosis, ROHHAD syndrome was suspected. Treatment with potassium bicarbonate was initiated in an attempt to control both the severe hypernatremia and chronic hyperchloremic metabolic acidosis. Patient developed dilated cardiomyopathy and kaliopenic nephropathy. Conclusion. The presence of dilated cardiomyopathy is in keeping with only one other reported case, while the severe hypernatremia joined by hyperchloremic metabolic acidosis seen in our patient has not been presented previously. Although it is a very rare medical condition, ROHHAD syndrome has to be considered in the differential diagnosis of any case with rapid onset obesity associated with hypothalamic-pituitary endocrine dysfunctions, and alveolar hypoventilation.

Quality of life is a widely used concept that tends to become an important part of clinical management. The present study performs an analysis of the impact of suppurative chronic otitis media with and without cholesteatoma on quality of life, using the COMQ-12 questionnaire. It was applied to a group of 40 healthy people and to 40 patients before surgery, and the answers to the questions were analyzed and correlated with socioeconomic factors. After the confirmation of the diagnosis based on clinical and imaging information, the patients completed the COMQ-12 questionnaire. It was observed that the chronic ear problems had negative impacts of varying degrees on daily and long-term activities. The evaluation and analysis of information can be used in setting therapeutic targets.