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BackgroundWastewater surveillance has become an important public health tool with numerous research studies indicating its potential for monitoring coronavirus disease 2019 (COVID-19) outbreaks. The aim of this study was to apply wastewater surveillance as an indicator for COVID-19 to monitor the impact of a mass sporting event in the City of Cape Town. The study compared the same event over 2 years (2022 and 2023).MethodsWeekly grab wastewater samples were collected from wastewater treatment plants in the City of Cape Town, and quantitative reverse transcription-polymerase chain reaction used to quantify severe acute respiratory syndrome 2 (SARS-CoV-2) RNA in wastewater.ResultsOur findings show a statistically significant correlation (rho = 0.68, p = 0.01) between clinical cases and concentrations of SARS-CoV-2 RNA in wastewater in the 2022 study period. During this specific period, a rise in clinical cases was observed 2 weeks after the event and the peaks in clinical cases coincided with the peaks in SARS-CoV-2 RNA level in wastewater. The study also found a statistically significant positive correlation (R2 = 0.03, F (1,208) = 6.56, p = 0.01) between the SARS-CoV-2 RNA in wastewater and the 2022 event of the marathon hosted in the city.ConclusionDue to the decrease in clinical testing and the country being a popular destination for mass gatherings such as sporting events, the results from this study indicate the potential of wastewater surveillance providing supplementary information to form part of public health risk evaluations for mass gatherings.

ABSTRACT A key challenge in the analysis of microbiome data is the integration of multi-omic datasets and the discovery of interactions between microbial taxa, their expressed genes, and the metabolites they consume and/or produce. In an effort to improve the state of the art in inferring biologically meaningful multi-omic interactions, we sought to address some of the most fundamental issues in causal inference from longitudinal multi-omics microbiome data sets. We developed METALICA, a suite of tools and techniques that can infer interactions between microbiome entities. METALICA introduces novel unrolling and de-confounding techniques used to uncover multi-omic entities that are believed to act as confounders for some of the relationships that may be inferred using standard causal inferencing tools. The results lend support to predictions about biological models and processes by which microbial taxa interact with each other in a microbiome. The unrolling process helps identify putative intermediaries (genes and/or metabolites) to explain the interactions between microbes; the de-confounding process identifies putative common causes that may lead to spurious relationships to be inferred. METALICA was applied to the networks inferred by existing causal discovery, and network inference algorithms were applied to a multi-omics data set resulting from a longitudinal study of IBD microbiomes. The most significant unrollings and de-confoundings were manually validated using the existing literature and databases.IMPORTANCEWe have developed a suite of tools and techniques capable of inferring interactions between microbiome entities. METALICA introduces novel techniques called unrolling and de-confounding that are employed to uncover multi-omic entities considered to be confounders for some of the relationships that may be inferred using standard causal inferencing tools. To evaluate our method, we conducted tests on the inflammatory bowel disease (IBD) dataset from the iHMP longitudinal study, which we pre-processed in accordance with our previous work. From this dataset, we generated various subsets, encompassing different combinations of metagenomics, metabolomics, and metatranscriptomics datasets. Using these multi-omics datasets, we demonstrate how the unrolling process aids in the identification of putative intermediaries (genes and/or metabolites) to explain the interactions between microbes. Additionally, the de-confounding process identifies potential common causes that may give rise to spurious relationships to be inferred. The most significant unrollings and de-confoundings were manually validated using the existing literature and databases.

The pathophysiology of Gulf War Illness (GWI) remains elusive even after three decades. The persistence of multiple complex symptoms along with metabolic disorders such as obesity worsens the health of present Gulf War (GW) Veterans often by the interactions of the host gut microbiome and inflammatory mediators. In this study, we hypothesized that the administration of a Western diet might alter the host metabolomic profile, which is likely associated with the altered bacterial species. Using a five-month symptom persistence GWI model in mice and whole-genome sequencing, we characterized the species-level dysbiosis and global metabolomics, along with heterogenous co-occurrence network analysis, to study the bacteriome-metabolomic association. Microbial analysis at the species level showed a significant alteration of beneficial bacterial species. The beta diversity of the global metabolomic profile showed distinct clustering due to the Western diet, along with the alteration of metabolites associated with lipid, amino acid, nucleotide, vitamin, and xenobiotic metabolism pathways. Network analysis showed novel associations of gut bacterial species with metabolites and biochemical pathways that could be used as biomarkers or therapeutic targets to ameliorate symptom persistence in GW Veterans.

Abstract Gut microbiota, or the collection of diverse microorganisms in a specific ecological niche, are known to significantly impact human health. Decreased gut microbiota production of short-chain fatty acids (SCFAs) has been implicated in type 2 diabetes mellitus (T2DM) disease progression. Most microbiome studies focus on ethnic majorities. This study aims to understand how the microbiome differs between an ethnic majority (the Dutch) and minority (the South-Asian Surinamese (SAS)) group with a lower and higher prevalence of T2DM, respectively. Microbiome data from the Healthy Life in an Urban Setting (HELIUS) cohort were used. Two age- and gender-matched groups were compared: the Dutch (n = 41) and SAS (n = 43). Microbial community compositions were generated via DADA2. Metrics of microbial diversity and similarity between groups were computed. Biomarker analyses were performed to determine discriminating taxa. Bacterial co-occurrence networks were constructed to examine ecological patterns. A tight microbiota cluster was observed in the Dutch women, which overlapped with some of the SAS microbiota. The Dutch gut contained a more interconnected microbial ecology, whereas the SAS network was dispersed, i.e., contained fewer inter-taxonomic correlational relationships. Bacteroides caccae, Butyricicoccus, Alistipes putredinis, Coprococcus comes, Odoribacter splanchnicus, and Lachnospira were enriched in the Dutch gut. Haemophilus, Bifidobacterium, and Anaerostipes hadrus discriminated the SAS gut. All but Lachnospira and certain strains of Haemophilus are known to produce SCFAs. The Dutch gut microbiome was distinguished from the SAS by diverse, differentially abundant SCFA-producing taxa with significant cooperation. The dynamic ecology observed in the Dutch was not detected in the SAS. Among several potential gut microbial biomarkers, Haemophilus parainfluenzae likely best characterizes the ethnic minority group, which is more predisposed to T2DM. The higher prevalence of T2DM in the SAS may be associated with the gut dysbiosis observed.

Abstract Data on respiratory syncytial virus (RSV) incidence and household transmission are limited. To describe RSV incidence and transmission, we conducted a prospective cohort study in rural and urban communities in South Africa over two seasons during 2017-2018. Nasopharyngeal swabs were collected twice-weekly for 10 months annually and tested for RSV using PCR. We tested 81,430 samples from 1,116 participants in 225 households (follow-up 90%). 32% (359/1116) of individuals had ≥1 RSV infection; 10% (37/359) had repeat infection during the same season, 33% (132/396) of infections were symptomatic, and 2% (9/396) sought medical care. Incidence was 47.2 infections/100 person-years and highest in children 10 days were more likely to transmit; household contacts aged 1-4 years vs. ≥65 years were more likely to acquire infection. Within two South African communities, RSV attack rate was high, and most infections asymptomatic. Young children were more likely to introduce RSV into the home, and to be infected. Future studies should examine whether vaccines targeting children aged

Wastewater-based epidemiology (WBE) has been an important tool for the detection of COVID-19 outbreaks. The retrospective analysis of COVID-19 data is vital to understand the spread and impact of the virus as well as to inform future planning and response efforts. In this study, we evaluated the SARS-CoV-2 RNA levels in wastewater from 21 wastewater treatment plants (WWTPs) in the City of Cape Town (South Africa) over a period of 12 months and compared the (inactive) SARS-CoV-2 viral RNA in wastewater between wave 2 (November 2020 to January 2021) and wave 3 (June 2021 to September 2021). The SARS-CoV-2 RNA expression was quantified in wastewater using quantitative real-time PCR (qRT-PCR) by targeting the nucleocapsid (N) gene, and the resultant signal was normalized to the WWTP design capacity and catchment size. Our findings show that the maximum SARS-CoV-2 RNA signal was significantly higher in wave 3 than in wave 2 (p < 0.01). The duration of wave 3 (15 weeks) was longer than that of wave 2 (10 weeks), and the wastewater surveillance data supported the clinical findings, as evidenced by the two distinct waves. Furthermore, the data demonstrated the importance of long-term wastewater surveillance as a key indicator of changing trends.

A strong association between exposure to the common harmful algal bloom toxin microcystin and the altered host gut microbiome has been shown. We tested the hypothesis that prior exposure to the cyanotoxin microcystin-LR may alter the host resistome. We show that the mice exposed to microcystin-LR had an altered microbiome signature that harbored antibiotic resistance genes. Host resistome genotypes such as mefA, msrD, mel, ant6, and tet40 increased in diversity and relative abundance following microcystin-LR exposure. Interestingly, the increased abundance of these genes was traced to resistance to common antibiotics such as tetracycline, macrolides, glycopeptide, and aminoglycosides, crucial for modern-day treatment of several diseases. Increased abundance of these genes was positively associated with increased expression of PD1, a T-cell homeostasis marker, and pleiotropic inflammatory cytokine IL-6 with a concomitant negative association with immunosurveillance markers IL-7 and TLR2. Microcystin-LR exposure also caused decreased TLR2, TLR4, and REG3G expressions, increased immunosenescence, and higher systemic levels of IL-6 in both wild-type and humanized mice. In conclusion, the results show a first-ever characterization of the host resistome following microcystin-LR exposure and its connection to host immune status and antimicrobial resistance that can be crucial to understand treatment options with antibiotics in microcystin-exposed subjects in clinical settings.

Tanapox is a rarely diagnosed zoonosis endemic to equatorial Africa. Only 4 exported cases from Africa involving either human or nonhuman primates have been reported (Table). Initial human outbreaks, in [...]

Background. Pulmonary hypertension (PH) after tuberculosis (TB) is typically not included among the chronic lung diseases causing PH (group 3 PH), with few data available to support the inclusion. Objectives. To determine the prevalence of PH in an adult population completing TB treatment. Methods. This single-centre, cross-sectional study only included patients with their first documented episode of TB, and who were in the second half of treatment or had recently completed treatment. PH was assessed using transthoracic echocardiography. Questionnaires were also completed and spirometry and a 6-minute walk test were performed. Results. One hundred patients were enrolled, with a mean age of 37.1 years, of whom 58% were male and 46% HIV positive. The median time since initiation of TB treatment was 22 weeks. The mean (standard deviation) measured right ventricular systolic pressure (RVSP) was 23.6 (6.24) mmHg. One participant had PH (defined as RVSP ≥40 mmHg; 95% confidence interval (CI) 0.0 - 3.0) and a further 3 had possible PH (RVSP ≥35 and

Objective When considering proposals to improve diets, it is important to understand how factors like price and income can affect saturated fat (SF) intake and demand. In this study, we examine and estimate the influence of price and income on intake across 160 countries, by age and sex, and derive sensitivity measures (price elasticities) that vary by age, sex and world region.Design We econometrically estimate intake responsiveness to income and prices across countries, accounting for differences by world region, age and sex. Intake data by age, sex and country were obtained from the 2018 Global Dietary Database. These data were then linked to global price data for select food groups from the World Bank International Comparison Programme and income data from the World Development Indicators Databank (World Bank).Results Intake differences due to price were highly significant, with a 1% increase in price associated with a lower SF intake (% energy/d) of about 4.3 percentage points. We also find significant differences across regions. In high-income countries, median (age 40) intake reductions were 1.4, 0.8 and 0.2 percentage points, given a 1% increase in the price of meat, dairy, and oils and fats, respectively. Price elasticities varied with age but not sex. Intake differences due to income were insignificant when regional binary variables were included in the analysis.Conclusion The results of this study show heterogeneous associations among prices and intake within and across countries. Policymakers should consider these heterogeneous effects as they address global nutrition and health challenges.

Tanapox is a rarely diagnosed zoonosis known to be endemic to equatorial Africa. All previously reported human cases were acquired within 10° north or south of the Equator, most recently 19 years ago. We describe a human case of tanapox in South Africa (24° south of the Equator). Expanded surveillance for this pathogen is warranted.

Monitoring of SARS-CoV-2 RNA in wastewater has revealed the role of mobility in the transmission of coronavirus disease (COVID-19), and the surveillance of airport wastewater in cities across the world has demonstrated how travel entry points can give an indication of trends in transmission. This study undertook wastewater surveillance at the Cape Town International Airport (CTIA) to assess the use of a WBE approach to provide supplementary information on the presence of COVID-19 at a key air travel entry point in South Africa. Grab wastewater samples (n = 55) were collected from the CTIA wastewater pump station and analysed using quantitative real-time polymerase chain reaction (qRT-PCR) method. The study found a correlation between the wastewater data and clinical cases reported in the City of Cape Town during various time periods and during the peak of a COVID-19 wave. Highly elevated viral loads in the wastewater were observed at times there was increased mobility through the airport. The study also revealed elevated viral load levels at the airport despite the stricter restrictions and through the lower restrictions. The study findings indicate wastewater surveillance and airports can provide supplementary information to airport authorities to assess the impacts of imposed travel restrictions. HIGHLIGHTS This is the first published work to report on airport wastewater surveillance in Africa.; There was a strong correlation between wastewater data and clinical case data.; This study demonstrates the utility of wastewater monitoring at air travel entry points in an African setting.;

Abstract Background Air pollution is a global, public health emergency. The effect of living in areas with very poor air quality on adolescents’ physical health is largely unknown. The aim of this study was to investigate the prevalence of adverse respiratory health outcomes among adolescents living in a known air pollution hotspot in South Africa. Methods Ambient air quality data from 2005 to 2019 for the two areas, Secunda and eMbalenhle, in the Highveld Air Pollution Priority Area in Mpumalanga province, South Africa were gathered and compared against national ambient air pollution standards and the World Health Organization Air Quality Guidelines. In 2019, adolescents attending schools in the areas completed a self-administered questionnaire investigating individual demographics, socio-economic status, health, medical history, and fuel type used in homes. Respiratory health illnesses assessed were doctor-diagnosed hay fever, allergies, frequent cough, wheezing, bronchitis, pneumonia and asthma. The relationship between presence (at least one) or absence (none) of self-reported respiratory illness and risk factors, e.g., fuel use at home, was explored. Logistic regression was used to estimate the odds ratio and 95% confidence interval (CI) of risk factors associated with respiratory illness adjusted for body mass index (measured by field assistants), gender, education level of both parents / guardians and socio-economic status. Results Particulate matter and ozone were the two pollutants most frequently exceeding national annual air quality standards in the study area. All 233 adolescent participants were between 13 and 17 years of age. Prevalence of self-reported respiratory symptoms among the participants ranged from 2% for ‘ever’ doctor-diagnosed bronchitis and pneumonia to 42% ever experiencing allergies; wheezing chest was the second most reported symptom (39%). Half (52%) of the adolescents who had respiratory illness were exposed to environmental tobacco smoke in the dwelling. There was a statistically significant difference between the presence or absence of self-reported respiratory illness based on the number of years lived in Secunda or eMbalenhle (p = 0.02). For a one-unit change in the number of years lived in an area, the odds of reporting a respiratory illness increased by a factor of 1.08 (p = 0.025, 95% CI = 1.01–1.16). This association was still statistically significant when the model was adjusted for confounders (p = 0.037). Conclusions Adolescents living in air polluted areas experience adverse health impacts Future research should interrogate long-term exposure and health outcomes among adolescents living in the air polluted environment.

Ceramic ware is used around the world, usually daily. In the past, lead was used in the glazes and decorative paints applied to ceramic ware, mainly to increase durability, impart a smooth, glasslike finish to glazes and intensify decorative pigments. However, this use of lead at times contributed to lead exposure and poisoning. While measures have been put in place to limit the use of lead in ceramic ware in well-resourced countries, there is relatively little information on the situation in poorly resourced settings. In the current preliminary South African study, we assessed the lead content and leaching rates from newly purchased ceramic ware. The majority of the 44 ceramic ware items had lead levels ≥ 90 ppm. Elevated lead concentrations were found in the leachate from only one item. The findings indicate a need for further research on the potential for lead exposure from ceramic wares, and support calls for increased attention to the many potential sources of lead exposure in poorly resourced settings. Significance: • The study reveals the potential for lead contamination of certain types of ceramic ware available in South Africa. • Daily use of lead-contaminated ceramic ware may increase the risk of lead exposure, especially among the poorest. • The study findings are indicative of a need for further research to fully characterise the extent of lead in ceramic ware.

Abstract A strong association between exposure to the common harmful algal bloom toxin microcystin and the altered host gut microbiome has been shown. We tested the hypothesis that prior exposure to the cyanotoxin microcystin-LR may alter the host resistome. We show that the mice exposed to microcystin-LR had an altered microbiome signature that harbored antibiotic resistance genes. Host resistome genotypes such as mefA, msrD, mel, ant6, and tet40 increased in diversity and relative abundance following microcystin-LR exposure. Interestingly, the increased abundance of these genes was traced to resistance to common antibiotics such as tetracycline, macrolides, glycopeptide, and aminoglycosides, crucial for modern-day treatment of several diseases. Increased abundance of these genes was positively associated with increased expression of PD1, a T-cell homeostasis marker, and pleiotropic inflammatory cytokine IL-6 with a concomitant negative association with immunosurveillance markers IL-7 and TLR2. Microcystin-LR exposure also caused decreased TLR2, TLR4, and REG3G expressions, increased immunosenescence, and higher systemic levels of IL-6 in both wild-type and humanized mice. In conclusion, the results show a first-ever characterization of the host resistome following microcystin-LR exposure and its connection to host immune status and antimicrobial resistance that can be crucial to understand treatment options with antibiotics in microcystin-exposed subjects in clinical settings.

Abstract Background Lead has been associated with adverse health effects, especially neurocognitive and behavioural effects, in children. Communities living close to mining land are at risk of elevated exposure to lead. Methods This paper outlines a before and after intervention study protocol to evaluate the impact of a personal and domestic hygiene intervention on lead exposure in a community located adjacent to a mine dump. In each participating household, parents or guardians will be interviewed using a structured questionnaire to obtain information on socio-demographic characteristics, living conditions, domestic hygiene practices and potential alternative sources of exposure to lead. A registered nurse will collect hand wipe samples from children aged one to five years, for whom parental consent and where possible child assent has been obtained. Environmental dust samples will be collected from the floors and/or windowsills of children’s dwellings for lead content analysis. Soil samples will be collected from yards to determine lead content. An educational intervention will then be applied to the intervention group, including the engagement of households or guardians in an educational discussion on the sources, pathways of exposure, health effects of lead exposure and protective measures, with the aid of a specially designed educational brochure. Data will be analysed for descriptive and inferential statistics using Stata version 16. Discussion The study will determine whether the intervention led to a reduction in indoor dust lead levels, and if shown to be effective, will inform the development of an awareness campaign to reduce lead exposure in communities located in close proximity to mine dumps. Trial registration The study is retrospectively registered on ClinicalTrials.gov Protocol Registration and Results System with registration number NCT05265572 and first release date of 18th February 2022.

Wastewater-based epidemiology (WBE) has been an important tool for the detection of COVID-19 outbreaks. The retrospective analysis of COVID-19 data is vital to understand the spread and impact of the virus as well as to inform future planning and response efforts. In this study, we evaluated the SARS-CoV-2 RNA levels in wastewater from 21 wastewater treatment plants (WWTPs) in the City of Cape Town (South Africa) over a period of 12 months and compared the (inactive) SARS-CoV-2 viral RNA in wastewater between wave 2 (November 2020 to January 2021) and wave 3 (June 2021 to September 2021). The SARS-CoV-2 RNA expression was quantified in wastewater using quantitative real-time PCR (qRT-PCR) by targeting the nucleocapsid (N) gene, and the resultant signal was normalized to the WWTP design capacity and catchment size. Our findings show that the maximum SARS-CoV-2 RNA signal was significantly higher in wave 3 than in wave 2 (p < 0.01). The duration of wave 3 (15 weeks) was longer than that of wave 2 (10 weeks), and the wastewater surveillance data supported the clinical findings, as evidenced by the two distinct waves. Furthermore, the data demonstrated the importance of long-term wastewater surveillance as a key indicator of changing trends. [ABSTRACT FROM AUTHOR]

Abstract This study uses wastewater-based epidemiology (WBE) to rapidly and, through targeted surveillance, track the geographical distribution of SARS-CoV-2 variants of concern (Alpha, Beta and Delta) within 24 wastewater treatment plants (WWTPs) in the Western Cape of South Africa. Information obtained was used to identify the circulating variant of concern (VOC) within a population and retrospectively trace when the predominant variant was introduced. Genotyping analysis of SARS-CoV-2 showed that 50% of wastewater samples harbored signature mutations linked to the Beta variant before the third wave, with the Delta variant absent within the population. Over time, the prevalence of the beta variant decreased steadily. The onset of the third wave resulted in the Delta variant becoming the predominant variant, with a 100% prevalence supporting the theory that the Delta variant was driving the third wave. In silico molecular docking analysis showed that the signature mutations of the Delta variant increased binding to host proteins, suggesting a possible molecular mechanism that increased viral infectivity of the Delta variant.

Attention Deficit Hyperactivity Disorder (ADHD) is an increasingly prevalent neuropsychiatric disorder characterized by hyperactivity, inattention, and impulsivity. Symptoms emerge from underlying deficiencies in neurocircuitry, and recent research has suggested a role played by the gut microbiome. The gut microbiome is an ecosystem of interdependent taxa involved in an exponentially complex web of interactions, plus host gene and reaction pathways, some of which involve neurotransmitters with roles in ADHD neurocircuitry. Studies have analyzed the ADHD gut microbiome using macroscale metrics such as diversity and differential abundance, and have proposed several taxa as elevated or reduced in ADHD compared to Control. Few studies have delved into the complex underlying dynamics ultimately responsible for the emergence of such metrics, leaving a largely incomplete, sometimes contradictory, and ultimately inconclusive picture. We aim to help complete this picture by venturing beyond taxa abundances and into taxa relationships (i.e. cooperation and competition), using a publicly available gut microbiome dataset (targeted 16S, v3-4 region, qPCR) from an observational, case-control study of 30 Control (15 female, 15 male) and 28 ADHD (15 female, 13 male) undergraduate students. We first perform the same macroscale analyses prevalent in ADHD gut microbiome literature (diversity, differential abundance, and composition) to observe the degree of correspondence, or any new trends. We then estimate two-way ecological relationships by producing Control and ADHD Microbial Co-occurrence Networks (MCNs), using SparCC correlations (p ≤ 0.01). We perform community detection to find clusters of taxa estimated to mutually cooperate along with their centroids, and centrality calculations to estimate taxa most vital to overall gut ecology. We finally summarize our results, providing conjectures on how they can guide future experiments, some methods for improving our experiments, and general implications for the field.

Abstract Fibular free flap (FFF) is frequently used for reconstruction requiring vascularized bone. Thus, understanding its vasculature variation is crucial. This study investigates the popliteal artery branching variations in Thai cadavers and compares them with previous studies. One hundred and sixty-two legs from 81 formalin-embalmed cadavers were dissected. The popliteal artery branching patterns were classified. The previous data retrieved from cadaveric and angiographic studies were also collected and compared with the current study. The most common pattern is type I-A (90.7%). For the variants, type III-A was the majority among variants (6.2%). Type IV-A, hypoplastic peroneal artery, was found in one limb. A symmetrical branching pattern was found in 74 cadavers. Compared with cadaveric studies, type III-B and III-C are significantly common in angiographic studies (p = 0.015 and p = 0.009, respectively). Type I-A is most common according to previous studies. Apart from this, the prevalence of type III-A variant was higher than in previous studies. Furthermore, type III-B and III-C are more frequent in angiographic studies which might be from atherosclerosis. Thus, if the pre-operative CTA policy is not mandatory, the patients at risk for atherosclerosis and population with high variants prevalence should undergo pre-operative CTA with cost-effectiveness consideration.

Objective: To investigate and develop the saturated salt embalming method and evaluate the cadavers. Materials and Methods: Eight cadavers were embalmed with a saturated salt solution (SSS) by submerged (SG, N=2) and non-submerged (NSG, N=6), then evaluated by gross dissection, which compared to living humans, fresh and Thiel’s cadavers. The histological evaluation was compared to textbook pictures. The assessments were recorded on a Likert scale from 0 (no resemblance) to 5 (most resemblance). Pre-and post-embalming swabs were collected for bacterial and fungal cultures and lung tissues for acid-fast staining and mycobacterial cultures. Comparisons between the evaluated items were performed using the Kruskal–Wallis test. The Likert scale results were reported by percentage. Results: The submerge method (N=2) was terminated after three months of embalming because it showed insufficient quality for dissection. Six cadavers in NSG had gross tissue qualities that resembled living humans or fresh cadavers on a scale of 3 or 4. NSG had excellent joint flexibility. The histological tissues showed similarity to textbook pictures, with a scale of 4 or 5. There were bacterial and fungal cultures at the end of embalming. The pathogenic bacteria were Clostridium perfringens and Pseudomonas aeruginosa. Mycobacterium cultures were negative. Conclusion: Injected SSS, 80% total body water volume, is a promising embalming method that yields cadavers with high tissue quality, flexible joints, and good histological structures. However, this technique cannot eliminate bacteria and normal flora. It may result from the tropical climate setting.

Abstract Causal inference in biomedical research allows us to shift the paradigm from investigating associational relationships to causal ones. Inferring causal relationships can help in understanding the inner workings of biological processes. Association patterns can be coincidental and may lead to wrong conclusions about causality in complex systems. Microbiomes are highly complex, diverse, and dynamic environments. Microbes are key players in human health and disease. Hence knowledge of critical causal relationships among the entities in a microbiome, and the impact of internal and external factors on microbial abundance and their interactions are essential for understanding disease mechanisms and making appropriate treatment recommendations. In this paper, we employ causal inference techniques to understand causal relationships between various entities in a microbiome, and to use the resulting causal network to make useful computations. We introduce a novel pipeline for microbiome analysis, which includes adding an outcome or “disease” variable, and then computing the causal network, referred to as a “disease network”, with the goal of identifying disease-relevant causal factors from the microbiome. Internventional techniques are then applied to the resulting network, allowing us to compute a measure called the causal effect of one or more microbial taxa on the outcome variable or the condition of interest. Finally, we propose a measure called causal influence that quantifies the total influence exerted by a microbial taxon on the rest of the microiome. Our pipeline is robust, sensitive, different from traditional approaches, and able to predict interventional effects without any controlled experiments. The pipeline can be used to identify potential eubiotic and dysbiotic microbial taxa in a microbiome. We validate our results using synthetic data sets and using results on real data sets that were previously published.