Synthesis, structure-activity relationship and solubility improvement studies of potential antimalarial and antischistosomal pyrido[1,2-a]benzimidazoles

In 2016, 216 million malaria cases with 445,000 associated deaths were recorded according to the World Health Organization (WHO). Schistosomiasis also remains a public health issue with 207 million cases recorded globally and 280,000 deaths in the same year. Widespread emergence of parasite resistance to once-effective antimalarial options has rendered currently used drugs ineffective. Moreover, the current WHO-recommended first-line antimalarial drugs in clinical use, the artemisinin combination therapies (ACTs) are faced with the challenges of limited availability, unaffordable cost, and undesirable adverse effects. On the other hand, the treatment of schistosomiasis is severely limited to one treatment regimen, praziquantel (PQZ) which, unfortunately, has recently shown low curing rates in some parts of West Africa. Furthermore, this treatment option is far from ideal because its activity is limited to only adult schistosomes while displaying no activity towards young stages of the liver flukes. These challenges collectively provide a justification for stepping up drug discovery and development efforts aimed at identifying novel, safe and efficacious antimalarial and antischistosomal agents. Whereas, the pyrido[1,2-a]benzimidazole (PBI) scaffold is found in many pharmacologically relevant molecules including Rifaximin, an approved gastrointestinal antibacterial drug, medicinal chemistry explorations around the PBI nucleus have recently identified analogues as novel antimalarial and antischistosomal agents. Additionally, while promising antimalarial efficacy has been demonstrated in animal studies, preliminary in vitro studies of the PBI class of compounds have also demonstrated good activity against Schistosoma parasites. Recently, Mayoka reported the impressive dual antiparasitic potency of the lead compound GMP-19 (figure 1) against Plasmodium and Schistosoma parasites in vitro (IC50 = 0.430 μΜ, drug sensitive strain (NF54) and IC50 = 0.210 μΜ, adult S. mansoni, (unpublished data)). However, GMP-19 and other PBI analogues in this series of compounds, have been beset by poor solubility. Towards addressing solubility issues while retaining and improving antiparasitic activity, in this MSc dissertation, the design, synthesis, structure-activity relationship (SAR) and solubility improvement studies of PBI analogues based on the GMP-19 template are reported. In this regard, chemical modification approaches such as disruption of molecular planarity, increasing saturation, incorporating water solubilizing groups such as the polar-ionizable and the neutralpolar functionalities around the PBI nucleus were adopted. Consequently, we obtained SAR 1analogues after substituting the 4-(trifluoromethoxy)phenyl (4-OCF3Ph) moiety of GMP-19 with assorted α-methyl benzylamines. In addition, the phenyl ring on the left-hand side of the core scaffold was substituted with electron withdrawing groups such as the chloro and fluoro atoms (SAR 1.1 - 1.4), (figure 1). Although some analogues demonstrated a significant loss of antiparasitic activity (> 6.00 μM), strong submicromolar antiparasitic activity was observed with most analogues (IC50 = 0.022 -0.940 μM, PfNF54 and 30 - 69% inhibitory effect at 0.370 μM, against young forms of S. mansoni). Moreover, some analogues demonstrated poor solubility as low as < 10 μM while others showed highly improved solubility as good as 80 μM. In SAR 2.1 - 2.2, the 4-OCF3Ph and the trifluoromethyl (CF3) on the right-hand side (RHS) of the scaffold were fixed while introducing amino moieties (R) on the lipophilic phenyl ring on the left-hand side (LHS) of the PBI core (figure 2). Upon identifying the moiety with the best balance of solubility and biological activity, the 4-OCF3Ph was replaced with various acyclic amino (SAR 2.3) while the CF3 was maintained on C-3 of the core scaffold. Finally, the CF3 was replaced with the 4-CF3Ph (SAR 2.4 and 2.5) while keeping fixed the optimal basic amine and the acyclic amino moieties on the LHS, respectively. Interestingly, the pursued structural modifications delivered analogues with a wide diversity of pharmacological and physicochemical properties. While some analogues demonstrated significant loss of pharmacological activity, others exhibited potent submicromolar antiparasitic activity (IC50 < 0.012 - 0.990 μM, PfNF54 and 0.360 - 0.850 μM, adult S. mansoni). Similarly, some analogues demonstrated poor solubility as low as < 10 μM while others demonstrated improved solubility as good as 180 μM

Epidemiological Tools in Focus: A Comprehensive Assessment of Their Role in Addressing Infectious Disease Challenges in Zambia

In the relentless pursuit of mitigating infectious diseases, this investigative study critically examines the nuanced application and effectiveness of epidemiological tools within the context of Zambia. The study meticulously navigates the landscape of infectious diseases in Zambia, considering its unique ecological and socio-economic features. Employing a rigorous methodology that integrates primary data from epidemiological reports, field observations, and laboratory analyses with insights from diverse scientific literature, the study investigates the types and applications of epidemiological tools such as spatial analysis, case-control studies, molecular epidemiology, and serological assays. Unfolding the challenges posed by resource constraints, data reliability issues, and the dynamic nature of infectious diseases in Zambia, the study offers a comprehensive assessment that extends to the implications of these tools for informed public health decision-making. This scholarly inquiry concludes by affirming the significance of ongoing refinement and adaptation of epidemiological tools, emphasizing their pivotal role in addressing infectious disease challenges within Zambia and advocating for their continued enhancement on the global public health stage

Multicriteria Risk Ranking of Zoonotic Diseases in a Developing Country: A Case Study of Zambia

The integration of a multicriteria decision analysis approach, including techniques such as the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), has yielded valuable insights in the realm of zoonotic disease risk assessment. This analytical framework draws from the OIE-supported manual, utilizing impact assessments, transmission pathways, and categorizations as provided by the OIE itself. Moreover, the consideration of specific zoonotic disease scenarios tailored to individual countries enhances the contextual relevance of the analysis. Through this approach, the ranking of zoonotic diseases is systematically established, offering a comprehensive evaluation of their potential impacts and risks. This methodology encompasses pivotal criteria, including prevalence, economic impact, health impact, transmission pathways, and healthcare capacity, collectively offering a holistic perspective that mirrors the intricate nature of zoonotic diseases. The resultant rankings, derived from both ECDC and OIE data, illuminate diseases that harbor significant threats to both human and animal populations. This ranking fosters the identification of diseases with potential for rapid spread and substantial impact, guiding resource allocation towards prevention, control, and mitigation strategies. The alignment between ECDC and OIE rankings underscores the robustness of the applied methodology, with Plague and Zoonotic TB consistently emerging as high-ranking diseases, reinforcing their acknowledged significance. A consolidated ranking, amalgamating data from both sources, provides an insightful overview of potential risks linked to various zoonotic diseases. Plague, Zoonotic TB, Brucellosis, Trypanosomiasis, and Rabies consistently occupy top positions, presenting a valuable instrument for policymakers, public health officials, and stakeholders in prioritizing resource allocation and intervention strategies. The implementation of a multicriteria decision analysis approach, integrating AHP and TOPSIS methodologies, underpins the generation of informed rankings for Zambian zoonotic diseases. The intricate interplay of criteria like prevalence, economic impact, health impact, transmission pathways, and healthcare capacity forms a comprehensive framework for evaluating the potential risks of diverse diseases. The ensuing ranking, led by Plague and succeeded by Anthrax, Rabies, and others, mirrors their collective risk scores calculated via the adopted methodology. This approach empowers strategic decision-making by pinpointing diseases with heightened potential for adverse impacts on both human and animal populations. The rankings serve as invaluable aids in directing resources, devising strategic interventions, and formulating targeted measures for prevention and control. However, acknowledgment of the dynamic disease landscape and the imperative of adaptive strategies underscores the ongoing importance of monitoring and managing zoonotic diseases effectively in Zambia. By amalgamating data from authoritative sources and embracing a systematic, evidence-based approach, this study accentuates the necessity of addressing zoonotic diseases with a holistic lens, fostering proactive perspectives that augment public health and avert future outbreaks

Advances in Artificial Intelligence for Infectious Disease Surveillance in Livestock in Zambia

The global livestock industry grapples with formidable challenges stemming from the escalation and dissemination of infectious diseases. Zambia, an agricultural cornerstone where livestock is pivotal for economic sustenance and food security, confronts the imperative task of effectually surveilling and managing infectious diseases. This study investigates into the possibilities of the application of artificial intelligence (AI) for infectious disease surveillance in the Zambian livestock sector. The study meticulously scrutinizes the prevailing state of infectious disease surveillance, evaluates the latent capabilities of AI technologies, and critically discusses the intricate landscape of challenges and opportunities entailed in their implementation. In the intricate tapestry of Zambia\u27s economy, livestock farming assumes a central and irreplaceable role, contributing substantially to the well-being and livelihoods of a significant portion of the populace. However, the omnipresent specter of infectious diseases perpetually menaces livestock health, casting a shadow on productivity and economic equilibrium. Conventional methodologies in disease surveillance exhibit inherent shortcomings, characterized by delays in reporting and inherent inaccuracies. This study is an exploration of possibilities of the AI applications designed to fortify infectious disease surveillance within Zambia\u27s livestock domain. The infusion of AI technologies holds the transformative potential to reshape disease monitoring paradigms, enabling early detection and facilitating swift response strategies in the face of emerging threats. The ensuing critical analysis navigates the intricate terrain of the application of AI in the Zambian livestock context, shedding light on its promising prospects, while pragmatically addressing the hurdles that may accompany its incorporation

How much control do smallholder maize farmers have over yield?

Smallholder agriculture is critical for current and future food security, yet quantifying the sources of smallholder yield variance remains a major challenge. Attributing yield variance to farmer management, as opposed to soil and weather constraints, is an important step to understanding the impact of farmer decision-making, in a context where smallholder farmers use a wide range of management practices and may have limited access to fertilizer. This study used a process-based crop model to simulate smallholder maize (Zea mays) yield at the district-level in Zambia and quantify the percent of yield variance (effect size) attributed to soil, weather, and three management inputs (cultivar, fertilizer, planting date). Effect sizes were calculated via an ANOVA variance decomposition. Further, to better understand the treatment effects of management practices, effect sizes were calculated both for all years combined and for individual years. We found that farmer management decisions explained 27–82 % of total yield variance for different agro-ecological regions in Zambia, primarily due to fertilizer impact. Fertilizer explained 45 % of yield variance for the average district, although its effect was much larger in northern districts of Zambia that typically have higher precipitation, where it explained 72 % of yield variance on average. When fixing a specific fertilizer amount, the “low-cost” management options of varying planting dates and cultivars explained 20–28 % of yield variance, with some regional variation. To better understand why management practices impact yield more in particular years, we performed a correlation analysis comparing yearly management effect sizes with four meteorologically based variables: total growing season precipitation, rainy season onset, extreme heat degree days, and longest dry spell. Results showed that fertilizer's impact generally increased under favorable weather conditions, and planting date's impact increased under adverse weather conditions. This study demonstrates how a national yield variance decomposition can be used to understand where specific management interventions would have a greater impact and can provide policymakers with quantification of soil, weather, and management effects. In addition, the variance composition can easily be adapted to a different range of management inputs, such as other cultivars or fertilizer quantities, and can also be used to assess the effect size of management adaptations under climate change.</p

How much control do smallholder maize farmers have over yield?

Smallholder agriculture is critical for current and future food security, yet quantifying the sources of smallholder yield variance remains a major challenge. Attributing yield variance to farmer management, as opposed to soil and weather constraints, is an important step to understanding the impact of farmer decision-making, in a context where smallholder farmers use a wide range of management practices and may have limited access to fertilizer. This study used a process-based crop model to simulate smallholder maize (Zea mays) yield at the district-level in Zambia and quantify the percent of yield variance (effect size) attributed to soil, weather, and three management inputs (cultivar, fertilizer, planting date). Effect sizes were calculated via an ANOVA variance decomposition. Further, to better understand the treatment effects of management practices, effect sizes were calculated both for all years combined and for individual years. We found that farmer management decisions explained 27–82 % of total yield variance for different agro-ecological regions in Zambia, primarily due to fertilizer impact. Fertilizer explained 45 % of yield variance for the average district, although its effect was much larger in northern districts of Zambia that typically have higher precipitation, where it explained 72 % of yield variance on average. When fixing a specific fertilizer amount, the “low-cost” management options of varying planting dates and cultivars explained 20–28 % of yield variance, with some regional variation. To better understand why management practices impact yield more in particular years, we performed a correlation analysis comparing yearly management effect sizes with four meteorologically based variables: total growing season precipitation, rainy season onset, extreme heat degree days, and longest dry spell. Results showed that fertilizer’s impact generally increased under favorable weather conditions, and planting date’s impact increased under adverse weather conditions. This study demonstrates how a national yield variance decomposition can be used to understand where specific management interventions would have a greater impact and can provide policymakers with quantification of soil, weather, and management effects. In addition, the variance composition can easily be adapted to a different range of management inputs, such as other cultivars or fertilizer quantities, and can also be used to assess the effect size of management adaptations under climate change. La agricultura en pequeña escala es fundamental para la seguridad alimentaria actual y futura, pero cuantificar las fuentes de variación del rendimiento de los pequeños agricultores sigue siendo un desafío importante. Atribuir la variación del rendimiento a la gestión de los agricultores, en contraposición a las limitaciones del suelo y el clima, es un paso importante para comprender el impacto de la toma de decisiones de los agricultores, en un contexto en el que los pequeños agricultores utilizan una amplia gama de prácticas de gestión y pueden tener un acceso limitado a los fertilizantes. Este estudio utilizó un modelo de cultivo basado en procesos para simular el rendimiento del maíz (Zea mays) de los pequeños agricultores a nivel de distrito en Zambia y cuantificar el porcentaje de variación del rendimiento (tamaño del efecto) atribuido al suelo, el clima y tres insumos de manejo (cultivar, fertilizante, fecha de siembra). Los tamaños del efecto se calcularon mediante una descomposición de la varianza ANOVA. Además, para comprender mejor los efectos del tratamiento de las prácticas de gestión, se calcularon los tamaños del efecto tanto para todos los años combinados como para años individuales. Descubrimos que las decisiones de gestión de los agricultores explicaban entre el 27 % y el 82 % de la variación total del rendimiento en diferentes regiones agroecológicas de Zambia, principalmente debido al impacto de los fertilizantes. El fertilizante explicó el 45 % de la variación del rendimiento en el distrito promedio, aunque su efecto fue mucho mayor en los distritos del norte de Zambia que normalmente tienen mayores precipitaciones, donde explicó el 72 % de la variación del rendimiento en promedio. Al fijar una cantidad específica de fertilizante, las opciones de manejo de “bajo costo” de variar las fechas de siembra y los cultivares explicaron entre el 20% y el 28% de la variación del rendimiento, con alguna variación regional. Para comprender mejor por qué las prácticas de manejo impactan más el rendimiento en años particulares, realizamos un análisis de correlación comparando los tamaños del efecto de manejo anual con cuatro variables meteorológicas: precipitación total de la temporada de crecimiento, inicio de la temporada de lluvias, grados día de calor extremo y la racha seca más larga. Los resultados mostraron que el impacto de los fertilizantes generalmente aumentó bajo condiciones climáticas favorables, y el impacto de la fecha de siembra aumentó bajo condiciones climáticas adversas. Este estudio demuestra cómo se puede utilizar una descomposición de la varianza del rendimiento nacional para comprender dónde las intervenciones de manejo específicas tendrían un mayor impacto y puede proporcionar a los responsables de políticas la cuantificación de los efectos del suelo, el clima y el manejo. Además, la composición de la varianza se puede adaptar fácilmente a una gama diferente de insumos de manejo, como otros cultivares o cantidades de fertilizantes, y también se puede utilizar para evaluar el tamaño del efecto de las adaptaciones de manejo bajo el cambio climático.Centro de Investigación en Economía y ProspectivaFil: Cecil, Michael. Clark University. Department of Geography; Estados UnidosFil: Chilenga, Allan. Zambia Agriculture Research Institute (ZARI). Ministry of Agriculture. Mount Makulu Central Research Station; ZambiaFil: Chisanga, Charles. Copperbelt University. School of Natural Resources. Department of Plant & Environmental Sciences; ZambiaFil: Gatti, Nicolás. Instituto Nacional de Tecnología Agropecuaria (INTA). Centro de Investigación en Economía y Prospectiva (CIEP); ArgentinaFil: Gatti, Nicolás. Universidad del Centro de Estudios Macroeconómicos de Argentina (UCEMA); ArgentinaFil: Krell, Natasha. University of California Santa Barbara. Department of Geography; Estados UnidosFil: Vergopolan, Noemi. Princeton University. Atmospheric and Oceanic Sciences Program; Estados UnidosFil: Vergopolan, Noemi. NOAA Geophysical Fluid Dynamics Laboratory; Estados UnidosFil: Baylis, Kathy. University of California Santa Barbara. Department of Geography; Estados UnidosFil: Caylor, Kelly. University of California Santa Barbara. Department of Geography; Estados UnidosFil: Evans, Tom. University of Arizona. School of Geography, Development & Environment; Estados UnidosFil: Konar, Megan. University of Illinois Urbana-Champaign. Department of Civil and Environmental Engineering, Newmark Civil Engineering Laboratory; Estados UnidosFil: Sheffield, Justin. University of Southampton. Department of Geography and Environmental Science; Reino UnidoFil: Estes, Lyndon. Clark University. Department of Geography; Estados Unido

Benzimidazole derivatives are potent against multiple life cycle stages of Plasmodium falciparum malaria parasites

The continued emergence of resistance to front-line antimalarial treatments is of great concern. Therefore, new compounds that potentially have a novel target in various developmental stages of Plasmodium parasites are needed to treat patients and halt the spread of malaria. Here, several benzimidazole derivatives were screened for activity against the symptom-causing intraerythrocytic asexual blood stages and the transmissible gametocyte stages of P. falciparum. Submicromolar activity was obtained for 54 compounds against asexual blood stage parasites with 6 potent at IC50 < 100 nM while not displaying any marked toxicity against mammalian cells. Nanomolar potency was also observed against gametocytes with two compounds active against early stage gametocytes and two compounds active against late-stage gametocytes. The transmission-blocking potential of the latter was confirmed as they could prevent male gamete exflagellation and the lead compound reduced transmission by 72% in an in vivo mosquito feeding model. These compounds therefore have activity against multiple stages of Plasmodium parasites with potential for differential targets.Supporting Information 1 : Figure S1: screening cascade; chemical and spectroscopic information on new compounds (PDF)Supporting Information 2 : Summary of all data for all in vitro experiments (XLSX)https://pubs.acs.org/journal/aidcbchj2021BiochemistryGeneticsMicrobiology and Plant PathologyUP Centre for Sustainable Malaria Control (UP CSMC