Air pollution is one of the greatest public health threats worldwide. All substances appearing in excessive quantities in the atmosphere, such as particulate matter, nitrogen oxides or sulphur oxides may be its ingredients. Depending on their size and nature, these compounds may cause greater...

Air pollution has a negative influence on neurological and psychiatric disorders. However, findings concerning the impact of air pollution on depression remain inconclusive. A deeper insight into these associations is warranted. To evaluate the impact of long-term exposure to air pollution on the incidence of depression among residents of 13 counties in the Lower Silesia region of Poland. We used data on cases of depression from the National Health Fund (Narodowy Fundusz Zdrowia - NFZ) from 13 counties of Lower Silesia between January 1, 2010, and December 31, 2015. Patients with a confirmed diagnosis of depression were included. Data on air pollution levels were extracted from the Chief Inspectorate of Environmental Protection (Główny Inspektorat Ochrony Środowiska - GIOŚ), and demographic data were extracted from Statistics Poland (Główny Urząd Statystyczny - GUS). The percentage of people diagnosed with depression over the 6-year study period depended on the group of counties homogeneous in terms of air pollution exposure (p < 0.001). We showed statistically significant correlations between different depression diagnoses and exposure to air pollutants. Elevated concentration of airborne fine particles with a diameter less than 2.5 μm (PM2.5) and carbon monoxide (CO), and low benzo(a)pyrene (BaP), sulfur dioxide (SO2) and cadmium (Cd) levels were independent risk factors for major depressive episodes with psychotic symptoms (F32.3). There was a significant negative correlation between ozone (O3) levels and depression incidence. Regions with heavy air pollution had a higher incidence of depression. There is a significant association between the exposure to air pollutants and different depression diagnoses.

(1) Introduction: Anorexia nervosa (AN) is a severe, debilitating disease with high incidence and high mortality. The methods of treatment used so far are moderately effective. Evidence from neuroimaging studies helps to design modern methods of therapy. One of them is transcranial direct current stimulation (tDCS), a non-invasive brain neuromodulation technique. (2) Methods: The purpose of this narrative review is to bring together all studies investigating the use of tDCS in the treatment of AN and to evaluate its effect and efficiency. Searches were conducted in the Pubmed/Medline, Research Gate, and Cochrane databases. (3) Results: The literature search resulted in five articles. These studies provide preliminary evidence that tDCS has the potential to alter eating behaviour, body weight, and food intake. Additionally, tDCS reduced symptoms of depression. Throughout all trials, stimulation targeted the left dorsolateral prefrontal cortex (DLPFC). Although the number of studies included is limited, attempts were made to elucidate the potential mechanisms underlying tDCS action in individuals with AN. Recommendations for future tDCS research in AN were issued. (4) Conclusions: The included studies have shown that tDCS stimulation of the left DLPFC has a positive effect on AN clinical symptoms and may improve them, as measured by various assessment measures. It is important to conduct more in-depth research on the potential benefits of using tDCS for treating AN. This should entail well-designed studies incorporating advanced neuroimaging techniques, such as fMRI. The aim is to gain a better understanding of how tDCS works in AN.

Exposure to particulate matter is an important risk factor for mental health disturbances and overall mortality. However, the knowledge on relationship between long-term particulate matter level and suicide rate is limited and requires in-depth study. Population and air pollution data were obtained from the Polish Central Statistics Office and Chief Inspectorate of Environmental Protection for the period 2014–2015. Aspatial multivariate and one factor regression analysis were performed and followed by spatial global regression analysis for district reference units in geographic information system (GIS). At the district level of aggregation, data showed spatial stationarity. The best-fitting spatial global model was based on number of disorders caused by the use of psychoactive substances, number of people treated in psychiatric hospitals, population density, unemployment rate and per capita income. Global spatial model with PM2.5 level parameter was an improvement over the one without it (adj. R2 = 0.87 compared to adj. R2 = 0.83). There is a positive relationship between particular matter concentrations and suicides in Poland. Application of Geographic Information Science analytical functions in medicine can be viewed as a new efficient methodological approach.

Mental health counseling remains a major challenge in modern society due to cost, stigma, fear, and unavailability. We posit that generative artificial intelligence (AI) models designed for mental health counseling could help improve outcomes by lowering barriers to access. To this end, we have developed a deep learning (DL) dialogue system called Serena. The system consists of a core generative model and post-processing algorithms. The core generative model is a 2.7 billion parameter Seq2Seq Transformer fine-tuned on thousands of transcripts of person-centered-therapy (PCT) sessions. The series of post-processing algorithms detects contradictions, improves coherency, and removes repetitive answers. Serena is implemented and deployed on \url{https://serena.chat}, which currently offers limited free services. While the dialogue system is capable of responding in a qualitatively empathetic and engaging manner, occasionally it displays hallucination and long-term incoherence. Overall, we demonstrate that a deep learning mental health dialogue system has the potential to provide a low-cost and effective complement to traditional human counselors with less barriers to access.