DL Brasaemle
Nov 1, 1997; 38:2249-2263
Articles

Expert

Prioritizing equity and justice in climate action 30 June 2021 — 11:00AM TO 12:00PM Anonymous (not verified) 10 June 2021 Online

London Climate Action Week event: Why understanding equity and justice is essential to the ability to meaningfully inform climate politics.

Citizen-led climate activism is demonstrating the need to think about climate change ‘not just as a problem for science to solve’ but also as a problem of equity, human rights and justice.

The disproportionate impacts of climate change on the poor and the marginalized across the world means that understanding equity and justice is essential for the ability to meaningfully inform climate politics.

Excluding these issues risks ignoring, or intentionally omitting, the consequences of policies, tools and frameworks on those who are most likely to face the severe costs of any climate action or inaction.

In a pivotal year for climate decision-making, this event explores the necessity of equity and justice in climate action and how the world can move the political conversation to one that is more inclusive.

The speakers explore how communities themselves articulate the justice dimensions of climate change and how fairness can create a greener future for current and future generations.

This event is being hosted as a part of Strengthening Climate Diplomacy, a series of events from Chatham House during London Climate Action Week 2021.

Artificial Intelligence Apps Risk Entrenching India’s Socio-economic Inequities Expert comment sysadmin 14 March 2018

Artificial intelligence applications will not be a panacea for addressing India’s grand challenges. Data bias and unequal access to technology gains will entrench existing socio-economic fissures.

Artificial intelligence (AI) is high on the Indian government’s agenda. Some days ago, Prime Minister Narendra Modi inaugurated the Wadhwani Institute for Artificial Intelligence, reportedly India’s first research institute focused on AI solutions for social good. In the same week, Niti Aayog CEO Amitabh Kant argued that AI could potentially add $957 billion to the economy and outlined ways in which AI could be a ‘game changer’.

During his budget speech, Finance Minister Arun Jaitley announced that Niti Aayog would spearhead a national programme on AI; with the near doubling of the Digital India budget, the IT ministry also announced the setting up of four committees for AI-related research. An industrial policy for AI is also in the pipeline, expected to provide incentives to businesses for creating a globally competitive Indian AI industry.

Narratives on the emerging digital economy often suffer from technological determinism — assuming that the march of technological transformation has an inner logic, independent of social choice and capable of automatically delivering positive social change. However, technological trajectories can and must be steered by social choice and aligned with societal objectives. Modi’s address hit all the right notes, as he argued that the ‘road ahead for AI depends on and will be driven by human intentions’. Emphasising the need to direct AI technologies towards solutions for the poor, he called upon students and teachers to identify ‘the grand challenges facing India’ – to ‘Make AI in India and for India’.

To do so, will undoubtedly require substantial investments in R&D, digital infrastructure and education and re-skilling. But, two other critical issues must be simultaneously addressed: data bias and access to technology gains.

While computers have been mimicking human intelligence for some decades now, a massive increase in computational power and the quantity of available data are enabling a process of ‘machine learning.’ Instead of coding software with specific instructions to accomplish a set task, machine learning involves training an algorithm on large quantities of data to enable it to self-learn; refining and improving its results through multiple iterations of the same task. The quality of data sets used to train machines is thus a critical concern in building AI applications.

Much recent research shows that applications based on machine learning reflect existing social biases and prejudice. Such bias can occur if the data set the algorithm is trained on is unrepresentative of the reality it seeks to represent. If for example, a system is trained on photos of people that are predominantly white, it will have a harder time recognizing non-white people. This is what led a recent Google application to tag black people as gorillas.

Alternatively, bias can also occur if the data set itself reflects existing discriminatory or exclusionary practices. A recent study by ProPublica found for example that software that was being used to assess the risk of recidivism in criminals in the United States was twice as likely to mistakenly flag black defendants as being at higher risk of committing future crimes.

The impact of such data bias can be seriously damaging in India, particularly at a time of growing social fragmentation. It can contribute to the entrenchment of social bias and discriminatory practices, while rendering both invisible and pervasive the processes through which discrimination occurs. Women are 34 per cent less likely to own a mobile phone than men – manifested in only 14 per cent of women in rural India owning a mobile phone, while only 30 per cent of India’s internet users are women.

Women’s participation in the labour force, currently at around 27 per cent, is also declining, and is one of the lowest in South Asia. Data sets used for machine learning are thus likely to have a marked gender bias. The same observations are likely to hold true for other marginalized groups as well.

Accorded to a 2014 report, Muslims, Dalits and tribals make up 53 per cent of all prisoners in India; National Crime Records Bureau data from 2016 shows in some states, the percentage of Muslims in the incarcerated population was almost three times the percentage of Muslims in the overall population. If AI applications for law and order are built on this data, it is not unlikely that it will be prejudiced against these groups.

(It is worth pointing out that the recently set-up national AI task force is comprised of mostly Hindu men – only two women are on the task force, and no Muslims or Christians. A recent article in the New York Times talked about AI’s ‘white guy problem’; will India suffer from a ‘Hindu male bias’?)

Yet, improving the quality, or diversity, of data sets may not be able to solve the problem. The processes of machine learning and reasoning involve a quagmire of mathematical functions, variables and permutations, the logic of which are not readily traceable or predictable. The dazzle of AI-enabled efficiency gains must not blind us to the fact that while AI systems are being integrated into key socio-economic systems, their accuracy and logic of reasoning have not been fully understood or studied.

The other big challenge stems from the distribution of AI-led technology gains. Even if estimates of AI contribution to GDP are correct, the adoption of these technologies is likely to be in niches within the organized sector. These industries are likely to be capital- rather than labour-intensive, and thus unlikely to contribute to large-scale job creation.

At the same time, AI applications can most readily replace low- to medium-skilled jobs within the organized sector. This is already being witnessed in the outsourcing sector – where basic call and chat tasks are now automated. Re-skilling will be important, but it is unlikely that those who lose their jobs will also be those who are being re-skilled – the long arch of technological change and societal adaptation is longer than that of people’s lives. The contractualization of work, already on the rise, is likely to further increase as large industries prefer to have a flexible workforce to adapt to technological change. A shift from formal employment to contractual work can imply a loss of access to formal social protection mechanisms, increasing the precariousness of work for workers.

The adoption of AI technologies is also unlikely in the short- to medium-term in the unorganized sector, which engages more than 80 per cent of India’s labor force. The cost of developing and deploying AI applications, particularly in relation to the cost of labour, will inhibit adoption. Moreover, most enterprises within the unorganized sector still have limited access to basic, older technologies – two-thirds of the workforce are employed in enterprises without electricity. Eco-system upgrades will be important but incremental. Given the high costs of developing AI-based applications, most start-ups are unlikely to be working towards creating bottom-of-the-pyramid solutions.

Access to AI-led technology gains is thus likely to be heavily differentiated – a few high-growth industries can be expected, but these will not necessarily result in the welfare of labour. Studies show that labour share of national income, especially routine labour, has been declining steadily across developing countries.

We should be clear that new technological applications themselves are not going to transform or disrupt this trend – rather, without adequate policy steering, these trends will be exacerbated.

Policy debates about AI applications in India need to take these two issues seriously. AI applications will not be a panacea for addressing ‘India’s grand challenges’. Data bias and unequal access to technology gains will entrench existing socio-economic fissures, even making them technologically binding.

In addition to developing AI applications and creating a skilled workforce, the government needs to prioritize research that examines the complex social, ethical and governance challenges associated with the spread of AI-driven technologies. Blind technological optimism might entrench rather than alleviate the grand Indian challenge of inequity and growth.

This article was originally published in the Indian Express.

Ryan J Lumpkin
Dec 2, 2020; 0:RA120.002414v1-mcp.RA120.002414
Research

The glucagon receptor (GCGR) activated by the peptide hormone glucagon is a seven-transmembrane G protein–coupled receptor (GPCR) that regulates blood glucose levels. Ubiquitination influences trafficking and signaling of many GPCRs, but its characterization for the GCGR is lacking. Using endocytic colocalization and ubiquitination assays, we have identified a correlation between the ubiquitination profile and recycling of the GCGR. Our experiments revealed that GCGRs are constitutively ubiquitinated at the cell surface. Glucagon stimulation not only promoted GCGR endocytic trafficking through Rab5a early endosomes and Rab4a recycling endosomes, but also induced rapid deubiquitination of GCGRs. Inhibiting GCGR internalization or disrupting endocytic trafficking prevented agonist-induced deubiquitination of the GCGR. Furthermore, a Rab4a dominant negative (DN) that blocks trafficking at recycling endosomes enabled GCGR deubiquitination, whereas a Rab5a DN that blocks trafficking at early endosomes eliminated agonist-induced GCGR deubiquitination. By down-regulating candidate deubiquitinases that are either linked with GPCR trafficking or localized on endosomes, we identified signal-transducing adaptor molecule–binding protein (STAMBP) and ubiquitin-specific protease 33 (USP33) as cognate deubiquitinases for the GCGR. Our data suggest that USP33 constitutively deubiquitinates the GCGR, whereas both STAMBP and USP33 deubiquitinate agonist-activated GCGRs at early endosomes. A mutant GCGR with all five intracellular lysines altered to arginines remains deubiquitinated and shows augmented trafficking to Rab4a recycling endosomes compared with the WT, thus affirming the role of deubiquitination in GCGR recycling. We conclude that the GCGRs are rapidly deubiquitinated after agonist-activation to facilitate Rab4a-dependent recycling and that USP33 and STAMBP activities are critical for the endocytic recycling of the GCGR.

Cullin RING E3 Ligases (CRLs) ubiquitylate hundreds of important cellular substrates. Here we have assembled and purified the Ankyrin repeat and SOCS Box protein 9 CUL5 RBX2 Ligase (ASB9-CRL) in vitro and show how it ubiquitylates one of its substrates, CKB. CRLs occasionally collaborate with RING between RING E3 ligases (RBRLs) and indeed, mass spectrometry analysis showed that CKB is specifically ubiquitylated by the ASB9-CRL-ARIH2-UBE2L3 complex. Addition of other E2s such as UBE2R1 or UBE2D2 contribute to polyubiquitylation but do not alter the sites of CKB ubiquitylation. Hydrogen-deuterium exchange mass spectrometry (HDX-MS) analysis revealed that CUL5 neddylation allosterically exposes its ARIH2 binding site, promoting high affinity binding, and it also sequesters the NEDD8 E2 (UBE2F) binding site on RBX2. Once bound, ARIH2 helices near the Ariadne domain active site are exposed, presumably relieving its autoinhibition. These results allow us to propose a model of how neddylation activates ASB-CRLs to ubiquitylate their substrates.

Archbishop of Canterbury Justin Welby has opted to quit as head of the Church of England after a critical report over his handling of an abuse scandal, it was announced.

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Recent Census data finds households in the South and Midwest lagging those in other regions in access to remote learning technologies and learning interactions with teachers and family members.

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Recent Census data finds households in the South and Midwest lagging those in other regions in access to remote learning technologies and learning interactions with teachers and family members.

To understand the circuitry of the brain, it is often advantageous to visualize the processes of a single neuron or population of neurons. Identifying sites where a neuron, or neurons, originates and where it projects can allow a researcher to begin to map the circuitry underlying various processes, including sensory-guided behaviors. Furthermore, neural tracing allows one to map locations where processes terminate onto regions of the brain that may have known functions and sometimes to identify candidate upstream or downstream connections, based on proximity. Many methods of neural tracing are available; here, we focus on loading fluorescent dyes into a neuron (fluorescent dye filling). Different options for dyes exist to label neurites. Among the most versatile and easy to use are dextran amine–conjugated dyes. They fill neurons bidirectionally, not discriminating between anterograde or retrograde loading direction. Dye filling must be done in unfixed tissue, as the dye needs to move through the neurons; however, dextran amine conjugates are aldehyde-fixable and once cells have been fully loaded with dye the tissue can be fixed and subjected to immunostaining. Coupling neural tracing with immunofluorescence is a useful way to determine specific brain or ventral nerve cord (VNC) regions where a neuron projects. This protocol describes methods for loading dextran amine conjugated dyes into a sensory tissue in the mosquito to visualize sites of sensory neuron innervation in the central nervous system, as well as efferent projections to these structures. This protocol is described for Aedes aegypti, for which it was optimized, but it also works across a variety of insects.

Mosquito-borne disease is a major global public health issue. One path toward the development of evidence-based strategies to limit mosquito biting is the study of the mosquito nervous system—in particular, the sensory systems that drive biting behavior. The central nervous system of insects consists of the brain and the ventral nerve cord. Here, we describe a protocol for dissecting, immunofluorescent labeling, and imaging both of these structures in the mosquito. This protocol was optimized for Aedes aegypti and works well on Anopheles gambiae tissue. It has not been tested in other mosquito species, but we anticipate that it would work on a range of mosquitoes, and, if not, our protocol will provide a starting point from which to optimize. Notably, a limited number of antibodies cross-react with Ae. aegypti proteins. This protocol is intended for use with validated antibodies and can also be used to test new antibodies as they are generated. It has been successfully used to visualize protein tags, such as green fluorescent protein, that have been introduced into the mosquito to amplify or detect their presence.

Laboratory study of field-collected mosquitoes can allow researchers to better understand the ways variation within and among mosquito populations shapes burdens of mosquito-borne disease. The Anopheles gambiae complex comprises the most important vectors of malaria, but it can be challenging to keep in the laboratory. For some species of mosquitoes, especially An. gambiae, it is very difficult to bring viable eggs into the laboratory. Instead, it is preferable to collect larvae or pupae and then transport them as carefully as possible back to the laboratory. This simple protocol allows a researcher to start new laboratory colonies from larvae or pupae collected from natural breeding sites or proceed directly to their planned experiments. The use of natural breeding sites provides additional reassurance that the resulting colonies are representative of natural populations.

In insects, gustatory neurons sense chemicals upon contact and directly inform many behaviors critical for survival and reproduction, including biting, feeding, mating, and egg laying. However, the taste sensory system is underexplored in many anthropophilic disease vectors such as mosquitoes, which acquire and transmit human pathogens during blood feeding from human hosts. This results in a big gap in vector biology—the study of organisms that spread disease by transmitting pathogens—because insect vectors closely interact with humans while selecting suitable individuals and appropriate bite sites for blood meals. Human sweat and skin-associated chemistries are rich in nonvolatile compounds that can be sensed by the mosquito's taste system when she lands on the skin. Taste sensory units, called sensilla, are distributed in many organs across the mosquito body, including the mouthparts, legs, and ovipositors (female-specific structures used to lay eggs). Each sensillum is innervated by as many as five taste neurons, which allow detection and discrimination between various tastants such as water, sugars, salts, amino acids, and plant-derived compounds that taste bitter to humans. Single-sensillum recordings provide a robust way to survey taste responsiveness of individual sensilla to various diagnostic and ecologically relevant chemicals. Such analyses are of immense value for understanding links between mosquito taste responses and behaviors to specific chemical cues and can provide insights into why mosquitoes prefer certain hosts. The results can also aid development of strategies to disrupt close-range mosquito–human interactions to control disease transmission. Here we describe a protocol that is curated for electrophysiological recordings from taste sensilla in mosquitoes and sure to yield exciting results for the field.

Mosquitoes take blood meals from a diverse range of host animals and their host associations vary by species. Characterizing these associations is an important element of the transmission dynamics of mosquito-vectored pathogens. To characterize mosquito host associations, various molecular techniques have been developed, which are collectively referred to as blood meal analysis. DNA barcoding has diverse biological applications and is well-suited to mosquito blood meal analysis. The standard DNA barcoding marker for animals is a 5' fragment of the cytochrome c oxidase I (COI) gene. A major advantage of this marker is its taxonomic coverage in DNA sequence reference databases, making it feasible to identify a wider range of mosquito host species than with any other gene. However, the COI gene contains high sequence variation at potential priming sites between vertebrate orders. Coupled with the need for primer sequences to be mismatched with mosquito priming sites so that annealing to mosquito DNA is inhibited, it can be difficult to design primers suitable for blood meal analysis applications. Several primers are available that perform well in mosquito blood meal analysis, annealing to priming sites for most vertebrate host taxa, but not to those of mosquitoes. Because priming site sequence variation among vertebrate taxa can cause amplification to fail, a hierarchical approach to DNA barcoding-based blood meal analysis can be applied. In such an approach, no single primer set is expected to be effective for 100% of potential host species. If amplification fails in the initial reaction, a subsequent reaction is attempted with primers that anneal to different priming sites, and so on, until amplification is successful.

Mosquito species vary in their host associations. Although some species are relative generalists, most specialize, to varying extents, on particular types of host animals. Mosquito host associations are among the most important factors that influence the transmission dynamics of mosquito-vectored pathogens, and understanding these associations can provide insight on how such pathogens move within ecosystems. Characterization of the host associations of mosquito species requires applying blood meal analysis to the largest possible sample size of mosquito blood meals. Processing large samples of mosquito blood meals can be time-consuming, especially when chain-termination sequencing is used, necessitating individual processing of each specimen. Various methods and commercially available kits and products are available for extracting DNA from mosquito blood meals. The hot sodium hydroxide and Tris (HotSHOT) method is a rapid and inexpensive method of DNA extraction that is compatible with the recovery of DNA from mosquito blood meals preserved on QIAcard Flinders Technology Associates (FTA) Classic Cards (FTA cards). FTA cards allow nucleic acids found in blood meals to be preserved easily, even in field conditions. DNA prepared using this method is suitable for polymerase chain reaction (PCR)-based blood meal analysis.

All PCR- and DNA-based blood meal analyses require host DNA from a mosquito blood meal to be effectively preserved between the time when the specimen is collected and the extraction of DNA. As soon as a mosquito ingests blood from a host animal, digestion of host cells and cellular components within the blood meal by enzymes in the mosquito midgut begins to degrade the host DNA templates that are the targets of polymerase chain reaction (PCR) amplification. Without effective preservation, host DNA is typically undetectable by PCR 48 h after feeding, because of digestion. Preservation methods for mosquito blood meals vary in their efficacy, and the logistics of fieldwork can limit the options for preservation of blood meals and maintenance of the integrity of host DNA. This protocol describes a method of blood meal preservation that is effective, convenient, and amenable to fieldwork in remote locations where cryopreservation at –20°C or –80°C may not be feasible. It uses a Flinders Technology Associates (FTA) card, which is a chemically treated card that lyses cells and allows nucleic acids to be preserved. This method is also expected to preserve the DNA or RNA of pathogens present within the engorged mosquito abdomen, including RNA viruses.

The insect eggshell is a multifunctional structure with several important roles, including generating an entry point for sperm via the micropyle before oviposition, serving as an oviposition substrate attachment surface, and functioning as a protective layer during embryo development. Eggshell proteins play major roles in eggshell tanning and hardening following oviposition and provide molecular cues that define dorsal–ventral axis formation. Precise eggshell formation during ovarian follicle maturation is critical for normal embryo development and the synthesis of a defective eggshell often gives rise to inviable embryos. Therefore, simple and accurate methods for identifying eggshell proteins will facilitate our understanding of the molecular pathways regulating eggshell formation and the mechanisms underlying normal embryo development. This protocol describes how to isolate and enrich eggshells from mature oocytes of Aedes aegypti mosquitoes and how to extract their eggshell proteins for liquid chromatography with tandem mass spectrometry (LC–MS/MS) proteomic analysis. Although this methodology was developed for studying mosquito eggshells, it may be applicable to eggs from a variety of insects. Mosquitoes are ideal model organisms for this study as their ovarian follicle development and eggshell formation are meticulously regulated by blood feeding and their follicles develop synchronously throughout oogenesis in a time-dependent manner.

In insects, oocyte resorption (oosorption) or follicular atresia is one of the key physiological processes and evolutionary strategies used to optimize reproductive fitness. Mosquitoes are ideal model organisms for studying egg maturation in arthropods, as their follicle development is initiated only following the ingestion of a blood meal, followed by a carefully orchestrated series of hormonally regulated events leading to egg maturation. A cohort of approximately 100 follicles per mosquito ovary begin developing synchronously. However, a significant fraction of follicles ultimately undergo apoptosis and oosorption, especially when available resources from the blood meal are limited. Therefore, simple, rapid, and reliable techniques to accurately evaluate follicular atresia are necessary to understand mechanisms underlying follicle development in insects. This protocol describes how to detect apoptotic follicle cells within the Aedes aegypti mosquito ovaries using a commercially available fluorescent-labeled inhibitor of caspases (FLICA). Caspases are key players in animal apoptosis. In this assay, the FLICA reagent enters the intracellular compartment of follicles in dissected mosquito ovaries and covalently binds to active caspases. The bound reagent remains within the cell and its fluorescent signal can be observed by confocal microscopy. Although this method was specifically developed for visualizing apoptotic ovarian follicles during Ae. aegypti mosquito egg development, it should be applicable to other mosquito tissues that undergo caspase-mediated program cell death in a time-dependent manner.

Transposon-mediated transgenesis has revolutionized both basic and applied studies of mosquito vectors of disease. Currently, techniques such as enhancer traps and transposon tagging, which rely on remobilizable insertional mutagenesis, are only possible with transposon-based vector systems. Here, we provide general descriptions of methods and applications of transposon-based mosquito transgenesis. The exact procedures must be adapted to each mosquito species and comparisons of some differences among different mosquito species are outlined. A number of excellent publications showing detailed and specific protocols and methods are featured and referenced.

Advocates say pay equity laws, while needed, often do not help the most vulnerable workers.

Is a Fed rate hike in March a certainty? If the correction in equity markets is prolonged, the central bank could decide to postpone any increase until June.

Mosquitoes transmit deadly pathogens from person to person as they obtain the blood meal that is essential for their life cycle. Female mosquitoes of many species are unable to reproduce without consuming protein that they obtain from blood. This developmental stage makes them highly efficient disease vectors of deadly pathogens. They can transmit pathogens between members of the same species and different species that can provide a route for evolving zoonotic viruses to jump from animals to humans. One possible way to develop novel strategies to combat pathogen transmission by mosquitoes is to study the sensory systems that drive mosquito reproductive behaviors, in particular the neural architecture and circuits of mosquito sensory afferent neurons, the central circuits that process sensory information, and the downstream circuits that drive reproductive behaviors. The study of mosquito neuroanatomy and circuitry also benefits basic neuroscience, allowing for comparative neuroanatomy in insect species, which has great value in the current model species-heavy landscape of neuroscience. Here, we introduce two important techniques that are used to study neuroanatomy and neural circuitry—namely, immunofluorescent labeling and neural tracing. We describe how to apply these approaches to study mosquito neuroanatomy and describe considerations for researchers using the techniques.

A researcher may have many reasons for wanting to establish new laboratory colonies from field-collected mosquitoes. In particular, the ability to study the diversity found within and among natural populations in a controlled laboratory environment opens up a wide range of possibilities for understanding how and why burdens of vector-borne disease vary over space and time. However, field-collected mosquitoes are often more difficult to work with than established laboratory strains, and considerable logistical challenges are involved in safely transporting field-collected mosquitoes into the laboratory. Here, we provide advice for researchers working with Aedes aegypti, Anopheles gambiae, and Culex pipiens, as well as notes on other closely related species. We provide guidance on each stage of the life cycle and highlight the life stages for which it is easiest to initiate new laboratory colonies for each species. In accompanying protocols, we provide methods detailing Ae. aegypti egg collection and hatching as well as how to transport larvae and pupae from the field.

CRISPR–Cas9 has revolutionized gene editing for traditional and nontraditional model organisms alike. This tool has opened the door to new mechanistic studies of basic mosquito biology as well as the development of novel vector control strategies based on CRISPR–Cas9, including gene drives that spread genetic elements in the population. Although the promise of the specificity, flexibility, and ease of deployment CRISPR is real, its implementation still requires empirical optimization for each new species of interest, as well as to each genomic target within a given species. Here, we provide an overview of designing and testing single-guide RNAs for the use of CRISPR-based gene editing tools.

Analysis of taste sensory responses has been a powerful approach for understanding principles of taste detection and coding. The shared architecture of external taste sensing units, called sensilla, in insects opened up the study of tastant-evoked responses in any model of choice using a single-sensillum tip recording method that was developed in the mid-1900s. Early studies in blowflies were instrumental for identifying distinct taste neurons based on their responses to specific categories of chemicals. Broader system-wide analyses of whole organs have since been performed in the genetic model insect Drosophila melanogaster, revealing principles of stereotypical organization and function that appear to be evolutionarily conserved. Although limited in scope, investigations of taste sensory responses in mosquitoes showcase conservation in sensillar organization, as well as in groupings of functionally distinct taste neurons in each sensillum. The field is now poised for more thorough dissections of mosquito taste function, which should be of immense value in understanding close-range chemosensory interactions of mosquitoes with their hosts and environment. Here, we provide an introduction to the basic structure of a taste sensillum and functional analysis of the chemosensory neurons within it.

The host associations of mosquitoes vary by species, with some species being relative generalists, whereas others specialize, to varying extents, on a particular subset of the available host community. These host associations are driving factors in transmission dynamics of mosquito-vectored pathogens. For this reason, characterizing the host associations of mosquito species is critical for understanding the epidemiology of mosquito-vectored pathogens. Diverse methods have been used to associate mosquito species with their hosts. These typically include collecting mosquitoes that bite a restrained host (bait) or collecting wild blood-engorged mosquitoes and matching their blood meal to reference samples (blood meal analysis). Blood meal analysis refers to a collection of molecular techniques for determining the taxonomic identity of the source of a mosquito blood meal using cytological, serological, or DNA-based characteristics of the blood meal. Blood meal analyses that are based on DNA markers have advantages over cytological and serological methods and are effective for determining species-level identities of hosts from a broad range of potential host taxa. Here, we discuss effective techniques for analyzing blood meals.

Transposon-mediated transgenesis of mosquito vectors of disease pathogens followed the early success of transgenesis in the vinegar fly, Drosophila melanogaster. The P transposable element used in Drosophila does not function canonically in mosquitoes, and repeatable, routine transgenesis in mosquitoes was not accomplished until new transposable elements were discovered and validated. A number of distinct transposons were subsequently identified that mediate the introduction of exogenous DNA in a stable and heritable manner in mosquito species, including members of the genera Aedes, Anopheles, and Culex. The most versatile element, piggyBac, is functional in all of these mosquito genera, as well as in many other insects in diverse orders, and has been used extensively outside the class. Transposon-mediated transgenesis of recessive and dominant marker genes and reporter systems has been used to define functional fragments of gene control sequences, introduce exogenous DNA encoding products beneficial to medical interests, and act as "enhancer traps" to identify endogenous genes with specific expression characteristics.

Anautogenous female mosquitoes, which ingest a blood meal from warm-blooded vertebrates to produce eggs, have become a valuable model organism for investigating signaling pathways and physiological processes that occur during egg development. Different molecular pathways tightly regulate the initiation of egg development and are governed by a balance among different insect hormones. Gravid (mature egg-carrying) females deposit fully developed eggs at the end of each gonotrophic cycle, which is defined as the time interval between the ingestion of a blood meal to oviposition. An intact eggshell protects the oocyte and embryo inside from external factors such as desiccation, physical damage, etc., and the various eggshell proteins are spatially and temporary deposited during oogenesis. Additionally, follicle resorption (oosorption) during blood meal–induced mosquito ovarian follicle development is an adapted physiological process that optimizes reproductive fitness. Mosquito oocytes grow and mature synchronously throughout oogenesis; however, during the later stages of oogenesis, some oocytes may undergo oosorption if sufficient nutrients are unavailable. This introduction highlights how mosquito egg development can be used to investigate follicular resorption and identify proteins involved in eggshell formation in Aedes aegypti mosquitoes.

Scott Bauer, Prosper Trading Academy

Todd Colvin, Ambrosino Brothers

Bob Iaccino, Path Trading Partners

Scott Bauer, Prosper Trading Academy

Todd Colvin, Ambrosino Brothers

Scott Bauer, Prosper Trading Academy

Todd Colvin, Ambrosino Brothers

Bob Iaccino, Path Trading Partners

Todd Colvin, Ambrosino Brothers

Dan Deming, KKM Financial

Todd Colvin, Ambrosino Brothers

Bob Iaccino, Path Trading Partners

Scott Bauer, Prosper Trading Academy

Scott Bauer, Prosper Trading Academy

Dan Deming, KKM Financial