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Hintergrund: Ein bidirektionaler Zusammenhang zwischen Diabetes mellitus und Parodontitis wird durch zahlreiche wissenschaftliche Arbeiten bestätigt. Bislang weitgehend unerforscht bleibt jedoch die Frage, ob die beiden pathophysiologisch verschiedenen Krankheitsbilder des Typ-1- und des Typ-2-Diabetes bezüglich Häufigkeit und Ausmaß parodontaler Erkrankungen Divergenzen aufzeigen. Zielstellung: Ziel der vorliegenden Untersuchung war es die parodontale Gesundheit eines Patientenkollektivs alterskorrelierter Diabetiker mit inadäquat eingestelltem Blutzucker in Abhängigkeit vom vorliegenden Diabetestyp (Typ-1 bzw. Typ-2) zu evaluieren. Material und Methoden: 101 insulinpflichtige Diabetiker (Typ-1: n=47, Typ-2: n=54.), welche in der Klinik Saale im Rahmen einer stationären Reha-Maßnahme behandelt wurden, nahmen an der Studie teil. Dabei mussten sie folgende Einschlusskriterien erfüllen: Alter 35-60J., HbA1c≥7%, Insulintherapie, Nichtraucher, ≥10 natürliche Zähne, keine parodontale Therapie oder syste¬mische Antibiose in den letzten 6 Monaten. Erfasst wurden die Zahl der natürlichen Zähne sowie an den Zähnen 16,21,24,36,41,44 (Ramfjord-Zähne) die Parameter Taschentiefe, Attachmentniveau, Gingiva-Index (GI) nach Löe&Silness und Plaque-Index (PI) nach Quigley&Hein. Basierend auf Attachmentniveau und Sondie-rungstiefen wurden die Patienten zudem gemäß den Kriterien der CDC/AAP-Arbeitsgruppe zur Klassifizierung parodontaler Erkrankungen einer von drei parodontalen Erkrankungskategorien (gesund-mild/moderat/schwer) zugeordnet. Des Weiteren wurden den ärztlichen Entlassungsbriefen der Klinik Saale zahlreiche charakteristische Daten entnommen, wie Patientenalter, Krankheitsdauer, HbA1c, Ausmaß von Folge- und Begleiterkrankungen sowie insbesondere auch BMI und CRP. Ergebnisse: Trotz erheblich kürzerer Krankheitsdauer (11,7 vs. 20,3 Jahre) und bei vergleichbarer Altersstruktur (51,3 vs. 48,3 Jahre) zeigten Typ-2-Diabetiker gegenüber Typ-1-Diabetikern eine signifikant geringere Zahnzahl (24,5 vs. 26,2 Zähne; p<0,05), einen signifikant erhöhten GI-Score (4,8 vs. 2,9; p<0,001), einen signifikant erhöhten PI-Score (8,8 vs. 6,4), einen signifikant höheren Anteil schwerer Parodontalerkankungen gemäß CDC/AAP-Kriterien (40,7% vs. 23,4%; p<0,05), signifikant höhere CRP-Werte (0,66 vs.0,31 mg/dl; p<0,001) und einen signifikant höheren BMI (37,08 vs. 27,05 kg/m²; p<0,001). Die HbA1c-Werte beider Gruppen waren nicht statistisch signifikant unterschiedlich (8,88 vs. 8,39%). Schlussfolgerung: Im Vergleich von Typ-1- und insulinpflichtigen Typ-2-Diabetikern mit annähernd vergleichbarer Altersstruktur und Diabeteseinstellung zeigen Typ-2-Diabetiker, trotz deutlich kürzerer Diabetesdauer, signifikant häufiger Symptome einer schweren Parodontitis. Dies deutet darauf hin, dass neben Hyperglykämien weitere für Typ-2-Diabetes typische ätiologische Faktoren, insbesondere subklinische Inflammationen im Rahmen des Metabolischen Syndroms, für die erhöhte Prävalenz parodontaler Erkrankungen unter Diabetikern von Bedeutung sind. Für detaillierte Aussagen sind weitere gezielte klinische Studien notwendig.
The present study investigated changes in cortical oxygenation during mental arithmetic using near-infrared spectroscopy (NIRS). Twenty-nine male volunteers were examined using a 52-channel continuous wave system for analyzing activity in prefrontal areas. With the help of a probabilistic mapping method, three regions of interest (ROIs) on each hemisphere were defined: The inferior frontal gyri (IFG), the middle frontal gyri (MFG), and the superior frontal gyri (SFG). Oxygenation as an indicator of functional brain activation was compared over the three ROI and two levels of arithmetic task difficulty (simple and complex additions). In contrast to most previous studies using fMRI or NIRS, in the present study arithmetic tasks were presented verbally in analogue to many daily life situations. With respect to task difficulty, more complex addition tasks led to higher oxygenation in all defined ROI except in the left IFG compared to simple addition tasks. When compared to the channel positions covering different gyri of the temporal lobe, the observed sensitivity to task complexity was found to be restricted to the specified ROIs. As to the comparison of ROIs, the highest oxygenation was found in the IFG, while MFG and SFG showed significantly less activation compared to IFG. The present cognitive-neuroscience approach demonstrated that NIRS is a suitable and highly feasible research tool for investigating and quantifying neural effects of increasing arithmetic task difficulty.
Butyrophilin (BTN)–3A and BTN2A1 molecules control the activation of human Vγ9Vδ2 T cells during T cell receptor (TCR)-mediated sensing of phosphoantigens (PAg) derived from microbes and tumors. However, the molecular rules governing PAg sensing remain largely unknown. Here, we establish three mechanistic principles of PAg-mediated γδ T cell activation. First, in humans, following PAg binding to the intracellular BTN3A1-B30.2 domain, Vγ9Vδ2 TCR triggering involves the extracellular V-domain of BTN3A2/BTN3A3. Moreover, the localization of both protein domains on different chains of the BTN3A homo-or heteromers is essential for efficient PAg-mediated activation. Second, the formation of BTN3A homo-or heteromers, which differ in intracellular trafficking and conformation, is controlled by molecular interactions between the juxtamembrane regions of the BTN3A chains. Finally, the ability of PAg not simply to bind BTN3A-B30.2, but to promote its subsequent interaction with the BTN2A1-B30.2 domain, is essential for T-cell activation. Defining these determinants of cooperation and the division of labor in BTN proteins improves our understanding of PAg sensing and elucidates a mode of action that may apply to other BTN family members.
Introduction: The German PID-NET registry was founded in 2009, serving as the first national registry of patients with primary immunodeficiencies (PID) in Germany. It is part of the European Society for Immunodeficiencies (ESID) registry. The primary purpose of the registry is to gather data on the epidemiology, diagnostic delay, diagnosis, and treatment of PIDs.
Methods: Clinical and laboratory data was collected from 2,453 patients from 36 German PID centres in an online registry. Data was analysed with the software Stata® and Excel.
Results: The minimum prevalence of PID in Germany is 2.72 per 100,000 inhabitants. Among patients aged 1-25, there was a clear predominance of males. The median age of living patients ranged between 7 and 40 years, depending on the respective PID. Predominantly antibody disorders were the most prevalent group with 57% of all 2,453 PID patients (including 728 CVID patients). A gene defect was identified in 36% of patients. Familial cases were observed in 21% of patients. The age of onset for presenting symptoms ranged from birth to late adulthood (range 0-88 years). Presenting symptoms comprised infections (74%) and immune dysregulation (22%). Ninety-three patients were diagnosed without prior clinical symptoms. Regarding the general and clinical diagnostic delay, no PID had undergone a slight decrease within the last decade. However, both, SCID and hyper IgE-syndrome showed a substantial improvement in shortening the time between onset of symptoms and genetic diagnosis. Regarding treatment, 49% of all patients received immunoglobulin G (IgG) substitution (70%-subcutaneous; 29%-intravenous; 1%-unknown). Three-hundred patients underwent at least one hematopoietic stem cell transplantation (HSCT). Five patients had gene therapy.
Conclusion: The German PID-NET registry is a precious tool for physicians, researchers, the pharmaceutical industry, politicians, and ultimately the patients, for whom the outcomes will eventually lead to a more timely diagnosis and better treatment.
Background
Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes.
Methods
A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported.
Results
1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict “survival”. Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients’ age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy.
Conclusions
Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models.
Trial registration “ClinicalTrials” (clinicaltrials.gov) under NCT04455451.