Fig 2 -

Severity of mental distress of subjects with (A) and without (B) a previous diagnosis of anxiety disorder or depression by occupational SARS-CoV-2 risk group and time of survey. Mental distress is assessed using the PHQ-4 score indicating the severity of anxiety and depressive symptoms as normal (green), mild (yellow), moderate (orange) and severe (red), with missing values shown in gray. The survey was conducted during wave 1 (t1, retrospective), waves 2 and 3 (t2), wave 5 (t3, retrospective), and at the end of 2022 (t4).</p

Risk estimation for severe depressive symptoms (PHQ-2 ≥ 3).

Risk estimation for severe depressive symptoms (PHQ-2 ≥ 3).</p

Sociodemographic characteristics of the follow-up study population.

Sociodemographic characteristics of the follow-up study population.</p

Characterization of occupational strain in the follow-up study population.

Characterization of occupational strain in the follow-up study population.</p

Additional linear mixed model analysis for mental distress.

Additional linear mixed model analysis for mental distress.</p

Distribution of occupations at follow-up with assigned increased risk of SARS-CoV-2 infection.

Distribution of occupations at follow-up with assigned increased risk of SARS-CoV-2 infection.</p

Survey periods of the study in relation to SARS-CoV-2 incidences and pandemic waves with the respective prevailing variance of concern (VOC) in Germany.

Survey periods of the study in relation to SARS-CoV-2 incidences and pandemic waves with the respective prevailing variance of concern (VOC) in Germany.</p

Fig 1 -

Distribution of mental distress (A), probable generalized anxiety disorder (B), and probable major depressive disorder (C) by occupational SARS-CoV-2 risk group and time of survey for 260 participants with baseline and follow-up data. Mental distress is assessed using the PHQ-4 score indicating the severity of anxiety and depressive symptoms. GAD-2 scores ≥ 3 and PHQ-2 scores ≥ 3 indicate a probable generalized anxiety disorder and a probable major depressive disorder, respectively. The survey was conducted during wave 1 (t1, retrospective), waves 2 and 3 (t2), wave 5 (t3, retrospective), and at the end of 2022 (t4).</p

Risk estimation for severe anxiety symptoms (GAD-2 ≥ 3).

Risk estimation for severe anxiety symptoms (GAD-2 ≥ 3).</p

Effects of benzo[a]pyrene, aromatic amines, and a combination of both on CYP1A1 activities in RT-4 human bladder papilloma cells

<p>The interaction of arylamines and polycyclic aromatic hydrocarbons (PAH) is of particular interest in the etiology of bladder cancer. The aim of this study was to (1) examine the metabolic capacity of RT-4 human bladder papilloma cells and (2) investigate the influence of aromatic amines on the induction of cytochrome P-450 1A1 (CYP1A1) activity and their effects on benzo[a]pyrene (BaP)-induced CYP1A1 activities. Cells were incubated for 24 h with different concentrations of BaP, 1- or 2-naphthylamine (NA), 2-, 3-, or 4-aminobiphenyl (ABP), and binary mixtures consisting of 1 µ<i>M</i> BaP and different concentrations of each arylamine. Changes in CYP1A1 activities were measured at concentrations with no or only low cytotoxicity and accompanied by specific protein detection. Several phase I and II enzymes relevant to metabolism of PAH and arylamines were present in RT-4 cells. Concentration-dependent elevation in CYP1A1 activities accompanied by increasing protein levels was found after treating cells with BaP and 1- or 2-NA. The majority of synergistic effects in binary mixtures were less than additive. In contrast, concentration-dependent inhibition was observed for 2-, 3-, and 4-ABP and in both the presence and absence of BaP. Our results suggest that RT-4 cells represent a reliable model cell line to study arylamine- and PAH-induced effects in vitro and that BaP-induced CYP1A1 activities are modulated by aromatic amines. In general, the direction of the effect depends upon the aromatic amine, rather than being unidirectional for aromatic amines.</p