Mortality from Congenital Zika Syndrome - Nationwide Cohort Study in Brazil.

BACKGROUND: Prenatal exposure to Zika virus has potential teratogenic effects, with a wide spectrum of clinical presentation referred to as congenital Zika syndrome. Data on survival among children with congenital Zika syndrome are limited. METHODS: In this population-based cohort study, we used linked, routinely collected data in Brazil, from January 2015 through December 2018, to estimate mortality among live-born children with congenital Zika syndrome as compared with those without the syndrome. Kaplan-Meier curves and survival models were assessed with adjustment for confounding and with stratification according to gestational age, birth weight, and status of being small for gestational age. RESULTS: A total of 11,481,215 live-born children were followed to 36 months of age. The mortality rate was 52.6 deaths (95% confidence interval [CI], 47.6 to 58.0) per 1000 person-years among live-born children with congenital Zika syndrome, as compared with 5.6 deaths (95% CI, 5.6 to 5.7) per 1000 person-years among those without the syndrome. The mortality rate ratio among live-born children with congenital Zika syndrome, as compared with those without the syndrome, was 11.3 (95% CI, 10.2 to 12.4). Among infants born before 32 weeks of gestation or with a birth weight of less than 1500 g, the risks of death were similar regardless of congenital Zika syndrome status. Among infants born at term, those with congenital Zika syndrome were 14.3 times (95% CI, 12.4 to 16.4) as likely to die as those without the syndrome (mortality rate, 38.4 vs. 2.7 deaths per 1000 person-years). Among infants with a birth weight of 2500 g or greater, those with congenital Zika syndrome were 12.9 times (95% CI, 10.9 to 15.3) as likely to die as those without the syndrome (mortality rate, 32.6 vs. 2.5 deaths per 1000 person-years). The burden of congenital anomalies, diseases of the nervous system, and infectious diseases as recorded causes of deaths was higher among live-born children with congenital Zika syndrome than among those without the syndrome. CONCLUSIONS: The risk of death was higher among live-born children with congenital Zika syndrome than among those without the syndrome and persisted throughout the first 3 years of life. (Funded by the Ministry of Health of Brazil and others.).

Causes of death in children with congenital Zika syndrome in Brazil, 2015 to 2018: A nationwide record linkage study.

BACKGROUND: Children with congenital Zika syndrome (CZS) have severe damage to the peripheral and central nervous system (CNS), greatly increasing the risk of death. However, there is no information on the sequence of the underlying, intermediate, immediate, and contributing causes of deaths among these children. The aims of this study are describe the sequence of events leading to death of children with CZS up to 36 months of age and their probability of dying from a given cause, 2015 to 2018. METHODS AND FINDINGS: In a population-based study, we linked administrative data on live births, deaths, and cases of children with CZS from the SINASC (Live Birth Information System), the SIM (Mortality Information System), and the RESP (Public Health Event Records), respectively. Confirmed and probable cases of CZS were those that met the criteria established by the Brazilian Ministry of Health. The information on causes of death was collected from death certificates (DCs) using the World Health Organization (WHO) DC template. We estimated proportional mortality (PM%) among children with CZS and among children with non-Zika CNS congenital anomalies (CA) by 36 months of age and proportional mortality ratio by cause (PMRc). A total of 403 children with confirmed and probable CZS who died up to 36 months of age were included in the study; 81.9% were younger than 12 months of age. Multiple congenital malformations not classified elsewhere, and septicemia unspecified, with 18 (PM = 4.5%) and 17 (PM = 4.2%) deaths, respectively, were the most attested underlying causes of death. Unspecified septicemia (29 deaths and PM = 11.2%) and newborn respiratory failure (40 deaths and PM = 12.1%) were, respectively, the predominant intermediate and immediate causes of death. Fetuses and newborns affected by the mother's infectious and parasitic diseases, unspecified cerebral palsy, and unspecified severe protein-caloric malnutrition were the underlying causes with the greatest probability of death in children with CZS (PMRc from 10.0 to 17.0) when compared to the group born with non-Zika CNS anomalies. Among the intermediate and immediate causes of death, pneumonitis due to food or vomiting and unspecified seizures (PMRc = 9.5, each) and unspecified bronchopneumonia (PMRc = 5.0) were notable. As contributing causes, fetus and newborn affected by the mother's infectious and parasitic diseases (PMRc = 7.3), unspecified cerebral palsy, and newborn seizures (PMRc = 4.5, each) were more likely to lead to death in children with CZS than in the comparison group. The main limitations of this study were the use of a secondary database without additional clinical information and potential misclassification of cases and controls. CONCLUSION: The sequence of causes and circumstances involved in the deaths of the children with CZS highlights the greater vulnerability of these children to infectious and respiratory conditions compared to children with abnormalities of the CNS not related to Zika.

Complex network analysis of arboviruses in the same geographic domain: Differences and similarities.

Arbovirus can cause diseases with a broad spectrum from mild to severe and long-lasting symptoms, affecting humans worldwide and therefore considered a public health problem with global and diverse socio-economic impacts. Understanding how they spread within and across different regions is necessary to devise strategies to control and prevent new outbreaks. Complex network approaches have widespread use to get important insights on several phenomena, as the spread of these viruses within a given region. This work uses the motif-synchronization methodology to build time varying complex networks based on data of registered infections caused by Zika, chikungunya, and dengue virus from 2014 to 2020, in 417 cities of the state of Bahia, Brazil. The resulting network sets capture new information on the spread of the diseases that are related to the time delay in the synchronization of the time series among different municipalities. Thus the work adds new and important network-based insights to previous results based on dengue dataset in the period 2001-2016. The most frequent synchronization delay time between time series in different cities, which control the insertion of edges in the networks, ranges 7 to 14 days, a period that is compatible with the time of the individual-mosquito-individual transmission cycle of these diseases. As the used data covers the initial periods of the first Zika and chikungunya outbreaks, our analyses reveal an increasing monotonic dependence between distance among cities and the time delay for synchronization between the corresponding time series. The same behavior was not observed for dengue, first reported in the region back in 1986, either in the previously 2001-2016 based results or in the current work. These results show that, as the number of outbreaks accumulates, different strategies must be adopted to combat the dissemination of arbovirus infections.

Population-based surveillance for congenital zika virus syndrome: a latent class analysis of recorded cases from 2015-2018.

OBJECTIVE: This study aims to describe clinical findings and determine the medium-term survival of congenital zika syndrome (CZS) suspected cases. METHODS: A retrospective cohort study using routine register-based linked data. It included all suspected cases of CZS born in Brazil from January 1, 2015, to December 31, 2018, and followed up from birth until death, 36 months, or December 31, 2018, whichever came first. Latent class analysis was used to cluster unconfirmed cases into classes with similar combinations of anthropometry at birth, imaging findings, maternally reported rash, region, and year of birth. Kaplan-Meier curves were plotted, and Cox proportional hazards models were fitted to determine mortality up to 36 months. RESULTS: We followed 11,850 suspected cases of CZS, of which 28.3% were confirmed, 9.3% inconclusive and 62.4% unconfirmed. Confirmed cases had almost two times higher mortality when compared with unconfirmed cases. Among unconfirmed cases, we identified three distinct clusters with different mortality trajectories. The highest mortality risk was observed in those with abnormal imaging findings compatible with congenital infections (HR = 12.6; IC95%8.8-18.0) and other abnormalities (HR = 11.6; IC95%8.6-15.6) compared with those with normal imaging findings. The risk was high in those with severe microcephaly (HR = 8.2; IC95%6.4-10.6) and macrocephaly (HR = 6.6; IC95%4.5-9.7) compared with normal head size. CONCLUSION: Abnormal imaging and head circumference appear to be the main drivers of the increased mortality among suspected cases of CZS. We suggest identifying children who are more likely to die and have a greater need to optimise interventions and resource allocation regardless of the final diagnoses.

Modeling nonlocal behavior in epidemics via a reaction-diffusion system incorporating population movement along a network.

The outbreak of COVID-19, beginning in 2019 and continuing through the time of writing, has led to renewed interest in the mathematical modeling of infectious disease. Recent works have focused on partial differential equation (PDE) models, particularly reaction-diffusion models, able to describe the progression of an epidemic in both space and time. These studies have shown generally promising results in describing and predicting COVID-19 progression. However, people often travel long distances in short periods of time, leading to nonlocal transmission of the disease. Such contagion dynamics are not well-represented by diffusion alone. In contrast, ordinary differential equation (ODE) models may easily account for this behavior by considering disparate regions as nodes in a network, with the edges defining nonlocal transmission. In this work, we attempt to combine these modeling paradigms via the introduction of a network structure within a reaction-diffusion PDE system. This is achieved through the definition of a population-transfer operator, which couples disjoint and potentially distant geographic regions, facilitating nonlocal population movement between them. We provide analytical results demonstrating that this operator does not disrupt the physical consistency or mathematical well-posedness of the system, and verify these results through numerical experiments. We then use this technique to simulate the COVID-19 epidemic in the Brazilian region of Rio de Janeiro, showcasing its ability to capture important nonlocal behaviors, while maintaining the advantages of a reaction-diffusion model for describing local dynamics.

Smart Home IoT Network Risk Assessment Using Bayesian Networks.

A risk assessment model for a smart home Internet of Things (IoT) network is implemented using a Bayesian network. The directed acyclic graph of the Bayesian network is constructed from an attack graph that details the paths through which different attacks can occur in the IoT network. The parameters of the Bayesian network are estimated with the maximum likelihood method applied to a data set obtained from the simulation of attacks, in five simulation scenarios. For the risk assessment, inferences in the Bayesian network and the impact of the attacks are considered, focusing on DoS attacks, MitM attacks and both at the same time to the devices that allow the automation of the smart home and that are generally the ones that individually have lower levels of security.

Extended Methodology for DFA and DCCA: Application of Automatic Search Procedure and Correlation Map to the Weierstrass-Mandelbrot Functions.

Detrended fluctuation analysis and detrended cross-correlation analysis are used in this study to identify and characterize correlated data. The objective of these two techniques is to separate different fluctuations from the contributions due to external trends by evaluating the autocorrelation and cross-correlation exponents, in order to determine if scale properties persist with the size of the series. Two new methodologies were extended from cross-correlation coefficients for local analysis, which we call the \textit{automatic search procedure.

Scaling effect in COVID-19 spreading: The role of heterogeneity in a hybrid ODE-network model with restrictions on the inter-cities flow.

The new Covid-19 pandemic has left traces of suffering and devastation to individuals of almost all countries worldwide and severe impact on the global economy. Understanding the clinical characteristics, interactions with the environment, and the variables that favor or hinder its dissemination help the public authorities in the fight and prevention, leading for a rapid response in society. Using models to estimate contamination scenarios in real time plays an important role. Population compartments models based on ordinary differential equations (ODE) for a given region assume two homogeneous premises, the contact mechanisms and diffusion rates, disregarding heterogeneous factors as different contact rates for each municipality and the flow of contaminated people among them. This work considers a hybrid model for covid-19, based on local SIR models and the population flow network among municipalities, responsible for a complex lag dynamic in their contagion curves. Based on actual infection data, local contact rates ( ß ) are evaluated. The epidemic evolution at each municipality depends on the local SIR parameters and on the inter-municipality transport flow. When heterogeneity of ß values and flow network are included, forecasts differ from those of the homogeneous ODE model. This effect is more relevant when more municipalities are considered, hinting that the latter overestimates new cases. In addition, mitigation scenarios are assessed to evaluate the effect of earlier interventions reducing the inter-municipality flux. Restricting the flow between municipalities in the initial stage of the epidemic is fundamental for flattening the contamination curve, highlighting advantages of a contamination lag between the capital curve and those of other municipalities in the territories.

Environmental and individual factors associated with quality of life of adults who underwent bariatric surgery: a cohort study.

INTRODUCTION: Obesity is a multifactorial chronic condition associated with genetic, behavioral and environmental factors. Understanding the role of the built and social environment in Quality of Life (QOL) is critical to reducing the negative impacts of the environment on health. OBJECTIVE: To estimate the built and social environmental and individual factors that influence the QOL of adults who underwent bariatric surgery. METHODS: A prospective cohort study conducted with adults who underwent bariatric surgery. Using longitudinal linear regression analysis, we verified the association between the domains of World Health Organization Quality of Life in version bref (WHOQOL-Bref) - General QOL and domains psychological, physical health, social relations and environment - and possible influencing factors. RESULTS: The increase in Body Mass Index (BMI) reduces on average 0.47 points in physical domain assessment score. The increase of healthy establishments within the buffer increases on average 0.52 points in the physical domain score. Being female reduces, on average, 5.35 points in the psychological domain evaluation score. Adults who practiced less than 150 min a week of leisure-time physical activity had a 3.27 point average reduction in the social relations domain assessment score. The increase in the number of Supermarkets and Hypermarkets in the buffer increases on average 2.18 points from the Social Relations domain score. CONCLUSIONS: Individual and contextual factors were associated with the QOL of adults who underwent bariatric surgery. Although the surgery yields positive results, the maintenance of same is strongly related to changes in lifestyle, the built environment and multi-professional guidance.

Single Dose Versus 3 Doses of Intramuscular Benzathine Penicillin for Early Syphilis in HIV: A Randomized Clinical Trial.

Background: Patients coinfected with syphilis and human immunodeficiency virus (HIV) may have a slower decrease in rapid plasma reagin (RPR) titers. Currently a single dose of 2.4 million units of intramuscular benzathine penicillin G (BPG) is recommended for the treatment of early syphilis. Some observational studies have suggested that this regimen may lead to high failure rates in coinfected patients. Methods: We conducted an open-label randomized clinical trial to compare the efficacy of single-dose and 3-dose regimens of BPG for the treatment of early syphilis in HIV-infected individuals. RPR titers were monitored every 3 months. Treatment success was defined as a decrease in RPR titers of ≥2 dilutions (4-fold) during a 12-month follow-up period. Results: Sixty-four patients were included. In the intention-to-treat analysis, treatment success rates were 80% (28 of 35 subjects) and 93% (27 of 29 subjects) in the single-dose and 3-dose regimens, respectively (absolute difference, 13% [95% confidence interval {CI}, -5% to 30%; P = .17). In the per-protocol analysis, success rates were 93% (27 of 29) and 100% in the single-dose and 3-dose regimens, respectively (absolute difference, 7% [95% CI, -7% to 22%]; P = .49). CD4 T-cell count, RPR titer and syphilis stage did not affect treatment results. Conclusions: When compared with a single dose of BPG, a 3-dose regimen did not improve syphilis serological outcomes. Our results support the Centers for Disease Control and Prevention recommendation of a single dose of BPG in HIV-infected patients with early syphilis. Clinical Trials Registration: NCT02611765.

Synchronization unveils the organization of ecological networks with positive and negative interactions.

Network science has helped to understand the organization principles of the interactions among the constituents of large complex systems. However, recently, the high resolution of the data sets collected has allowed to capture the different types of interactions coexisting within the same system. A particularly important example is that of systems with positive and negative interactions, a usual feature appearing in social, neural, and ecological systems. The interplay of links of opposite sign presents natural difficulties for generalizing typical concepts and tools applied to unsigned networks and, moreover, poses some questions intrinsic to the signed nature of the network, such as how are negative interactions balanced by positive ones so to allow the coexistence and survival of competitors/foes within the same system? Here, we show that synchronization phenomenon is an ideal benchmark for uncovering such balance and, as a byproduct, to assess which nodes play a critical role in the overall organization of the system. We illustrate our findings with the analysis of synthetic and real ecological networks in which facilitation and competitive interactions coexist.

Evolutionary analysis of apolipoprotein E by Maximum Likelihood and complex network methods.

Apolipoprotein E (apo E) is a human glycoprotein with 299 amino acids, and it is a major component of very low density lipoproteins (VLDL) and a group of high-density lipoproteins (HDL). Phylogenetic studies are important to clarify how various apo E proteins are related in groups of organisms and whether they evolved from a common ancestor. Here, we aimed at performing a phylogenetic study on apo E carrying organisms. We employed a classical and robust method, such as Maximum Likelihood (ML), and compared the results using a more recent approach based on complex networks. Thirty-two apo E amino acid sequences were downloaded from NCBI. A clear separation could be observed among three major groups: mammals, fish and amphibians. The results obtained from ML method, as well as from the constructed networks showed two different groups: one with mammals only (C1) and another with fish (C2), and a single node with the single sequence available for an amphibian. The accordance in results from the different methods shows that the complex networks approach is effective in phylogenetic studies. Furthermore, our results revealed the conservation of apo E among animal groups.

Two-phase fluid flow in geometric packing.

We investigate how a plug of obstacles inside a two-dimensional channel affects the drainage of high viscous fluid (oil) when the channel is invaded by a less viscous fluid (water). The plug consists of an Apollonian packing with, at most, 17 circles of different sizes, which is intended to model an inhomogeneous porous region. The work aims to quantify the amount of retained oil in the region where the flow is influenced by the packing. The investigation, carried out with the help of the computational fluid dynamics package ANSYS-FLUENT, is based on the integration of the complete set of equations of motion. The study considers the effect of both the injection speed and the number and size of obstacles, which directly affects the porosity of the system. The results indicate a complex dependence in the fraction of retained oil on the velocity and geometric parameters. The regions where the oil remains trapped is very sensitive to the number of circles and their size, which influence in different ways the porosity of the system. Nevertheless, at low values of Reynolds and capillary numbers Re<4 and n(c)≃10(-5), the overall expected result that the volume fraction of oil retained decreases with increasing porosity is recovered. A direct relationship between the injection speed and the fraction of oil is also obtained.

SearchSmallRNA: a graphical interface tool for the assemblage of viral genomes using small RNA libraries data.

BACKGROUND: Next-generation parallel sequencing (NGS) allows the identification of viral pathogens by sequencing the small RNAs of infected hosts. Thus, viral genomes may be assembled from host immune response products without prior virus enrichment, amplification or purification. However, mapping of the vast information obtained presents a bioinformatics challenge. METHODS: In order to by pass the need of line command and basic bioinformatics knowledge, we develop a mapping software with a graphical interface to the assemblage of viral genomes from small RNA dataset obtained by NGS. SearchSmallRNA was developed in JAVA language version 7 using NetBeans IDE 7.1 software. The program also allows the analysis of the viral small interfering RNAs (vsRNAs) profile; providing an overview of the size distribution and other features of the vsRNAs produced in infected cells. RESULTS: The program performs comparisons between each read sequenced present in a library and a chosen reference genome. Reads showing Hamming distances smaller or equal to an allowed mismatched will be selected as positives and used to the assemblage of a long nucleotide genome sequence. In order to validate the software, distinct analysis using NGS dataset obtained from HIV and two plant viruses were used to reconstruct viral whole genomes. CONCLUSIONS: SearchSmallRNA program was able to reconstructed viral genomes using NGS of small RNA dataset with high degree of reliability so it will be a valuable tool for viruses sequencing and discovery. It is accessible and free to all research communities and has the advantage to have an easy-to-use graphical interface. AVAILABILITY AND IMPLEMENTATION: SearchSmallRNA was written in Java and is freely available at http://www.microbiologia.ufrj.br/ssrna/.

Interpreting measures of tuberculosis transmission: a case study on the Portuguese population.

BACKGROUND: Tuberculosis remains a high burden for Human society despite considerable investments in its control. Unique features in the history of infection and transmission dynamics of tuberculosis pose serious limitations on the direct interpretation of surveillance data and call for models that incorporate latent processes and simulate specific interventions. METHODS: A transmission model was adjusted to the dataset of active tuberculosis cases reported in Portugal between 2002 and 2009. We estimated key transmission parameters from the data (i.e. time to diagnosis, treatment length, default proportion, proportion of pulmonary TB cases). Using the adjusted model to the Portuguese case, we estimated the total burden of tuberculosis in Portugal. We further performed sensitivity analysis to heterogeneities in susceptibility to infection and exposure intensity. RESULTS: We calculated a mean time to diagnose of 2.81 months and treatment length of 8.80 months in Portugal. The proportion defaulting treatment was calculated as 0.04 and the proportion of pulmonary cases as 0.75. Using these values, we estimated a TB burden of 1.6 million infected persons, corresponding to more than 15% of the Portuguese population. We further described the sensitivity of these estimates to heterogeneity. CONCLUSIONS: We showed that the model reproduces well the observed dynamics of the Portuguese data, thus demonstrating its adequacy for devising control strategies for TB and predicting the effects of interventions.

Eosinophilia and associated factors in a large cohort of patients infected with human immunodeficiency virus.

OBJECTIVES: To determine the prevalence of eosinophilia among antiretroviral therapy (ART)-naïve patients infected with human immunodeficiency virus (HIV) and to identify variables associated with eosinophilia. METHODS: We included all ART-naïve HIV-infected patients entering into care at the Thomas Street Health Center (Houston, Texas) between February 2007 and January 2009. Eosinophilia was defined as absolute eosinophil count ≥ 400 cells per cubic millimeter. Patients with eosinophilia (cases) at baseline were matched to patients without baseline eosinophilia (controls). Clinical and laboratory data were collected for cases and controls. Variables associated with eosinophilia were evaluated by univariate and multivariate analyses. RESULTS: Sixty-five (9.7%) of 671 ART-naïve patients had eosinophilia. There was no difference in age, sex, race, or baseline CD4 count between patients with and without eosinophilia; however, patients with eosinophilia were more likely to have higher HIV RNA viral loads (5.05 vs 4.82 log10 copies per milliliter; P = 0.019). A total of 52 (80%) of 65 patients with eosinophilia (cases) had at least two follow-up clinic visits. They were matched to 104 controls. Skin rash was the only variable associated with eosinophilia (odds ratio 2.16, 95% confidence interval 1.04-4.47) in our multivariate analysis. Of eight cases tested, only one, from Central America, had a parasitic infection (hookworm). Thirty-eight (73.1%) patients experienced resolution of their eosinophilia by the end of the study (mean follow-up 1019 days). Resolution of eosinophilia did not differ between patients with and without HIV viral suppression. CONCLUSIONS: Eosinophilia is not an infrequent occurrence among ART-naïve HIV-infected patients. Patients with eosinophilia are more likely than patients without eosinophilia to present with a skin rash. HIV RNA viral suppression did not necessarily result in the resolution of eosinophilia. Extensive workup for eosinophilia may not be necessary in most cases.

Combining Digital and Molecular Approaches Using Health and Alternate Data Sources in a Next-Generation Surveillance System for Anticipating Outbreaks of Pandemic Potential.

Globally, millions of lives are impacted every year by infectious diseases outbreaks. Comprehensive and innovative surveillance strategies aiming at early alert and timely containment of emerging and reemerging pathogens are a pressing priority. Shortcomings and delays in current pathogen surveillance practices further disturbed informing responses, interventions, and mitigation of recent pandemics, including H1N1 influenza and SARS-CoV-2. We present the design principles of the architecture for an early-alert surveillance system that leverages the vast available data landscape, including syndromic data from primary health care, drug sales, and rumors from the lay media and social media to identify areas with an increased number of cases of respiratory disease. In these potentially affected areas, an intensive and fast sample collection and advanced high-throughput genome sequencing analyses would inform on circulating known or novel pathogens by metagenomics-enabled pathogen characterization. Concurrently, the integration of bioclimatic and socioeconomic data, as well as transportation and mobility network data, into a data analytics platform, coupled with advanced mathematical modeling using artificial intelligence or machine learning, will enable more accurate estimation of outbreak spread risk. Such an approach aims to readily identify and characterize regions in the early stages of an outbreak development, as well as model risk and patterns of spread, informing targeted mitigation and control measures. A fully operational system must integrate diverse and robust data streams to translate data into actionable intelligence and actions, ultimately paving the way toward constructing next-generation surveillance systems.

Wildfire, deforestation and health in tropical rainforest areas: a scoping review protocol.

INTRODUCTION: Wildfires and deforestation potentially have direct effects on multiple health outcomes as well as indirect consequences for climate change. Tropical rainforest areas are characterised by high rainfall, humidity and temperature, and they are predominantly found in low-income and middle-income countries. This study aims to synthesise the methods, data and health outcomes reported in scientific papers on wildfires and deforestation in these locations. METHODS AND ANALYSIS: We will carry out a scoping review according to the Joanna Briggs Institute's (JBI) manual for scoping reviews and the framework proposed by Arksey and O'Malley, and Levac et al. The search for articles was performed on 18 August 2023, in 16 electronic databases using Medical Subject Headings terms and adaptations for each database from database inception. The search for local studies will be complemented by the manual search in the list of references of the studies selected to compose this review. We screened studies written in English, French, Portuguese and Spanish. We included quantitative studies assessing any human disease outcome, hospitalisation and vital statistics in regions of tropical rainforest. We exclude qualitative studies and quantitative studies whose outcomes do not cover those of interest. The text screening was done by two independent reviewers. Subsequently, we will tabulate the data by the origin of the data source used, the methods and the main findings on health impacts of the extracted data. The results will provide descriptive statistics, along with visual representations in diagrams and tables, complemented by narrative summaries as detailed in the JBI guidelines. ETHICS AND DISSEMINATION: The study does not require an ethical review as it is meta-research and uses published, deidentified secondary data sources. The submission of results for publication in a peer-reviewed journal and presentation at scientific and policymakers' conferences is expected. STUDY REGISTRATION: Open Science Framework (https://osf.io/pnqc7/).

Expanding anti-venom strategies: Camelid polyclonal antibodies with high capacity to recognize snake venom.

Camelid immunoglobulins represent a unique facet of antibody biology, challenging conventional understandings of antibody diversification. IgG2 and IgG3 in particular are composed solely of heavy chains and exhibit a reduced molecular weight (90 kDa); their elongated complementarity determining region (CDR) loops play a pivotal role in their functioning, delving deep into enzyme active sites with precision. Serum therapy stands as the primary venom-specific treatment for snakebite envenomation, harnessing purified antibodies available in diverse forms such as whole IgG, monovalent fragment antibody (Fab), or divalent fragment antibody F (ab')2. This investigation looks into the intricacies of IgGs derived from camelid serum previously immunized with crotamine and crotoxin, toxins predominantly in Crotalus durissus venom, exploring their recognition capacity, specificity, and cross-reactivity to snake venoms and its toxins. Initially, IgG purification employed affinity chromatography via protein A and G columns to segregate conventional antibodies (IgG1) from heavy chain antibodies (IgG2 and IgG3) of camelid isotypes sourced from Lama glama serum. Subsequent electrophoretic analysis (SDS-PAGE) revealed distinct bands corresponding to molecular weight profiles of IgG's fractions representing isotypes in Lama glama serum. ELISA cross-reactivity assays demonstrated all three IgG isotypes' ability to recognize the tested venoms. Notably, IgG1 exhibited the lowest interactivity in analyses involving bothropic and crotalic venoms. However, IgG2 and IgG3 displayed notable cross-reactivity, particularly with crotalic venoms and toxins, albeit with exceptions such as PLA2-CB, showing reduced reactivity, and C. atrox, where IgGs exhibited insignificant reactivity. In Western blot assays, IgG2 and IgG3 exhibited recognition of proteins within molecular weight (≈15 kDa) of C. d. collilineatus to C. d. terrificus, with some interaction observed even with bothropic proteins despite lower reactivity. These findings underscore the potential of camelid heavy-chain antibodies, suggesting Lama glama IgGs as prospective candidates for a novel class of serum therapies. However, further investigations are imperative to ascertain their suitability for serum therapy applications.

Preclinical evaluation of single domain antibody efficacy in mitigating local tissue damage induced by Bothrops snake envenomation.

Camelid single-domain antibodies (VHH) represent a promising class of immunobiologicals for therapeutic applications due to their remarkable stability, specificity, and therapeutic potential. To enhance the effectiveness of antivenoms for snakebites, various methods have been explored to address limitations associated with serum therapy, particularly focusing on mitigating local damage and ensuring sustainable production. Our study aimed to characterize the pharmacological profile and neutralization capacity of anti-Phospholipase A2 (PLA2) monomeric VHH (Genbank accessions: KC329718). Using a post-envenoming mouse model, we used intravital microscopy to assess leukocyte influx, measured CK and LDH levels, and conducted a histopathology analysis to evaluate VHH KC329718's ability to neutralize myotoxic activity. Our findings demonstrated that VHH KC329718 exhibited heterogeneous distribution in muscle tissue. Treatment with VHH KC329718 reduced leukocyte influx caused by BthTX-I (a Lys-49 PLA2) by 28 %, as observed through intravital microscopy. When administered at a 1:10 ratio [venom or toxin:VHH (w/w)], VHH KC329718 significantly decreased myotoxicity, resulting in a 35-40 % reduction in CK levels from BthTX-I and BthTX-II (an Asp-49 PLA2) and a 60 % decrease in CK levels from B. jararacussu venom. LDH levels also showed reductions of 60%, 80%, and 60% induced by BthTX-I, BthTX-II, and B. jararacussu venom, respectively. Histological analysis confirmed the neutralization potential, displaying a significant reduction in tissue damage and inflammatory cell count in mice treated with VHH KC329718 post B. jararacussu venom inoculation. This study underscores the potential of monomeric anti-PLA2 VHH in mitigating myotoxic effects, suggesting a promising avenue for the development of new generation antivenoms to address current therapeutic limitations.