Giardia is a genus of flagellated protozoans that parasitize the gastrointestinal tract of humans and wildlife worldwide. While G. duodenalis is well-studied due to its potential to cause outbreaks of diarrheal illness in humans, other Giardia species from wildlife have been largely understudied. This study examines the occurrence, host specificity, and genotypic diversity of Giardia in wild rodents living within the New York City water supply watershed. A novel nested PCR assay targeting the 18S ssu-rDNA gene is introduced, which captures nearly the entire gene for improved species-level determination versus existing molecular typing methods. Molecular characterization of 55 Giardia specimens reveals at least seven novel lineages. Phylogenetic analysis indicates a close relationship between the newly characterized Giardia lineages and rodent hosts, suggesting rodents as important reservoirs of Giardia and its close relatives. These findings provide insights into the diversity of Giardia species and their public health potential in localities with human-wildlife interaction and further emphasizes the need for continued efforts to improve the molecular tools used to study microbial eukaryotes, especially those with zoonotic potential. © 2024

Schistosomiasis, a highly prevalent parasitic disease, affects more than 200 million people worldwide. Current diagnostics based on parasite egg detection in stool detect infection only at a late stage, and current antibody-based tests cannot distinguish past from current infection. Here, we developed and used a multiplexed antibody profiling platform to obtain a comprehensive repertoire of antihelminth humoral profiles including isotype, subclass, Fc receptor (FcR) binding, and glycosylation profiles of antigen-specific antibodies. Using Essential Regression (ER) and SLIDE, interpretable machine learning methods, we identified latent factors (context-specific groups) that move beyond biomarkers and provide insights into the pathophysiology of different stages of schistosome infection. By comparing profiles of infected and healthy individuals, we identified modules with unique humoral signatures of active disease, including hallmark signatures of parasitic infection such as elevated immunoglobulin G4 (IgG4). However, we also captured previously uncharacterized humoral responses including elevated FcR binding and specific antibody glycoforms in patients with active infection, helping distinguish them from those without active infection but with equivalent antibody titers. This signature was validated in an independent cohort. Our approach also uncovered two distinct endotypes, nonpatent infection and prior infection, in those who were not actively infected. Higher amounts of IgG1 and FcR1/FcR3A binding were also found to be likely protective of the transition from nonpatent to active infection. Overall, we unveiled markers for antibody-based diagnostics and latent factors underlying the pathogenesis of schistosome infection. Our results suggest that selective antigen targeting could be useful in early detection, thus controlling infection severity.

Human cases of avian influenza virus (AIV) infections are associated with an age-specific disease burden. As the influenza virus N2 neuraminidase (NA) gene was introduced from avian sources during the 1957 pandemic, we investigate the reactivity of N2 antibodies against A(H9N2) AIVs. Serosurvey of healthy individuals reveal the highest rates of AIV N2 antibodies in individuals aged ≥65 years. Exposure to the 1968 pandemic N2, but not recent N2, protected against A(H9N2) AIV challenge in female mice. In some older adults, infection with contemporary A(H3N2) virus could recall cross-reactive AIV NA antibodies, showing discernable human- or avian-NA type reactivity. Individuals born before 1957 have higher anti-AIV N2 titers compared to those born between 1957 and 1968. The anti-AIV N2 antibodies titers correlate with antibody titers to the 1957 N2, suggesting that exposure to the A(H2N2) virus contribute to this reactivity. These findings underscore the critical role of neuraminidase immunity in zoonotic and pandemic influenza risk assessment.

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

BACKGROUND: The Ministry of Health in Côte d'Ivoire and the International Training and Education Center for Health at the University of Washington, funded by the United States President's Emergency Plan for AIDS Relief, have been collaborating to develop and implement the Open-Source Enterprise-Level Laboratory Information System (OpenELIS). The system is designed to improve HIV-related laboratory data management and strengthen quality management and capacity at clinical laboratories across the nation. OBJECTIVE: This evaluation aimed to quantify the effects of implementing OpenELIS on data quality for laboratory tests related to HIV care and treatment. METHODS: This evaluation used a quasi-experimental design to perform an interrupted time-series analysis to estimate the changes in the level and slope of 3 data quality indicators (timeliness, completeness, and validity) after OpenELIS implementation. We collected paper and electronic records on clusters of differentiation 4 (CD4) testing for 48 weeks before OpenELIS adoption until 72 weeks after. Data collection took place at 21 laboratories in 13 health regions that started using OpenELIS between 2014 and 2020. We analyzed the data at the laboratory level. We estimated odds ratios (ORs) by comparing the observed outcomes with modeled counterfactual ones when the laboratories did not adopt OpenELIS. RESULTS: There was an immediate 5-fold increase in timeliness (OR 5.27, 95% CI 4.33-6.41; P<.001) and an immediate 3.6-fold increase in completeness (OR 3.59, 95% CI 2.40-5.37; P<.001). These immediate improvements were observed starting after OpenELIS installation and then maintained until 72 weeks after OpenELIS adoption. The weekly improvement in the postimplementation trend of completeness was significant (OR 1.03, 95% CI 1.02-1.05; P<.001). The improvement in validity was not statistically significant (OR 1.34, 95% CI 0.69-2.60; P=.38), but validity did not fall below pre-OpenELIS levels. CONCLUSIONS: These results demonstrate the value of electronic laboratory information systems in improving laboratory data quality and supporting evidence-based decision-making in health care. These findings highlight the importance of OpenELIS in Côte d'Ivoire and the potential for adoption in other low- and middle-income countries with similar health systems.

Cryptosporidium ubiquitum is an emerging zoonotic pathogen. In the past, it was not possible to identify an association between cases of human and animal infection. We conducted a genomic survey of the species, developed a subtyping tool targeting the 60-kDa glycoprotein (gp60) gene, and identified 6 subtype families (XIIa-XIIf) of C. ubiquitum. Host adaptation was apparent at the gp60 locus; subtype XIIa was found in ruminants worldwide, subtype families XIIb-XIId were found in rodents in the United States, and XIIe and XIIf were found in rodents in the Slovak Republic. Humans in the United States were infected with isolates of subtypes XIIb-XIId, whereas those in other areas were infected primarily with subtype XIIa isolates. In addition, subtype families XIIb and XIId were detected in drinking source water in the United States. Contact with C. ubiquitum-infected sheep and drinking water contaminated by infected wildlife could be sources of human infections.

The use of molecular diagnostic tools in epidemiological investigations of Cryptosporidium, Giardia, and Enterocytozoon has provided new insights into their diversity and transmission pathways. In this study, 157 stool specimens from 2-month to 70-year-old patients were collected, a polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP) analysis of the small subunit (SSU) rRNA gene was used to detect and differentiate Cryptosporidium species, and DNA sequence analysis of the 60 kDa glycoprotein (gp60) gene was used to subtype Cryptosporidium hominis and Cryptosporidium parvum. Giardia duodenalis, and Enterocytozoon bieneusi in the specimens were detected using PCR and sequence analysis of the triosephosphate isomerase (tpi) gene and internal transcribed spacer (ITS), respectively. C. hominis and C. parvum were found in two (1.3%) and one (0.6%) specimen respectively, comprising of Ia and IIe (with 8 nucleotide substitutions) subtype families. The G. duodenalis A2 subtype was detected in five (3.2%) specimens, while four genotypes of E. bieneusi, namely A, type IV, D and WL7 were found in 10 (6.4%) specimens. Children aged two years or younger had the highest occurrence of Cryptosporidium (4.4%) and Enterocytozoon (13.0%) while children of 6 to 17 years had the highest Giardia infection rate (40.0%). No Cryptosporidium, Giardia, and Enterocytozoon were detected in patients older than 60 years. Enterocytozoon had high infection rates in both HIV-positive (3.3%) and HIV-negative (8.3%) patients. Results of the study suggest that anthroponotic transmission may be important in the transmission of Cryptosporidium spp. and G. duodenalis while zoonotic transmissions may also play a role in the transmission of E. bieneusi in humans in Kaduna State, Nigeria.

To infer population genetics of Enterocytozoon bieneusi in nonhuman primates (NHPs), 126 positive specimens in 839 fecal specimens from 23 NHP species in China based on ITS locus were used, belonging to genotypes Type IV, D, Peru8, Henan V, Peru11, PigEBITS7 and 3 novel ones (CM1, CM2 and CM3). Multilocus sequence typing employing four micro and minisatellites (MS1, MS3, MS4 and MS7) and ITS were used to analyze population structure of 85 isolates successfully amplified at all five loci, which yielded 59 multilocus genotypes. Linkage disequilibrium (LD) was measured using both multilocus sequences and allelic profile data. The observation of strong and significant LD with limited recombination in multilocus sequence analysis indicated the presence of overall clonal population structure of E. bieneusi, which was supported by allelic profile data analysis. Fu's selective neutrality test demonstrated the absence of neutral mutations and molecular selection. The population structure of common ITS genotypes (CM1, Type IV and D) was compared. Strong LD in multilocus sequence analysis versus insignificant LD and/or LE in allelic profile data analysis implied epidemic population in common ITS genotypes. No significant genetic isolation was evidenced by either phylogenetic or substructural analyses. The population genetics was also compared among the sub-population 1 (contained mainly genotype Type IV), sub-population 2 (contained mainly genotypes CM1 and D), sub-population 3 (contained mixed genotypes) and sub-population 4 (contained genotype Henan V). The presence of strong LD in multilocus data analysis with insignificant LD and/or LE in allele profile data analysis suggested the epidemic population in sub-populations.

BACKGROUND: Changes to policies at the federal, state, and local levels over the last decade have influenced the school nutrition environment and services. METHODS: This systematic review includes an analysis of individual research articles and government reports published from 2010 to 2021 that examine interventions to improve the school nutrition environment and services and increase the availability, selection, and consumption of healthier foods and beverages in K-12 schools in the United States. RESULTS: Nutrition standards for school meals and food outside of meals improved access to healthier options in school. Providing school nutrition professionals with professional development, improving the palatability of school meals, offering taste tests, pre-slicing fruit, providing recess before lunch, offering incentives for trying healthier options, and providing access to drinking water resulted in increased selection and consumption of healthier items. There were inconclusive or mixed findings for some intervention strategies including adequate seat time for meals. CONCLUSIONS: Despite demonstrated improvements to school meal programs and competitive foods, more work is needed to change the selection and consumption of healthier options among K-12 students. Schools can use multiple interventions to improve the school nutrition environment and services and help students adopt food and beverage choices that support health.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. In 2020, the COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized hundreds of thousands of specific predictions from more than 50 different academic, industry, and independent research groups. This manuscript systematically evaluates 23 models that regularly submitted forecasts of reported weekly incident COVID-19 mortality counts in the US at the state and national level. One of these models was a multi-model ensemble that combined all available forecasts each week. The performance of individual models showed high variability across time, geospatial units, and forecast horizons. Half of the models evaluated showed better accuracy than a naïve baseline model. In combining the forecasts from all teams, the ensemble showed the best overall probabilistic accuracy of any model. Forecast accuracy degraded as models made predictions farther into the future, with probabilistic accuracy at a 20-week horizon more than 5 times worse than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work.Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below. CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook. CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation. COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health. Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information&amp; Data Science Pilot Project. Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation. DDS-NBDS: NSF III-1812699. EPIFORECASTS-ENSEMBLE1: Wellcome Trust (210758/Z/18/Z) GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowments, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. &amp; Charlene Zalesky, and Claudia &amp; Paul Raines GT-DeepCOVID: CDC MInD-Healthcare U01CK000531-Supplement. NSF (Expeditions CCF-1918770, CAREER IIS-2028586, RAPID IIS-2027862, Medium IIS-1955883, NRT DGE-1545362), CDC MInD program, ORNL and funds/computing resources from Georgia Tech and GTRI. IHME: This work was supported by the Bill &amp; Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096). IowaStateLW-STEM: Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1916204, NSF CCF-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics. JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, US Office of Foreign Disaster Assistance, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers fo Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, &amp; Infectious Disease Initiative (26798 Seed Grant). LANL-GrowthRate: LANL LDRD 20200700ER. MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01. NotreDame-mobility and NotreDame-FRED: NSF RAPID DEB 2027718 UA-EpiCovDA: NSF RAPID Grant # 2028401. UCSB-ACTS: NSF RAPID IIS 2029626. UCSD-NEU: Google Faculty Award, DARPA W31P4Q-21-C-0014, COVID Supplement CDC-HHS-6U01IP001137-01. UMass-MechBayes: NIGMS R35GM119582, NSF 1749854. UMich-RidgeTfReg: The University of Michigan Physics Department and the University of Michigan Office of Research.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:UMass-Amherst IRBAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data and code referred to in the manuscript are publicly available. https://github.com/reichlab/covid19-forecast-hub/ https://github.com/reichlab/covidEnsembles https://zoltardata.com/project/44

Salmonella enterica serovar (Salmonella Typhi) is the causative bacterial agent of typhoid fever. Environmental surveillance of wastewater and wastewater-impacted surface waters has proven effective in monitoring various pathogens and has recently been applied to Salmonella Typhi. This study evaluated eight sample collection and concentration methods with 12 variations currently being developed and used for Salmonella Typhi surveillance globally to better understand the performance of each method based on its ability to detect Salmonella Typhi and its feasibility. Salmonella Typhi strains Ty21a and Ty2 were seeded to influent wastewater at known concentrations to evaluate the following methods: grab sampling using electropositive filters, centrifugation, direct enrichment, or membrane filtration and trap sampling using Moore swabs. Concentrated samples underwent nucleic acid extraction and were detected and/or quantified via quantitative polymerase chain reaction (qPCR). Results suggest that all methods tested can be successful at concentrating Salmonella Typhi for subsequent detection by qPCR, although each method has its own strengths and weaknesses, including the Salmonella Typhi concentration it is best suited for, with a range of positive detections observed as low as 0.1-0.001 colony-forming units (CFU) Ty21a/mL and 0.01 CFU Ty2/mL. These factors should be considered when identifying a method for environmental surveillance and will greatly depend on the use case planned.

Salmonella enterica serovar (Salmonella Typhi) is the causative bacterial agent of Typhoid fever. Environmental surveillance of wastewater and wastewater-impacted surface waters has proven effective in monitoring various pathogens, and has recently been applied to Salmonella Typhi. This study evaluated eight sample collection and concentration methods with twelve variations currently being developed and used for Salmonella Typhi surveillance globally to better understand the performance of each method based on their ability to detect Salmonella Typhi and feasibility. Salmonella Typhi strains, Ty21a and Ty2, were seeded to influent wastewater at known concentrations to evaluate the following methods: grab sampling using electropositive filters, centrifugation, direct enrichment, or membrane filtration and trap sampling using Moore swabs. Concentrated samples underwent nucleic acid extraction and were detected and/or quantified via qPCR. Results suggest that all methods tested can be successful at concentrating Salmonella Typhi for subsequent detection by qPCR, although each method has its own strengths and weaknesses including the Salmonella Typhi concentrations they are best suited for with a range of positive detections observed as low as 0.1-0.001 CFU Ty21a/mL and 0.01 CFU Ty2/mL. These factors should be considered when identifying a method for environmental surveillance and will greatly depend on the use case planned. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.

Cryptosporidium canis is a zoonotic species causing cryptosporidiosis in humans in addition to its natural hosts dogs and other fur animals. To understand the genetic basis for host adaptation, we sequenced the genomes of C. canis from dogs, minks, and foxes and conducted a comparative genomics analysis. While the genomes of C. canis have similar gene contents and organisations, they (~41.0 %) and C. felis (39.6 %) have GC content much higher than other Cryptosporidium spp. (24.3-32.9 %) sequenced to date. The high GC content is mostly restricted to subtelomeric regions of the eight chromosomes. Most of these GC-balanced genes encode Cryptosporidium-specific proteins that have intrinsically disordered regions and are involved in host-parasite interactions. Natural selection appears to play a more important role in the evolution of codon usage in GC-balanced C. canis, and most of the GC-balanced genes have undergone positive selection. While the identity in whole genome sequences between the mink- and dog-derived isolates is 99.9 % (9365 SNVs), it is only 96.0 % (362 894 SNVs) between them and the fox-derived isolate. In agreement with this, the fox-derived isolate possesses more subtelomeric genes encoding invasion-related protein families. Therefore, the change in subtelomeric GC content appears to be responsible for the more GC-balanced C. canis genomes, and the fox-derived isolate could represent a new Cryptosporidium species.

The measurement of uranium (U) isotope ratios in urine provides valuable information about the source of U exposure in humans and can be vitally important in a radiological emergency. This method provides rapid and accurate results for 235U/238U at 235U concentrations as low as 0.42 ng/L, which is equivalent to ~ 200 ng/L of total U for a depleted U (DU) at a 235U/238U ratio of ~ 0.002. The results are within 6% of Certified Reference Materials target values and agree with Department of Defense Armed Forces Institute of Pathology inter-laboratory comparison target values with a bias range of -6.9–7.6%. © 2022, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.

The parasite Cryptosporidium hominis is a leading cause of the diarrheal disease cryptosporidiosis, whose incidence in the United States has increased since 2005. Here, we show that the newly emerged and hyper-transmissible subtype IfA12G1R5 is now dominant in the United States. In a comparative analysis of 127 newly sequenced and 95 published C. hominis genomes, IfA12G1R5 isolates from the United States place into three of the 14 clusters (Pop6, Pop13, and Pop14), indicating that this subtype has multiple ancestral origins. Pop6 (IfA12G1R5a) has an East Africa origin and has recombined with autochthonous subtypes after its arrival. Pop13 (IfA12G1R5b) is imported from Europe, where it has recombined with the prevalent local subtype, whereas Pop14 (IfA12G1R5c) is a progeny of secondary recombination between Pop6 and Pop13. Selective sweeps in invasion-associated genes have accompanied the emergence of the dominant Pop14. These observations offer insights into the emergence and evolution of hyper-transmissible pathogens.

Determining actinides in urine is vital for occupational exposure monitoring and radiological emergency response because of the toxicity and radiological dose effects of actinides on human health. Traditional radiochemistry analytical methods used to determine actinide concentrations in urine are time-consuming (sample analysis takes several days) and are hindered by a variety of technical and instrumentation-related obstacles. A high-throughput, fully automated, precise, and accurate in-line method was developed for determining five actinides ((241)Am, (239)Pu, (237)Np, (232)Th, and (238)U) at ng/L levels in urine using extraction chromatography combined with quadrupole inductively coupled plasma mass spectrometry (EC-ICP-MS). In this method, the five actinides were successfully separated with the required sensitivity, peak shape, and resolution using a simplified single Eichrom TRU column with a Dionex ICS-5000 system. The separated actinides were subsequently injected into an in-line PerkinElmer (PE) NexION 300D ICP-MS for quantitative determination. The sample-to-sample run time was 23 min for automatic chemical separation and quantification using only 0.5 mL of urine. The limits of detection (LOD) obtained using this method were 0.015, 0.022, 0.039, 4.5, and 2.4 ng/L for (241)Am, (239)Pu, (237)Np, (232)Th, and (238)U, respectively. The method routinely had a chemical yield of >84% as well as a linearity (R(2)) coefficient of ≥0.999 for the calibrators. The method proved to be rapid, reliable, and effective for actinide quantification in urine and therefore is appropriate for radiological emergency response incidents.

OBJECTIVE: to conduct a systematic review of the observational studies analyzing the association between ultra-processed food (UPF) intake and the risk of depression. DESIGN: the search adhered to the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA); a search for observational studies published until June 2020 was performed in PubMed, Embase, Cochrane Library, and Web of Science databases, followed by additional manual searches. Eight reviewers, working independently in teams of two, screened studies for eligibility, extracted data, and assessed risk of bias. We resolved disagreements through discussion or, if necessary, through adjudication by a third (LH). And the study assessed cross-sectional studies using the Agency for Healthcare Research and Quality (AHRQ) methodological checklist and cohort and case-control studies using the Newcastle-Ottawa Scale (NOS) for quality. We used a tabular format to summarize the articles. RESULTS: twenty-eight studies evaluating UPF intake and risk of depression were finally selected, 21 of which had a cross-sectional design, 6 studies had a cohort design, and 1 had a case-control design. Of these, 4 cohort studies and 17 cross-sectional studies found that consumption of UPF were positively associated with depression or depressive symptoms. CONCLUSIONS: our review demonstrated that most studies included in the systematic review showed that UPF consumption is associated with the risk of depression. Future studies should consider the use of validated food intake assessments and standardized depression assessment methods to promote comparability between studies.

Inductively coupled plasma mass spectrometry (ICP-MS) has proven to be an excellent analytical technique with high sensitivity for detecting low levels of long-lived radionuclides, such as thorium. However, the high-sensitivity technique increases the memory effect of thorium. This study developed a rapid, high-throughput, simple method for measuring thorium in urine using quadrupole inductively coupled plasma mass spectrometry (Q-ICP-MS). Replacing the commonly used hazardous hydrofluoric acid with a rinse solution of 0.025 mol/L oxalic acid and 5% (v/v) nitric acid eliminated the memory effect of thorium. 233U was used as internal standard in this study. The limit of detection (LOD) for thorium in this study is 0.77 ng/L, which is comparable to those of reported methods using more sophisticated and expensive sector field inductively coupled plasma mass spectrometry (SF-ICP-MS). This proposed method can determine thorium concentrations in urine in both occupationally exposed workers and populations that live in areas with high background levels of thorium. © 2022, Akadémiai Kiadó, Budapest, Hungary.

Genetic recombination plays a critical role in the emergence of pathogens with phenotypes such as drug resistance, virulence, and host adaptation. Here, we tested the hypothesis that recombination between sympatric ancestral populations leads to the emergence of divergent variants of the zoonotic parasite Cryptosporidium parvum with modified host ranges. Comparative genomic analyses of 101 isolates have identified seven subpopulations isolated by distance. They appear to be descendants of two ancestral populations, IIa in northwestern Europe and IId from southwestern Asia. Sympatric recombination in areas with both ancestral subtypes and subsequent selective sweeps have led to the emergence of new subpopulations with mosaic genomes and modified host preference. Subtelomeric genes could be involved in the adaptive selection of subpopulations, while copy number variations of genes encoding invasion-associated proteins are potentially associated with modified host ranges. These observations reveal ancestral origins of zoonotic C. parvum and suggest that pathogen import through modern animal farming might promote the emergence of divergent subpopulations of C. parvum with modified host preference.

Enterocytozoon bieneusi is the most common microsporidia in humans worldwide, in addition to infecting a wide range of animals. However, there is limited information about this pathogen in children in Egypt. Here, we carried out a molecular epidemiological study of E. bieneusi in child care centers in three provinces in Egypt. Altogether, 585 fresh fecal samples were collected from children attending 18 child care centers in El-Dakahlia, El-Gharbia, and Damietta provinces in Northeast Egypt during March 2015 to April 2016. PCR and sequence analyses of the ribosomal internal transcribed spacer (ITS) were used to detect and genotype E. bieneusi. Twenty-seven fecal samples (4.6%, 27/585) were positive for E. bieneusi. Five genotypes were identified, including type IV (n = 13), Peru8 (n = 9), Peru6 (n = 2), Peru11 (n = 2), and D (n = 1). Phylogenetic analysis indicated that the five genotypes of E. bieneusi detected in this study were clustered into zoonotic group 1. These data provide important information on the prevalence and genetic diversity of E. bieneusi in children in this country. Further epidemiological studies should be conducted to elucidate the role of zoonotic transmission in human E. bieneusi infections.

SignificanceThis paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the United States. Results show high variation in accuracy between and within stand-alone models and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public-health action.

Background: Molecular diagnostics are considered the most promising route to achievement of rapid, universal drug susceptibility testing for Mycobacterium tuberculosis complex (MTBC). We aimed to generate a WHO-endorsed catalogue of mutations to serve as a global standard for interpreting molecular information for drug resistance prediction. Methods: In this systematic analysis, we used a candidate gene approach to identify mutations associated with resistance or consistent with susceptibility for 13 WHO-endorsed antituberculosis drugs. We collected existing worldwide MTBC whole-genome sequencing data and phenotypic data from academic groups and consortia, reference laboratories, public health organisations, and published literature. We categorised phenotypes as follows: methods and critical concentrations currently endorsed by WHO (category 1); critical concentrations previously endorsed by WHO for those methods (category 2); methods or critical concentrations not currently endorsed by WHO (category 3). For each mutation, we used a contingency table of binary phenotypes and presence or absence of the mutation to compute positive predictive value, and we used Fisher's exact tests to generate odds ratios and Benjamini-Hochberg corrected p values. Mutations were graded as associated with resistance if present in at least five isolates, if the odds ratio was more than 1 with a statistically significant corrected p value, and if the lower bound of the 95% CI on the positive predictive value for phenotypic resistance was greater than 25%. A series of expert rules were applied for final confidence grading of each mutation. Findings: We analysed 41 137 MTBC isolates with phenotypic and whole-genome sequencing data from 45 countries. 38 215 MTBC isolates passed quality control steps and were included in the final analysis. 15 667 associations were computed for 13 211 unique mutations linked to one or more drugs. 1149 (73%) of 15 667 mutations were classified as associated with phenotypic resistance and 107 (07%) were deemed consistent with susceptibility. For rifampicin, isoniazid, ethambutol, fluoroquinolones, and streptomycin, the mutations' pooled sensitivity was more than 80%. Specificity was over 95% for all drugs except ethionamide (914%), moxifloxacin (916%) and ethambutol (933%). Only two resistance mutations were identified for bedaquiline, delamanid, clofazimine, and linezolid as prevalence of phenotypic resistance was low for these drugs. Interpretation: We present the first WHO-endorsed catalogue of molecular targets for MTBC drug susceptibility testing, which is intended to provide a global standard for resistance interpretation. The existence of this catalogue should encourage the implementation of molecular diagnostics by national tuberculosis programmes. Funding: Unitaid, Wellcome Trust, UK Medical Research Council, and Bill and Melinda Gates Foundation. 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

Cryptosporidium spp. are important enteric pathogens in a wide range of vertebrates including humans. Previous comparative analysis revealed conservation in genome composition, gene content, and gene organization among Cryptosporidium spp., with a progressive reductive evolution in metabolic pathways and invasion-related proteins. In this study, we sequenced the genome of zoonotic pathogen Cryptosporidium felis and conducted a comparative genomic analysis. While most intestinal Cryptosporidium species have similar genomic characteristics and almost complete genome synteny, fewer protein-coding genes and some sequence inversions and translocations were found in the C. felis genome. The C. felis genome exhibits much higher GC content (39.6 %) than other Cryptosporidium species (24.3-32.9 %), especially at the third codon position (GC3) of protein-coding genes. Thus, C. felis has a different codon usage, which increases the use of less energy costly amino acids (Gly and Ala) encoded by GC-rich codons. While the tRNA usage is conserved among Cryptosporidium species, consistent with its higher GC content, C. felis uses a unique tRNA for GTG for valine instead of GTA in other Cryptosporidium species. Both mutational pressures and natural selection are associated with the evolution of the codon usage in Cryptosporidium spp., while natural selection seems to drive the codon usage in C. felis. Other unique features of the C. felis genome include the loss of the entire traditional and alternative electron transport systems and several invasion-related proteins. Thus, the preference for the use of some less energy costly amino acids in C. felis may lead to a more harmonious parasite-host interaction, and the strengthened host-adaptation is reflected by the further reductive evolution of metabolism and host invasion-related proteins.

Rabbits are increasingly farmed in Egypt for meat. They are, however, known reservoirs of infectious pathogens. Currently, no information is available on the genetic characteristics of Cryptosporidium spp. in rabbits in Egypt. To understand the prevalence and genetic identity of Cryptosporidium spp. in these animals, 235 fecal samples were collected from rabbits of different ages on nine farms in El-Dakahlia, El-Gharbia, and Damietta Provinces, Egypt during the period from July 2015 to April 2016. PCR-RFLP analysis of the small subunit rRNA gene was used to detect and genotype Cryptosporidium spp. The overall detection rate was 11.9% (28/235). All 28 samples were identified as Cryptosporidium cuniculus. The 16 samples successfully subtyped by the sequence analysis of the partial 60 kDa glycoprotein gene belonged to two subtypes, VbA19 (n = 1) and VbA33 (n = 15). As C. cuniculus is increasingly recognized as a cause of human cryptosporidiosis, Cryptosporidium spp. in rabbits from Egypt have zoonotic potential.

Noroviruses are a leading cause of acute gastroenteritis (AGE) among adults and children worldwide. NoroSurv is a global network for norovirus strain surveillance among children <5 years of age with AGE. Participants in 16 countries across 6 continents used standardized protocols for dual typing (genotype and polymerase type) and uploaded 1,325 dual-typed sequences to the NoroSurv web portal during 2016-2020. More than 50% of submitted sequences were GII.4 Sydney[P16] or GII.4 Sydney[P31] strains. Other common strains included GII.2[P16], GII.3[P12], GII.6[P7], and GI.3[P3] viruses. In total, 22 genotypes and 36 dual types, including GII.3 and GII.20 viruses with rarely reported polymerase types, were detected, reflecting high strain diversity. Surveillance data captured in NoroSurv enables the monitoring of trends in norovirus strains associated childhood AGE throughout the world on a near real-time basis.

BACKGROUND: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals. OBJECTIVES: The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different end points: Lethal Dose 50 (LD50 value, U.S. Environmental Protection Agency hazard (four) categories, Globally Harmonized System for Classification and Labeling hazard (five) categories, very toxic chemicals [LD50 (LD50 ≤ 50 mg/kg)], and nontoxic chemicals (LD50 > 2,000 mg/kg). METHODS: An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. RESULTS: The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared with in vivo results. DISCUSSION: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for more than 800,000 chemicals have been made available via the National Toxicology Program's Integrated Chemical Environment tools and data sets (ice.ntp.niehs.nih.gov). The models are also implemented in a free, standalone, open-source tool, OPERA, which allows predictions of new and untested chemicals to be made. https://doi.org/10.1289/EHP8495.

Octomitus is a diplomonad genus known to inhabit the intestinal tracts of rodents. Ultrastructural morphology and 18S rDNA gene sequence analysis support the placement of Octomitus as the closest sister lineage to Giardia, a parasite which causes diarrheal disease in humans and animals worldwide. However, further information on the ecology and diversity of Octomitus is currently scarce. Expanding the available database of characterized sequences for this organism would therefore be helpful to studies of Diplomonad ecology, evolution, and epidemiology, particularly related to the evolution of parasitism in Giardia and Spironucleus, another related Diplomonad common in commercial fish farming. In order to study the prevalence and genotypic diversity of Octomitus, we developed a nested PCR assay specific to Octomitus and optimized to detect genotypes in fecal samples collected from wildlife in a New York watershed, and sequenced a portion of the small subunit ribosomal DNA (18S rDNA) gene to identify samples to species level. Molecular evidence suggested that Octomitus genotypes display similar prevalence to Cryptosporidium and microsporidian pathogens in wildlife as well as strong host preference for rodent and opossum hosts. Phylogenetic analysis showed strong support for 14 Octomitus genotypes, 13 of these novel, and patterns of host-parasite co-evolution. © 2021

Here we report a new procedure to determine 239Pu in urine using a custom-made automated pre-analytical processing system (single probe) with 242Pu as a tracer followed by analysis by SF-ICP-MS. An average 242Pu recovery rate of 88% was obtained with CF-ThU-1000 columns reused &gt; 100 times. Analytical results agree with measurements obtained using the CDC manual method with a R2 of 0.9994. Results for Oak Ridge National Laboratory reference materials align with target values with a bias range of − 3.44 to 3.05%. The limit of detection for this method is 0.63 pg/L, which is comparable to previous manual methods.

We developed an inductively coupled plasma mass spectrometry (ICP-MS) method using Universal Cell Technology (UCT) with a PerkinElmer NexION ICP-MS, to measure arsenic (As), chromium (Cr), and nickel (Ni) in human urine samples. The advancements of the UCT allowed us to expand the calibration range to make the method applicable for both low concentrations of biomonitoring applications and high concentrations that may be observed from acute exposures and emergency response. Our method analyzes As and Ni in kinetic energy discrimination (KED) mode with helium (He) gas, and Cr in dynamic reaction cell (DRC) mode with ammonia (NH(3)) gas. The combination of these elements is challenging because a carbon source, ethanol (EtOH), is required for normalization of As ionization in urine samples, which creates a spectral overlap ((40)Ar(12)C(+)) on (52)Cr. This method additionally improved lab efficiency by combining elements from two of our previously published methods(Jarrett et al., 2007; Quarles et al., 2014) allowing us to measure Cr and Ni concentrations in urine samples collected as part of the National Health and Nutrition Examination Survey (NHANES) beginning with the 2017-2018 survey cycle. We present our rigorous validation of the method selectivity and accuracy using National Institute of Standards and Technology (NIST) Standard Reference Materials (SRM), precision using in-house prepared quality control materials, and a discussion of the use of a modified UCT, a BioUCell, to address an ion transmission phenomenon we observed on the NexION 300 platform when using higher elemental concentrations and high cell gas pressures. The rugged method detection limits, calculated from measurements in more than 60 runs, for As, Cr, and Ni are 0.23 μg L-1, 0.19 μg L-1, and 0.31 μg L-1, respectively.

Molecular characterizations of the microsporidian pathogen Enterocytozoon bieneusi at the ribosomal internal transcribed spacer (ITS) locus have identified nearly 500 genotypes in 11 phylogenetic groups with different host ranges. Among those, one unique group of genotypes, Group 11, is commonly found in dogs. Genetic characterizations of those and many divergent E. bieneusi genotypes at other genetic loci are thus far impossible. In this study, we sequenced 151 E. bieneusi isolates from several ITS genotype groups at the 16S rRNA locus and two new semi-conservative genetic markers (casein kinase 1 (ck1) and spore wall protein 1 (swp1)). Comparison of the near full (~1,200 bp) 16S rRNA sequences showed mostly two to three nucleotide substitutions between Group 1 and Group 2 genotypes, while Group 11 isolates differed from those by 26 (2.2%) nucleotides. Sequence analyses of the ck1 and swp1 loci confirmed the genetic uniqueness of Group 11 genotypes, which produced sequences very divergent from other groups. In contrast, genotypes in Groups 1 and 2 produced similar nucleotide sequences at these genetic loci, and there was discordant placement of ITS genotypes among loci in phylogenetic analyses of sequences. These results suggest that the canine-adapted Group 11 genotypes are genetically divergent from other genotype groups of E. bieneusi, possibly representing a different Enterocytozoon sp. They also indicate that there is no clear genetic differentiation of ITS Groups 1 and 2 at other genetic loci, supporting the conclusion on the lack of strict host specificity in both groups. Data and genetic markers from the study should facilitate population genetic characterizations of E. bieneusi isolates and improve our understanding of the zoonotic potential of E. bieneusi in domestic animals.