Remineralization of Artificially Demineralized Human Enamel and Dentin Samples by Zinc-Carbonate Hydroxyapatite Nanocrystals

(1) Background: Decalcified enamel and dentin surfaces can be regenerated with non-fluoride-containing biomimetic systems. This study aimed to investigate the effect of a zinc carbonate-hydroxyapatite-containing dentifrice on artificially demineralized enamel and dentin surfaces. (2) Methods: Human enamel and dentin discs were prepared and subjected to surface demineralization with 30% orthophosphoric acid for 60 s. Subsequently, in the test group (n = 20), the discs were treated three times a day for 3 min with a zinc carbonate-hydroxyapatite-containing toothpaste (biorepair®). Afterwards, all samples were gently rinsed with PBS (5 s) and stored in artificial saliva until next use. Samples from the control group (n = 20) received no dentifrice-treatment and were stored in artificial saliva, exclusively. After 15 days of daily treatment, specimens were subjected to Raman spectroscopy, energy-dispersive X-ray micro-analysis (EDX), white-light interferometry, and profilometry. (3) Results: Raman spectroscopy and white-light interferometry revealed no significant differences compared to the untreated controls. EDX analysis showed calcium phosphate and silicon dioxide precipitations on treated dentin samples. In addition, treated dentin surfaces showed significant reduced roughness values. (4) Conclusions: Treatment with biorepair® did not affect enamel surfaces as proposed. Minor mineral precipitation and a reduction in surface roughness were detected among dentin surfaces only

Why are different estimates of the effective reproductive number so different? A case study on COVID-19 in Germany

The effective reproductive number R$_t$ has taken a central role in the scientific, political, and public discussion during the COVID-19 pandemic, with numerous real-time estimates of this quantity routinely published. Disagreement between estimates can be substantial and may lead to confusion among decision-makers and the general public. In this work, we compare different estimates of the national-level effective reproductive number of COVID-19 in Germany in 2020 and 2021. We consider the agreement between estimates from the same method but published at different time points (within-method agreement) as well as retrospective agreement across eight different approaches (between-method agreement). Concerning the former, estimates from some methods are very stable over time and hardly subject to revisions, while others display considerable fluctuations. To evaluate between-method agreement, we reproduce the estimates generated by different groups using a variety of statistical approaches, standardizing analytical choices to assess how they contribute to the observed disagreement. These analytical choices include the data source, data pre-processing, assumed generation time distribution, statistical tuning parameters, and various delay distributions. We find that in practice, these auxiliary choices in the estimation of R$_t$ may affect results at least as strongly as the selection of the statistical approach. They should thus be communicated transparently along with the estimates

Collaborative nowcasting of COVID-19 hospitalization incidences in Germany

Real-time surveillance is a crucial element in the response to infectious disease outbreaks. However, the interpretation of incidence data is often hampered by delays occurring at various stages of data gathering and reporting. As a result, recent values are biased downward, which obscures current trends. Statistical nowcasting techniques can be employed to correct these biases, allowing for accurate characterization of recent developments and thus enhancing situational awareness. In this paper, we present a preregistered real-time assessment of eight nowcasting approaches, applied by independent research teams to German 7-day hospitalization incidences during the COVID-19 pandemic. This indicator played an important role in the management of the outbreak in Germany and was linked to levels of non-pharmaceutical interventions via certain thresholds. Due to its definition, in which hospitalization counts are aggregated by the date of case report rather than admission, German hospitalization incidences are particularly affected by delays and can take several weeks or months to fully stabilize. For this study, all methods were applied from 22 November 2021 to 29 April 2022, with probabilistic nowcasts produced each day for the current and 28 preceding days. Nowcasts at the national, state, and age-group levels were collected in the form of quantiles in a public repository and displayed in a dashboard. Moreover, a mean and a median ensemble nowcast were generated. We find that overall, the compared methods were able to remove a large part of the biases introduced by delays. Most participating teams underestimated the importance of very long delays, though, resulting in nowcasts with a slight downward bias. The accompanying prediction intervals were also too narrow for almost all methods. Averaged over all nowcast horizons, the best performance was achieved by a model using case incidences as a covariate and taking into account longer delays than the other approaches. For the most recent days, which are often considered the most relevant in practice, a mean ensemble of the submitted nowcasts performed best. We conclude by providing some lessons learned on the definition of nowcasting targets and practical challenges

Relationship between chronic pain and cognition in cognitively intact older persons and patients with Alzheimer's disease; the need to control for mood

Background: Brain areas that are involved in cognition and mood also play a role in pain processing. Objective: The goal of the present study was to examine the relationship between chronic pain and cognition [executive functions (EF) and memory], while controlling for mood, in cognitively intact older persons and in patients with Alzheimer's disease (AD). Methods: Two groups of subjects participated: 20 older persons without dementia and 19 patients in an early stage of probable AD who suffered from arthrosis/arthritis. Pain intensity and pain affect were assessed by the Colored Analogue Scale for Pain Intensity and for Pain Affect, the Faces Pain Scale (FPS) and the Number of Words Chosen-Affective (NWC-A). Level of depression and anxiety were evaluated by questionnaires. EF and memory were assessed by neuropsychological tests. Results: The results show that significant correlations between specific cognitive functions, pain intensity and pain affect were lacking in the cognitively intact older persons. Cognition, in particular memory, appeared to be related to depressive symptoms. In contrast, a significant positive correlation was observed between EF, pain intensity and pain affect measured by the FPS in the AD group. Conclusions: Although older persons with depression were excluded, in studies on pain and cognition one should control for the presence of depressive symptoms in older persons with and without dementia. Copyright © 2008 S. Karger AG

National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021

We compare forecasts of weekly case and death numbers for COVID-19 in Germany and Poland based on 15 different modelling approaches. These cover the period from January to April 2021 and address numbers of cases and deaths one and two weeks into the future, along with the respective uncertainties. We find that combining different forecasts into one forecast can enable better predictions. However, case numbers over longer periods were challenging to predict. Additional data sources, such as information about different versions of the SARS-CoV-2 virus present in the population, might improve forecasts in the future

The German National Pandemic Cohort Network (NAPKON): rationale, study design and baseline characteristics

Schons M, Pilgram L, Reese J-P, et al. The German National Pandemic Cohort Network (NAPKON): rationale, study design and baseline characteristics. European Journal of Epidemiology . 2022.The German government initiated the Network University Medicine (NUM) in early 2020 to improve national research activities on the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. To this end, 36 German Academic Medical Centers started to collaborate on 13 projects, with the largest being the National Pandemic Cohort Network (NAPKON). The NAPKON's goal is creating the most comprehensive Coronavirus Disease 2019 (COVID-19) cohort in Germany. Within NAPKON, adult and pediatric patients are observed in three complementary cohort platforms (Cross-Sectoral, High-Resolution and Population-Based) from the initial infection until up to three years of follow-up. Study procedures comprise comprehensive clinical and imaging diagnostics, quality-of-life assessment, patient-reported outcomes and biosampling. The three cohort platforms build on four infrastructure core units (Interaction, Biosampling, Epidemiology, and Integration) and collaborations with NUM projects. Key components of the data capture, regulatory, and data privacy are based on the German Centre for Cardiovascular Research. By April 01, 2022, 34 university and 40 non-university hospitals have enrolled 5298 patients with local data quality reviews performed on 4727 (89%). 47% were female, the median age was 52 (IQR 36-62-) and 50 pediatric cases were included. 44% of patients were hospitalized, 15% admitted to an intensive care unit, and 12% of patients deceased while enrolled. 8845 visits with biosampling in 4349 patients were conducted by April 03, 2022. In this overview article, we summarize NAPKON's design, relevant milestones including first study population characteristics, and outline the potential of NAPKON for German and international research activities.Trial registration https://clinicaltrials.gov/ct2/show/NCT04768998 . https://clinicaltrials.gov/ct2/show/NCT04747366 . https://clinicaltrials.gov/ct2/show/NCT04679584. © 2022. The Author(s)

Microfluidically-Assisted Isolation and Characterization of Achromobacter spanius from Soils for Microbial Degradation of Synthetic Polymers and Organic Solvents

A micro segmented-flow approach was utilized for the isolation soil bacteria that can degrade synthetic polymers as polyethylene glycols (PEG) and polyacrylamide (PAM). We had been able to obtain many strains; among them, five Achromobacter spanius strains from soil samples of specific sampling sites that were connected with ancient human impacts. In addition to the characterization of community responses and isolating single strains, this microfluidic approach allowed for investigation of the susceptibility of Achromobacter spanius strains against three synthetic polymers, including PEG, PAM, and Polyvinylpyrrolidone (PVP) and two organic solvents known as 1,4-dioxane and diglyme. The small stepwise variation of effector concentrations in 500 nL droplets provides a detailed reflection of the concentration-dependent response of bacterial growth and endogenous autofluorescence activity. As a result, all five strains can use PEG600 as carbon source. Furthermore, all strains showed similar dose-response characteristics in 1,4-dioxane and diglyme. However, significantly different PAM- and PVP-tolerances were found for these strains. Samples from the surface soil of prehistorical rampart areas supplied a strain capable of degradation of PEG, PVP, and PAM. This study demonstrates on the one hand, the potential of microsegment flow for miniaturized dose-response screening studies and its ability to detect novel strains, and on the other hand, two of five isolated Achromobacter spanius strains may be useful in providing optimal growth conditions in bioremediation and biodegradation processes