Gills and heart showed upregulation of HSP90 with statistical significance . In addition, HSP70 gene expression in gills was positively correlated with gas score (p = 0.033). These results suggest that gas embolism modify the expression of different biomarkers, with HSP70 being shown as a strong marker of this process. Furthermore, gas score is a useful tool to study the abundance of gas bubbles, although individual variability always remains present. These results support the validity of the GBD model in fish to study gas embolism in diseases such as DCS.Fish exposed to water supersaturated with dissolved gas experience gas embolism similar to decompression sickness (DCS), known as gas bubble disease (GBD) in fish. GBD has been postulated as an alternative to traditional mammals’ models on DCS. Gas embolism can cause mechanical and biochemical damage, generating pathophysiological responses. Increased expression of biomarkers of cell damage such as the heat shock protein (HSP) family, endothelin 1 (ET-1) or intercellular adhesion molecule 1 (ICAM-1) has been observed, being a possible target for further studies of gas embolism. The GBD model consisted of exposing fish to supersaturation in water with approximately 170% total dissolved gas (TDG) for 18 hours, producing severe gas embolism. This diagnosis was confirmed by a complete histopathological exam and the gas score method. HSP70 showed a statistically significant upregulation compared to the control in all the studied organs ( The circulation of gas bubbles through the vascular system is known as gas embolism. It can be developed under different conditions, including the accidental introduction of gas during surgical and medical procedures ,2, penetGBD and DCS share similarities in terms of pathophysiology, the latter has previously been postulated as an experimental model for studying DCS –13. VeláGBD occurs in fish when the water where they inhabit gets supersaturated of dissolved gases . This diGas embolism can cause mechanical and biochemical damage , generatCarassius auratus), we evaluated tissue damage through pathology, we assessed the presence, distribution, and amount of gas bubbles in several intra- and extravascular locations and analyzed the expression of different biomarkers that have previously been associated with the consequent biochemical damage of gas embolism in other laboratory animals.In this study, we tested the hypothesis that GBD in fish induces similar vascular and cellular responses to other gas embolisms, such as DCS in mammals, and if it can be used as an alternative experimental model. To test this hypothesis, we first induced a severe GBD in a group of goldfish (Carassius auratus), 10 males and 10 females , were purchased from Tropical Centre (ICA Canarias). Fish were kept in tap water conditioned with JBL Biotopol and JBL Denitrol, according to the manufacturer’s instructions, with a natural photoperiod of 12:12h light:dark cycle and fed twice daily. Using a colorimetric test kit, water parameters such as nitrate and nitrite concentration , pH (±6.8), total hardness (80–300 mg/dm3) and chlorine (0 mg/dm3) were measured every two days, along with measurement of temperature (23–25°C) and dissolved oxygen (>6.0 mg/ dm3).For this study, 20 goldfish (Fish were evenly divided into two treatment groups: control group (n = 10) and GBD group (n = 10). Fish in the GBD group were individually introduced into a pressurized aquarium for 18 hours with supersaturated water produced following Velázquez-Wallraf et al. . This suFish were introduced in the pressurized aquarium when TDG supersaturation levels of 169 ± 5% were reached in agreement with Velázquez-Wallraf et al. . Fish frTable 1), In the extravascular locations, the gas score was based on the presence of emphysema in the visceral fat and fins. Total gas score was calculated by the summation of the gas score index for each location. Gas score ranged from 0 to 54.Before dissection, the eyes, integument, gills, and fins were examined under a stereo microscope for the presence of gas bubbles and lesions. Later, the coelomic cavity was carefully opened to enable the visualization of internal organs and vasculature, and presence, amount, and distribution of intravascular and extravascular gas bubbles, was evaluated using a gas score index  adapted Simultaneously to the gas score, external and internal organs were examined macroscopically for lesions, and representative samples were collected and fixed in 10% buffered formalin. Samples were processed routinely, embedded in paraffin wax and 4-μm-thick sections were cut and stained with hematoxylin and eosin (H&E)  and examCarassius auratus were aligned using NCBI BLAST sequence alignment analysis (NIH) and primers designed on common conserved regions (Table 2). In addition, elongation factor 1-alpha (EF1α) and beta-2 microglobin (B2M) were chosen as reference (housekeeping) genes, according to GeNorm.Molecular studies of biomarkers of vascular damage were carried out in 6 fish from each group. Samples of posterior kidney, gills, heart, and ventral aorta were collected in cryotubes with 1 ml of RNA-later , maintained for 24 hours at 4°C and then preserved at -80°C until RNA extraction from the samples was performed. Sequences corresponding to the open reading frame (ORF) for selected genes, HSP70, HSP90, E-1, and ICAM-1, for Target tissues were dissected and homogenized in tubes with 900 μl of Qiazol Lysis Reagent using a stainless-steel bead in Tissuelyser II , and following the manufacturer’s instructions for total RNA extraction. Isolated RNA was quantified via spectrophotometry . RNA quality was estimated by visualization on 1% agarose gel with an UV transluminator . Complementary DNA (cDNA) was synthesized from 10 μl of extracted RNA using the High-capacity cDNA reverse transcription kit , and performing reverse transcription by thermocycler. To quantify this cDNA synthesis, a Qubit fluorometer  was used together with a Qubit ssDNA Assay kit, performing standard curves.Table 2 and were calculated to ensure that the efficiency is above 90% for all primer pairs.Confirmation of correct amplification of selected reference and target genes was carried out previously as follows: melting-curve analysis for each primer set was conducted to further confirm the specificity of PCR amplification. To calculate the PCR amplification efficiency of each primer set, serial dilution of cDNA from the samples and no-template control were used as templates for Real-Time quantitative PCR (RT-qPCR). The standard curve was generated for the calculation of amplification efficiency (E) and correlation coefficients (R2) of each primer set. These values are listed in 20. In addition, no-template control (C-NTC) and RT negative control (C-RT-) were used as negative controls for each primer set. The amplification programs were set as an initial denaturation step at 95°C for 30 sec, followed by 40 PCR cycles: 5 s at 95°C, 1 min at 62°C for annealing temperature.RT-qPCR was carried out using QuantStudio 12k flex RT-qPCR system  in 96 well-plates in triplicates . The total volume per reaction was set at 10 μl, containing 1 μl of cDNA sample (1:10 diluted), 5 μl of TB Green™ Premix Ex Taq™ II-Tli RNaseH Plus , 0.2 μl ROX Reference Dye II , 0.2 μl of forward and reverse specific primers for each gene and 3.4 μl of ddH-ΔCt method [The RT-qPCR data were analyzed using Design & Analysis Software v.2.4.3 . Cycle threshold (Ct) values were obtained using auto baseline and applied to all amplicons of the same primer set. The fold change in expression of target genes  was calculated using the 2t method . Gene exp < 0.05) or near statistically significantly different (p < 0.1), the correlation of these gene concentrations and total gas score was evaluated by Spearman’s correlation coefficient. The significance level used for all statistical tests performed was p value < 0.05. SPSS software package  and R software package  for Windows were used. Statistical power was calculated by post hoc test with a significance level of 0.05, using G*power software .The differences in biomarker gene concentration in control fish vs fish with GBD were analysed by Mann-Whitney test. Biomarker genes that were found to be statistically significant different  , posterior cardinal veins (60%) , ventral aorta (50%) , and dorsal aorta (30%). The subcutaneous caudal (50%)  and opercular veins (30%) presented a mode gas score of 4; and the subcutaneous cranial (60%)  and swim bladder (50%) vein had a mode gas score of 3 . Within the two extravascular locations studied, mode gas score was 2, both in visceral fat emphysema (60%) and fin emphysema (50%). All the control animals showed a total gas score of 0.The results obtained at each intravascular and extravascular location, as well as the total gas score of the GBD group are shown in Fig 3A and 3B), being the pectoral fins  followed by the caudal fins  the most affected locations. The gills presented severe hemorrhages  .Externally, the presence of subcutaneous emphysema was denoted by skin in 70% of fish (7/10), coinciding with areas where the loss of scales was observed in vivo. Fins presented emphysema and hemorrhages in all animals  . In addition, the swim bladder was hyperinflated  and the bulbus arteriosus of the heart appeared distended due to the presence of gas . Multiorgan congestion was observed: fins , gills (100%/10/10/10), posterior kidney , liver , spleen , and central nervous system .In the opening of the coelomic cavity, emphysema of the visceral adipose tissue stood out in most animals  . In the posterior kidney, severely dilated blood vessels were observed , without the presence of circulating blood, while in those with the presence of blood, congestion was observed  . Intravascular bubble-like round empty spaces among blood cells were identified in different blood vessels. These were predominantly observed in fins , gills  and posterior kidney  in considerable amounts. In other organs intravascular gas bubbles were also observed but only in some animals, such as ventral aorta  , in the coronary veins of the heart , spleen , gonads , and liver . These structures were neither stained by H&E or Oil Red, confirming that they were gas bubbles . Multiorgan congestion was confirmed via microscopic visualization.Microscopically, notable findings were emphysema of fins  observed as gas-distended areas between the fin rays, together with congestion . In some animals, hemorrhages due to the rupture of larger congested blood vessels were observed in the fins . The gills showed remarkably consistent microscopic congestion  and hemorrhages , together with fusion of the secondary lamellae in some animals  . The expression of HSP70 and HSP90 genes were significantly increased in gills  and heart (p = 0.002 in both). HSP70 gene expression was also significantly increased in the posterior kidney and ventral aorta (p = 0.002 in both), compared to the control group. ET-1 in posterior kidney and ventral aorta, HSP90 in posterior kidney, and ICAM-1 in gills showed a tendency towards upregulation compared to the control group although no statistically significant differences were observed. Results of statistical power for each biomarker expression performed are described in S1 Table. HSP70 expression statistical analyses in the four tissues had high statistical power (>90%).Gene expression results were logarithmically transformed and were expressed as mean ± standard error of the mean (SEM) . Additionally, a tendency to correlate was found for HSP70 expression in the heart and ET-1 expression in the posterior kidney with total gas score, although these correlations were not statistically significant  . Results of statistical power of correlation studies performed are described in S2 Table. HSP70 in gills and heart with total gas score had a correlation with high statistical power (>90%).HSP70 expression in gills correlated strongly with total gas score, with statistically significant results  following Velázquez-Wallraf et al. . The diaThe dissolution of atmospheric gas in the water of large dams occurs continuously, due to the constant fall of water from one reservoir to another causing nearby waters to remain supersaturated . VelázquThe main macroscopic and microscopic findings were gas bubbles systemically distributed. Other main pathological findings included: emphysema in fins, subcutaneous tissue, and adipose tissue, hemorrhages in fins, gills, and posterior kidney, and multiorgan congestion. These pathological findings were consistent with those described previously by our group  and otheAll fish in the GBD treatment group had a relatively high total gas score, although there was some inter-individual variability. This inter-individual variability was observed in the opercular veins, swim bladder vein, caudal subcutaneous veins, or the dorsal aorta. Hence, these locations were considered the most relevant to evaluate the severity of the gas embolism. Individual variability has been postulated to play a determining role in diseases that produce gas embolism ,37.Increased amount of gas bubbles in vascular locations systemically distributed have been also reported in DCS experimental models: in guinea pigs , dogs 3,40, miceCirculating intravascular gas bubbles trigger activation of the vascular endothelium, widely described in diseases such as DCS ,60 and GHSPs are a superfamily of proteins that regulate different physiological processes mainly related to other proteins . As a deHSP70 expression in gills, heart, posterior kidney, and ventral aorta showed a statistically significant pattern of upregulation in the GBD group. The gills were the location with the greatest magnitude difference between groups. The gills are the tissue that functionally resembles the lung in mammals . ConsideHSP90 showed a statistically significant upregulation in gills and heart. HSP90 is mainly a constitutive protein that, in certain circumstances, is induced to regulate client proteins in response to damage . HSP90 eZhang et al.,  suggesteIn the present study, no significant differences in ICAM-1 expression were found in the GBD group, in contrast to other studies ,77. ICAMTotal gas score presented a statistically significant correlation with HSP70 in gills. In the case of HSP70 in heart and ET-1 in posterior kidney, there was a tendency to correlate with the total gas score, but it was not statistically significant. These organs are highly perfused; therefore, the greater the amount of gas bubbles circulating through the vascular structures, the greater the expression of biomarkers associated with stress and endothelial dysfunction should be observed. ET-1 in blood serum correlated positively with the amount of gas bubbles observed in rats .The correlations between gene upregulation and the gas score demonstrate that the damage was produced by the gas bubbles. In the case of the remaining correlations that did not exhibit a statistical significance, it is probably related to the limitations of this study: small sample size, the semiquantitative nature of the gas score index, and small variability in total gas score. Future studies should increase the sample size but also induce different degrees of severity of gas score so correlations between gas score and other markers can be better established. Furthermore, the gas score is a semiquantitative variable and the gene expression of markers a quantitative variable, consequently the correlation study performed cannot discriminate as much as if both variables were quantitative. Still, with these limitations, we were able to detect a statistically significant correlation between total gas score and HSP70 expression in gills, and a tendency to correlate with no statistical significance between total gas score and HSP90 in gills and heart, and ET-1 in posterior kidney. Power analysis for correlations with total gas score showed that HSP70 in both gills and heart had high statistical power (>90%) while the trend to correlation with ET-1 in the posterior kidney showed acceptable statistical power (>70%) and may be promising correlations with a larger sample size.The limitation of the sample size also applies to those biomarkers that, showing a tendency to upregulation, did not present statistically significant differences, being starting points for future studies with a larger sample size. The power analyses indicated that significance may have been reached if sample size were larger. On the other hand, the effect size of the non-significant samples was very small, requiring an excessively large sample size to achieve statistical significance, suggesting that there were no differences for GBD vs control for those markers. Overall, our study suggests that fish with GBD might be a valid model to experimentally study gas embolism and DCS and its effects similar to other traditional laboratory animals  but in a species with lower capacity to feel pain following the 3Rs replacement principle (Directive 2010/63/EU of the European Parliament).In conclusion, fish with severe gas embolism showed an increase in HSPs, mainly HSP70, and a positive correlation with the gas score. Our results confirmed that HSP70 is a strong marker of gas embolism as has previously been demonstrated in other animal models, validating this model for the study of gas embolism and its effects. These results validated fish with GBD as a model for further investigation of the pathophysiological pathways of gas embolism, with the possibility of extrapolating the results to other susceptible species such as cetaceans, sea turtles or humans.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


S. aureus biofilms on a variety of 3D printed materials  as compared to standard, commercially available laryngectomy tubes.The customizability of 3D printing allows for the manufacturing of personalized medical devices such as laryngectomy tubes, but it is vital to establish the biocompatibility of printing materials to ensure that they are safe and durable. The goal of this study was to assess the presence of S. aureus growth was compared to Shiley™ laryngectomy tubes made from polyvinyl chloride. Discs of each material were inoculated with S. aureus cultures and incubated overnight. All materials were then removed from solution, washed in phosphate-buffered saline to remove planktonic bacteria, and sonicated to detach biofilms. Some solution from each disc was plated and colony-forming units were manually counted the following day. The resulting data was analyzed using a Kruskal-Wallis and Wilcoxon Rank Sum test to determine pairwise significance between the laryngectomy tube material and the 3D printed materials.C-shaped discs  were printed with five different biocompatible 3D printing materials and The Shiley™ tube grew a median of 320 colonies (IQR 140–520), one surgical guide resin grew a median of 640 colonies (IQR 356–920), the photopolymer grew a median of 340 colonies (IQR 95.5–739), the other surgical guide resin grew a median of 431 colonies (IQR 266.5–735), the thermoplastic elastomer filament grew a median of 188 colonies (IQR 113.5–335), and the elastomer grew a median of 478 colonies (IQR 271–630). Using the Wilcoxon Rank Sum test, manual quantification showed a significant difference between biofilm formation only between the Shiley™ tube and a surgical guide resin (p = 0.018).This preliminary study demonstrates that bacterial colonization was comparable among most 3D printed materials as compared to the conventionally manufactured device. Continuation of this work with increased replicates will be necessary to determine which 3D printing materials optimally resist biofilm formation. Three-dimensional 3D) printing is an innovative technology, the applications of which have the potential to significantly improve patient outcomes. 3D printing allows for the manufacturing of complex anatomical structures and is already used for surgical training, pre-surgical planning, prosthetics, and implants in a variety of medical fields , 2. ThisD printinMaterials used for the printing of implantable devices include polymers such as polyethylene, biological materials such as collagen and cellulose, ceramics, and metals such as titanium and cobalt chrome. Biodegradable vascular stents and prosthetic heart valves have been manufactured using 3D printing from polylactic acid (PLA), polycaprolactone (PCL) powders and methacrylate composite hydrogels, respectively . FurtherIn the field of otorhinolaryngology, 3D printed devices made from PCL have been used to replace airways in newborns and infants with tracheobronchomalacia , 12. 3D Silicone is often preferred for soft-tissue implants as it is less susceptible to biofilm formation than materials such as acrylic and polymethylmethacrylate (PMMA) . HoweverAll medical devices deemed “biocompatible” must comply with the ISO 10993 standards. This set of standards assesses device safety by examining several key components of material usage including: contact duration, cytotoxicity, sensitization, irritation, systemic toxicity, material-mediated pyrogenicity, genotoxicity, implantation, hemocompatibility, carcinogenicity, reproductive/developmental toxicity, and degradation . In the 3D printing laryngectomy tubes have tremendous potential, offering a cost-effective solution that can be available for patients at the point of care. Furthermore, customization of these devices may prevent future costs of complication management due to improved fit and comfort.Staphylococcus aureus (S. aureus) is a pathogen known to colonize implanted foreign bodies and artificial airways, leading to infection and Staphylococcus species account for two-thirds of infections associated with surgical implants. Such infection adds to the already heavy clinical and financial burden of device implantation [S. aureus can be difficult to treat as the resulting biofilms are often not as responsive to antibiotics [However, since these devices are used in the upper airway, it is imperative to ensure good manufacturing practices and biocompatibility of these foreign materials in the human body. The development of bacterial biofilms poses a significant problem for these devices. It has been reported that biofilms are seen on more than 90% of tracheostomy tubes within 7 days of insertion . In the antation –25. Infeibiotics . Furtheribiotics .S. aureus biofilms on a variety of 3D printed materials as compared to standard laryngectomy tubes in order to provide rationale for selection for optimal substrates for 3D printed versions.The presence of biofilms on 3D printed materials has primarily been studied in the context of development of anti-microbial polymers. However, there is a lack of knowledge about how biofilm growth compares between biocompatible 3D printed materials and standard traditionally manufactured implantable devices, especially with regards to laryngectomy tubes. The goal of this study is to assess the presence of Five biocompatible 3D printing materials including: two surgical guide resins , a photopolymer , an elastomer , and a thermoplastic elastomer filament  were 3D printed and underwent post-processing using appropriate 3D printing technologies to form C-shaped discs , designed using Tinkercad , exported as stereolithography (STL) files for printing, and printed using 3D printers specific to each material  vaporized hydrogen peroxide gas plasma sterilization (STERRAD) for 28 minutes. All materials were sterilized according to manufacturer guidelines.S. aureus cultures were created with 100 µL of bacteria in 10 mL of Tryptic Soy Broth (TSB) and were left in a 37 °C shaker for 3 hours. Using McFarland’s standard, the appropriate S. aureus dilution was determined and created in TSB. Discs of each material were placed into a 24-well plate and inoculated with 2 mL of the S. aureus cultures .S. aureus demonstrated growth on all five 3D printed disc types and the control Shiley™ tube samples. Only the 1/103 dilution concentrate ended up being used in the analysis as the 1/102 dilution did not yield enough data for analysis.Model discs were successfully printed using all 3D printing technologies and materials. Following sterilization and inoculation Fig. , S. aureThe Kruskal-Wallis test demonstrated a significant difference in colony growth between groups . The data was not normally distributed. Further, the post-hoc Wilcoxon rank sum test showed a significant difference between the Shiley™ tube and the FormLabs Surgical Guide Resin p = 0.02) Medical devices that are marketed in the United States are subject to the regulatory controls in the Federal Food, Drug, and Cosmetic Act and its implementing regulations in Title 21 of the Code of Regulations . TraditiIt is important to note, however, that the Food and Drug Administration (FDA) is closely monitoring this landscape, has proposed several scenarios of 3D printing at the point of care, and will likely provide guidance for this in the future to ensure the safe and effective use of 3D printing in the hospital setting .Escherichia coli and Pseudomonas aeruginosa in addition to S. aureus. They found biofilm growth was not only comparable on 3D printed polymers as compared to controls, but was even reduced [To our knowledge, there are limited studies evaluating biocompatibility of commonly available 3D printed materials. One study by Hall et al., focused on PLA polymers and evaluated growth of  reduced . These rS. aureus and other microbes, including fungi, should also be examined.This study was limited in several ways. The first limitation was the method of Shiley™ tube slicing used. They were cut using a handsaw; therefore, they may not be consistently the same size introducing possible variability in the surface area available for biofilm formation. Next, the number of materials tested along with the single geometry of the 3D printed part, the number of replicates, and the sample size were limited. These limitations were due to financial constraints of our laboratory as we were unable to procure additional materials and printers for testing. Furthermore, this study did not directly measure biofilm presence or volume. Future research could look to measure these variables directly via electron microscopy. Finally, this study focused solely on colonization by In the future, creating 3D printed medical devices, such as laryngectomy tubes, may save time and cost for patients. This technology also offers a solution for patients who may not otherwise have access due to cost or supply chain barriers for manufactured items. With advancements in personalized 3D modeling based on medical imaging data, patient-specific, customized medical devices may lead to personalized items (such as form-fitted laryngectomy tubes), that are readily accessible at the point of care. For any healthcare delivery system endeavoring toward this, it is imperative to implement quality systems and check points to ensure the safe and effective use of these devices.This study is a first of its kind – exploring a variety of potential materials for the production of point-of-care laryngectomy tubes. As this field grows, obviously a wide variety of materials should be tested in a robust fashion against an array of potential pathogenic microbes to arrive at optimal materials for 3D printed devices. The preliminary experiments performed herein suggest one such potential approach to identify safe materials for the creation of 3D printed laryngectomy tubes.S. aureus growth on five biocompatible 3D printed materials was quantified and compared to the growth seen on a conventionally manufactured medical device, the Shiley™ laryngectomy tube. The 3D printed materials tested had varying levels of biofilm colonization as compared to the Shiley™ laryngectomy tube. The FormLabs surgical guide resin demonstrated significantly higher colony formation. The DSM material also appeared to be more prone to colonization, though these results were not statistically significant (p > 0.05). Furthermore, neither the NextDent surgical guide resin, 3D Systems VisiJet M3-X, or 3D Systems VisiJet ENT materials demonstrated a significant difference in colonization as compared to the Shiley control. Consequently, all three of these materials show promise in the manufacturing of laryngectomy tubes at the point of care.In this study,


Mycobacterium tuberculosis (Mtb) by analysing its phylogeographic signatures jointly with the human Y-chromosome. We demonstrate the Y-chromosome lineages enriched in the traditionally hunter-gatherer groups associated with East Asia’s first layer of peopling to display deep roots, low long-term effective population size, and diversity patterns consistent with a southern entry route. These characteristics mirror those of the evolutionarily ancient Mtb lineage 1. The remaining East Asian Y-chromosome lineage is almost entirely absent from traditionally hunter-gatherer groups and displays spatial and temporal characteristics which are incompatible with a southern entry route, and which link it to the development of agriculture in modern-day China. These characteristics mirror those of the evolutionarily modern Mtb lineage 2. This model paves the way for novel host-pathogen coevolutionary research hypotheses in East Asia.The Two Layer hypothesis is fast becoming the favoured narrative describing East Asian population history. Under this model, hunter-gatherer groups who initially peopled East Asia via a route south of the Himalayas were assimilated by agriculturalist migrants who arrived via a northern route across Eurasia. A lack of ancient samples from tropical East Asia limits the resolution of this model. We consider insight afforded by patterns of variation within the human pathogen  Mycobacterium tuberculosis lineages in East Asia mirror those of human Y-chromosome haplogroups, supporting the Two Layer hypothesis, and a Paleolithic emergence scenario for the Mycobacterium tuberculosis complex.The phylogeographic patterns of  This newly emerged consensus holds that East Asia was peopled in two main population movements or layers. The first layer consisted of hunter-gatherer groups with darkly pigmented skin, who arrived in East Asia via a dispersal route south of the Himalaya mountain range. These populations were later displaced and partially assimilated by agriculturalist groups with cold adapted physical features, who were likely to have reached East Asia via a route north of the Himalayas2.With contributions from the fields of anthropometry and the study of ancient and contemporary DNA, a new paradigm has emerged in our understanding of East Asian population history10. Similarly, the Dual Structure model describes the displacement and integration of hunter-gatherer Jomon groups by agriculturalist migrants across the Japanese archipelago. Under this theory, which draws from skeletal, odontal and craniometric data, Jomon-related ancestry was argued to persist mainly in the Indigenous Ainu and Ryukyuan groups from the northern and southern extremes of the island chain20. Genetic studies garnered support for both the Two Layer and Dual Structure models, by demonstrating the strong degree of shared genetic drift between ancient Jomon and modern Ainu genomes21, and between ancient Jomon and Hoabinhian genomes3.Interestingly, the Two Layer model, and the closely related Dual Structure model of Japanese population history were originally rooted in the field of physical anthropology and received support from genetic studies only recently. The Two Layer model was initially proposed to explain the replacement of Hoabinhian hunter-gatherers exhibiting Australo-Melanesian features with agriculturalist groups exhibiting Northeast Asian features in the Southeast Asian archaeological record1. Under these models, the Onge are argued to be amongst a number of modern-day human populations who represent largely unadmixed descendants of the first layer of peopling, including Papuans, the Ainu of Japan, and hunter-gatherers from the Philippines and Malaysia4.Current studies now describe East Asian populations, at a basal level, to be modelled as mixtures of first and second layer ancestry, with the Indigenous Onge and the ancient Tianyuan genome from Neolithic northern China acting as surrogates for each respective layer24.While analyses of ancient DNA have afforded great insight into the Two Layer model, they are limited by the low availability of this form of data from the region. An underutilised means of deciphering aspects of human demography is by analysing patterns of genetic variation amongst human symbiotic species, including commensals and pathogensMtb. We complement these inferences by investigating patterns of human genetic variation, inferred from Y-chromosome sequencing and genotype data. We pair these two marker systems, as they both possess ample phylogenetic signal, and are both inherited clonally, thus permitting the use of an identical suite of phylogenetic and phylogeographic tools in their analysis. The joint analysis of variation in these marker systems may reveal parallel phylodynamic and geographic signatures, which may be relevant to our understanding of the Two Layer model, and may furnish us with additional insights. We are also motivated to complete this investigation, as existing models describing the distribution of both Y-chromosome and Mtb genetic variation are largely incompatible with the Two Layer hypothesis.In this study, we consider the insight afforded into the Two Layer model by analysing genetic variation within the genomes of the human obligate pathogen 26, and describing male mediated demographic processes28, has not been robustly reconciled with the Two Layer model. Current models of East Asian Y-chromosome variation generally argue a single southern route origin of the four haplogroups which make up 90–95% of male lineages , followed by subsequent northwards expansion33. These theories therefore don’t account for the proposed northern dispersal route associated with the second layer of peopling, or the implied genetic affinities shared by the present-day representatives of the first layer.Y-Chromosome data, while having played a seminal role in illuminating our African originsMtb pathogen has also been well characterised in an East Asian context but has not been assessed in light of the Two Layer model. The East Asian Mtb landscape is dominated by isolates from the ‘evolutionarily ancient’ lineage 1, found at highest frequency in southern regions, and the ‘evolutionarily modern’ lineage 2, which display enhanced virulence and transmissibility36, and which predominates in northerly regions37. Under models proposing a Paleolithic39, as opposed to an argued Neolithic41 origin of Mtb, lineage 2 arrived in East Asia via a southern route, before expanding northwards, and radiating southwards again with the movement of the Han people39. This model doesn’t reconcile all aspects of the Two Layer hypothesis, including the proposed northern entry route of the second layer, nor the demographic processes and migrations which gave rise to the distribution of lineage 1.Similarly, genetic variation in the Mtb and Y-chromosome variation to propose a coevolutionary scenario compatible with the Two Layer model. In addition to illuminating a key chapter of human history, it will provide background context relevant to our understanding of the long-term interaction of humans and one of the deadliest diseases of all time.Here we conduct a joint analysis of patterns of 42, and to cover a wide geographical extent We see a strong contrast between the inferred historic populations sizes of the NO clade, and the three lineages which predominate in traditionally hunter-gatherer groups: C, D and K2b1 Fig. , with co56.The NO clade, which diversified more recently, experiences an initial population size increase around 15Kya, and begins a phase of exponential growth around 9Kya, expanding by a factor of almost 3 within the next 3000 years , and the frequency of lineage 1 to be positively correlated with the summed frequencies of haplogroups C, D and K2b1  to a certain node, based off archaeological or biogeographic data, or signatures of co-divergence71. We chose this method in favour of the ‘tip calibration’ approach used by prior studies, which infer node ages and a substitution rate by incorporating heterochronous sequences into their phylogeny73. In addition to requiring adequate temporal structure75, tip dating is liable to the time dependent rate phenomenon77 (TDRP), which systematically underestimates the ages of deep nodes of a tree (see Discussion). Node calibration, while not subject to the TDRP, does, however, rely on a robust biogeographic or genetic model to justify the codivergence scenario proposed78 (see Discussion).As there is ongoing debate surrounding our ability to accurately estimate substitution rates in 38, who calibrate nodes of the Mtb phylogeny to match key divergence events in the human mitochondrial tree. As we infer Mtb lineage 1 to be the lineage carried by the first layer dispersal into East Asia, we assigned a prior distribution over its root age, such that it matches the average age of first layer Y-chromosome lineages C, D and K2b1 . Our inferred timepoint for the coalescence age of lineage 1 (56.5Kya) is therefore intermediate between the co-divergence scenarios proposed by Comas et al. (2013)38 (ranging from 6 to 100Kya), yet older than estimates derived from tip dating such as Menardo et al. (2021)79 (0.85Kya) and O’Neill et al. (2019)37 338, who Mtb lineage 2  and Y-chromosome haplogroup NO . We also observed Mtb Lineage 1 to display similar qualitative characteristics to putative first layer Y-chromosome haplogroups C, D and K2b1. These lineages displayed early ‘lineage proliferation’ phases, in which the number of lineages initially expands, followed by a period of little subsequent increase .By comparing the tree structures quantitatively using the ‘lineages through time’ metric, we also observe correspondence between the Y-chromosome and −9s/s/y) is intermediate between the various estimates of Comas et al. (2013)38 (9.42 × 10−10 to 1.66 × 10−8), but slower than estimates derived from tip dating using contemporary samples80 (around 1×10−7). As detailed subsequently (see Discussion), this magnitude of substitution rate differences is typical of other pathogens when applying these two techniques over comparable timescales82. We also discuss the plausibility of the inferred substitution rate given available estimates from Mtb during latency84, and when considering patterns of rate heterogeneity within similar bacteria86. Although recent studies have implemented methods for modelling variation in substitution rates over different timescales76, the lack of additional high-confidence internal calibration points within the Mtb tree precluded us from applying these approaches with certainty.In line with the divergence ages we estimate, our inferred substitution rate  representing the single deepest split within the remaining L1 sublineages: L1.1.1, L1.1.2, L1.1.3 and L1.2.287. We inferred a phylogeny, and labelled L1.2.1 sublineages according to the nomenclature of three available schemes, but here refer to them as Clades 1 to 4  and Ancestral Southern Indian (ASI) ancestry, the latter component of which is linked to Indigenous first peoples of East Asia such as the Andamanese93. Populations enriched for ASI ancestry, which are predominantly located in southern India, possess high frequencies of haplogroup H44, which we note to possess the phylogenetic characteristics of deep divergence times and limited population growth46. Considering south Indian populations are also enriched for Mtb lineage 194, we tentatively propose Y-chromosome haplogroup H to be associated with the initial hunter-gatherer presence in South Asia, and to be associated with this Mtb lineage.While we did not undertake this analysis, we do observe congruent features in the Mtb lineages from our model due to their low frequencies or lack of available data. One notable omission is Mtb lineage 4, which is present in low to moderate frequencies in some East Asian populations96. We omitted this lineage, as our focus was on Mtb and Y-chromosome lineages originating in East Asia, hence why Y-chromosome haplogroups Q, R, F* and H were not analysed extensively. As prior phylogeographic studies have shown the majority of L4 sublineages to display European origin points40, and a history of multiple introductions into Southeast Asia35, we chose to exclude this lineage from consideration. Interestingly, however, a small number of L4 sublineages are geographically restricted to East Asia, with highest frequencies in Chinese populations (L4.4 and 4.597). More detailed analysis may reveal these to be minor lineages associated with the second layer of peopling, or later demographic processes outside the scope of this investigation. For context, lineage 4 was only observed at a frequency >20% in the single Chinese cohort included in this analysis95. Spatial frequency interpolation also revealed low L4 frequencies in East Asia  isolates analysed, incidentally all belonging to M.pinnipedii, were <1Ky old100. The phenomenon of ‘time dependency’ in substitution rate estimates is well documented in viruses and bacteria, with studies documenting systematic over-estimation of mutation rates when calibrating based on more recent samples101.Firstly, none of the recent studies inferring substitution rates on −9) relative to tip dating80 (~1 × 10−7), are roughly within the ranges established for other pathogens82. Hepatitis B virus substitution rate estimates vary around two orders of magnitude when comparing human co-divergence calibration with tip dating81, and foamy virus substitution rates vary up to four when considering primate species co-divergence82. Available data for bacteria, although more limited, has suggested an order of magnitude difference in substitution rates inferred from contemporary samples vs samples approximately 1Ky old67. A recent review collating estimated mutation and substitution rates in Mtb specifically has also concluded the presence of a time-dependence effect102, although high quality DNA from more ancient Mtb genomes will be required to properly gauge its magnitude80.We note the differences in substitution rates inferred from our analysis 85 find that branches of the Y. pestis phylogeny, a bacterial species with a similar genome size and general mutation rate to Mtb, can vary in substitution rates by 40-fold, from ~1.3 × 10−7 to 3.1 × 10−9. They attribute this variation to the bacteria’s ability to enter a dormant phase between epidemic periods. Similar substitution rates and levels of rate heterogeneity are also reported by Spyrou et al. (2019)86 for Y. pestis. It is plausible that the combination of latency and the relatively stronger effect of purifying selection in Mtb (dN/dS = 0.6104); relative to Y. pestis (dN/dS = 0.985); could explain the slow long-term substitution rate we infer.Available data from other bacteria supports dormancy-related levels of rate variation which may be capable of explaining the substitution rate we infer for Mtb infection during latency supports a slowdown effect84, and mutation rates broadly consistent with Paleolithic emergence theories during long-term latency. When analysing samples with an apparent latency period of around 20 years, Colangeli et al. (2014)83, for instance, propose a mutation rate of 7.01 × 10−9. It should be noted, however, that these studies are sparse, have low sample sizes, and have produced conflicting results105. Collectively though, these data provide reasonable justification to credit the likelihood of a broad range of possible substitution rates for Mtb.In addition, data describing the mutation rate in human Mtb emergence scenarios comes from the fields of paleomicrobiology and ancient DNA108. These studies, which amplify Mtb sequence motifs, have produced evidence consistent with the presence of the pathogen in samples from Neolithic Israel110, Syria112, Germany113, Hungary116, Egypt117 and Britain118, dating up to an estimated 10.8Kya. Multiple studies have also detected the TbD1 deletion118, implying that evolutionarily modern lineages were present at these timepoints. Further scrutiny will be required to verify these findings, and claims addressing the impact of mycobacterial contaminants, which have been previously brought into question120.A final form of data which should be taken into account when considering Mtb emergence theories, we present in Supplementary Table Mtb node ages appear to correspond to key demographic events in human history.To facilitate a comparison of possible Mtb phylogeny so that the age of putative first layer lineage (L1) matches that of first layer Y-chromosome lineages, we also see a strong similarity between the inferred ages of putative second layer lineages and haplogroups . This date is also consistent with the date proposed by Matsumura et al. (2019)2 for the arrival of this second layer dispersal on the basis of archaeological data (45Kya).For instance, when calibrating the Mtb lineages 1 and 2 coalesce 112.4Kya (HPD: 94.1–131.9Kya), and prior phylogenetic analyses show the split of M.africanum lineages (L5 and L6) to be roughly 10% older than this 38. Aside from the rare West African A00 haplogroup discovered after extensive consumer genetic testing (divergence time: 250Kya), the divergence times of all major Y-chromosome haplogroups fall between roughly 60 and 190Kya121. The localisation of the most deeply rooted Mtb lineages to the African continent, with phylogenetic depths comparable with human uniparental lineages supports an out-of-Africa co-dispersal scenario for the pathogen22.Our model also predicts a coalescence point for the entire MTBC that is consistent with the deepest splits of human Y-chromosome lineages within the African continent. Mtb lineages, as well as their clinical characteristics and life history strategies. The ‘evolutionarily modern’ lineages 2, 3 and 4 show expansion centres corresponding to major centres of agriculture in Asia and Europe, and levels of transmissibility suggesting adaptation to high population sizes123. By contrast, the less virulent and transmissible lineage 1 has been hypothesised to be adapted to hunter-gatherer human populations66. Our model therefore provides an explicit demographic explanation for the distribution and dynamics of lineage 1, by linking it to the original hunter-gatherer populations of East Asia.Paleolithic emergence scenarios also receive support from the geospatial dynamics of Mtb node ages and evolutionary dynamics dated using tip calibration are incompatible with Paleolithic emergence theories. As others have hypothesised80, substitution rates inferred using tip calibration may be appropriate for dating relatively shallow nodes within the tree, but not for the deep nodes we focus on in this study. The combination of ancient DNA, and research into the demographic factors underpinning the spread of Mtb lineages will clarify this matter.Available tip calibration scenarios, on the other hand, don’t provide node ages as immediately parsimonious with known human demographic events, or at least, no single model linking these dates and events has been proposed to date. This, however, does not necessarily mean that 124 and Greenland125, as well as the initial peopling of Polynesia126 and Madagascar127. We caution that Y-chromosome lineages from the first layer of peopling may have contributed in disproportionately low frequencies to the present-day genetic constitution of East Asian populations. This factor may explain the finding that putative first layer Mtb lineages are comparatively more numerous than first layer Y-chromosome lineages across many contemporary East Asian populations and show signs of more pronounced lineage expansion .42. The studies from which the frequencies of Y-chromosome haplogroups in traditionally hunter-gatherer populations were summarised are discussed in Supplementary Note Y-chromosome haplogroup frequencies were collated from previous studies, described in greater detail in Supplementary Note 128 and visualised using ggmap129. We provide an illustration of the concordance between observed and interpolated haplogroup frequencies in Supplementary Note Spatial interpolation of haplogroup frequencies was carried out using the kriging procedure. This process includes fitting a variogram describing the relationship between geographic distance and haplogroup frequency differences for the chosen haplogroup, before interpolating the frequency of this haplogroup across a spatial surface. These steps were completed using various functions of the gstat package in R137. Six short tandem repeats which were genotyped across all datasets were used for diversity calculations . Minor discrepancies in the way the DYS389II repeat length was recorded between studies were corrected for, and haplotype diversity was measured using the approach of Nei (1987)138 using custom Unix scripts.Y-chromosome STR profiles were obtained from previous studies46 were restricted to biallelic SNPs and used to produce a fasta alignment of all variable sites. The regions of the Y-chromosome analysed were further restricted to the 10.4 Mb shown to be amenable to phylogenetic research71. BEAST139 was used to construct a Y-chromosome phylogeny describing the relationship between all lineages in this dataset falling into clades C, D, K2b1 and NO, which were identified from data presented in the supplementary material of Bergstrom et al. (2020)46. The BEAST parameters included a GTR model of nucleotide substitution, an uncorrelated lognormal relaxed clock to model rate heterogeneity between branches, a Coalescent Bayesian skyline tree prior, and a Y-chromosome specific mutation rate derived from the analysis of Fu et al. (2014)140. This rate was corrected to account for the fact that the alignment was restricted to variable sites only. BEAST was run in five independent replicates of 10,000,000 iterations, sampling every thousandth, before combining with LogCombiner. A Maximum Clade Credibility tree was produced using TreeAnnotator. Key splits in the phylogeny received high posterior support and were in fine agreement with those of Bergstrom et al. (2020)46 on the basis of both branching pattern and node age. Bayesian skyline estimates of effective population size were obtained after running BEAST on samples from each haplogroup individually for 30,000,000 iterations.Genotypes called across the Y-chromosome for samples from the HGDPMtb lineage frequencies was carried out using an identical approach to that described above for Y-chromosome haplogroups. We used the dataset of Wiens et al. (2018), which describes global lineage frequencies, to perform kriging and calculated spoligotype diversity using data from SITVIT263. We calculated diversity values for spoligotype families representative of lineages 1  and 2 (‘Beijing’ clades) at each sampling location using the same diversity index as described for Y-chromosome haplogroups. We excluded isolates which were sampled from immigrants, and populations represented by a low number of isolates (n = 40) for each lineage. As per the rationale of prior studies79, we have not shown diversity values for countries in Western Europe or Australia, however frequency values for these countries are still shown. Plots showing the concordance of observed and interpolated Mtb lineage frequencies for lineages 1, 2, 3 and 4 are shown in Supplementary Figs. Kriging of s et al. 18, whichMtb WGS data from prior studies which conducted random sampling within East Asian populations, and which weren’t enriched for drug resistant isolates143. To obtain an unbiased comparison of the dynamics of Mtb and Y-chromosome evolution, we down-sampled isolates from each of these studies so that the total number of Mtb lineage 1 and 2 isolates matched the number of Y-chromosome sequences from which the phylogeny was inferred. Fastq files for all isolates were downloaded from the Sequence Read Archive, and were quality trimmed using cutadapt144. Reads were then aligned to the H37Rv reference genome using BWA145, filtered for duplicates using Picard146, and subjected to variant calling using Pilon147. Poor quality and ambiguous variant calls were then set to missing, and a lineage was assigned to each sample using ‘fast-lineage-caller’148 and the nomenclature scheme of Coll et al. (2014)149. All per-sample vcf files were then merged, and both per-site and per-sample missingness filters were applied using bcftools150. Finally, variant calls were restricted to those in uniquely mappable regions of the Mtb genome before phylogenetic inference, using the coordinates of Brynildsrud et al. (2018)40.We collated 71 to scale our Mtb tree using signatures of human-Mtb co-divergence. We initially inferred an Mtb phylogeny from a sequence alignment incorporating all L1 and L2 isolates, assigning a prior distribution over the age of the L1 root. For this prior, we used a lognormal distribution with mean value of 56.5Ky  ± 5Ky. Our phylogenetic parameters were otherwise the same as used for the Y-chromosome analysis, including the use of an uncorrelated lognormal relaxed molecular clock. We again ran BEAST in five independent replicates, before combining log files using LogCombiner. We obtained a substitution rate from this log file  after correcting for the fact that only polymorphic sites were included in the alignment. The resulting Maximum Clade Credibility tree is presented in Fig. As described in the Main Text, we used the phylogenetic technique of ‘node calibration’79 and Netikul et al. (2022)87 were collated. As detailed sublineage data was available for the isolates from Netikul et al. (2022)87, we were able to preferentially down-sample isolates from Clade 1 88. The protocol for downloading and calling variants on these isolates was identical to that used above for the Mtb ‘lineage 1 and 2’ dataset, with the only difference being an additional adapter inference and filtering step151, and appropriate pipeline adjustments for samples with single end reads. Representative isolates from lineages 1.1.1.1, 1.1.1, 1.1.2, 1.1.3, 1.2.2 and 5 were also downloaded and processed in the same manner as other samples. We used data presented by Netikul et al. (2022)87 to identify isolates representing the deepest split in each L1 sublineage. We inferred a phylogeny using RAxML152 using a GTR substitution model, an L5 outgroup, and annotated lineages according to various nomenclature schemes153.To infer a phylogeny representative of known lineage 1.2.1 diversity, isolates used in the investigations of Menardo et al. (2021)Mtb phylogenetic analyses [‘lineage 1 and 2 analysis’  were used. Samples were only filtered on the basis of sequencing data quality. For the is’ Fig.  and ‘linis’ Fig. ] that inp value threshold of 0.05 was used for the statistical tests reported in Supplementary Notes Multiple independent replicates of each BEAST phylogenetic analysis were run to check for consistency, and skyline trajectories were replicated after running BEAST with different parameter values (see Supplementary Note Further information on research design is available in the Peer Review FileSupplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Reporting Summary


The possible ecological risk caused by PAH atmospheric deposition based on risk quotient was also estimated. A bulk  deposition and PM10 particle fraction  were collected from June 2020 to May 2021 at an urban residential location in the northern part of Zagreb, Croatia. The monthly average of total equivalent BaPeq mass concentrations of PM10 varied from 0.057 ng m−3 in July to 3.656 ng m−3 in December; the annul ∑BaPeq average was 1.348 ng m−3. In bulk deposition, ∑BaPeq mass concentrations varied from 1.94 to 57.60 ng L−1. In both investigated media, BaP had the highest contribution in carcinogenic activity. For PM10 media, dermal absorption implied the greatest potential cancer risk, followed by ingestion and inhalation. For bulk media, a moderate ecological risk for BaA, BbF and BaP was observed according to the risk quotient approach.This paper present seasonal variation in the equivalent concentration (BaP In the atmosphere, particulate matter (PM) can originate from natural sources , but they also may be a consequence of human activity  . AirbornAtmospheric deposition is one of the main removal mechanisms of toxic compounds from the atmosphere to aquatic and terrestrial systems ,17,18. A1 particle fraction  [Previous studies in Croatia were based mostly on the determination of PAH levels in particulate matter ,35,36,37 < 1 µm) . Conside < 1 µm) ,41,42,43 < 1 µm) . To the eq) in the PM10 fraction of particulate matter  and bulk deposition. The PM10 fraction was chosen because Directive 2004/107/EC of the European Union, as well as several national and air quality standards, are principally focused exclusively on PAHs bound to this fraction, so the data obtained in this study will be easy comparable with other similar studies and already published data [10 exposure. Furthermore, this is the first investigation of possible ecological risk caused by PAHs in bulk deposition based on risk quotient calculations.In this study, the main objectives were to investigate the temporal variation in PAHs’ carcinogenic activity by calculating the carcinogenic equivalent concentration  were collected from June 2020 to May 2021 at an urban residential site in the northern part of Zagreb, Croatia’s capital. The geographical coordinate of the measuring site was 45°50′9″ N, 15°59′4″ E. This area is characterized by low resident density and modest traffic. A previous study in this area showed that households mostly used gas for residential heating, but oil and wood were also in use for heating or cooking [In this study, samples of PM cooking ,37.10 particle fraction on quartz filters , low-volume sequential automatic samplers  were used according to the EN 12, 341 standard (2.3 m3 h−1). Over a one-year period, 24-hour samples were collected and wrapped in aluminum foil and kept frozen until analysis [For sampling of the PManalysis ,47. Durianalysis . At the 10 particles was already described in previous papers [10 particle fraction were determined by an Agilent Infinity 1260 high performance liquid chromatograph coupled with a fluorescence detector, with acetonitrile as the mobile phase and a flow rate of 1 mL min−1. The following PAHs were determined: fluoranthene (Flu), pyrene (Pyr), benzo(a)anthracene (BaA), chrysene (Chry), benzo(b)fluoranthene (BbF), benzo(k)fluoranthene (BkF), benzo(a)pyrene (BaP), dibenzoanthracene (DahA), benzo(ghi)perylene (BghiP) and indenopyrene (IP). Five-point calibration curves were used ranging from 0.005 ng μL−1 to 0.08 ng μL−1 for Pyr, BaA, Chry, BkF, BaP and IP and from 0.01 ng μL−1 to 0.16 ng μL−1 for Flu, BbF, DahA and BghiP. The accuracy of the method was confirmed by analysis of urban dust 1649 b . The method accuracy ranged from 88% for Flu to 109% for BkF. The limit of detection (LOD) was from 0.001 ng m−3 for BaA to 0.03 ng m−3 for BjF.The PAH extraction procedure from PMs papers ,37,47. B10 particle fraction were funded by the City of Zagreb, City Office for Economy, Energetics and Environment Protection, and are available to public at the Zagreb air quality monitoring network website (http://www1.zagreb.hr/kvzraka/index.htm accessed on 28 December 2022).The measurements of PAHs in the PM10 particle fraction were analyzed. Analysis was carried out by a gas chromatograph  coupled with a tandem mass spectrometer . The conditions of gas chromatograph and mass spectrometer were described in a previous paper [−1.The detailed procedure for extraction and analysis of PAHs in bulk deposition samples was described in an earlier paper ,18. In bus paper ,18. Quanp < 0.05). Seasonal variances between warm and cold period for each PAH in the PM10 particle fraction and in bulk deposition were tested by Kruskal–Wallis analysis of variance test. Cancer risk and exposure dose for PAHs in PM10 particle was estimated using a model developed by the US EPA [The statistical analysis was processed by Microsoft Excel and Statistica 13 . Statistical significance was set at 5% , dermal absorption (Dder) and ingestion (Ding). Total cancer risk (Risktot) was calculated by summing the risk from each exposure pathway . The health risk assessment performed in the present study was based on the guidelines defined by the United States Environmental Protection Agency (US EPA). The biometric and exposure parameters of the residence were assumed to be similar to those of the U. S. residents, so the values of parameters used in the calculation of risk assessment in this study were taken from the standard default exposure factors of the US EPA [The cancer risk assessment was estimated as the possibility of developing all types of cancer from lifetime exposure to carcinogen compounds. The exposure dose (D) was estimated using a model developed by the US EPA . As route US EPA  and weree US EPA ,53,54,55−1) estimated on the basis of toxic equivalency factors (TEFs) from the literature. Many TEF schemes are established by different authors [−6 kg mg−1) [−1); EF is the exposure frequency (day year−1); ED is the exposure duration (year), BW body weight (kg); AT is average time (day); SA is exposed skin area (cm2); AF is skin adherence factor (mg cm−2); ABS is absorption factor (unitless); IRα is inhalation rate (m3 h−1); ET is exposure time (h day−1); and PEF is the particle emission factor (m3 kg−1).Risks were estimated for two different types of residents, children under the age of 6 and adults from 20 to 40 based on EPA guidance on selecting age groups for monitoring and assessing exposures to environmental contaminants . For par authors ,58,59. T authors ,38. For kg mg−1) ; IRs is −1) for oral, dermal or inhalation, respectively. The sum of the pathways is the total cancer risk (Risktot). The parameters used for the calculation of doses are shown in Cancer risk assessments were calculated by multiplying the dose received with the cancer slope factor . Rainwater is used only in some parts of the country in agriculture for irrigation; therefore, the use of the US EPA methodology for assessing human risk due to water consumption on PAHs in bulk deposition samples would not be appropriate.In environmental conditions, water can be contaminated with more or less harmful organic compounds. Human exposure to PAHs from water can be estimated using the methodology of the US EPA  for resiPAHs represented the mass concentration of certain PAHs in the bulk deposition expressed as the ∑BaPeq, and CQV represented the quality values for each PAH. The negligible concentrations (NCs) and the maximum permissible concentrations (MPCs) of PAHs in water recommended by Kalf et al. (1997) [NCs and RQMPCs as follows:QV(NCs) represented the quality values of the NCs of PAHs in the water, and CQV(MPCs) represented the quality values of the MPCs of PAHs in the water. The RQ∑PAHs(NCs) and were defined as follows [The occurrence of toxic PAHs in the aquatic environment can cause potential risks for flora and fauna. In this study, the ecological risk assessment was employed to estimate the risk of ten PAHs to surrounding organisms as well as the ecosystem. Risk quotient (RQ) was used for evaluating the ecosystem risk by toxic PAHs in the bulk deposition, which was calculated as follows:. (1997)  and Cao . (1997)  were use follows :(7)RQ∑ Peq). The carcinogenic activity of PAHs, expressed as the monthly average equivalent ∑BaPeq mass concentrations of PAHs in the PM10 particle fraction and bulk deposition during the measurement period are shown in eq mass concentrations of individual toxic PAHs in the PM10 particle fraction and bulk deposition are shown in To quantify the PAH carcinogenic activity of particulate matter and bulk deposition, the TEFs proposed by Nisbet et LaGoy (1992)  were useeq mass concentrations of PM10 varied from 0.057 ng m−3 during July to 3.656 ng m−3 during December, and the annual ∑BaPeq average was 1.348 ng m−3. Concentrations of ∑BaPeq were higher from October to February, while during March to September concentrations decreased, and the lowest values were observed during summer months  of total equivalent ∑BaPeq mass concentrations in the PM10 particle fraction between cold months  and moderately warm  and warm months . Data analysis by seasons showed no differences between autumn and winter or between spring and summer, but differences were found between cold (autumn and winter) and warm periods (spring and summer). During the cold period, mass concentrations of PAHs were higher than in the warm period because of emissions from households; in the study area, residential heating relied mostly on gas, oil or wood, so seasonal differences were expected. Various meteorological parameters such as temperature, precipitation and wind also take part in levels of PAHs in the air. Previous studies showed that air temperature and humidity negatively correlated with PAHs in particle matter while pressure and PAH concentrations positively correlated. However, in bulk deposition air, temperature, humidity and pressure were not correlated with depositions of PAHs while a positive correlation was found with precipitation [The monthly average of total equivalent BaPr months . The mon996/1997  and slig996/1997  than thepitation ,68,69,70eq. We found only one study that used the TEF approach to assess the risk from PAHs in dry deposition samples [eq mass concentrations of bulk deposition varied from 1.94 ng L−1 during July to 57.60 ng L−1 during November, and the average ∑BaPeq during the whole measurement period was 22.34 ng L−1. The temporal variations in ∑BaPeq in bulk deposition did not follow a regular seasonal cycle as observed in the study by Feng et al. (2017), Garban et al. (2002) and Moon et al. (2006) [eq in bulk deposition samples were higher during November, February, March and April. In the summer months as well as in October, the total equivalent BaPeq mass concentrations in deposition samples were very low. Due to the small number of samples, data for bulk depositions were tested statistically only between cold (October–March) and warm periods (April–September), and differences were found only for Flu (p < 0.05). Levels of Flu were much higher during winter probably due to increased emissions from household heating. The average BaPeq of each toxic PAH taken individually varied from 0.06 ng L−1 (Pyr) to 11.45 ng L−1 (BaP). The monthly equivalent BaPeq mass concentrations of individual PAHs in the bulk deposition are given in eq mass concentrations of PAHs in bulk deposition samples during the measurement period, as shown in To the best of our knowledge, this paper is the first to present an assessment of the carcinogenic activity of PAHs in a bulk deposition sample using the TEF value, expressed as BaP samples . Total eg et al. 17, Garba. (2006) ,72 whereeq levels for specific carcinogenic PAHs, percent contributions of individual PAHs in carcinogenic activity were also calculated and shown in 10, the contribution of BaP, the most studied PAH often used as the reference compound, was 63% in warm periods and 66% in cold periods. During both the cold and warm periods, BaP was the highest carcinogenic contributor in PM10 followed by DahA, BbF and IP. The lowest contribution, less than 1%, came from Flu and Pyr. A previous study at same location but over a shorter sampling period (one month per each season 2014) for the PM10 particle fraction showed a slightly lower contribution of BaP in carcinogenic activity for the overall measured period (54%) [Based on the calculated BaPod (54%) . The conod (54%)  ranged fod (54%)  and Norrod (54%) , confirm10 and amounted to 51% in both periods. In bulk deposition samples, the contribution was different during warm and cold periods. In the cold period, BaP had the highest contribution followed by BbF with 16%, BaA and IP with 9% and BkF and DahA with 6%. In the warm period, BaP was also the highest contributor followed by DahA with 19%, BbF with 10% and IP with 7%. The lowest contribution, less than 1%, came from Flu and Pyr. As this paper presented the first results of the contribution of individual PAHs to carcinogenic activity for a bulk deposition, we could not compare our results with similar studies due to the fact that by now there was no other study assessing the carcinogenic potency of PAHs in the bulk deposition samples expressed as Bapeq. A study by He et al. (2017) evaluated the carcinogenic potency of PAHs in the particle dry deposition samples, and results showed that the BaPeq∑15-PAHs of dry deposition was highest in the winter where the highest contribution came from BaP and DahA [In bulk deposition samples, BaP contribution was lower than in PM10 and bulk deposition samples with no significant differences between cold and warm periods, so it can be regarded as a good representative for evaluating the carcinogenicity of the PAH mixture. BaP showed a higher contribution to the total carcinogenic potential in the PM10 particle fraction than in the bulk deposition. After the highest percentage contribution of BaP, the next dominant contributor in the PM10 was DahA (10%) regardless of whether the period was cold or warm, while in the bulk deposition dominant contributor was DahA (19%) in the warm period and BbF (16%) in the cold period. This deviation in the contribution of individual PAHs in the mixture between PM10 and bulk deposition could be a consequence of PAHs variability due to meteorological conditions, especially the amount of precipitation  fractions could lead to some overestimations of the risk.PAHs in the particulate matter were dominantly present in smaller fractions ,75,76. Aexcluded ,78. Even10 was assessed considering inhalation, dermal absorption and ingestion for two different types of residents, for children under the age of 6 and for adults from 20 to 40 at a two-level concentration. The first level was calculated with median concentrations (moderate scenario) of carcinogenic PAHs (∑BaPeq), while the second level was based on the maximum concentration (worst scenario). The doses received by these three pathways for PAHs in the PM10 particle fraction are shown in −1 day−1 for children and 55.925 ng kg−1 day−1 for adults. The lowest dose received was through inhalation: 0.003 ng kg−1 day−1 and 0.011 ng kg−1 day−1 for children and adults, respectively. During the warm period of the year, the dose received was ten times lower than in the cold period for both groups, children and adults. Additionally, in the warm period, the doses received for children were higher than for adults. The lowest dose was for inhalation and the highest was for ingestion. In the worst scenario, the dose received during the cold period was twice higher than in the warm period. The dermal absorption dose was 79.405 ng kg−1 day−1 and 68.801 ng kg−1 day−1 for children and adults, respectively. In the warm period, the dermal absorption dose was lower and was 34.949 ng kg−1 day−1 for children and 30.282 ng kg−1 day−1 for adults.A human risk assessment using PAH concentration data in PMtot) was the sum of the three pathways. The total cancer risks (Risktot) for exposure routes of inhalation, ingestion and dermal absorption from PM10 are given in −6 or less are considered insignificant to human health; values between 10−6 and 10−4 point to probable carcinogenic effects of PAHs to humans, while levels higher than 10−4 imply a high cancer risk to humans [10 exposure during the warm and cold periods, the results of the moderate scenario showed that the lowest cancer risk was obtained for the inhalation pathway, and it was several magnitudes lower than the accepted level (10−6), for both children and adults. Risks via ingestion and dermal absorption were higher and exceeded levels of 10−4 during the cold period, while during the warm period levels were slightly lower but between 10−6 and 10−4, which indicated a probable carcinogenic effect to human. The cancer risk levels for the inhalation pathway obtained in this study were several magnitudes higher than the results found in Franco et al. (2017) (risk 10−13) [−6 and for adults was 2.61 × 10−9) [−7 and for adults 1.37 × 10−6) [Cancer risk is considered as the possibility of developing cancer over a lifetime due to exposure to a probable carcinogen. Cancer risks were calculated multiplying doses with their corresponding carcinogenic slope factor (CSF). Total cancer risk  , who obt × 10−9) , but in  × 10−6) .Atmospheric deposition is one of the main mechanisms of transport of PAHs to all ecosystems, including aquatic ones. The occurrence of PAHs in aquatic environments can cause risks to the aquatic ecosystem. Furthermore, Wright et al. (2018) reported that the deposition of PAHs causes significant damage to plant organisms and is carcinogenic and mutagenic to humans and animals . Mainly,NCs ≥ 1 and RQ(MPCs) < 1 indicate that the contamination of individual PAHs presents a moderate risk, while RQ(MPCs) ≥ 1 suggests a high ecological risk, ((NCs) and RQ(MPCs) were calculated for individual toxic PAHs and ∑PAHs in bulk deposition samples collected in Zagreb, Croatia, in order to avoid possible misinterpretations due to extreme PAH values. However, no significant differences were found between mean and median values, so only the median values of RQ(NCs) and RQ(MPCs) are shown in Potential ecological risk was assesses through a classification of individual PAHs as well as ∑PAHs suggested by Cao et al. (2010) . Furtheral risk,  and some(NCs) of each PAHs were higher than the recommended NC values for PAHs in water, except for Flu, Pyr and Chry. RQ(MPCs) of individual PAHs were all less than 1.0. As shown in (NCs) were all more than 1, and RQ(MPCs) values were all less than 1 indicating moderate risk to which the flora and fauna was exposed by being in contact with water containing concentrations of the PAHs collected in the bulk deposition samples. There were no values for RQ∑PAHs(MPCs) due to the fact that RQ(MPCs) > 1 were summed to calculate risk quotients for the sum of toxic PAHs. Overall, there is a moderate ecological risk from some PAHs in bulk deposition which stresses the need for further investigation at other locations as well as during long periods.The median values of RQ10 particle fraction and bulk deposition in Zagreb, Croatia, was assessed based on toxic equivalence factors and equivalent BaP concentrations. Statistically significant differences (p < 0.05) in total equivalent ∑BaPeq mass concentrations in PM10 particle fraction were found between cold and warm months, while for bulk deposition statistically significant differences were found only for Flu. The most studied PAH in the PM10 particle fraction, BaP, contributed to the total PAH carcinogenic activity with 63% in the warm and 66% in the cold period while in bulk deposition samples its contribution was lower (51% for both periods). The human health risk via PAH compounds was evaluated via ingestion, dermal absorption and inhalation using PM10-bound PAHs and the literature data. Dermal absorption implied the greatest potential cancer risk, followed by ingestion and inhalation. Cancer risk was slightly higher for children than for adults. Results of this study showed that the population of the investigated area could possibly develop cancer over a lifetime due to exposure to PAHs. The potential ecological risk of PAHs in bulk deposition was estimated based on the risk quotient approach for the first time. A moderate ecological risk for BaA, BbF and BaP was observed, which pointed out the need for further studies.The carcinogenic activity of PAHs in the PM


Salmonella and Campylobacter are common foodborne pathogens in chickens, but their persistence mechanisms within flocks are not fully understood. In this study, 4 groups of SPF Leghorn chickens (n = 50) were orally inoculated with 108Salmonella Enteritidis and 108Campylobacter jejuni, housed in BSL-2 rooms inside containers with autoclaved bedding and beetles (n = 200). Phase I (wk 1–3): the infected chickens remained in the containers and were then euthanized while beetles and litter remained in the container (group A), beetles were removed and litter remained in the container (group B), beetles remained and litter was removed (group C), and beetles and litter were removed (group D). Phase II (wk 5–7): autoclaved bedding was added to containers in groups C and D, and new SPF chickens (n = 50) were introduced and kept. Phase III (wk 8–20): all chickens were euthanized, and the litter and/or beetles remained in the containers for 17 wk. The prevalence of Salmonella Enteritidis and Campylobacter was significantly higher when detected by PCR compared to culture. In phase II, when infected chickens were removed and new chickens were introduced, 1 fecal sample in group B and 3 litter samples in groups B and C were found positive for Salmonella Enteritidis, and Campylobacter was still detected in groups A, B, and C litter samples, but not in beetles. In phase III, when all chickens were removed, Salmonella Enteritidis was identified in beetle samples from group A and the litter samples of all tested groups A, B, and C, and C. jejuni was positive in litter samples from groups A and B but not in the beetle. Sixty-nine days after removing infected chickens, culturable Salmonella was still found in beetles. Salmonella and Campylobacter were detectable in litter up to 127 d after removing infected chickens. This study highlights the transmission of Salmonella and Campylobacter via beetles and litter to new flocks in successive rearing cycles. Intensive control programs should target insect exclusion and implement strict poultry litter management or litter changes between flocks. Salmonella spp. and Campylobacter spp. remains a significant concern within the US food industry.The poultry industry, specifically broiler chicken, has been recognized as the fastest-growing segment, with a significantly increased market share in the United States. However, associated with this growth, the occurrence of foodborne illnesses caused by foodborne pathogens such as Salmonella infections result in over 1 million cases and 420 deaths, contributing to approximately $4.4 billion in medical costs , also known as the litter beetle, is a resilient pest commonly found in poultry houses. It is a scavenger arthropod and the most abundant pest in such environments. Both adult beetles and their larvae can survive within flocks by consuming chicken feed, feces, and even dead birds. Darkling beetles have been identified as significant vectors for several pathogenic bacteria affecting poultry, including E. coli, Campylobacter, and Salmonella Enteritidis  were obtained from a laboratory-bred colony maintained at Dr. Ruediger Hauck's laboratory, Auburn University. Before the start of all experiments, these beetles were tested and confirmed as Salmonella and Campylobacter negative by PCRs as described below.Adult black lesser mealworms (SPF) Leghorn chickens, aged 3 wk, were purchased from Charles River . They were subsequently housed in isolation rooms with BSL-2 containment at the Sugg Isolation Facility, College of Veterinary Medicine, Auburn University. The chickens were placed in bulk high-density polyethylene containers  with dimensions of 45 × 45 × 33 inches, while autoclaved pine shaving bedding was included. Throughout the study, the chickens were closely monitored 2 to 3 times daily to ensure their welfare. Adequate feed and water were provided ad libitum. This research project was approved by the Auburn University Institutional Biosafety Committee (BUA # 981) and the University Institutional Animal Care and Use Committee (IACUC # 2022-5076).Specific pathogen-free , group B (n = 13), group C (n = 12), and group D (n = 12). On d 0, all chickens were orally inoculated with Salmonella Enteritidis and C. jejuni, while 200 adult beetles were introduced into the litter of each container on the same day.This study allocated 50 three-wk-old SPF chickens to 4 groups and housed them in separate isolation rooms. The chicken distribution during phases I and II was as follows: group A (n = 50) was introduced into each container of the 4 groups for phase II. The chickens were maintained for 3 wk (wk 5–7) before euthanizing.Following the euthanization of the chickens at the end of phase I at wk 3, the treatment of beetles and litter differed among the groups. In group A, the beetles and used litter were retained in the container. In group B, stackable mealworm sifting trays were used to trap beetles from the litter. In this group, only the beetles were removed, leaving the used litter in the container. Group C maintained the beetles, but the litter was removed, the container was cleaned and disinfected using Virocid disinfectant , and then replaced with new autoclaved bedding. In group D, the beetles and the litter were removed; the container was cleaned and disinfected using Virocid disinfectant  and fresh autoclaved bedding was provided. After the 1-wk interval after phase I, a new batch of SPF chickens . Group D was excluded from phase III.Salmonella Enteritidis and C. jejuni status in the chicken flocks. The swabs were immediately placed in a 15-mL centrifuge tube containing 2 mL of PBS and transported to the laboratory for analysis.Fresh fecal swabs from each bird during wk 1 to 3 (phase I) and wk 5 to 7 (phase II) were collected to assess the For beetle sampling, 10 beetles were randomly collected from each container in phases I and II and from groups A, B, and C in phase III. The beetles were placed in centrifuge tubes, transported to the laboratory on sampling day, and homogenized with 1 mL of PBS using 4 zirconia beads in a Precellys 24 lysis and homogenization instrument .Salmonella Enteritidis and C. jejuni.Litter samples were collected from each container of the 4 groups in all 3 phases (phases I–III). The samples were placed in Ziploc bags and transported to the laboratory. After thoroughly mixing the sample, 1 g of litter was weighed and vortexed in 10 mL of PBS. Sampling frequency was weekly during phases I and II, while in phase III, samples were collected on a monthly basis to assess the presence of Salmonella Enteritidis. Xylose lysine agar  supplemented with tergitol 4  and nalidixic acid antibiotic (35 ppm) was used. These plates were incubated at 37°C for 24 to 48 h, and colonies with black or black-centered appearance (indicating H2S production) were considered potential Salmonella Enteritidis isolates.The collected and processed samples (500 µL) from chicken fecal swabs, beetle homogenates, and litter were directly spread on selective media to isolate Campylobacter spp., 500 µL of the processed samples from fecal swabs, beetle homogenates, and litter were plated directly onto Campy Cefex agar  supplemented with horse blood and ciprofloxacin (2 ppm). Characteristic small, mucoid, and grayish colonies were observed to identify Campylobacter.For the bacteriological examination of Salmonella Enteritidis and C. jejuni PCRs were conducted on a Roche light cycler 480 II systems  as previously described  was performed using the High Pure PCR Template Preparation Kit  following the manufacturer's instructions. The escribed .FRET)-PCR was performed for the Salmonella Enteritidis quantification that amplifies a 216-bp target. This PCR targets the tetrathionate reductase response regulator (ttrR) gene, a highly conserved gene located within the Salmonella pathogenicity island 2. The positions of primers and probes  are as follows: forward primer: 5′-GATGTTYCTTAGCGCYTTACAGGC-3′; reverse primer: 5′-CCGACMGCGTAATATTTGGCTGAC-3′; anchor probe: 5′-ATACGCTTTCCGGCACGGCAAT-6-FAM-3′; reporter probe: 5′-LCRED640-CGTCRGTGGATTWCCGTCGCCCT-Phosphate-3′  with an 82-bp amplicon size as described .Quantitative standards for Salmonella Enteritidis and C. jejuni, and the detection rates of Salmonella or Campylobacter in different types of samples. A difference at P  ≤  0.05 was considered significant.All statistical analyses were performed using Statistica 7.0 software package . A chi-square test was performed to compare the prevalence of Salmonella Enteritidis was significantly higher when detected by PCR compared to culture in fecal swabs  and in litter . Similarly, the positivity of Campylobacter was also significantly higher when detected by PCR as compared to culture in fecal swabs  and in the litter . The detection rates for both bacteria were not significantly different in beetles. The specificity of the PCRs used in this study was ensured by validated primers and probes designs and DNA sequencing. The detection limit for the PCRs used in this study was 1 copy of the target gene per reaction . Therefore, the analysis of bacterial prevalence was based on the detection of Salmonella and Campylobacter PCRs.The prevalence of C. jejuni (128/150) was significantly higher than Salmonella Enteritidis (58/150) in fecal swabs . Additionally, the detection rate of Campylobacter was significantly higher in fecal swabs than in beetles   .Table 1PSalmonella Enteritidis. In this phase, the infection rate of C. jejuni also significantly decreased in fecal swabs and was found positive in groups A and B only. However, Campylobacter was still detected in groups A, B, and C litter samples, but not in beetles.Moving to phase II, when infected chickens were removed and new chickens were introduced, only 1 fecal sample in group B and 3 litter samples in groups B and C were found positive for Salmonella Enteritidis was identified in beetle samples from group A and the litter samples of all tested groups A, B, and C  were positive for C. jejuni. Viable Salmonella Enteritidis and C. jejuni remained detectable for up to 127 d, the end of the experiment, in litter after the infected chickens were removed.The detection rates in the litter for both pathogens were higher than in beetles after the infected chickens were removed. In litter, 11 of 24 litter samples (45.8%) were positive for C. jejuni in chickens in this study aligns with findings reported in the existing literature. It has been documented that once introduced, C. jejuni can rapidly spread horizontally throughout a broiler facility . This finding is consistent with other studies that have identified beetles as potential carriers of Salmonella and Campylobacter  state of the cells  of the beetles before detecting the pathogens.One limitation of this this study was not to differentiate external and internal n = 10) and the limited number of samples collected at each collection time. This small sample size and low sampling frequency may not fully reflect the real prevalence of the pathogens in the beetles and litter. In this study, the direct plating for prevalence of Salmonella was performed, and the more sensitive Salmonella culture method with pre-enrichment on more samples shall be used on the future studies.Another limitation of our study is the relatively small number of beetles (Salmonella and Campylobacter can be transmitted via beetles and litter to new flocks in successive rearing cycles. Implementing intensive control programs to exclude poultry insects and practicing proper poultry litter management between flocks will help reduce the spread of foodborne pathogens between rearing cycles in broiler houses.This study suggested that