Abstract Cryogenic technologies have emerged as promising sample preparation techniques for preserving sample integrity and improving analytical performance in occupational exposure assessment. However, evidence regarding their application in occupational exposure monitoring remains scattered and has not been systematically synthesized. A systematic literature review was conducted in 2025 to evaluate the application of cryogenic technologies in sample preparation for occupational exposure assessment of chemical contaminants. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Searches were performed in Scopus, PubMed, Web of Science, and Google Scholar without time restrictions. Studies published in English and Persian were screened based on predefined eligibility criteria. The methodological reliability of toxicological studies was assessed using the Toxicological data Reliability Assessment Tool. Of 862 retrieved records, 18 studies were included. The included studies investigated four cryogenic technologies: Cryo-Electron Microscopy (Cryo-EM), Cryo-Trapping/Cryo-Focusing, Cryo-Grinding, and Cryo-Milling. Cryo-Trapping/Cryo-Focusing was the most frequently applied technique, whereas Cryo-Milling and Cryo-EM were reported only in a limited number of occupational exposure studies. Most applications focused on volatile organic compounds in air, blood, urine, and standard solutions. Cryogenic technologies were associated with improved sample preservation and analytical sensitivity, although methodological heterogeneity limited comparison across studies. Cryogenic technologies represent valuable complementary approaches for sample preparation in occupational exposure assessment. However, current evidence remains limited and heterogeneous, emphasizing the need for standardized studies to establish their broader applicability in occupational hygiene and toxicology.
Aims: Water used in dental settings plays a critical role in patient care, and its microbiological safety is essential for protecting both patients and dental staff. This study aimed to investigate the presence of Pseudomonas aeruginosa and Aeromonas hydrophila in dental unit waterlines (DUWLs). Methods: In this cross-sectional study, 140 water samples were collected from different points of DUWLs at Gorgan Dental School, northern Iran, as well as from municipal water supplies, between August 2022 and May 2023. The presence of P. aeruginosa and A. hydrophila was detected using polymerase chain reaction. Associations between physicochemical parameters and bacterial presence were analyzed using the Chi-squared test, with P < 0.05 considered statistically significant. Results: P. aeruginosa and A. hydrophila were detected in 66.4% (93/140) and 32.1% (45/140) of the samples, respectively. A statistically significant association was observed between bacterial prevalence and sampling points (P < 0.05). The highest prevalence of both bacteria was found in dental handpieces before flushing, whereas the lowest prevalence was observed in municipal water supply points. Flushing did not significantly reduce bacterial prevalence. Mean values of pH, residual chlorine, and temperature ranged from 7.20 to 7.50, 0.0 to 0.3 mg/L, and 19.30°C to 23.80°C, respectively. Residual chlorine levels in contaminated samples were generally low. Conclusion: The presence of opportunistic bacteria in DUWLs indicates potential health risks, particularly for immunocompromised patients. Implementing effective water safety plans and improving dental staff training are essential to enhance DUWL microbiological quality and reduce infection risks in dental clinics.
Aim: This study seeks to investigate the inadequacy of the A-weighting network for measuring noise characterized by substantial infrasound and lower frequency components. Utilizing a computational approach, the research aims to elucidate the limitations of A-weighting, which primarily focuses on frequencies perceptible to the human ear. Methods: The methodologies and equations employed in this analysis adhere to the international standard IEC 61672-1 for the computation of the A, C, and Z frequency-weighting networks. Weighting values for these three different networks were determined across various frequencies within one-third octave bands. Subsequently, utilizing the derived weighting values, sound pressure levels were calculated across 34 distinct one-third octave band frequencies, ranging from 10 to 20,000 Hz, as well as the total sound pressure level for artificial high-content and low-frequency noise. Results: The largest (most negative) weighting factor was at 10-Hz frequency for both the A and C networks. The weighting factor decreases with increasing frequency: for the A-network, from 10 to 500 Hz, and for the C-network, from 10 to 160 Hz. Above those frequencies, the weighting factor becomes smaller (more positive). The C weighting was zero (0 dB), for nine, contiguous one-third octave frequency bands from 200 Hz to 1250 Hz, while for the A-weighting, only the 1000 Hz frequency band has zero (0 dB) weighting. Weighting for the Z-network was zero (0 dB) at all frequencies. For an artificial high-content and low-frequency noise, the A network greatly reduces the value of the total sound pressure level (73.68 dB) when compared to the C network (96.44 dB), and especially when compared to the Z network (104.33 dB). Conclusions: The utilization of the A-weighting network in noise measurement fails to adequately identify locations characterized by high levels of infrasound and low-frequency noise. Consequently, individuals residing in these areas may inadvertently be exposed to noise-induced health effects, yet the lack of recognition regarding this issue may hinder appropriate public health responses and interventions.
Aims: Indoor air quality (IAQ) in healthcare settings is critical for preventing the spread of infectious diseases. This study aimed to quantitatively assess the impact of key ventilation parameters on indoor bioaerosol burden and particulate matter 10 (PM10) concentrations across four educational hospitals. Methods: Bioaerosol samples were collected from multiple locations within each hospital, including operating rooms, intensive care units, and general wards, in accordance with NIOSH Method 0800, using a Quick Take 30 sampler. Concurrently, temperature, relative humidity, ventilation rate expressed as air changes per hour (ACH), and PM10 concentrations were measured as potential factors influencing bioaerosol levels. Results: The results revealed significant variations in bioaerosol concentrations among the hospitals. D Hospital exhibited the highest levels, potentially due to factors such as the facility’s age, maintenance practices, and ventilation system efficiency. Positive correlation was observed between bioaerosol concentration and both temperature and the number of people present. However, a significant correlation was not found between ACH and bioaerosol concentration. Conclusion: These findings underscore the importance of effective ventilation systems and regular maintenance to minimize bioaerosol levels in healthcare facilities. Further research is recommended to investigate the impact of specific ventilation strategies and environmental factors on IAQ and infection control.
