Search

ABSTRACT Respiratory disease, attributed to influenza, respiratory syncytial virus (RSV), and SARS-CoV-2, was reported nationally during the 2023/2024 respiratory viral season. The emergence of novel SARS-CoV-2 variants was considered a significant factor contributing to the rise in COVID-19 cases. Data from the Johns Hopkins Hospital System (JHHS) showed that enterovirus/rhinovirus had also been circulating at high rates. Analyzing clinical outcomes of the most prevalent respiratory viruses is crucial for understanding the role of circulating viral genotypes. A retrospective cohort of patients who tested positive for SARS-CoV-2, influenza, RSV, or enterovirus/rhinovirus between 1 June and 31 December 2023 was included in the study. Remnant clinical samples were utilized for targeted viral whole-genome sequencing and genotyping. Patients’ metadata and outcomes following infection were studied, stratified by viral variants and genotypes. The increase of SARS-CoV-2 positivity in December was associated with the predominance of JN.1. Admissions for patients under 18 years old were primarily associated with enterovirus/rhinovirus and RSV, while older age groups were mainly linked to SARS-CoV-2 and influenza infections. SARS-CoV-2-related admissions increased with the predominance of the JN.1 variant in December. No significant difference in admissions for influenza subtypes, rhinovirus species, or SARS-CoV-2 variants was observed. RSV A was associated with slightly higher odds of admission compared with RSV B. Our data highlight the importance of systematically analyzing respiratory viral infections to inform public health strategies and clinical management, especially as SARS-CoV-2 becomes endemic. The findings highlight the value of expanded genomic surveillance in elucidating the clinical significance of viral evolution.IMPORTANCEThe analysis of the epidemiology and clinical outcomes of multiple co-circulating respiratory viruses in the early 2023/2024 respiratory virus season highlights the emergence of the SARS-CoV-2 JN.1 variant as well as underscores the importance of enterovirus/rhinovirus in respiratory infections. Understanding these dynamics is essential for refining public health strategies and clinical management, especially as SARS-CoV-2 transitions to an endemic status. This work emphasizes the need for ongoing surveillance, robust diagnostic algorithms, and detailed genomic analyses to anticipate and mitigate the burden of respiratory viral infections, ultimately contributing to more informed decision-making in healthcare settings and better patient outcomes.

ABSTRACTPregnant patients are at greater risk of hospitalization with severe COVID-19 than non-pregnant people. This was a retrospective observational cohort study of remnant clinical specimens from patients who visited acute care hospitals within the Johns Hopkins Health System in the Baltimore, MD–Washington DC, area between October 2020 and May 2022. Participants included confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected pregnant people and matched non-pregnant people (the matching criteria included age, race/ethnicity, area deprivation index, insurance status, and vaccination status to ensure matched demographics). The primary dependent measures were clinical COVID-19 outcomes, infectious virus recovery, viral RNA levels, and mucosal anti-spike (S) IgG titers from upper respiratory tract samples. A total of 452 individuals (117 pregnant and 335 non-pregnant) were included in the study, with both vaccinated and unvaccinated individuals represented. Pregnant patients were at increased risk of hospitalization (odds ratio [OR] = 4.2; confidence interval [CI] = 2.0–8.6), intensive care unit admittance (OR = 4.5; CI = 1.2–14.2), and being placed on supplemental oxygen therapy (OR = 3.1; CI = 1.3–6.9). Individuals infected during their third trimester had higher mucosal anti-S IgG titers and lower viral RNA levels (P < 0.05) than those infected during their first or second trimesters. Pregnant individuals experiencing breakthrough infections due to the Omicron variant had reduced anti-S IgG compared to non-pregnant patients (P < 0.05). The observed increased severity of COVID-19 and reduced mucosal antibody responses particularly among pregnant participants infected with the Omicron variant suggest that maintaining high levels of SARS-CoV-2 immunity through booster vaccines may be important for the protection of this at-risk population.IMPORTANCEIn this retrospective observational cohort study, we analyzed remnant clinical samples from non-pregnant and pregnant individuals with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections who visited the Johns Hopkins Hospital System between October 2020 and May 2022. Disease severity, including intensive care unit admission, was greater among pregnant than non-pregnant patients. Vaccination reduced recovery of infectious virus and viral RNA levels in non-pregnant patients, but not in pregnant patients. In pregnant patients, increased nasopharyngeal viral RNA levels and recovery of infectious virus were associated with reduced mucosal IgG antibody responses, especially among women in their first trimester of pregnancy or experiencing breakthrough infections from Omicron variants. Taken together, this study provides insights into how pregnant patients are at greater risk of severe COVID-19. The novelty of this study is that it focuses on the relationship between the mucosal antibody response and its association with virus load and disease outcomes in pregnant people, whereas previous studies have focused on serological immunity. Vaccination status, gestational age, and SARS-CoV-2 omicron variant impact mucosal antibody responses and recovery of infectious virus from pregnant patients.

Recent advances in image data proccesing through deep learning allow for new optimization and performance-enhancement schemes for radiation detectors and imaging hardware. This enables radiation experiments, which includes photon sciences in synchrotron and X-ray free electron lasers as a subclass, through data-endowed artificial intelligence. We give an overview of data generation at photon sources, deep learning-based methods for image processing tasks, and hardware solutions for deep learning acceleration. Most existing deep learning approaches are trained offline, typically using large amounts of computational resources. However, once trained, DNNs can achieve fast inference speeds and can be deployed to edge devices. A new trend is edge computing with less energy consumption (hundreds of watts or less) and real-time analysis potential. While popularly used for edge computing, electronic-based hardware accelerators ranging from general purpose processors such as central processing units (CPUs) to application-specific integrated circuits (ASICs) are constantly reaching performance limits in latency, energy consumption, and other physical constraints. These limits give rise to next-generation analog neuromorhpic hardware platforms, such as optical neural networks (ONNs), for high parallel, low latency, and low energy computing to boost deep learning acceleration (LA-UR-23-32395).

Abstract As air masses move within the troposphere, they transport a multitude of components including gases and particles such as pollen and microorganisms. These movements generate atmospheric highways that connect geographic areas at distant, local, and global scales that particles can ride depending on their aerodynamic properties and their reaction to environmental conditions. In this article we present an approach and an accompanying web application called tropolink for measuring the extent to which distant locations are potentially connected by air‐mass movement. This approach is based on the computation of trajectories of air masses with the HYSPLIT atmospheric transport and dispersion model, and on the computation of connection frequencies, called connectivities, in the purpose of building trajectory‐based geographical networks. It is illustrated for different spatial and temporal scales with three case studies related to plant epidemiology. The web application that we designed allows the user to easily perform intensive computation and mobilize massive archived gridded meteorological data to build weighted directed networks. The analysis of such networks allowed us for example, to describe the potential of invasion of a migratory pest beyond its actual distribution. Our approach could also be used to compute geographical networks generated by air‐mass movement for diverse application domains, for example, to assess long‐term risk of spread from persistent or recurrent sources of pollutants, including wildfire smoke.

We tested the effects of prolonged voluntary wheel running on the muscle function of mdx mice treated with one of two different microdystrophin constructs. At 7 weeks of age mdx mice were injected with a single dose of AAV9-CK8-microdystrophin with (gene therapy 1, GT1) or without (gene therapy 2, GT2) the nNOS-binding domain and were assigned to one of four gene therapy treated groups: mdxRGT1 (run, GT1), mdxGT1 (no run, GT1), or mdxRGT2 (run,GT2), mdxGT2 (no run, GT2). There were two mdx untreated groups injected with excipient: mdxR (run, no gene therapy) and mdx (no run, no gene therapy). A third no treatment group, Wildtype (WT) received no injection and did not run. mdxRGT1, mdxRGT2 and mdxR performed voluntary wheel running for 52 weeks; WT and remaining mdx groups were cage active. Robust expression of microdystrophin occurred in diaphragm, quadriceps, and heart muscles of all treated mice. Dystrophic muscle pathology was high in diaphragms of non-treated mdx and mdxR mice and improved in all treated groups. Endurance capacity was rescued by both voluntary wheel running and gene therapy alone, but their combination was most beneficial. All treated groups increased in vivo plantarflexor torque over both mdx and mdxR mice. mdx and mdxR mice displayed ∼3-fold lower diaphragm force and power compared to WT values. Treated groups demonstrated partial improvements in diaphragm force and power, with mdxRGT2 mice experiencing the greatest improvement at ∼60% of WT values. Evaluation of oxidative red quadriceps fibers revealed the greatest improvements in mitochondrial respiration in mdxRGT1 mice, reaching WT levels. Interestingly, mdxGT2 mice displayed diaphragm mitochondrial respiration values similar to WT but mdxRGT2 animals showed relative decreases compared to the no run group. Collectively, these data demonstrate that either microdystrophin construct combined with voluntary wheel running increased in vivo maximal muscle strength, power, and endurance. However, these data also highlighted important differences between the two microdystrophin constructs. GT1, with the nNOS-binding site, improved more markers of exercise-driven adaptations in metabolic enzyme activity of limb muscles, while GT2, without the nNOS-binding site, demonstrated greater protection of diaphragm strength after chronic voluntary endurance exercise but decreased mitochondrial respiration in the context of running.

The oxidation of dimethyl sulfide (DMS; CH3SCH3), emitted from the surface ocean, contributes to the formation of Aitken mode particles and their growth to cloud condensation nuclei (CCN) sizes in remote marine environments. It is not clear whether other less commonly measured marine-derived, sulfur-containing gases share similar dynamics to DMS and contribute to secondary marine aerosol formation. Here, we present measurements of gas-phase volatile organosulfur molecules taken with a Vocus proton-transfer-reaction high-resolution time-of-flight mass spectrometer during a mesocosm phytoplankton bloom experiment using coastal seawater. We show that DMS, methanethiol (MeSH; CH3SH), and benzothiazole (C7H5NS) account for on average over 90 % of total gas-phase sulfur emissions, with non-DMS sulfur sources representing 36.8 ± 7.7 % of sulfur emissions during the first 9 d of the experiment in the pre-bloom phase prior to major biological growth, before declining to 14.5 ± 6.0 % in the latter half of the experiment when DMS dominates during the bloom and decay phases. The molar ratio of DMS to MeSH during the pre-bloom phase (DMS : MeSH = 4.60 ± 0.93) was consistent with the range of previously calculated ambient DMS-to-MeSH sea-to-air flux ratios. As the experiment progressed, the DMS to MeSH emission ratio increased significantly, reaching 31.8 ± 18.7 during the bloom and decay. Measurements of dimethylsulfoniopropionate (DMSP), heterotrophic bacteria, and enzyme activity in the seawater suggest the DMS : MeSH ratio is a sensitive indicator of the bacterial sulfur demand and the composition and magnitude of available sulfur sources in seawater. The evolving DMS : MeSH ratio and the emission of a new aerosol precursor gas, benzothiazole, have important implications for secondary sulfate formation pathways in coastal marine environments.

We report enterovirus D68 circulation in Maryland, USA, during September–October 2021, which was associated with a spike in influenza-like illness. The characterized enterovirus D68 genomes clustered within the B3 subclade that circulated in 2018 in Europe and the United States.

BACKGROUND Increased SARS-CoV-2 reinfection rates have been reported recently, with some locations basing reinfection on a second positive PCR test at least 90 days after initial infection. In this study, we used Johns Hopkins SARS-CoV-2 genomic surveillance data to evaluate the frequency of sequencing-validated, confirmed, and inferred reinfections between March 2020 and July 2022.METHODS Patients who had 2 or more positive SARS-CoV-2 tests in our system, with samples sequenced as a part of our surveillance efforts, were identified as the cohort for our study. SARS-CoV-2 genomes of patients’ initial and later samples were compared.RESULTS A total of 755 patients (920 samples) had a positive test at least 90 days after the initial test, with a median time between tests of 377 days. Sequencing was attempted on 231 samples and was successful in 127. Rates of successful sequencing spiked during the Omicron surge; there was a higher median number of days from initial infection in these cases compared with those with failed sequences. A total of 122 (98%) patients showed evidence of reinfection; 45 of these patients had sequence-validated reinfection and 77 had inferred reinfections (later sequencing showed a clade that was not circulating when the patient was initially infected). Of the 45 patients with sequence-validated reinfections, 43 (96%) had reinfections that were caused by the Omicron variant, 41 (91%) were symptomatic, 32 (71%) were vaccinated prior to the second infection, 6 (13%) were immunosuppressed, and only 2 (4%) were hospitalized.CONCLUSION Sequence-validated reinfections increased with the Omicron surge but were generally associated with mild infections.FUNDING Funding was provided by the Johns Hopkins Center of Excellence in Influenza Research and Surveillance (HHSN272201400007C), CDC (75D30121C11061), Johns Hopkins University President’s Fund Research Response, Johns Hopkins Department of Pathology, and the Maryland Department of Health.

ABSTRACT Lymphatic filariasis is a debilitating disease that afflicts over 70 million people worldwide. It is caused by the parasitic nematodes Wuchereria bancrofti, Brugia malayi, and Brugia timori. Despite substantial success, efforts to eliminate LF will likely require more time and resources than predicted. Identifying new drug and vaccine targets in adult filariae could help elimination efforts. This study’s aim was to evaluate intestinal proteins in adult Brugia malayi worms as possible therapeutic targets. Using short interfering RNA (siRNA), we successfully targeted four candidate gene transcripts: Bma-Serpin, Bma-ShTK, Bma-Reprolysin, and Bma-LAD-2. Of those, Bma-LAD-2, an immunoglobulin superfamily cell adhesion molecule (IgSF CAM), was determined to be essential for adult worm survival. We observed a 70.42% knockdown in Bma-LAD-2 transcript levels 1 day post-siRNA incubation and an 87.02% reduction in protein expression 2 days post-siRNA incubation. This inhibition of Bma-LAD-2 expression resulted in an 80% decrease in worm motility over 6 days, a 93.43% reduction in microfilaria release (Mf) by day 6 post-siRNA incubation, and a dramatic decrease in (4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) reduction. Transmission electron microscopy revealed the loss of microvilli and unraveling of mitochondrial cristae in the intestinal epithelium of Bma-LAD-2 siRNA-treated worms. Strikingly, Bma-LAD-2 siRNA-treated worms exhibited an almost complete loss of pseudocoelomic fluid. A luciferase immunoprecipitation system assay did not detect anti-Bma-LAD-2 IgE in the serum of 30 LF patients, indicating that LF exposure does not result in IgE sensitization to this antigen. These results indicate that Bma-LAD-2 is an essential protein for adult Brugia malayi and may be an effective therapeutic target. IMPORTANCE Brugia malayi is a parasitic nematode that can cause lymphatic filariasis, a debilitating disease prevalent in tropical and subtropical countries. Significant progress has been made toward eliminating the disease. However, complete eradication may require new therapeutics such as drugs or a vaccine that kill adult filariae. In this study, we identified an immunoglobulin superfamily cell adhesion molecule (Bma-LAD-2) as a potential drug and vaccine candidate. When we knocked down Bma-LAD-2 expression, we observed a decrease in worm motility, fecundity, and metabolism. We also visualized the loss of microvilli, destruction of the mitochondria in the intestinal epithelium, and loss of pseudocoelomic fluid contents after Bma-LAD-2 siRNA treatment. Finally, we demonstrated that serum from filaria-infected patients does not contain preexisting IgE to Bma-LAD-2, which indicates that this antigen would be safe to administer as a vaccine in populations where the disease is endemic.

Summary: Background: The increase in SARS-CoV-2 infections in December 2021 was driven primarily by the Omicron variant, which largely displaced the Delta over a three-week span. Outcomes from infection with Omicron remain uncertain. We evaluated whether clinical outcomes and viral loads differed between Delta and Omicron infections during the period when both variants were co-circulating. Methods: In this retrospective observational cohort study, remnant clinical specimens, positive for SARS-CoV-2 after standard of care testing at the Johns Hopkins Microbiology Laboratory, between the last week of November and the end of December 2021, were used for whole viral genome sequencing. Cycle threshold values (Ct) for viral RNA, the presence of infectious virus, and levels of respiratory IgG were measured, and clinical outcomes were obtained. Differences in each measure were compared between variants stratified by vaccination status. Findings: The Omicron variant displaced Delta during the study period and constituted 95% of the circulating lineages by the end of December 2021. Patients with Omicron infections (N = 1,119) were more likely to be vaccinated compared to patients with Delta (N = 908), but were less likely to be admitted (0.33 CI 0.21–0.52), require ICU level care (0.38 CI 0.17–0.87), or succumb to infection (0.26 CI 0.06–1.02) regardless of vaccination status. There was no statistically significant difference in Ct values based on the lineage regardless of the vaccination status. Recovery of infectious virus in cell culture was reduced in boosted patients compared to fully vaccinated without a booster and unvaccinated when infected with the Delta lineage. However, in patients with Omicron infections, recovery of infectious virus was not affected by vaccination. Interpretation: Compared to Delta, Omicron was more likely to cause breakthrough infections of vaccinated individuals, yet admissions were less frequent. Admitted patients might develop severe disease comparable to Delta. Efforts for reducing Omicron transmission are required as, though the admission risk might be lower, the increased numbers of infections cause large numbers of hospitalizations. Funding: NIH/NIAID Center of Excellence in Influenza Research and Surveillance contract HHS N2772201400007C, Johns Hopkins University, Maryland department of health, Centers for Disease Control and Prevention contract 75D30121C11061, and The Modeling Infectious Diseases in Healthcare Network (MInD) under awards U01CK000589.

Large-scale SARS-CoV-2 molecular testing coupled with whole genome sequencing in the diagnostic laboratories is instrumental for real-time genomic surveillance. The extensive genomic, laboratory, and clinical data provide a valuable resource for understanding cases of reinfection versus prolonged RNA shedding and protracted infections. In this study, data from a total of 22,292 clinical specimens, positive by SARS-CoV-2 molecular diagnosis at Johns Hopkins clinical virology laboratory between March 11th 2020 to September 23rd 2021, were used to identify patients with two or more positive results. A total of 3,650 samples collected from 1,529 patients who had between 2 and 20 positive results were identified in a time frame that extended up to 403 days from the first positive. Cycle threshold values (Ct) were available for 1,622 samples, the median of which was over 30 by 11 days after the first positive. Extended recovery of infectious virus on cell culture was notable for up to 70 days after the first positive in immunocompromised patients. Whole genome sequencing data generated as a part of our SARS-CoV-2 genomic surveillance was available for 1,027 samples from patients that had multiple positive tests. Positive samples collected more than 10 days after initial positive with high quality sequences (coverage >90% and mean depth >100), were more likely to be from unvaccinated, or immunosuppressed patients. Reinfections with viral variants of concern were found in 3 patients more than 130 days from prior infections with a different viral clade. In 75 patients that had 2 or more high quality sequences, the acquisition of more substitutions or deletions was associated with lack of vaccination and longer time between the recovered viruses. Our study highlights the value of integrating genomic, laboratory, and clinical data for understanding the biology of SARS-CoV-2 as well as for setting a precedent for future epidemics and pandemics.

Some biological particles and macromolecules are particularly efficient ice nuclei (IN), triggering ice formation at temperatures close to 0 ∘C. The impact of biological particles on cloud glaciation and the formation of precipitation is still poorly understood and constitutes a large gap in the scientific understanding of the interactions and coevolution of life and climate. Ice nucleation activity in fungi was first discovered in the cosmopolitan genus Fusarium, which is widespread in soil and plants, has been found in atmospheric aerosol and cloud water samples, and can be regarded as the best studied ice-nucleation-active (IN-active) fungus. The frequency and distribution of ice nucleation activity within Fusarium, however, remains elusive. Here, we tested more than 100 strains from 65 different Fusarium species for ice nucleation activity. In total, ∼11 % of all tested species included IN-active strains, and ∼16 % of all tested strains showed ice nucleation activity above −12 ∘C. Besides Fusarium species with known ice nucleation activity, F. armeniacum, F. begoniae, F. concentricum, and F. langsethiae were newly identified as IN-active. The cumulative number of IN per gram of mycelium for all tested Fusarium species was comparable to other biological IN like Sarocladium implicatum, Mortierella alpina, and Snomax®. Filtration experiments indicate that cell-free ice-nucleating macromolecules (INMs) from Fusarium are smaller than 100 kDa and that molecular aggregates can be formed in solution. Long-term storage and freeze–thaw cycle experiments revealed that the fungal IN in aqueous solution remain active over several months and in the course of repeated freezing and thawing. Exposure to ozone and nitrogen dioxide at atmospherically relevant concentration levels also did not affect the ice nucleation activity. Heat treatments at 40 to 98 ∘C, however, strongly reduced the observed IN concentrations, confirming earlier hypotheses that the INM in Fusarium largely consists of a proteinaceous compound. The frequency and the wide distribution of ice nucleation activity within the genus Fusarium, combined with the stability of the IN under atmospherically relevant conditions, suggest a larger implication of fungal IN on Earth’s water cycle and climate than previously assumed.

The early COVID-19 pandemic was characterized by rapid global spread. In Maryland and Washington, DC, United States, more than 2500 cases were reported within 3 weeks of the first COVID-19 detection in March 2020. We aimed to use genomic sequencing to understand the initial spread of SARS-CoV-2 — the virus that causes COVID-19 — in the region. We analyzed 620 samples collected from the Johns Hopkins Health System during March 11–31, 2020, comprising 28.6% of the total cases in Maryland and Washington, DC. From these samples, we generated 114 complete viral genomes. Analysis of these genomes alongside a subsampling of over 1000 previously published sequences showed that the diversity in this region rivaled global SARS-CoV-2 genetic diversity at that time and that the sequences belong to all of the major globally circulating lineages, suggesting multiple introductions into the region. We also analyzed these regional SARS-CoV-2 genomes alongside detailed clinical metadata and found that clinically severe cases had viral genomes belonging to all major viral lineages. We conclude that efforts to control local spread of the virus were likely confounded by the number of introductions into the region early in the epidemic and the interconnectedness of the region as a whole.

The movement of atmospheric air masses can be seen as a continuous flow of gases and particles hovering over our planet, and it can be locally simplified by means of three-dimensional trajectories. These trajectories can hence be seen as a way of connecting distant areas of the globe during a given period of time. In this paper we present a mathematical formalism to construct spatial and spatiotemporal networks where the nodes represent the subsets of a partition of a geographical area and the links between them are inferred from sampled trajectories of air masses passing over and across them. We propose different estimators of the intensity of the links, relying on different bio-physical hypotheses and covering adjustable time periods. This construction leads to a new definition of spatiotemporal networks characterized by adjacency matrices giving, e.g., the probability of connection between distant areas during a chosen period of time. We applied our methodology to characterize tropospheric connectivity in two real geographical contexts: the watersheds of the French region Provence-Alpes-Côte d’Azur and the coastline of the Mediterranean Sea. The analysis of the constructed networks allowed identifying a marked seasonal pattern in air mass movements in the two study areas. If our methodology is applied to samples of air-mass trajectories, with potential implications in aerobiology and plant epidemiology, it could be applied to other types of trajectories, such as animal trajectories, to characterize connectivity between different components of the landscape hosting the animals.

Microbial aerosols (mainly composed of bacterial and fungal cells) may constitute up to 74 % of the total aerosol volume. These biological aerosols are not only relevant to the dispersion of pathogens, but they also have geochemical implications. Some bacteria and fungi may, in fact, serve as cloud condensation or ice nuclei, potentially affecting cloud formation and precipitation and are active at higher temperatures compared to their inorganic counterparts. Simulations of the impact of microbial aerosols on climate are still hindered by the lack of information regarding their emissions from ground sources. This present work tackles this knowledge gap by (i) applying a rigorous micrometeorological approach to the estimation of microbial net fluxes above a Mediterranean grassland and (ii) developing a deterministic model (the PLAnET model) to estimate these emissions on the basis of a few meteorological parameters that are easy to obtain. The grassland is characterized by an abundance of positive net microbial fluxes and the model proves to be a promising tool capable of capturing the day-to-day variability in microbial fluxes with a relatively small bias and sufficient accuracy. PLAnET is still in its infancy and will benefit from future campaigns extending the available training dataset as well as the inclusion of ever more complex and critical phenomena triggering the emission of microbial aerosol (such as rainfall). The model itself is also adaptable as an emission module for dispersion and chemical transport models, allowing further exploration of the impact of land-cover-driven microbial aerosols on the atmosphere and climate.

Experiments were conducted to determine the efficacy of replacing phosphates in marinated chicken and chunked and formed deli ham using alternative ingredient blends. For the marinated chicken study, broiler breasts were marinated with a 13% solution of 1.0% NaCl, water and either 0.35% sodium tripolyphosphate or a phosphate alternative. Treatment variables consisted of (1) 0.35% sodium tripolyphosphate (STP), (2) negative control (no phosphate, NP), (3) 0.83% Whey protein concentrate (WPC), (4) 0.83% Oat fiber (OF, marinated chicken only), or (5) 1.05% Oat fiber with dry vinegar (OFDV).The WPC, OF, and OF-DV treatments also included 1,000 ppm of a natural flavor that served as an antioxidant. The STP treatment yielded breast meat with less (P < 0.05) cooking loss and a higher pH (P < 0.05) than the NP and alternative ingredient treatments. On average, no differences were observed (P > 0.05) in consumer acceptability for chicken breast appearance, texture and overall acceptability. For the ham study, each treatment formulation consisted of approximately 77% pork, 20% water, common commercial curing ingredients, and the following treatment effects: STP (0.4% STP), NP (no phosphate, NP), 1.3% OF-DV, and 1.1% WPC. STP had less cooking loss than all other treatments (P < 0.05). The STP treatment had greater protein bind (P < 0.05) than all other treatments, and the OF-DV treatment had greater protein bind than the WPC and NP treatments. The NP, STP, and WPC treatments were preferred (P < 0.05) over the OF-DV treatment. Application of WPC or OF-DV may help meat processors meet current clean label trends if the decrease in yields for chicken breast and deli hams and the decrease in firmness of texture in deli hams is acceptable to processors and consumers.

Lymphatic filariasis (LF), a morbid disease caused by the tissue-invasive nematodes Wuchereria bancrofti, Brugia malayi, and Brugia timori, affects millions of people worldwide. Global eradication efforts have significantly reduced worldwide prevalence, but complete elimination has been hampered by limitations of current anti-filarial drugs and the lack of a vaccine. The goal of this study was to evaluate B. malayi intestinal UDP-glucuronosyltransferase (Bm-UGT) as a potential therapeutic target. To evaluate whether Bm-UGT is essential for adult filarial worms, we inhibited its expression using siRNA. This resulted in a 75% knockdown of Bm-ugt mRNA for 6 days and almost complete suppression of detectable Bm-UGT by immunoblot. Reduction in Bm-UGT expression resulted in decreased worm motility for 6 days, 70% reduction in microfilaria release from adult worms, and significant reduction in adult worm metabolism as detected by MTT assays. Because prior allergic-sensitization to a filarial antigen would be a contraindication for its use as a vaccine candidate, we tested plasma from infected and endemic normal populations for Bm-UGT-specific IgE using a luciferase immunoprecipitation assay. All samples (n = 35) tested negative. We then tested two commercially available medicines known to be broad inhibitors of UGTs, sulfinpyrazone and probenecid, for in vitro activity against B. malayi. There were marked macrofilaricidal effects at concentrations achievable in humans and very little effect on microfilariae. In addition, we observed that probenecid and sulfinpyrazone exhibit a synergistic macrofilaricidal effect when used in combination with albendazole. The results of this study demonstrate that Bm-UGT is an essential protein for adult worm survival. Lack of prior IgE sensitization in infected and endemic populations suggest it may be a feasible vaccine candidate. The finding that sulfinpyrazone and probenecid have in vitro effects against adult B. malayi worms suggests that these medications have promise as potential macrofilaricides in humans.

Ice nucleation is a means by which the deposition of an airborne microorganism can be accelerated under favourable meteorological conditions. Analysis of 56 snow samples collected at the high-altitude observatory Jungfraujoch (3580 m a.s.l.) revealed an order-of-magnitude-larger dynamic range of ice-nucleating particles active at −8 °C (INPs−8) compared to the total number of bacterial cells (of which on average 60 % was alive). This indicates a shorter atmospheric residence time for INPs−8. Furthermore, concentrations of INPs−8 decreased much faster, with an increasing fraction of water precipitated from the air mass prior to sampling, than the number of total bacterial cells. Nevertheless, at high wind speeds (> 50 km h−1) the ratio of INPs−8 to total bacterial cells largely remained in a range between 10−2 and 10−3, independent of prior precipitation, likely because of recent injections of particles in regions upwind. Based on our field observations, we conclude that ice nucleators travel shorter legs of distance with the atmospheric water cycle than the majority of bacterial cells. A prominent ice-nucleating bacterium, Pseudomonas syringae, has been previously supposed to benefit from this behaviour as a means to spread via the atmosphere and to colonise new host plants. Therefore, we targeted this bacterium with a selective cultivation approach. P. syringae was successfully isolated for the first time at such an altitude in 3 of 13 samples analysed. Colony-forming units of this species constituted a minor fraction (10−4) of the numbers of INPs−8 in these samples. Overall, our findings expand the geographic range of habitats where this bacterium has been found and corroborate theories on its robustness in the atmosphere and its propensity to spread to colonise new habitats.

Nucleation of ice affects the properties of clouds and the formation of precipitation. Quantitative data on how ice nucleating particles (INPs) determine the distribution, occurrence and intensity of precipitation are still scarce. INPs active at −8 °C (INPs−8) were observed for 2 years in precipitation samples at the High-Altitude Research Station Jungfraujoch (Switzerland) at 3580 m a.s.l. Several environmental parameters were scanned for their capability to predict the observed abundance and variability of INPs−8. Those singularly presenting the best correlations with observed number of INPs−8 (residual fraction of water vapour, wind speed, air temperature, number of particles with diameter larger than 0.5 µm, season, and source region of particles) were implemented as potential predictor variables in statistical multiple linear regression models. These models were calibrated with 84 precipitation samples collected during the first year of observations; their predictive power was successively validated on the set of 15 precipitation samples collected during the second year. The model performing best in calibration and validation explains more than 75 % of the whole variability of INPs−8 in precipitation and indicates that a high abundance of INPs−8 is to be expected whenever high wind speed coincides with air masses having experienced little or no precipitation prior to sampling. Such conditions occur during frontal passages, often accompanied by precipitation. Therefore, the circumstances when INPs−8 could be sufficiently abundant to initiate the ice phase in clouds may frequently coincide with meteorological conditions favourable to the onset of precipitation events.

The residence time of bacterial cells in the atmosphere is predictable by numerical models. However, estimations of their aerial dispersion as living entities are limited by a lack of information concerning survival rates and behavior in relation to atmospheric water. Here we investigate the viability and ice nucleation (IN) activity of typical atmospheric ice nucleation active bacteria (Pseudomonas syringae and P. fluorescens) when airborne in a cloud simulation chamber (AIDA, Karlsruhe, Germany). Cell suspensions were sprayed into the chamber and aerosol samples were collected by impingement at designated times over a total duration of up to 18 h, and at some occasions after dissipation of a cloud formed by depressurization. Aerosol concentration was monitored simultaneously by online instruments. The cultivability of airborne cells decreased exponentially over time with a half-life time of 250 ± 30 min (about 3.5 to 4.5 h). In contrast, IN activity remained unchanged for several hours after aerosolization, demonstrating that IN activity was maintained after cell death. Interestingly, the relative abundance of IN active cells still airborne in the chamber was strongly decreased after cloud formation and dissipation. This illustrates the preferential precipitation of IN active cells by wet processes. Our results indicate that from 106 cells aerosolized from a surface, one would survive the average duration of its atmospheric journey estimated at 3.4 days. Statistically, this corresponds to the emission of 1 cell that achieves dissemination every ~ 33 min m−2 of cultivated crops fields, a strong source of airborne bacteria. Based on the observed survival rates, depending on wind speed, the trajectory endpoint could be situated several hundreds to thousands of kilometers from the emission source. These results should improve the representation of the aerial dissemination of bacteria in numeric models.

Cloud glaciation is critically important for the global radiation budget (albedo) and for initiation of precipitation. But the freezing of pure water droplets requires cooling to temperatures as low as 235 K. Freezing at higher temperatures requires the presence of an ice nucleator, which serves as a template for arranging water molecules in an ice-like manner. It is often assumed that these ice nucleators have to be insoluble particles. We point out that also free macromolecules which are dissolved in water can efficiently induce ice nucleation: the size of such ice nucleating macromolecules (INMs) is in the range of nanometers, corresponding to the size of the critical ice embryo. As the latter is temperature-dependent, we see a correlation between the size of INMs and the ice nucleation temperature as predicted by classical nucleation theory. Different types of INMs have been found in a wide range of biological species and comprise a variety of chemical structures including proteins, saccharides, and lipids. Our investigation of the fungal species Acremonium implicatum, Isaria farinosa, and Mortierella alpina shows that their ice nucleation activity is caused by proteinaceous water-soluble INMs. We combine these new results and literature data on INMs from fungi, bacteria, and pollen with theoretical calculations to develop a chemical interpretation of ice nucleation and water-soluble INMs. This has atmospheric implications since many of these INMs can be released by fragmentation of the carrier cell and subsequently may be distributed independently. Up to now, this process has not been accounted for in atmospheric models.

The lack of effective short-course therapies for treatment of the adult stage of filarial worms is a major limitation in the global effort to eliminate lymphatic filariasis. Studies using current small mammal models of lymphatic filariasis are limited by difficulties in quantifying adult worm numbers and in assessing lymphatic anatomy and function.Here, we re-established Brugia malayi infection of ferrets as a model for lymphatic filariasis and demonstrated parasitological, immunological, and histological parallels with human infection. Subcutaneous injection of L3 larvae into a hind-footpad resulted in a mean of 18 adult worms recovered 16 weeks post-infection, primarily from the draining inguinal and femoral lymphatics of the injected limb. Infected ferrets developed microfilaremia, with patency lasting from 12-26 weeks post-infection. Quantitative PCR assessing cytokine transcription by antigen-stimulated lymph node cells demonstrated a mixed Th1/Th2 response occurring during early infection. Immunoregulation with production of down-regulatory cytokine IL-10 occurred just prior to peak microfilaremia. Histological analysis revealed progressive inflammation of the lymphatic vessel walls, with intimal thickening and disorganization of collagen fibers. Inflammation was observed as early as 8 weeks post-infection and extended into the perivascular and subcutaneous tissues by 16 weeks post-infection. Finally, we developed a novel ferret PET/CT lymphoscintigraphy method demonstrating substantial changes in lymphatic anatomy and function as early as 3 weeks post-infection, with progression over the course of infection.B. malayi infection of ferrets is a robust model of human lymphatic filariasis that can be utilized to study efficacy of novel antifilarial agents against adult worms residing within lymphatic vessels. In conjunction with PET/CT lymphoscintigraphy, this model can also be used to investigate pathogenesis of lymphatic dysfunction in lymphatic filariasis and efficacy of medications aimed at reversing lymphatic dysfunction after clearance of adult worms.

Rainfall is one of the most important aspects of climate, but the extent to which atmospheric ice nuclei (IN) influence its formation, quantity, frequency, and location is not clear. Microorganisms and other biological particles are released following rainfall and have been shown to serve as efficient IN, in turn impacting cloud and precipitation formation. Here we investigated potential long-term effects of IN on rainfall frequency and quantity. Differences in IN concentrations and rainfall after and before days of large rainfall accumulation (i.e., key days) were calculated for measurements made over the past century in southeastern and southwestern Australia. Cumulative differences in IN concentrations and daily rainfall quantity and frequency as a function of days from a key day demonstrated statistically significant increasing logarithmic trends (R2 > 0.97). Based on observations that cumulative effects of rainfall persisted for about 20 days, we calculated cumulative differences for the entire sequence of key days at each site to create a historical record of how the differences changed with time. Comparison of pre-1960 and post-1960 sequences most commonly showed smaller rainfall totals in the post-1960 sequences, particularly in regions downwind from coal-fired power stations. This led us to explore the hypothesis that the increased leaf surface populations of IN-active bacteria due to rain led to a sustained but slowly diminishing increase in atmospheric concentrations of IN that could potentially initiate or augment rainfall. This hypothesis is supported by previous research showing that leaf surface populations of the ice-nucleating bacterium Pseudomonas syringae increased by orders of magnitude after heavy rain and that microorganisms become airborne during and after rain in a forest ecosystem. At the sites studied in this work, aerosols that could have initiated rain from sources unrelated to previous rainfall events (such as power stations) would automatically have reduced the influences on rainfall of those whose concentrations were related to previous rain, thereby leading to inhibition of feedback. The analytical methods described here provide means to map and delimit regions where rainfall feedback mediated by microorganisms is suspected to occur or has occurred historically, thereby providing rational means to establish experimental set-ups for verification.

For decades, drop-freezing instruments have contributed to a better understanding of biological ice nucleation and its likely implications for cloud and precipitation development. Yet, current instruments have limitations. Drops analysed on a cold stage are subject to evaporation and potential contamination. The use of closed tubes provides a partial solution to these problems, but freezing events are still difficult to be clearly detected. Here, we present a new apparatus where freezing in closed tubes is detected automatically by a change in light transmission upon ice development, caused by the formation of air bubbles and crystal facets that scatter light. Risks of contamination and introduction of biases linked to detecting the freezing temperature of a sample are then minimized. To illustrate the performance of the new apparatus we show initial results of two assays with snow samples. In one, we repeatedly analysed the sample (208 tubes) over the course of a month with storage at +4 °C, during which evidence for biological ice nucleation activity emerged through an increase in the number of ice nucleators active around −4 °C. In the second assay, we indicate the possibility of increasingly isolating a single ice nucleator from a precipitation sample, potentially determining the nature of a particle responsible for a nucleation activity measured directly in the sample. These two seminal approaches highlight the relevance of this handy apparatus for providing new points of view in biological ice nucleation research.

Various features of the biology of the rust fungi and of the epidemiology of the plant diseases they cause illustrate the important role of rainfall in their life history. Based on this insight we have characterized the ice nucleation activity (INA) of the aerially disseminated spores (urediospores) of this group of fungi. Urediospores of this obligate plant parasite were collected from natural infections of 7 species of weeds in France, from coffee in Brazil and from field and greenhouse-grown wheat in France, the USA, Turkey and Syria. Immersion freezing was used to determine freezing onset temperatures and the abundance of ice nuclei in suspensions of washed spores. Microbiological analyses of spores from France, the USA and Brazil, and subsequent tests of the ice nucleation activity of the bacteria associated with spores were deployed to quantify the contribution of bacteria to the ice nucleation activity of the spores. All samples of spores were ice nucleation active, having freezing onset temperatures as high as −4 °C. Spores in most of the samples carried cells of ice nucleation-active strains of the bacterium Pseudomonas syringae (at rates of less than 1 bacterial cell per 100 urediospores), but bacterial INA accounted for only a small fraction of the INA observed in spore suspensions. Changes in the INA of spore suspensions after treatment with lysozyme suggest that the INA of urediospores involves a polysaccharide. Based on data from the literature, we have estimated the concentrations of urediospores in air at cloud height and in rainfall. These quantities are very similar to those reported for other biological ice nucleators in these same substrates. However, at cloud level convective activity leads to widely varying concentrations of particles of surface origin, so that mean concentrations can underestimate their possible effects on clouds. We propose that spatial and temporal concentrations of biological ice nucleators active at temperatures > −10 °C and the specific conditions under which they can influence cloud glaciation need to be further evaluated so as to understand how evolutionary processes could have positively selected for INA.

Although ice nuclei from bacterial origin are known to be efficient at the highest temperatures known for ice catalysts, quantitative data are still needed to assess their role in cloud processes. Here we studied the effects of three typical cloud conditions (i) acidic pH (ii) NO2 and O3 exposure and (iii) UV-A exposure on the ice nucleation activity (INA) of four Pseudomonas strains. Three of the Pseudomonas syringae strains were isolated from cloud water and the phyllosphere and Pseudomonas fluorescens strain CGina-01 was isolated from Antarctic glacier ice melt. Among the three conditions tested, acidic pH caused the most significant effects on INA likely due to denaturation of the ice nucleation protein complex. Exposure to NO2 and O3 gases had no significant or only weak effects on the INA of two P. syringae strains whereas the INA of P. fluorescens CGina-01 was significantly affected. The INA of the third P. syringae strain showed variable responses to NO2 and O3 exposure. These differences in the INA of different Pseudomonas suggest that the response to atmospheric conditions could be strain-specific. After UV-A exposure, a substantial loss of viability of all four strains was observed whereas their INA decreased only slightly. This corroborates the notion that under certain conditions dead bacterial cells can maintain their INA. Overall, the negative effects of the three environmental factors on INA were more significant at the warmer temperatures. Our results suggest that in clouds where temperatures are near 0 °C, the importance of bacterial ice nucleation in precipitation processes could be reduced by some environmental factors.

Many studies from the last decades have shown that airborne microorganisms can be intrinsically linked to atmospheric processes. Certain bacteria may constitute the most active ice nuclei found in the atmosphere and might have some influence on the formation of ice crystals in clouds. This study deals with the ice nucleation activity of Pseudomonas syringae inside of thunderstorms through numerical simulations using BRAMS (Brazilian Regional Atmospheric Model System). The numerical simulations were developed in order to investigate the effect on the total amount of rainwater as a function of ice nuclei (IN) P. syringae concentrations with different scenarios (classified as S2 to S4 scenarios) corresponding to a maximum of 102 to 104 IN bacteria per liter of cloud water plus the BRAMS default (classified as S5 scenario). Additionally, two other scenarios were included without any IN (S1) and the sum of RAMS default and S4 scenario (classified as S6). The chosen radiosonde data is for 3 March 2003, typical summertime in São Paulo City which presents a strong convective cell. The objective of the simulations was to analyze the effect of the IN concentrations on the BRAMS modeled cloud properties and precipitation. The simulated electrification of the cloud permitted analysis of the total flashes estimated from precipitable and non-precipitable ice mass fluxes in two different lightning frequencies. Among all scenarios, only S4 and S6 presented a tendency to decrease the total cloud water, and all bacteria scenarios presented a tendency to decrease the total amount of rain (−8%), corroborating other reports in the literature. All bacteria scenarios also present higher precipitable ice concentrations compared to S5 scenario, the RAMS default. The main results present the total flash number per simulation as well. From the results, the total flash numbers, from both lightning frequencies, in S4 and S6 scenarios, are from 3.1 to 3.7 higher than the BRAMS default. Even the lower bacterial concentrations (scenarios S2 and S3) produced 3 time higher number of flashes, compared to S5 scenario. This result is a function of the hydrometeors in each simulation. In conclusion, IN bacteria could affect directly the thunderstorm structure and lightning formation with many other microphysical implications.

Small number concentrations render it difficult to quantify ice nucleators (IN) in the atmosphere active at warm temperatures. A useful new method for IN measurement based around filter collections is proposed. It makes use of quartz filters used in 24 h PM10 monitoring (720 m3 air sample). Small subsamples (1.8 mm diameter) from the effective filter area and from the clean fringe (blank) are subjected to immersion freezing tests. We applied the method to eight filters from the High Alpine Research Station Jungfraujoch (3580 m above sea level) in the Swiss Alps. All filters carried IN active at −7 °C and below. Number concentrations of IN active at −8, −10, and −12 °C were on average 3.3, 10.7, and 17.2 m−3, respectively. Several-fold larger numbers of IN active at ≥ −12 °C per unit mass of PM10 were found in air masses influenced by Swiss and southern German atmospheric boundary layer air, compared to a Saharan dust event. In combination with data on PM10 mass, the method may be used to re-construct time series of IN number concentrations.

Soil dust is a major driver of ice nucleation in clouds leading to precipitation. It consists largely of mineral particles with a small fraction of organic matter constituted mainly of remains of micro-organisms that participated in degrading plant debris before their own decay. Some micro-organisms have been shown to be much better ice nuclei than the most efficient soil mineral. Yet, current aerosol schemes in global climate models do not consider a difference between soil dust and mineral dust in terms of ice nucleation activity. Here, we show that particles from the clay and silt size fraction of four different soils naturally associated with 0.7 to 11.8 % organic carbon (w/w) can have up to four orders of magnitude more ice nucleation sites per unit mass active in the immersion freezing mode at −12 °C than montmorillonite, the nucleation properties of which are often used to represent those of mineral dusts in modelling studies. Most of this activity was lost after heat treatment. Removal of biological residues reduced ice nucleation activity to, or below that of montmorillonite. Desert soils, inherently low in organic content, are a large natural source of dust in the atmosphere. In contrast, agricultural land use is concentrated on fertile soils with much larger organic matter contents than found in deserts. It is currently estimated that the contribution of agricultural soils to the global dust burden is less than 20 %. Yet, these disturbed soils can contribute ice nuclei to the atmosphere of a very different and much more potent kind than mineral dusts.

For the past 200 years, the field of aerobiology has explored the abundance, diversity, survival and transport of micro-organisms in the atmosphere. Micro-organisms have been explored as passive and severely stressed riders of atmospheric transport systems. Recently, an interest in the active roles of these micro-organisms has emerged along with proposals that the atmosphere is a global biome for microbial metabolic activity and perhaps even multiplication. As part of a series of papers on the sources, distribution and roles in atmospheric processes of biological particles in the atmosphere, here we describe the pertinence of questions relating to the potential roles that air-borne micro-organisms might play in meteorological phenomena. For the upcoming era of research on the role of air-borne micro-organisms in meteorological phenomena, one important challenge is to go beyond descriptions of abundance of micro-organisms in the atmosphere toward an understanding of their dynamics in terms of both biological and physico-chemical properties and of the relevant transport processes at different scales. Another challenge is to develop this understanding under contexts pertinent to their potential role in processes related to atmospheric chemistry, the formation of clouds, precipitation and radiative forcing. This will require truly interdisciplinary approaches involving collaborators from the biological and physical sciences, from disciplines as disparate as agronomy, microbial genetics and atmosphere physics, for example.

A survey was conducted on the wetlands in the South African section of the Maloti-Drakensberg Transfrontier Park (MDTP), along altitudinal gradients from the foothills to the summit plateau in six different catchments. Environmental indices of soil wetness, texture and organic contents of the soil were determined to relate wetland community types to their environment. Thirty-six plant communities were recognized with a total of 56 subcommunities. These communities fall into five different categories: I, the high-altitude fens and seepages are a loose grouping of distinct vegetation types from the summit plateau and just below; 2, hygrophilous grasslands are the marginal areas of the wetlands that are temporarily wet and dominated by grasses, most of which are common outside wetlands; 3, shrubby wetlands are in most cases hygrophilous grasslands that have been invaded by shrubby species due to disturbance; 4, mixed sedgelands are the largest grouping and are dominated by sedges or grass species that are specifically adapted to wet conditions; 5, low-altitude sedge and reedlands are vegetation types that occur only marginally in the Maloti-Drakensberg area and are dominated by Carex acutiformis and Phragmites australis.The most important variables that explain the variation in wetland egetation are altitude and soil wetness.

An aerosol-cloud modeling framework is described to simulate the activation of ice particles and droplets by biological aerosol particles, such as airborne ice-nucleation active (INA) bacteria. It includes the empirical parameterisation of heterogeneous ice nucleation and a semi-prognostic aerosol component, which have been incorporated into a cloud-system resolving model (CSRM) with double-moment bulk microphysics. The formation of cloud liquid by soluble material coated on these partially insoluble organic aerosols is represented. It determines their partial removal from deep convective clouds by accretion onto precipitation in the cloud model. This "aerosol-cloud model" is validated for diverse cases of deep convection with contrasting aerosol conditions, against satellite, ground-based and aircraft observations. Simulations are performed with the aerosol-cloud model for a month-long period of summertime convective activity over Oklahoma. It includes three cases of continental deep convection simulated previously by Phillips and Donner (2006). Elevated concentrations of insoluble organic aerosol, boosted by a factor of 100 beyond their usual values for this continental region, are found to influence significantly the following quantities: (1) the average numbers and sizes of ice crystals and droplets in the clouds; (2) the horizontal cloud coverage in the free troposphere; (3) precipitation at the ground; and (4) incident solar insolation at the surface. This factor of 100 is plausible for natural fluctuations of the concentration of insoluble organic aerosol, in view of variability of cell concentrations for airborne bacteria seen by Lindemann et al. (1982). In nature, such boosting of the insoluble organic aerosol loading could arise from enhanced emissions of biological aerosol particles from a land surface. Surface wetness and solar insolation at the ground are meteorological quantities known to influence rates of growth of certain biological particles (e.g. bacteria). Their rates of emission into the atmosphere must depend on these same quantities, in addition to surface wind speed, turbulence and convection. Finally, the present study is the first attempt at evaluating the impacts from biological aerosols on mesoscale cloud ensembles in the literature.