Recommendations are given for the extent of the medical evaluation of minor refugees, including the medical history and physical examination, adapted to the situation of refugees from Ukraine. Ablood count and screening for tuberculosis, hepatitisB andC as well as human immunodeficiency virus (HIV) infections are recommended for all minor refugees.For a rapid completion of the vaccination status, an age-related and indications-related prioritization of individual vaccinations will be undertaken.

In view of the continuing high numbers of refugees not only from Ukraine, a further professionalization of medical health care is necessary. For this purpose, the necessary structural and personnel framework conditions need to be accomplished.
In view of the continuing high numbers of refugees not only from Ukraine, a further professionalization of medical health care is necessary. For this purpose, the necessary structural and personnel framework conditions need to be accomplished.Refugee children and adolescents with chronic diseases and disabilities are among the most vulnerable persons as their health and developmental chances are considerably at risk. This article describes the challenges and opportunities in the care of this group of patients from the perspective of different care sectors initial reception center, public health service, pediatricians in private practice, social pediatric centers and patient organizations. The starting point is a presentation of the rights to optimal healthcare that can be derived from the United Nations (UN) Convention on the Rights of Persons with Disabilities and the UN Convention on the Rights of the Child. It becomes clear that for children and adolescents in the status of asylum seekers there are systematic gaps in the recognition and care of chronic diseases, disabilities and support needs. An expansion of the health examination after arrival, which has so far focused on the detection of communicable diseases, is important and necessary in order to identify individual needs and improve the data situation for this group. A strengthening of the school entry screening by the public health service, especially for older children entering school as lateral entrants, could also significantly improve the nationwide coverage. In contrast to these deficits, which require changes at the political level, there are innovative models of care, especially in local contexts, such as pediatric consultation clinics in initial reception centers, diverse examples of voluntary commitment or the use of social media in patient organizations, which are presented as examples.It is widely agreed that the DSM-5, the handbook of psychiatric diagnosis, suffers from both high overlap among its putative disorders and high heterogeneity (variability) within each disorder. While these may appear to be opposite problems, in fact both may stem from failure to recognize transdiagnostic dimensions of emotion, cognition, and personality, among others, that inform psychopathology. These fundamental nosological challenges are exemplified in the case of attention-deficit/hyperactivity disorder (ADHD). In ADHD, broad clinical heterogeneity has defied easy clinical prediction of outcomes or clean statistical differentiation of meaningful, biologically informative sub-groups. Progress for ADHD heterogeneity looks promising, however, when we consider dimensions of trait affectivity such as surgency and negative affectivity, their constituent lower order traits such as irritability, and the integrative function of self-regulation. Focusing on developments in the study of temperament traits and ADHD as they relate to emotional dysregulation, several lines of investigation are proving useful. Utilization of selective computational models, biological validators, and longitudinal analyses points toward potential improvements in nosology and clinical assessment in the future by taking temperament traits into account.Compound-protein interaction (CPI) prediction is a foundational task for drug discovery, which process is time-consuming and costly. The effectiveness of CPI prediction can be greatly improved using deep learning methods to accelerate drug development. Large number of recent research results in the field of computer vision, especially in deep learning, have proved that the position, geometry, spatial structure and other features of objects in an image can be well characterized. We propose a novel molecular image-based model named CAT-CPI (combining CNN and transformer to predict CPI) for CPI task. We use Convolution Neural Network (CNN) to learn local features of molecular images and then use transformer encoder to capture the semantic relationships of these features. To extract protein sequence feature, we propose to use a k-gram based method and obtain the semantic relationships of sub-sequences by transformer encoder. In addition, we build a Feature Relearning (FR) module to learn interaction features of compounds and proteins. We evaluated CAT-CPI on three benchmark datasets-Human, Celegans, and Davis-and the experimental results demonstrate that CAT-CPI presents competitive performance against state-of-the-art predictors. In addition, we carry out Drug-Drug Interaction (DDI) experiments to verify the strong potential of the methods based on molecular images and FR module.Objective Breast cancer (BC) is becoming the leading cause of cancer-related death in women all over the word. Identification of diagnostic biomarkers for early detection of BC is one of the most effective ways to reduce the mortality. Methods Plasma samples from BC patients (n = 120) and normal controls (n = 50) were collected to determine the differentially expressed circulating miRNAs in BC patients. Binary logistic regression was applied to develop miRNA diagnostic models. Receiver operating characteristic (ROC) curves were applied to calculate the area under the curve (AUC). MMTV-PYMT mammary tumor mice were used to validate the expression change of those circulating miRNAs. Plasma samples from patients with other tumor types were collected to determine the specificity of the model in diagnosis of BC. Results In the screening phase, 5 circulating miRNAs (miR-16, miR-17, miR-19b, miR-27a, and miR-106a) were identified as the most significantly upregulated miRNAs in plasma of BC patients. In consistence, the 5 miRNAs showed upregulation in the circulation of additional 80 BC patients in a tumor stage-dependent manner. Application of a tumor-burden mice model further confirmed upregulation of the 5 miRNAs in circulation. Based on these data, five models with diagnostic potential of BC were developed. Among the 5 miRNAs, miR-19b ranked at the top position with the highest specificity and the biggest contribution. In combination with miR-16 and miR-106a, a miR-19b-based 3-circulating miRNA model was selected as the best for further validation. Taken the samples together, the model showed 92% of sensitivity and 90% of specificity in diagnosis of BC. In addition, three other tumor types including prostate cancer, thyroid cancer and colorectal cancer further verified the specificity of the BC diagnostic model. Conclusion The current study developed a miR-19b-based 3-miRNA model holding potential for diagnosis of BC using blood samples.Background Laminin subunit gamma 1 (LAMC1) protein is associated with tumor cell invasion and metastasis. However, its role in kidney cancer remains unclear. In this work, we sought to probe the expression as well as its carcinogenic mechanisms of LAMC1 in kidney renal papillary cell carcinoma (KIRP) and kidney renal clear cell carcinoma (KIRC). Methods Public databases including TIMER, Oncomine, UALCAN, TISIDB, TCGA, Kaplan-Meier plotter, UCSC Xena, cBioPortal, SurvivalMeth, KEGG, GeneMANIA, Metascape, GSCALite and GDSC were adopted, and the expression, clinical pathological correlation, prognostic signatures, dominant factors influencing LAMC1 expression, DNA methylation levels, gene mutations, copy number variations, functional networks, and drug sensitivity were analyzed. Expression of LAMC1 protein in clinical KIRP and KIRC was validated using tissue array. Results LAMC1 expression in KIRP and KIRC were significantly higher than those in normal tissues. High LAMC1 expression indicated poor overall survivnsitivity in Cancer database. Conclusion Enhanced LAMC1 expression suggests a poor prognosis in KIRP while a better prognosis in KIRC, and these opposite prognostic signatures of LAMC1 may be related to different immune microenvironments.Signal transduction cascades efficiently transmit chemical and/or physical signals from the extracellular environment to intracellular compartments, thereby eliciting an appropriate cellular response. Most often, these signaling processes are mediated by specific protein-protein interactions involving hundreds of different receptors, enzymes, transcription factors, and signaling, adaptor and scaffolding proteins. Among them, 14-3-3 proteins are a family of highly conserved scaffolding molecules expressed in all eukaryotes, where they modulate the function of other proteins, primarily in a phosphorylation-dependent manner. Through these binding interactions, 14-3-3 proteins participate in key cellular processes, such as cell-cycle control, apoptosis, signal transduction, energy metabolism, and protein trafficking. To date, several hundreds of 14-3-3 binding partners have been identified, including protein kinases, phosphatases, receptors and transcription factors, which have been implicated in the onset of various diseases. As such, 14-3-3 proteins are promising targets for pharmaceutical interventions. https://www.selleckchem.com/products/tenalisib-rp6530.html However, despite intensive research into their protein-protein interactions, our understanding of the molecular mechanisms whereby 14-3-3 proteins regulate the functions of their binding partners remains insufficient. This review article provides an overview of the current state of the art of the molecular mechanisms whereby 14-3-3 proteins regulate their binding partners, focusing on recent structural studies of 14-3-3 protein complexes.Background The type 2 mannose receptor C (MRC2) is involved in tumor biological processes and plays a new role in the remodeling of the extracellular matrix turnover. Previous studies have demonstrated MRC2 expression profiling and prognostic relevance in some tumor types. However, the clinical and immunotherapeutic value of MRC2 in pan-cancers remains controversial. Our study aimed to evaluate MRC2 expression pattern, clinical characteristics and prognostic significance in 33 cancers, explore the relationship between MRC2 and immune-related characteristics, and assess the prediction of MRC2 for the immunotherapeutic response. Methods Transcriptional and clinical data of 33 cancers were downloaded from The Cancer Genome Atlas database (TCGA) database and two independent immunotherapeutic cohorts were obtained from GSE67501 and the IMvigor210 study. Next, patients stratified by MRC2 expression levels were displayed by Kaplan-Meier plot to compare prognosis-related indexes. Meanwhile, immune infiltrates of diffatic melanoma and advanced urothelial carcinoma cohort. Conclusion This study demonstrated that MRC2 could be a prognostic indicator for certain cancer and is critical for tumor immune microenvironments. MRC2 expression level may influence and predict immune checkpoint blockade response as a potential indicator.