ABSTRACTHistoplasmosis is an endemic mycosis in North America frequently reported along the Ohio and Mississippi River Valleys, although autochthonous cases occur in non-endemic areas. In the United States, the disease is provoked by two genetically distinct clades of Histoplasma capsulatum sensu lato, Histoplasma mississippiense (Nam1) and H. ohiense (Nam2). To bridge the molecular epidemiological gap, we genotyped 93 Histoplasma isolates (62 novel genomes) including clinical, environmental, and veterinarian samples from a broader geographical range by whole-genome sequencing, followed by evolutionary and species niche modelling analyses. We show that histoplasmosis is caused by two major lineages, H. ohiense and H. mississippiense; with sporadic cases caused by H. suramericanum in California and Texas. While H. ohiense is prevalent in eastern states, H. mississipiense was found to be prevalent in the central and western portions of the United States, but also geographically overlapping in some areas suggesting that these species might co-occur. Species Niche Modelling revealed that H. ohiense thrives in places with warmer and drier conditions, while H. mississippiense is endemic to areas with cooler temperatures and more precipitation. In addition, we predicted multiple areas of secondary contact zones where the two species co-occur, potentially facilitating gene exchange and hybridization. This study provides the most comprehensive understanding of the genomic epidemiology of histoplasmosis in the USA and lays a blueprint for the study of invasive fungal diseases.
Evolutionary constraints greatly favor compact genomes that efficiently encode proteins. However, several eukaryotic organisms, including apicomplexan parasites such as Toxoplasma gondii, Plasmodium falciparum and Babesia duncani, the causative agents of toxoplasmosis, malaria and babesiosis, respectively, encode very large proteins, exceeding 20 times their average protein size. Although these large proteins represent <1% of the total protein pool and are generally expressed at low levels, their persistence throughout evolution raises important questions about their functions and possible evolutionary pressures to maintain them. In this study, we examined the trends in gene and protein size, function and expression patterns within seven apicomplexan pathogens. Our analysis revealed that certain large proteins in apicomplexan parasites harbor domains potentially important for functions such as antigenic variation, erythrocyte invasion and immune evasion. However, these domains are not limited to or strictly conserved within large proteins. While some of these proteins are predicted to engage in conventional metabolic pathways within these parasites, others fulfill specialized functions for pathogen-host interactions, nutrient acquisition and overall survival.
Identifying and understanding behavioral resistance to insecticides is vital for maintaining global food security, public health, and ecological balance. Behavioral resistance has been documented to occur in a multitude of insect taxa dating back to the 1940s, but has not received significant research attention due primarily to the complexities of studying insect behavior and a lack of any clear definition of behavioral resistance. In recent years, a systematic effort to investigate the mechanism(s) of behavioral resistance in pest taxa (e.g. the German cockroach and the house fly) has been undertaken. Here, we practically define behavioral resistance, describe the efforts taken by research groups to elucidate resistance mechanisms, and provide insight on designing appropriate bioassays for investigating behavioral resistance mechanisms in the future.
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a routine method to noninvasively quantify perfusion dynamics in tissues. The standard practice for analyzing DCE-MRI data is to fit an ordinary differential equation to each voxel. Recent advances in data science provide an opportunity to move beyond existing methods to obtain more accurate measurements of fluid properties. Here, we developed a localized convolutional function regression that enables simultaneous measurement of interstitial fluid velocity, diffusion, and perfusion in 3D. We validated the method computationally and experimentally, demonstrating accurate measurement of fluid dynamics in situ and in vivo. Applying the method to human MRIs, we observed tissue-specific differences in fluid dynamics, with an increased fluid velocity in breast cancer as compared to brain cancer. Overall, our method represents an improved strategy for studying interstitial flows and interstitial transport in tumors and patients. We expect that our method will contribute to the better understanding of cancer progression and therapeutic response.
BACKGROUND: The chicken body louse is an obligate ectoparasite of domestic chickens. Chicken body lice feed on feathers, and infestation with this louse is linked to decreases in egg production, hen weight, and feed conversion efficiency. However, it is unknown how chicken body lice impact egg-laying chickens in cage-free environments. Welfare and behavior metrics were collected from flocks of egg-laying chickens either infested with chicken body lice or left uninfested. METHODS: In two trials, two flocks of cage-free commercial egg-laying chickens were infested with chicken body lice or maintained as uninfested controls. At three timepoints, behavior and welfare of all chickens was measured. On-animal sensors were used to quantify pecking, preening, and dustbathing behavior. Other animal-based welfare metrics included recording comb wounds and skin lesions. RESULTS: Birds infested with chicken body lice exhibited significantly more preening behaviors than uninfested birds, even at low louse levels. Moderate or severe skin lesions were detected on birds that were moderately infested with chicken body lice while skin lesions were never detected on uninfested birds. CONCLUSIONS: The welfare of chickens was impacted by the chicken body louse, a chewing louse that primarily feather feeds. Evidence of skin lesions on infested birds suggests that lice may cause more damage to birds than previously thought, and further evaluation of louse economic damage is necessary.
To develop a peri-implantitis model in a Gottingen minipig and evaluate the effect of local application of salicylic acid poly(anhydride-ester) (SAPAE) on peri-implantitis progression in healthy, metabolic syndrome (MS), and type-2 diabetes mellitus (T2DM) subjects. Eighteen animals were allocated to three groups: (i) control, (ii) MS (diet for obesity induction), and (iii) T2DM (diet plus streptozotocin for T2DM induction). Maxillary and mandible premolars and first molar were extracted. After 3 months of healing, four implants per side were placed in both jaws of each animal. After 2 months, peri-implantitis was induced by plaque formation using silk ligatures. SAPAE polymer was mixed with mineral oil (3.75 mg/μL) and topically applied biweekly for up to 60 days to halt peri-implantitis progression. Periodontal probing was used to assess pocket depth over time, followed by histomorphologic analysis of harvested samples. The adopted protocol resulted in the onset of peri-implantitis, with healthy minipigs taking twice as long to reach the same level of probing depth relative to MS and T2DM subjects (∼3.0 mm), irrespective of jaw. In a qualitative analysis, SAPAE therapy revealed decreased levels of inflammation in the normoglycemic, MS, and T2DM groups. SAPAE application around implants significantly reduced the progression of peri-implantitis after ∼15 days of therapy, with ∼30% lower probing depth for all systemic conditions and similar rates of probing depth increase per week between the control and SAPAE groups. MS and T2DM conditions presented a faster progression of the peri-implant pocket depth. SAPAE treatment reduced peri-implantitis progression in healthy, MS, and T2DM groups.
Light-absorbing secondary organic aerosols (SOAs), also known as secondary brown carbon (BrC), are major components of wildfire smoke that can have a significant impact on the climate system; however, how environmental factors such as relative humidity (RH) influence their formation is not fully understood, especially for heterocyclic precursors. We conducted chamber experiments to investigate secondary BrC formation from the nighttime oxidation of furan and pyrrole, two primary heterocyclic precursors in wildfires, in the presence of pre-existing particles at RH < 20% and ∼ 50%. Our findings revealed that increasing RH significantly affected the size distribution dynamics of both SOAs, with pyrrole SOA showing a stronger potential to generate ultrafine particles via intensive nucleation processes. Higher RH led to increased mass fractions of oxygenated compounds in both SOAs, suggesting enhanced gas-phase and/or multiphase oxidation under humid conditions. Moreover, higher RH reduced the mass absorption coefficients of both BrC, contrasting with those from homocyclic precursors, due to the formation of non-absorbing high-molecular-weight oxygenated compounds and the decreasing mass fractions of molecular chromophores. Overall, our findings demonstrate the unique RH dependence of secondary BrC formation from heterocyclic precursors, which may critically modulate the radiative effects of wildfire smoke on climate change.
A simple aqueous host:guest sensing array can selectively discriminate between different types of citrus varietal from peel extract samples. It can also distinguish between identical citrus samples at varying stages of ripening. The discrimination effects stem from detection of changes in the terpenoid composition of the peel extracts by the host:guest array, despite the overwhelming excess of a single component, limonene, in each sample. The hosts are insensitive to limonene but bind other monoterpenes strongly, even though they are similar in structure to the major limonene component. This work demonstrates the capability of host:guest arrays in sensing target molecules in environments with the competing agents present at high abundances in the sample matrix.
