One Health Priorities: Advancing Veterinary Public Health in Latin America and the Caribbean.

One Health (OH) is an integrative approach to human, animal, and environmental health and can be used as a comprehensive indicator for comparative purposes. Although an OH index has been proposed for comparing cities, states, and countries, to date, no practical study has compared countries using this approach. Accordingly, this study aimed to assess OH initiatives using a survey with a veterinary public health focus. The questionnaire contained 104 quantitative questions and was sent to representatives of governmental institutions of 32 countries in the Americas. After exclusion criteria were considered, a total of 35 questionnaires from 17 countries were analyzed, with country names remaining undisclosed during the statistical analyses to protect potentially sensitive information. Principal component analysis (PCA) of health parameters in Latin America and the Caribbean (LAC) as a function of country perception (self-vector) showed that food safety was ranked higher than public policies (p = 0.009), and that both (p = 0.003) were ranked higher than institutional routines related to zoonosis programs. National policies in accordance with international standards, regulations, recommendations, and guidelines was considered the standout topic for public policy, with higher-ranking topics including standard. Meanwhile, challenging topics included tools, preparedness, governance, and research. Food safety showed both strengths and challenges in the coordination of its activities with other sectors. Food safety communication was scored as a strength, while foodborne diseases prevention was ranked as a challenge. Institutional routines for zoonosis maintained both strong and challenging topics in the execution and implementation of attributions and daily routine. Thus, the survey showed that topics such as access to and compliance with international guidelines and intercountry integration were ranked higher than in-country articulation, particularly among food safety, zoonoses, and environmental institutions.

Rare genetic cerebrotendinous xanthomatosis (CTX) cases without cholestanol elevation but with prominent cholesterol-rich tendon xanthomas.

Cerebrotendinous xanthomatosis (CTX) is a rare inherited metabolic disease attributed to the mutation of the gene CYP27A1, resulting in sterol 27-hydroxylase deficiency characterized by deposition of cholestanol and cholesterol in several tissues, like the central nervous system and tendons. Furthermore, cataracts, gallstones, diarrhea and premature atherosclerosis have been reported. Nonetheless, clinical development is extremely heterogeneous in CTX. We report here two cases of CTX genetic alteration in the absence of cholestanol elevation in plasma and tendons but with prominent xanthomas. We propose that CTX may not be characteized by increased plasma cholestanol concentration due to alteration in the sterol 27-hydroxylase gene, but is a more complex pathology where there is significant genetic heterogeneity caused by various CYP27A1 mutations.

Evidence of a causal and modifiable relationship between kidney function and circulating trimethylamine N-oxide.

The host-microbiota co-metabolite trimethylamine N-oxide (TMAO) is linked to increased cardiovascular risk but how its circulating levels are regulated remains unclear. We applied "explainable" machine learning, univariate, multivariate and mediation analyses of fasting plasma TMAO concentration and a multitude of phenotypes in 1,741 adult Europeans of the MetaCardis study. Here we show that next to age, kidney function is the primary variable predicting circulating TMAO, with microbiota composition and diet playing minor, albeit significant, roles. Mediation analysis suggests a causal relationship between TMAO and kidney function that we corroborate in preclinical models where TMAO exposure increases kidney scarring. Consistent with our findings, patients receiving glucose-lowering drugs with reno-protective properties have significantly lower circulating TMAO when compared to propensity-score matched control individuals. Our analyses uncover a bidirectional relationship between kidney function and TMAO that can potentially be modified by reno-protective anti-diabetic drugs and suggest a clinically actionable intervention for decreasing TMAO-associated excess cardiovascular risk.

Consistency across multi-omics layers in a drug-perturbed gut microbial community.

Multi-omics analyses are used in microbiome studies to understand molecular changes in microbial communities exposed to different conditions. However, it is not always clear how much each omics data type contributes to our understanding and whether they are concordant with each other. Here, we map the molecular response of a synthetic community of 32 human gut bacteria to three non-antibiotic drugs by using five omics layers (16S rRNA gene profiling, metagenomics, metatranscriptomics, metaproteomics and metabolomics). We find that all the omics methods with species resolution are highly consistent in estimating relative species abundances. Furthermore, different omics methods complement each other for capturing functional changes. For example, while nearly all the omics data types captured that the antipsychotic drug chlorpromazine selectively inhibits Bacteroidota representatives in the community, the metatranscriptome and metaproteome suggested that the drug induces stress responses related to protein quality control. Metabolomics revealed a decrease in oligosaccharide uptake, likely caused by Bacteroidota depletion. Our study highlights how multi-omics datasets can be utilized to reveal complex molecular responses to external perturbations in microbial communities.

A faecal microbiota signature with high specificity for pancreatic cancer.

BACKGROUND: Recent evidence suggests a role for the microbiome in pancreatic ductal adenocarcinoma (PDAC) aetiology and progression. OBJECTIVE: To explore the faecal and salivary microbiota as potential diagnostic biomarkers. METHODS: We applied shotgun metagenomic and 16S rRNA amplicon sequencing to samples from a Spanish case-control study (n=136), including 57 cases, 50 controls, and 29 patients with chronic pancreatitis in the discovery phase, and from a German case-control study (n=76), in the validation phase. RESULTS: Faecal metagenomic classifiers performed much better than saliva-based classifiers and identified patients with PDAC with an accuracy of up to 0.84 area under the receiver operating characteristic curve (AUROC) based on a set of 27 microbial species, with consistent accuracy across early and late disease stages. Performance further improved to up to 0.94 AUROC when we combined our microbiome-based predictions with serum levels of carbohydrate antigen (CA) 19-9, the only current non-invasive, Food and Drug Administration approved, low specificity PDAC diagnostic biomarker. Furthermore, a microbiota-based classification model confined to PDAC-enriched species was highly disease-specific when validated against 25 publicly available metagenomic study populations for various health conditions (n=5792). Both microbiome-based models had a high prediction accuracy on a German validation population (n=76). Several faecal PDAC marker species were detectable in pancreatic tumour and non-tumour tissue using 16S rRNA sequencing and fluorescence in situ hybridisation. CONCLUSION: Taken together, our results indicate that non-invasive, robust and specific faecal microbiota-based screening for the early detection of PDAC is feasible.

A novel CD34-specific T-cell engager efficiently depletes acute myeloid leukemia and leukemic stem cells in vitro and in vivo.

Less than a third of patients with acute myeloid leukemia (AML) are cured by chemotherapy and/or hematopoietic stem cell transplantation, highlighting the need to develop more efficient drugs. The low efficacy of standard treatments is associated with inadequate depletion of CD34+ blasts and leukemic stem cells, the latter a drug-resistant subpopulation of leukemia cells characterized by the CD34+CD38- phenotype. To target these drug-resistant primitive leukemic cells better, we have designed a CD34/CD3 bi-specific T-cell engager (BTE) and characterized its anti-leukemia potential in vitro, ex vivo and in vivo. Our results show that this CD34-specific BTE induces CD34-dependent T-cell activation and subsequent leukemia cell killing in a dose-dependent manner, further corroborated by enhanced T-cell-mediated killing at the singlecell level. Additionally, the BTE triggered efficient T-cell-mediated depletion of CD34+ hematopoietic stem cells from peripheral blood stem cell grafts and CD34+ blasts from AML patients. Using a humanized AML xenograft model, we confirmed that the CD34-specific BTE had in vivo efficacy by depleting CD34+ blasts and leukemic stem cells without side effects. Taken together, these data demonstrate that the CD34-specific BTE has robust antitumor effects, supporting development of a novel treatment modality with the aim of improving outcomes of patients with AML and myelodysplastic syndromes.

Microbiome and metabolome features of the cardiometabolic disease spectrum.

Previous microbiome and metabolome analyses exploring non-communicable diseases have paid scant attention to major confounders of study outcomes, such as common, pre-morbid and co-morbid conditions, or polypharmacy. Here, in the context of ischemic heart disease (IHD), we used a study design that recapitulates disease initiation, escalation and response to treatment over time, mirroring a longitudinal study that would otherwise be difficult to perform given the protracted nature of IHD pathogenesis. We recruited 1,241 middle-aged Europeans, including healthy individuals, individuals with dysmetabolic morbidities (obesity and type 2 diabetes) but lacking overt IHD diagnosis and individuals with IHD at three distinct clinical stages-acute coronary syndrome, chronic IHD and IHD with heart failure-and characterized their phenome, gut metagenome and serum and urine metabolome. We found that about 75% of microbiome and metabolome features that distinguish individuals with IHD from healthy individuals after adjustment for effects of medication and lifestyle are present in individuals exhibiting dysmetabolism, suggesting that major alterations of the gut microbiome and metabolome might begin long before clinical onset of IHD. We further categorized microbiome and metabolome signatures related to prodromal dysmetabolism, specific to IHD in general or to each of its three subtypes or related to escalation or de-escalation of IHD. Discriminant analysis based on specific IHD microbiome and metabolome features could better differentiate individuals with IHD from healthy individuals or metabolically matched individuals as compared to the conventional risk markers, pointing to a pathophysiological relevance of these features.

Trends, Limits, and Challenges of Computer Technologies in Attention Deficit Hyperactivity Disorder Diagnosis and Treatment.

Attention deficit hyperactivity disorder (ADHD) is a neurobiological condition that appears during an individual's childhood and may follow her/him for life. The research objective was to understand better how and which computer technologies have been applied to support ADHD diagnosis and treatment. The research used the systematic literature review method: a rigorous, verifiable, and repeatable approach that follows well-defined steps. Six well-known academic data sources have been consulted, including search engines and bibliographic databases, from technology and health care areas. After a rigorous research protocol, 1,239 articles were analyzed. For the diagnosis, the use of machine learning techniques was verified in 61 percent of the articles. Neurofeedback was ranked second with 9.3 percent participation, followed by serious games and eye tracking with 5.6 percent each. For the treatment, neurofeedback was present in 50 percent of the articles, whereas some studies combined both approaches, accounting for 31 percent of the total. Nine percent of the articles reported remote assistance technology, whereas another 9 percent have used virtual reality. By highlighting the leading computer technologies used, their applications, results, and challenges, this literature review breaks ground for further investigations. Moreover, the study highlighted the lack of consensus on ADHD biomarkers. The approaches using machine learning call attention to the probable occurrence of overfitting in several studies, thus demonstrating limitations of this technology on small-sized bases. This research also presented the convergence of evidence from different studies on the persistence of long-term effects of using neurofeedback in treating ADHD.

Towards the biogeography of prokaryotic genes.

Microbial genes encode the majority of the functional repertoire of life on earth. However, despite increasing efforts in metagenomic sequencing of various habitats1-3, little is known about the distribution of genes across the global biosphere, with implications for human and planetary health. Here we constructed a non-redundant gene catalogue of 303 million species-level genes (clustered at 95% nucleotide identity) from 13,174 publicly available metagenomes across 14 major habitats and use it to show that most genes are specific to a single habitat. The small fraction of genes found in multiple habitats is enriched in antibiotic-resistance genes and markers for mobile genetic elements. By further clustering these species-level genes into 32 million protein families, we observed that a small fraction of these families contain the majority of the genes (0.6% of families account for 50% of the genes). The majority of species-level genes and protein families are rare. Furthermore, species-level genes, and in particular the rare ones, show low rates of positive (adaptive) selection, supporting a model in which most genetic variability observed within each protein family is neutral or nearly neutral.

metaSNV v2: detection of SNVs and subspecies in prokaryotic metagenomes.

SUMMARY: Taxonomic analysis of microbial communities is well supported at the level of species and strains. However, species can contain significant phenotypic diversity and strains are rarely widely shared across global populations. Stratifying the diversity between species and strains can identify 'subspecies', which are a useful intermediary. High-throughput identification and profiling of subspecies is not yet supported in the microbiome field. Here, we use an operational definition of subspecies based on single nucleotide variant (SNV) patterns within species to identify and profile subspecies in metagenomes, along with their distinctive SNVs and genes. We incorporate this method into metaSNV v2, which extends existing SNV-calling software to support further SNV interpretation for population genetics. These new features support microbiome analyses to link SNV profiles with host phenotype or environment and niche-specificity. We demonstrate subspecies identification in marine and fecal metagenomes. In the latter, we analyze 70 species in 7524 adult and infant subjects, supporting a common subspecies population structure in the human gut microbiome and illustrating some limits in subspecies calling. AVAILABILITY AND IMPLEMENTATION: Source code, documentation, tutorials and test data are available at https://github.com/metasnv-tool/metaSNV and https://metasnv.embl.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Gestão em foco / Management in focus

Este e-book tem como objetivo trazer um compêndio de relatos de experiência relacionados à gestão de saúde do Estado de Goiás. Cada capítulo traz a descrição dos projetos desenvolvidos no âmbito da Secretaria de Estado da Saúde de Goiás, que são vinculados aos objetivos estratégicos do órgão. Estes projetos têm como objetivo fortalecer as ações estratégicas para otimizar o planejamento do Sistema Único de Saúde

This e-book aims to bring a compendium of experience reports related to health management in the State of Goiás. Each chapter brings a description of the projects developed within the scope of the State Department of Health of Goiás, which are linked to the strategic objectives of the agency. These projects aim to strengthen strategic actions to optimize the planning of the Unified Health System

Combinatorial, additive and dose-dependent drug-microbiome associations.

During the transition from a healthy state to cardiometabolic disease, patients become heavily medicated, which leads to an increasingly aberrant gut microbiome and serum metabolome, and complicates biomarker discovery1-5. Here, through integrated multi-omics analyses of 2,173 European residents from the MetaCardis cohort, we show that the explanatory power of drugs for the variability in both host and gut microbiome features exceeds that of disease. We quantify inferred effects of single medications, their combinations as well as additive effects, and show that the latter shift the metabolome and microbiome towards a healthier state, exemplified in synergistic reduction in serum atherogenic lipoproteins by statins combined with aspirin, or enrichment of intestinal Roseburia by diuretic agents combined with beta-blockers. Several antibiotics exhibit a quantitative relationship between the number of courses prescribed and progression towards a microbiome state that is associated with the severity of cardiometabolic disease. We also report a relationship between cardiometabolic drug dosage, improvement in clinical markers and microbiome composition, supporting direct drug effects. Taken together, our computational framework and resulting resources enable the disentanglement of the effects of drugs and disease on host and microbiome features in multimedicated individuals. Furthermore, the robust signatures identified using our framework provide new hypotheses for drug-host-microbiome interactions in cardiometabolic disease.