Potential dementia biomarkers based on the time-varying microstructure of sleep EEG spindles

Proceedings of the 29th Annual International Conference of the IEEE EMBS Cité Internationale, Lyon, France August 23-26, 2007

Embryology of Triatoma infestans (KLUG), (Hemiptera, Reduviidae), a Chagas' disease vector

This study reports the embryogenesis of T. infestans (Hemiptera, Reduviidae). Morphological parameters of growth sequences from oviposition until hatching (12-14 d 28ºC) were established. Five periods, as percent of time of development (TD), were characterized from oviposition until hatching. The most important morphological features were: 1) formation of blastoderm within 7% of TD; 2) germ band and gastrulation within 30% of TD; 3) nerve cord, limb budding, thoracic and abdominal segmentation and formation of body cavity within 50% of TD; 4) nervous system and blastokinesis end, and development of embryonic cuticle within 65% of TD; 5) differentiation of the mouth parts, fat body, and Malphigian tubules during final stage and completion of embryo at day 12 to day 14 around hatching. These signals were chosen as appropriate morphological parameters which should enable the evaluation of embryologic modifications due to the action/s of different insecticides

Lethal effect of a bait for Rhodnius prolixus (Hemiptera: Reduviidae), the vector of Chagas' disease, containing hexachlorocyclohexane (HCH), under laboratory conditions

The lethal effect of a bait containing an aqueous hexachlorocyclohexane (HCH) suspension at the concentration of 1g/l and maintained at room temperature was studied in the laboratory over a period of 12 weeks. The suspension was placed in a latex bag hanging inside a 1000-ml beaker tightly covered with nylon netting, and left there with no changes for 85 days. Sixteen groups of R. prolixas bugs, consisting on average of 30 specimens each, were successively exposed to the bait and observed at different intervals for one week each. The mortality rate was 100% for all groups, except for the 16th, whose mortality rate was 96.7%. As the groups succeeded one another, mortality started to occur more rapidly and was more marked at the 6- and 24-h intervals. Later tests respectively started at 6:00 a.m. and 6:00 p.m. showed that diurnal and nocturnal periodicity in the offer of food had no effect on mortality. First- and 2nd- instar nymphs and adults male were more sensitive and 5th- instar nymphs were more resistant to the active principle of the bait.

Commercial squids: Characterization, assessment of potential health benefits/risks and discrimination based on mineral, lipid and vitamin E concentrations

The most consumed squid species worldwide were characterized regarding their concentrations of minerals, fatty acids, cholesterol and vitamin E. Interspecific comparisons were assessed among species and geographical origin. The health benefits derived from squid consumption were assessed based on daily minerals intake and on nutritional lipid quality indexes. Squids contribute significantly to daily intake of several macro (Na, K, Mg and P) and micronutrients (Cu, Zn and Ni). Despite their low fat concentration, they are rich in long-chain omega-3 fatty acids, particularly docosahexaenoic (DHA) and eicosapentanoic (EPA) acids, with highly favorable ω-3/ω-6 ratios (from 5.7 to 17.7), reducing the significance of their high cholesterol concentration (140–549 mg/100 g ww). Assessment of potential health risks based on minerals intake, non-carcinogenic and carcinogenic risks indicated that Loligo gahi (from Atlantic Ocean), Loligo opalescens (from Pacific Ocean) and Loligo duvaucelii (from Indic Ocean) should be eaten with moderation due to the high concentrations of Cu and/or Cd. Canonical discriminant analysis identified the major fatty acids (C14:0, C18:0, C18:1, C18:3ω-3, C20:4ω-6 and C22:5ω-6), P, K, Cu and vitamin E as chemical discriminators for the selected species. These elements and compounds exhibited the potential to prove authenticity of the commercially relevant squid species.

Distribucion geografica de Lutzomyia verrucarum (Townsend, 1913) (Diptera, Psychodidae, Phlebotominae), vector de la batonellosis humana en el Peru

Lutzomyia verrucarum (Townsend, 1913) (Diptera: Psychodidae), vector natural de la verruga peruana o enfermedad de Carrión es una especie propia del Perú. Su distribución geográfica esta entre los paralelos 5º y 13º25' de latitud Sur, se encuentra en los valles Occidentales e Interandinos de los Andes. La distribución altitudinal de Lu. verrucarum en los diversos valles es variable; asi: Occidentales, desde 1100 hasta 2980 msnm e Interandinos, de 1200 a 3200 msnm. En ciertas áreas verrucógenas no hay correlación entre la presencia de Lu. verrucarum y la enfermedad de Carrión lo que suguiere la existencia de vectores secundarios.

Riesz potential versus fractional Laplacian

This paper starts by introducing the Grünwald–Letnikov derivative, the Riesz potential and the problem of generalizing the Laplacian. Based on these ideas, the generalizations of the Laplacian for 1D and 2D cases are studied. It is presented as a fractional version of the Cauchy–Riemann conditions and, finally, it is discussed with the n-dimensional Laplacian.

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

Terapêuticas antigénio-especificas no tratamento das doenças desmielinizantes: estudos sobre a vacinação com ADN e a descoberta de um novo alvo antigénico

RESUMO A Esclerose Múltipla (EM) é uma doença desmielinizante crónica do Sistema Nervoso Central (SNC), provocada, em grande parte, por um ataque imuno-mediado contra diversos elementos da bainha de mielina. Dentro dos alvos antigénicos desta resposta autoimune, vários componentes proteicos e lipídicos da mielina têm vindo a ser identificados ao longo dos anos, entre os quais se destacam a proteína básica de mielina(MBP), glicoproteína ligodendrocitária da mielina (MOG), proteína proteolipídica (PLP) e glicoproteína associada à mielina (MAG). Com o desenvolvimento do modelo animal de Encefalomielite Autoimune Experimental (EAE), diversas terapias antigénio-específicas foram desenhadas, baseadas na modificação benéfica da resposta autoimune contra a mielina, tais como a administração de mielina ou seus componentes, os copolímeros terapêuticos, os ligandos peptídeos alterados e, recentemente, a vacinação com ácido desoxirribonucleico (ADN) codificador de proteínas de mielina, integrado em plasmídeos e purificado para administração parentérica. Neste trabalho, apresentamos os resultados de um extenso conjunto de experiências, subordinadas a dois temas fundamentais: 1) avaliação do potencial terapêutico, e dos mecanismos de acção, da vacinação tolerizadora com ADN codificador de proteínas de mielina (MBP, MOG, PLP, MAG) na EAE, e da associação desta vacinação com a administração de ADN de citocinas Th2, ou de oligonucleótidos imunomoduladores; 2) identificação e caracterização da resposta imune contra um novo componente da mielina com potencial antigénico, a proteína inibidora do recrescimento axonal, Nogo-A. No que respeita à vacinação com ADN, os nossos resultados comprovam a eficácia desta terapêutica antigénio-específica na prevenção e tratamento da EAE. Os seus mecanismos de acção incluem, entre outros, a supressão anérgica da proliferação antigénioespecífica dos linfócitos T anti-mielina (no modo de prevenção da doença), o enviesamento Th2 da resposta imune (quando co-administrada com a vacina de ADN codificadora da citocina IL-4, funcionando como terapia génica local), e a redução da diversificação de epítopos da resposta humoral anti-mielina, avaliada através de myelin spotted arrays. A associação das vacinas de ADN com oligonucleótidos imunomoduladores GpG, desenvolvidos para contrariar as sequências CpG imunoestimuladoras presentes no vector de vacinação, levou à melhoria da sua eficácia terapêutica, devida, provavelmente, ao efeito estimulador preferencial dos oligonucleótidos GpG sobre linfócitos Th2 e sobre células reguladoras NK-T. Com base nestes resultados a vacinação com ADN foi desenvolvida para o tratamento da EM em humanos, com ensaios clínicos a decorrerem neste momento. Em relação à proteína Nogo-A, estudos de estrutura primária e de previsão de antigenicidade identificaram a região Nogo-66 como alvo antigénico potencial para a EAE. Nas estirpes de ratinho SJL/J e C57BL/6, fomos capazes de induzir sinais clínicos e histológicos de EAE após imunização com os epítopos encefalitogénicos Nogo1-22, Nogo23- 44 e Nogo45-66, utilizando protocolos de quebra de tolerância imune. Ao mesmo tempo, identificámos e caracterizámos uma resposta linfocitária T específica contra os antigénios contidos na região Nogo-66, e uma resposta linfocitária B com diversificação intra e intermolecular a vários determinantes presentes noutras proteínas da mielina. A transferência adoptiva de linhas celulares Th2 anti-Nogo45-66, levou à melhoria clínica e histológica da EAE em animais recipientes induzidos com outros antigénios de mielina, após migração destas células para o SNC. Estes dados comprovam a importância da Nogo-66 como antigénio na EAE, e a eficácia de terapias antigénio-específicas nela baseadas. No seu conjunto, os nossos resultados confirmam o potencial terapêutico das vacinas de ADN codificadoras de proteínas de mielina, bem como a importância dos encefalitogénios contidos na proteína Nogo-A para a fisiopatologia da EAE e da EM, com eventual relevância para o desenvolvimento de novas terapias antigénio-específicas. O aperfeiçoamento futuro destas terapias poderá levar, eventualmente, a uma capacidade de manipulação da resposta imune que permita o tratamento eficaz das doenças inflamatórias desmielinizantes, como a Esclerose Múltipla. ABSTRACT Multiple Sclerosis (MS) is a chronic demyelinating disease of the Central Nervous System (CNS), caused, mainly, by an immune-mediated attack against several elements of the myelin sheath. Among the antigenic targets for this autoimmune response, several proteic and lipidic myelin components have been identified throughout the years, of which myelin basic protein (MBP), myelin oligodendrocyte glycoprotein (MOG), proteolipidic protein (PLP), and myelin associated glycoprotein (MAG) are the best characterized. With the development of the animal model for MS, Experimental Autoimmune Encephalomyelitis (EAE), several antigen-specific therapies have been designed, based on beneficial modifications of the autoimmune response against myelin. These have included myelin and myelin component administration, therapeutic copolymers, altered peptide ligands and, more recently, vaccination with myelin-protein encoding deoxyribonucleic acid (DNA), integrated into plasmids and purified for parenteral administration. In this work we present the results of an extensive series of experiments, subordinate to two fundamental areas: 1) evaluating the therapeutic potential, and mechanisms of action, of tolerizing myelin protein (MBP, MOG, PLP, MAG) DNA vaccination in EAE, alone and in association with Th2 cytokine DNA administration, or immunomodulatory oligonucleotides; 2) identifying and characterizing the immuneresponse against a new myelin component with antigenic potential, the axonal regrowth inhibitor Nogo-A. Regarding DNA vaccination, our results prove the efficacy of this antigen-specific therapy for the prevention and treatment of EAE. Its mechanisms of action include, among others, anergic suppression of antigen-specific T-cell proliferation against myelin (in prevention mode), Th2 biasing of the immune response (when co-administered with the IL- 4 codifying DNA vaccine, acting as local gene therapy), and reduction of epitope spreading of the anti-myelin antibody response, assessed by myelin spotted arrays. The combination of myelin DNA vaccination with the administration of GpG immunomodulatory oligonucleotides, designed to counteract immunostimulatory CpG motifs present in the vaccination vector, led to an improvement in therapeutic efficacy, probably due to the preferential stimulatory effect of GpG oligonucleotides on Th2 lymphocytes and on regulatory NK-T cells. Based on these results, tolerizing DNA vaccination is being developed for human use, with ongoing clinical trials. As concerns the Nogo-A protein, based on studies of primary structure and prediction of antigenicity, we identified the Nogo-66 region (responsible for the most of the inhibitory capacity of this protein) as a potential antigenic target for EAE. In the SJL/Jand C57BL/6 mouse strains, we were able to induce clinical and histological signs of EAE,after immunization with the encefalitogenic epitopes Nogo1-22, Nogo23-44 and Nogo45-66,using a tolerance breakdown protocol. Concomitantly, we identified and characterized a specific T cell response against these antigens, together with a B cell response which showed extensive intra and intermolecular epitope spread to several determinants present in other myelin proteins. Adoptive transfer of nti-Nogo45-66 Th2 cell lines resulted in clinical and histological improvement of EAE in recipient animals induced with other myelin antigens, after intraparenchymal CNS migration of anti-Nogo cells. These data confirm the relevance of Nogo-66 as an antigen in EAE, as well as the efficacy of antigenspecific therapies based on the response against this protein.In conclusion, our results substantiate the therapeutic potential of myelin-encoding DNA vaccination, as well as the importance of encefalitogenic epitopes present in the Nogo-A protein for the pathophysiology of EAE and MS, with potential relevance for the creation of new antigen specific-therapies. The future development of these therapies may eventually lead to a degree of manipulation of the immune response that allows the effective treatment of autoimmune, inflammatory, demyelinating diseases, such as Multiple Sclerosis.

Chicken as potential contamination source of Campylocacter lari in Iquitos, Peru

In order to know the importance of chicken as natural reservoir of Campylobacter lari in Iquitos, Peru; samples were obtained by cloacal swabs from 200 chickens and immediately placed into a semisolid enrichment medium; these were streaked on modified Skirrow Agar. The organism was isolated from 21 (10.5%) samples, corresponding 58.8% to biovar I and 41.2% to biovar II (Lior scheme). The results provide evidence that chicken appear to be prominent reservoirs of Campylobacter lari in Iquitos.

Mycobacterium avium complex (MAC): an unusual potential pathogen in cerebrospinal fluid of AIDS patients

Mycobacterium avium complex (MAC) is frequently isolated from patients with late complications of Acquired Immunodeficiency Syndrome (AIDS), especially in North America and Europe. However, its isolation from the central nervous system (CNS) has been seldom reported in these countries. MAC infections in AIDS patients in African and Latin American countries are believed to be uncommon. We report the isolation of MAC from cerebrospinal fluid (CSF) of 11 AIDS patients out of 1723 (0.63%) seen at "Centro de Referência e Treinamento - AIDS", São Paulo and discuss the significance of its isolation.

Transglutaminases do mosquito Anopheles gambiae: Caracterização genética, bioquímica e funcional durante a infecção por Plasmodium berghei

A malária constitui um problema de saúde pública, que tem vindo a agravar-se, sendo crescente a necessidade de estratégias renovadas para o seu controlo, como a interrupção do ciclo esporogónico. Deste modo, é essencial compreender as respostas imunológicas de Anopheles anti-Plasmodium. Demonstrou-se anteriormente, que a inibição de transglutaminases, enzimas que participam em vários processos biológicos ao catalisarem a formação de ligações covalentes entre péptidos, agrava a infecção em mosquitos pelo parasita. O presente trabalho tem por objectivo caracterizar as transglutaminases AGAP009098 e AGAP009100 de Anopheles gambiae. Os métodos utilizados para este efeito foram: a sequenciação de regiões dos genes AGAP009098 e AGAP009100; a clonagem molecular de fragmentos da região codificante do gene AGAP009098, usando o vector plasmídico pET–28a(+) e Escherichia coli como sistema de expressão; e PCR em Tempo Real para analisar a expressão relativa dos genes AGAP009098 e AGAP009100 nos diferentes os estádios de desenvolvimento. AGAP009098 é expressa ubiquamente e AGAP009100 a partir do estádio pupa. Estes resultados apontam para a conclusão de que AGAP009098 e AGAP009100 poderão desempenhar funções em processos biológicos relevantes, por exemplo na defesa imunitária, ou no desenvolvimento. Os péptidos recombinantes, obtidos a partir da clonagem com sucesso de fragmentos da região codificante do gene AGAP009098, constituem uma ferramenta importante para averiguar a função destas TGases, no futuro.

Strategic Bidding for Electricity Markets Negotiation Using Support Vector Machines

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which simulates the electricity markets environment. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. This paper presents the application of a Support Vector Machines (SVM) based approach to provide decision support to electricity market players. This strategy is tested and validated by being included in ALBidS and then compared with the application of an Artificial Neural Network, originating promising results. The proposed approach is tested and validated using real electricity markets data from MIBEL - Iberian market operator.

Solar Intensity Forecasting using Artificial Neural Networks and Support Vector Machines

This paper presents several forecasting methodologies based on the application of Artificial Neural Networks (ANN) and Support Vector Machines (SVM), directed to the prediction of the solar radiance intensity. The methodologies differ from each other by using different information in the training of the methods, i.e, different environmental complementary fields such as the wind speed, temperature, and humidity. Additionally, different ways of considering the data series information have been considered. Sensitivity testing has been performed on all methodologies in order to achieve the best parameterizations for the proposed approaches. Results show that the SVM approach using the exponential Radial Basis Function (eRBF) is capable of achieving the best forecasting results, and in half execution time of the ANN based approaches.

Short-term Wind Speed Forecasting using Support Vector Machines

Wind speed forecasting has been becoming an important field of research to support the electricity industry mainly due to the increasing use of distributed energy sources, largely based on renewable sources. This type of electricity generation is highly dependent on the weather conditions variability, particularly the variability of the wind speed. Therefore, accurate wind power forecasting models are required to the operation and planning of wind plants and power systems. A Support Vector Machines (SVM) model for short-term wind speed is proposed and its performance is evaluated and compared with several artificial neural network (ANN) based approaches. A case study based on a real database regarding 3 years for predicting wind speed at 5 minutes intervals is presented.

Rapid Characterization of S. mansoni Expression Library Clones of Potential Interest

A S. mansoni adult worm cDNA expression library was screened with sera from baboons in a early phase after infection. The clones that were positive with the early infection sera were examined for reactivity with pre-infection sera and heterologous infection sera. In order to discriminate a positive antibody reaction from the reactivity due to residual anti-E. coli antibodies, an unrelated cDNA clone was plated with the positive clone. The unrelated clone provided the negative background and the contrast necessary to discern a positive antibody reaction. In this way, we were able to eliminate selected clones that were positive with the pre-infection sera or heterologous infection sera. This characterization of the expression library clones enabled us to quickly target only clones with the desired pattern of antibody reactivity for sequencing, subcloning, and expressing