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Snakebite envenoming kills and maims hundreds of thousands of people every year, especially in the rural settings of tropical regions. Envenomings are still treated with animal-derived antivenoms, which have prevented many lives from being lost but which are also medicines in need of innovation. Strides are being made to improve envenoming therapies, with promising efforts made toward optimizing manufacturing and quality aspects of existing antivenoms, accelerating research and development of recombinant antivenoms based on monoclonal antibodies, and repurposing of small-molecule inhibitors that block key toxins. Here, we review the most recent advances in these fields and discuss therapeutic opportunities and limitations for different snakebite treatment modalities. Finally, we discuss challenges related to preclinical and clinical evaluation, regulatory pathways, large-scale manufacture, and distribution and access that need to be addressed to fulfill the goals of the World Health Organization's global strategy to prevent and control snakebite envenoming. [ABSTRACT FROM AUTHOR]

Background: Snakebite envenoming is a serious condition that affects 2.5 million people and causes 81,000–138,000 deaths every year, particularly in tropical and subtropical regions. The World Health Organization has set a goal to halve the deaths and disabilities related to snakebite envenoming by 2030. However, significant challenges in achieving this goal include a lack of robust research evidence related to snakebite incidence and treatment, particularly in sub-Saharan Africa. This study aimed to combine established methodologies with the latest tools in Artificial Intelligence to assess the barriers to effective snakebite treatment in Ghana. Method: We used a MaxDiff statistical experiment design to collect data, and six supervised machine learning models were applied to predict responses whose performance showed an advantage over the other through 6921 data points partitioned using the hold-back validation method, with 70% training and 30% validation. The results were compared using key metrics: Akaike Information Criterion corrected, Bayesian Information Criterion, Root Average Squared Error, and Fit Time in milliseconds. Results: Considering all the responses, none of the six machine learning algorithms proved superior, but the Generalized Regression Model (Ridge) performed consistently better among the candidate models. The model consistently predicted several key significant barriers to effective snakebite treatment, such as the high cost of antivenoms, increased use of unorthodox, harmful practices, lack of access to effective antivenoms in remote areas when needed, and resorting to unorthodox and harmful practices in addition to hospital treatment. Conclusion: The combination of a MaxDiff statistical experiment design to collect data and six machine learning models allowed the identification of barriers to accessing effective therapies for snakebite envenoming in Ghana. Addressing these barriers through targeted policy interventions, including intensified advocacy, continuous education, community engagement, healthcare worker training, and strategic investments, can enhance the effectiveness of snakebite treatment, ultimately benefiting snakebite victims and reducing the burden of snakebite envenoming. There is a need for robust regulatory frameworks and increased antivenom production to address these barriers. Author summary: Snakebite envenoming, a severe condition, affects 2.5 million people and causes 81,000–138,000 deaths annually, particularly in tropical and subtropical regions of Africa, Asia, and Latin America. The World Health Organization aims to reduce this burden by 50% by 2030. However, significant barriers exist to achieving these targets, especially in Sub-Saharan Africa. These barriers include limited rigorous research evidence and the lack of investment in effective antivenoms for local snake species. Meeting this goal will require innovative research to gather better data on snakebite incidence and treatment. Artificial intelligence is one promising field that can contribute to this effort. For the first time, we have demonstrated how MaxDiff statistical experiment designs and machine learning algorithms can be explored to predict the barriers to effective snakebite treatment, such as the high cost of antivenoms, increased use of harmful practices, lack of access to effective antivenoms in remote areas, and resorting to unorthodox and harmful practices in addition to hospital treatment. Addressing these barriers through targeted policy interventions, including intensified advocacy, continuous education, community engagement, healthcare worker training, and strategic investments, can enhance the effectiveness of snakebite treatment. Robust regulatory frameworks and increased local antivenom production are also needed to address these barriers. [ABSTRACT FROM AUTHOR]

Background: The venom of Bothrops lanceolatus, a viperid species endemic to the Lesser Antillean Island of Martinique, induces thrombosis in a number of patients. Previous clinical observations indicate that thrombotic events are more common in patients bitten by juvenile specimens. There is a need to develop an experimental model of this effect in order to study the mechanisms involved. Methodology/Principal findings: The venoms of juvenile and adult specimens of B. lanceolatus were compared by (a) describing their proteome, (b) assessing their ability to induce thrombosis in a mouse model, and (c) evaluating their in vitro procoagulant activity and in vivo hemostasis alterations. Venom proteomes of juvenile and adult specimens were highly similar, albeit showing some differences. When injected by the intraperitoneal (i.p.) route, the venom of juvenile specimens induced the formation of abundant thrombi in the pulmonary vasculature, whereas this effect was less frequent in the case of adult venom. Thrombosis was not abrogated by the metalloproteinase inhibitor Batimastat. Both venoms showed a weak in vitro procoagulant effect on citrated mouse plasma and bovine fibrinogen. When administered intravenously (i.v.) venoms did not affect classical clotting tests (prothrombin time and activated partial thromboplastin time) but caused a partial drop in fibrinogen concentration. The venom of juvenile specimens induced partial alterations in some rotational thromboelastometry parameters after i.v. injection. When venoms were administered i.p., only minor alterations in classical clotting tests were observed with juvenile venom, and no changes occurred for either venom in rotational thromboelastometry parameters. Both juvenile and adult venoms induced a marked thrombocytopenia after i.p. injection. Conclusions/Significance: An experimental model of the thrombotic effect induced by B. lanceolatus venom was developed. This effect is more pronounced in the case of venom of juvenile specimens, despite the observation that juvenile and adult venom proteomes are similar. Adult and juvenile venoms do not induce a consumption coagulopathy characteristic of other Bothrops sp venoms. Both venoms induce a conspicuous thrombocytopenia. This experimental model reproduces the main clinical findings described in these envenomings and should be useful to understand the mechanisms of the thrombotic effect. Author summary: Envenomings by the viperid species Bothrops lanceolatus, endemic of the Caribbean Island of Martinique, are characterized by a thrombotic effect responsible for infarcts in various organs. Until now, no experimental in vivo models of this effect have been described. In this study, we developed a mouse model of thrombosis by using the intraperitoneal route of venom injection. The venom of juvenile specimens of B. lanceolatus induced the formation of abundant thrombi in the lungs, whereas the effect was much less pronounced with the venom of adult specimens. This difference in the ability of juvenile and adult venoms occurs despite both venoms having highly similar proteomic profiles. Both adult and juvenile venoms showed a weak in vitro procoagulant effect on plasma and fibrinogen, underscoring a thrombin-like (pseudo-procoagulant) activity. In vivo, the venoms did not affect the classical clotting tests (prothrombin time and activated partial thromboplastin time) but induced a partial drop in fibrinogen concentration and limited alterations in rotational thromboelastometry parameters when injected by the i.v. route. In contrast, few alterations of these parameters were observed after i.p. injection of venoms, in conditions in which thrombosis occurred, hence evidencing the lack of a consumption coagulopathy. After i.p. injection both venoms induced a pronounced thrombocytopenia. This experimental model reproduces some of the main clinical manifestations of envenoming by this species. This model can be used to identify the toxins responsible for the thrombotic effect, to study the mechanism(s) of thrombosis and to assess the preclinical efficacy of antivenoms and novel therapies. [ABSTRACT FROM AUTHOR]

Background: Multiparametric MRI provides assessment of functional and structural parameters in kidney allografts. It offers a non‐invasive alternative to the current reference standard of kidney biopsy. Purpose: To evaluate the diagnostic and prognostic utility of MRI parameters in the assessment of allograft function in the first 3‐months post‐transplantation. Study Type: Prospective. Subjects: 32 transplant recipients (54 ± 17 years, 20 females), divided into two groups according to estimated glomerular filtration rate (eGFR) at 3‐months post‐transplantation: inferior graft function (IGF; eGFR<45 mL/min/1.73 m2, n = 10) and superior graft function (SGF; eGFR ≥ 45 mL/min/1.73 m2, n = 22). Further categorization was based on the need for hemodialysis (C1) and decrease in s‐creatinine (C2) at 1‐week post‐transplantation: delayed‐graft‐function (DGF: n = 4 C1, n = 10 C2) and early graft‐function (EGF: n = 28 C1, n = 22 C2). Field Strength/Sequence: 3‐T, pseudo‐continuous arterial spin labeling, T1‐mapping, and diffusion‐weighted imaging. Assessment: Multiparametric MRI was evaluated at 1‐week in all patients and 3‐months after transplantation in 28 patients. Renal blood flow (RBF), diffusion coefficients (ADC, ΔADC, D, ∆D, D*, flowing fraction f), T1 and ∆T1 were calculated in cortex and medulla. The diagnostic and prognostic value of these parameters, obtained at 3‐months and 1‐week post‐transplantation, respectively, was evaluated in the cortex to discriminate between DGF and EGF, and between SGF and IGF. Statistical Tests: Logistic regression, receiver‐operating‐characteristics, area‐under‐the‐curve (AUC), confidence intervals (CIs), analysis‐of‐variance, t‐test, Wilcoxon‐Mann–Whitney test, Fisher's exact test, Pearson's correlation. P‐value<0.05 was considered significant. Results: DGF patients exhibited significantly lower cortical RBF and f and higher D*. The diagnostic value of MRI for detecting DGF was excellent (AUC = 100%). Significant differences between patients with IGF and SGF were found in RBF, ∆T1, and ∆D. Multiparametric MRI showed higher diagnostic (AUC = 95.32%; CI: 88%–100%) and prognostic (AUC = 97.47%, CI: 92%–100%) values for detecting IGF than eGFR (AUC = 89.50%, CI: 79%–100%). Data Conclusion: Multiparametric MRI may show high diagnostic and prognostic value in transplanted patients, yielding better results compared to eGFR measurements. Level of Evidence: 2 Technical Efficacy: Stage 1 [ABSTRACT FROM AUTHOR]