Polysubstance Use Among the Homeless in Germany: A Nationwide, Cross-Sectional Multicenter Study.

Background: The number of people experiencing homelessness (PEH) in Germany reached 440,000 in 2024, double the total from 2022. Representative data on substance use among PEH is largely lacking. In this study, we estimate the prevalence of substance use among PEH and identify subgroups at risk of polysubstance use.

Forecasting severe respiratory disease hospitalizations using machine learning algorithms.

Background: Forecasting models predicting trends in hospitalization rates have the potential to inform hospital management during seasonal epidemics of respiratory diseases and the associated surges caused by acute hospital admissions. Hospital bed requirements for elective surgery could be better planned if it were possible to foresee upcoming peaks in severe respiratory illness admissions. Forecasting models can also guide the use of intervention strategies to decrease the spread of respiratory pathogens and thus prevent local health system overload.

Advancements in biotransformation pathway prediction: enhancements, datasets, and novel functionalities in enviPath.

enviPath is a widely used database and prediction system for microbial biotransformation pathways of primarily xenobiotic compounds. Data and prediction system are freely available both via a web interface and a public REST API. Since its initial release in 2016, we extended the data available in enviPath and improved the performance of the prediction system and usability of the overall system.

Immunity against measles, mumps, rubella, and varicella among homeless individuals in Germany - A nationwide multi-center cross-sectional study.

Introduction: Homeless individuals suffer a high burden of vaccine-preventable infectious diseases. Moreover, they are particularly susceptible to adverse infection outcomes with limited access to the health care system. Data on the seroprevalence of measles, mumps, rubella, and varicella within this cohort are missing.

AdductHunter: identifying protein-metal complex adducts in mass spectra.

Mass spectrometry (MS) is an analytical technique for molecule identification that can be used for investigating protein-metal complex interactions. Once the MS data is collected, the mass spectra are usually interpreted manually to identify the adducts formed as a result of the interactions between proteins and metal-based species. However, with increasing resolution, dataset size, and species complexity, the time required to identify adducts and the error-prone nature of manual assignment have become limiting factors in MS analysis.

Determinants of health-related quality of life (HRQoL) among homeless individuals during the COVID-19 pandemic.

Objective: Thus far, there is very limited knowledge regarding homeless individuals during the COVID-19 pandemic, particularly related to the health-related quality of life (HRQoL). Thus, our aim was to evaluate HRQoL and to clarify the determinants of HRQoL among homeless individuals during the COVID-19 pandemic in Germany.

Methods: Data were taken from the national survey on psychiatric and somatic health of homeless individuals during the COVID-19 pandemic-NAPSHI (n = 616).

Combatting over-specialization bias in growing chemical databases.

Background: Predicting in advance the behavior of new chemical compounds can support the design process of new products by directing the research toward the most promising candidates and ruling out others. Such predictive models can be data-driven using Machine Learning or based on researchers' experience and depend on the collection of past results. In either case: models (or researchers) can only make reliable assumptions about compounds that are similar to what they have seen before.

The Mental and Physical Health of the Homeless.

Background: The health status of homeless individuals in Germany has been described incompletely. Mental and somatic illnesses seem to contribute to the high mortality in this cohort.

Methods: In this national, multicenter, cross-sectional study, data were collected on the health of 651 homeless individuals in the metropolitan regions of Hamburg, Frankfurt, Leipzig, and Munich metropolitan regions.

Predictors of Loneliness among Homeless Individuals in Germany during the COVID-19 Pandemic.

Purpose: The aim of the study was to identify the frequency of loneliness and to examine the factors associated with loneliness among homeless individuals in Germany during the COVID-19 pandemic.

Methods: Data were taken from the 'national survey on the psychiatric and somatic health of homeless individuals during the COVID-19 pandemic'. The data collection took place from 26th July to 17th September 2021 (the analytical sample included = 491 observations).

Fear of COVID-19 among homeless individuals in Germany in mid-2021.

Aims: To investigate the prevalence and the correlates of fear of COVID-19 among homeless individuals.

Methods: We used data from the "national survey on psychiatric and somatic health of homeless individuals during the COVID-19 pandemic" (NAPSHI-study) which took place in several large cities in Germany in Mid-2021 ( = 666 in the analytical sample). Mean age equaled 43.