Incidence of type 1 and type 2 diabetes before and during the COVID-19 pandemic in Germany: Analysis of routine data from 2015 to 2021

Background: To date, there is no data available depicting the trend of the incidence of type 1 and type 2 diabetes across all age groups for the COVID-19 pandemic years in Germany. Methods: Based on anonymized routine data from nine million persons covered by statutory health insurance, newly diagnosed diabetes cases (ICD diagnosis E10.- to E14.-) in inpatient or (confirmed in two quarters) outpatient setting were estimated for 2015 to 2021, differentiating between type 1 and type 2 diabetes. The data were linked to the German Index of Socioeconomic Deprivation. The results are age-standardised (population as of 31 Dec. 2021). Results: Between 2015 and 2021, the incidence of type 1 diabetes increased from 9.5 to 11.6 per 100,000 persons (from 7,007 to 8,699 new cases per year). In contrast, the incidence of type 2 diabetes tended to decline between 2015 and 2019. It continued to drop initially in 2020 during the pandemic, and then rose to 740 per 100,000 persons in 2021 (556,318 new cases per year). The diabetes type-specific seasonal pattern of previous years has changed during the pandemic years. The incidence of both type 1 and type 2 diabetes was observed to be higher in regions of high socioeconomic deprivation as compared to regions characterised by low socioeconomic deprivation. Conclusions: The increase in the incidence of type 1 and type 2 diabetes in 2021 may possibly be related to the COVID-19 pandemic. The high incidence and the differences by regional socioeconomic deprivation indicate that there is a need for targeted prevention strategies

Reproductive Toxicity and Life History Study of Silver Nanoparticle Effect, Uptake and Transport in Arabidopsis thaliana

Concerns about nanotechnology have prompted studies on how the release of these engineered nanoparticles impact our environment. Herein, the impact of 20 nm silver nanoparticles (AgNPs) on the life history traits of Arabidopsis thaliana was studied in both above- and below-ground parts, at macroscopic and microscopic scales. Both gross phenotypes (in contrast to microscopic phenotypes) and routes of transport and accumulation were investigated from roots to shoots. Wild type Arabidopsis growing in soil, regularly irrigated with 75 μg/L of AgNPs, did not show any obvious morphological change. However, their vegetative development was prolonged by two to three days and their reproductive growth shortened by three to four days. In addition, the germination rates of offspring decreased drastically over three generations. These findings confirmed that AgNPs induce abiotic stress and cause reproductive toxicity in Arabidopsis. To trace transport of AgNPs, this study also included an Arabidopsis reporter line genetically transformed with a green fluorescent protein and grown in an optical transparent medium with 75 μg/L AgNPs. AgNPs followed three routes: (1) At seven days after planting (DAP) at S1.0 (stages defined by Boyes et al. 2001 [41]), AgNPs attached to the surface of primary roots and then entered their root tips; (2) At 14 DAP at S1.04, as primary roots grew longer, AgNPs gradually moved into roots and entered new lateral root primordia and root hairs; (3) At 17 DAP at S1.06 when the Arabidopsis root system had developed multiple lateral roots, AgNPs were present in vascular tissue and throughout the whole plant from root to shoot. In some cases, if cotyledons of the Arabidopsis seedlings were immersed in melted transparent medium, then AgNPs were taken up by and accumulated in stomatal guard cells. These findings in Arabidopsis are the first to document specific routes and rates of AgNP uptake in vivo and in situ

Inzidenz von Typ-1- und Typ-2-Diabetes vor und während der COVID-19-Pandemie in Deutschland: Analyse von Routinedaten der Jahre 2015 bis 2021

Hintergrund: Für Deutschland existieren bisher keine Trenddaten zur Inzidenz von Typ-1- und Typ-2-Diabetes über alle Altersgruppen, die die COVID-19-Pandemiejahre berücksichtigen. Methode: Basierend auf anonymisierten Routinedaten von neun Millionen Krankenversicherten wurden Neuerkrankungen an Diabetes (ICD-Diagnose E10.- bis E14.-) im stationären oder (gesichert in zwei Quartalen) im ambulanten Bereich für 2015 bis 2021 geschätzt und nach Typ 1 und Typ 2 unterschieden. Die Daten wurden mit dem German Index of Socioeconomic Deprivation verknüpft. Die Ergebnisse sind altersstandardisiert (Bevölkerung zum 31.12.2021). Ergebnisse: Die Inzidenz von Typ-1-Diabetes stieg zwischen 2015 und 2021 von 9,5 auf 11,6 pro 100.000 Personen (von 7.007 auf 8.699 Neuerkrankte pro Jahr) an. Die Inzidenz von Typ-2-Diabetes zeigte zwischen 2015 und 2019 einen abnehmenden Trend. Während der Pandemie sank sie 2020 zunächst weiter ab und stieg 2021 an auf 740 pro 100.000 Personen (556.318 Neuerkrankte pro Jahr). Während der Pandemiejahre war das typenspezifische saisonale Muster der Vorjahre verändert. Sowohl für Typ-1- als auch für Typ-2-Diabetes wurde eine höhere Inzidenz in Regionen mit hoher als in Regionen mit niedriger sozioökonomischer Deprivation beobachtet. Schlussfolgerungen: Der Anstieg der Inzidenz von Typ-1- und Typ-2-Diabetes im Jahr 2021 steht möglicherweise im Zusammenhang mit der COVID-19-Pandemie. Die hohen Inzidenzen und die Unterschiede nach regionaler sozioökonomischer Deprivation weisen auf einen Bedarf an angemessenen Präventionsstrategien hin

Adaptation of Brucella melitensis Antimicrobial Susceptibility Testing to the ISO 20776 Standard and Validation of the Method

This article belongs to the Special Issue Emerging Themes in Brucella and Brucellosis.Brucellosis, mainly caused by Brucella (B.) melitensis, is associated with a risk of chronification and relapses. Antimicrobial susceptibility testing (AST) standards for B. melitensis are not available, and the agent is not yet listed in the EUCAST breakpoint tables. CLSI recommendations for B. melitensis exist, but they do not fulfill the requirements of the ISO 20776 standard regarding the culture medium and the incubation conditions. Under the third EU Health Programme, laboratories specializing in the diagnostics of highly pathogenic bacteria in their respective countries formed a working group within a Joint Action aiming to develop a suitable method for the AST of B. melitensis. Under the supervision of EUCAST representatives, this working group adapted the CLSI M45 document to the ISO 20776 standard after testing and validation. These adaptations included the comparison of various culture media, culture conditions and AST methods. A Standard Operation Procedure was derived and an interlaboratory validation was performed in order to evaluate the method. The results showed pros and cons for both of the two methods but also indicate that it is not necessary to abandon Mueller–Hinton without additives for the AST of B. melitensis.This research was funded by the EU Health Programme 2014–2020, through the Consumers, Health, Agriculture and Food Executive Agency (CHAFEA, European Commission), the Joint Action EMERGE (CHAFEA n° 677 066) and the Joint Action SHARP (848096-SHARP JA).info:eu-repo/semantics/publishedVersio

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

This work was in part supported by the PRIME-XS project, grant agreement number 262067, funded by the European Union seventh Framework Programme; The Netherlands Proteomics Centre, embedded in The Netherlands Genomics Initiative; The Netherlands Bioinformatics Centre; and the Centre for Biomedical Genetics (to S.C., B.B. and A.J.R.H); by NIH grants NCRR RR001614 and RR019934 (to the UCSF Mass Spectrometry Facility, director: A.L. Burlingame, P.B.); and by grants from the MRC, CR-UK, BBSRC and Barts and the London Charity (to P.C.

Lets Talk about Race: Identity, Chatbots, and AI

Why is it so hard for chatbots to talk about race? This work explores how the biased contents of databases, the syntactic focus of natural language processing, and the opaque nature of deep learning algorithms cause chatbots difficulty in handling race-talk. In each of these areas, the tensions between race and chatbots create new opportunities for people and machines. By making the abstract and disparate qualities of this problem space tangible, we can develop chatbots that are more capable of handling race-talk in its many forms. Our goal is to provide the HCI community with ways to begin addressing the question, how can chatbots handle race-talk in new and improved ways

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14