You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


Introduction {#Sec1}
============

*Theileria parva* is a tick-borne protozoan parasite which causes an acute and usually fatal cattle disease, known as East Coast fever (ECF), one of the most important cattle diseases in eastern and central Africa. ECF can eradicate up to 70% of the herd and can therefore confer serious impact \[[@CR1]\]. ECF has been listed by the Food and Agriculture Organization of the United Nations (FAO) and by the World Organization for Animal Health (OIE) as a high priority disease to control to improve livelihoods of poor smallholder farmers \[[@CR2]\].

The parasite infects bovine lymphocytes which subsequently undergo blast transformation and rapid multiplication \[[@CR3]\], which usually results in overwhelming parasitosis and death within 2--4 weeks of infection. Cattle which recover from natural infection develop strong immunity to subsequent challenge. This has been exploited in a vaccination procedure, the "Infection and Treatment Method" (ITM), where live sporozoites are administered simultaneously with oxytetracycline. The main protective mechanism in both vaccinated and naturally recovered animals is believed to be cytotoxic (CD8^+^) T lymphocyte (CTL) killing of infected lymphocytes \[[@CR4], [@CR5]\].

Strain specificity of the protective response induced by ITM was initially observed in vivo by Radley et al. \[[@CR6]\], and Irvin et al. \[[@CR7]\], by immunizing with one strain and challenging with another. However, Radley et al. (1975) showed that immunization with a mixture of stabilates from three parasite isolates (Muguga, Serengeti-transformed and Kiambu 5) induced a broader protection to heterologous challenge than immunization with single isolates \[[@CR8]\]. The mixture, known as the "Muguga cocktail", is the basis of a commercial ITM vaccine, which appears to provide broad protection against *T. parva* in the field \[[@CR9], [@CR10]\]. Strain specificity of the CTL response has also been described but mostly in context of CTL clones \[[@CR5], [@CR11]--[@CR14]\].

Various CTL antigens have been identified some of which are polymorphic \[[@CR15], [@CR16]\]. One such epitope (Tp1~214--224~) from the Tp1 antigen is presented by the A18 haplotype \[[@CR17]\] and varies among different strains, which can affect recognition of infected cells by some CTL clones \[[@CR18]\]. This does not seem to be a general phenomenon and was not the case when polyclonal responses were evaluated \[[@CR19]\].

In the present study we investigated the CTL response to immunization with the Muguga cocktail in three animals of the MHC class I (BoLA) A18 haplotype, two of which were haploidentical. We investigated the specificity of the CTL on a panel of different strains to elucidate the breadth of the response and determined if the immunized animals recognized two variants of the Tp1~214--224~ epitope, which has previously been reported in animals immunized with the Muguga stabilate.

Main text {#Sec2}
=========

Methods {#Sec3}
-------

### Animals {#Sec4}

Male cattle **(***Bos taurus*, Friesian) were bought from farms in the Nyeri area in Kenya, tested free of tickborne diseases and subsequently MHC-typed using MHC class-specific antibodies (ILRI antibodies B4/18 and ILA35), followed by determination of haplotype as previously described \[[@CR20], [@CR21]\]. Briefly, RNA was extracted from PBMC, used with primer pairs for A10, A11, A12, A14, A15, A17, A18, A19, A20 and A31 class I haplotypes (Additional file [1](#MOESM1){ref-type="media"}) in a RT-PCR assay. Products were analyzed on a 1% agarose gel, purified with the QIAquick PCR Purification Kit (QIAGEN, cat \# 28104) and sequenced on an ABI 3730 DNA Analyzer using the same primers used for the PCR reaction. Following this, three A18+ animals were selected for this study. Two cattle (BE033 and BE043) expressed the A12 haplotype (haploidentical), while one (BE017) expressed the A19 haplotype. The haploidentical animals expressed the variant A18 allele (BoLA-6\*01302), whereas BE017 expressed the canonical allele BoLA-6\*01301. A fourth animal (BE029) of the A14/A33 haplotypes was included as a control animal. Cattle were kept in a standard pen and subjected to standard husbandry procedures.

### Immunization {#Sec5}

Cattle were immunized intramuscularly, using ITM, in front and below the right ear using the Muguga cocktail, batch ILRI080, diluted 1:20 and immediately treated with tetracycline \[[@CR22]\]. Animals were boosted 5 weeks after immunization using the vaccine without oxytetracycline.

### PBMC separation {#Sec6}

PBMC were purified by standard density centrifugation using Ficoll-Paque \[[@CR23]\].

### Parasitized cell lines {#Sec7}

Cell lines infected with *T. parva* were established by infection of PBMC with sporozoites, as described previously \[[@CR24]\]. Briefly, PBMC were infected with sporozoites by adding crushed dissected salivary gland from infected ticks. Two weeks later, small immortalized colonies were visible, which could be expanded further. Cryopreserved sporozoites of the reference stabilates: Muguga 4230, Serengeti-transformed 4229, Kiambu 5 4228, components included in ILRI0801 \[[@CR22]\], were used for establishment of cell lines. Five cloned stabilates were also used: Marikebuni 3292, buffalo-derived 3570, Boleni 3198, \[[@CR25]\], Mariakani 3212 (unpublished; cloned from stabilate 1937) and Uganda 3645 (single passage from stabilate 3569) \[[@CR25]\].

### Peptides {#Sec8}

Peptides representing the CTL epitope in Tp1 (purity \> 95%, Mimotopes, Clayton, Australia) were used for pulsing of PBMC as target cells in CTL and ELISPOT assays. Tp1~214--224~ Muguga: VGYPKVKEEML; TP1~214--224~ Marikebuni: VGYPKVKEEII.

### Generation of CTL {#Sec9}

CTL bulk cultures were generated by stimulation of PBMC with a mixture of irradiated autologous cell lines, each infected with one of the three reference stabilates of the Muguga cocktail in a ratio of 10:1 (PBMC vs. stimulator cells). Three restimulations were performed before the CTL assay was made. For reactivity to the Tp1 epitope, CTL were expanded using autologous cells infected with the Muguga 4230 reference stabilate. The procedure was essentially as described before \[[@CR23]\].

### Tetramer analysis {#Sec10}

Staining of PBMC with tetramer and CD8 antibody was essentially as described in Svitek et al. \[[@CR23]\]. Twenty five microliters PE-labeled Tp1~214--224~ tetramer (provided by Pierre van der Bruggen, Ludwig Institute for Cancer, Brussels) was used to stain 4 × 10^5^ cells to a final concentration of 40 nM.

### Cytotoxicity assay {#Sec11}

Standard 4 h release assay using ^51^Cr-labeled target cells were used to measure cytotoxicity, essentially as described in Svitek et al. \[[@CR23]\].

Results {#Sec12}
-------

### Strain specificity of CTL from immunized animals {#Sec13}

Three animals of the A18 haplotype were selected for these experiments. One calf (BE017) expressed the canonical A18 allele (BoLA-6\*01301), with the other haplotype being A19. The other two cattle (BE033 and BE043) expressed the variant A18 allele (BoLA-6\*01302) and the other haplotype was determined to be A12, and so they are considered to be haploidentical. The two A18 alleles differ by a single amino acid, Glu → Leu at position 97 \[[@CR22]\].

Initially, CTL lines from each of the three A18+ animals were tested on autologous cell lines infected with each of the three component stabilates of the Muguga cocktail or with one of four cloned stabilates: Boleni, Mariakani, Uganda and a buffalo-derived strain. CTL from the three cattle showed different patterns of cytotoxic activity on the target cell lines (Fig. [1](#Fig1){ref-type="fig"}). BE017 recognized all cell lines, although with differences in intensity. CTL from BE043 showed consistently strong killing of all cell lines, whereas CTL from the haploidentical BE033 did not recognize cell lines infected with the Mariakani or buffalo-derived stabilates.Fig. 1Strain-specific response by CTL generated in three A18+ animals. BE017 (**a**), BE033 (**b**) and BE043 (**c**). Seven infected cell lines were prepared from each animal as detailed in the Methods. The CTL lines from were tested at several effector:target (E:T) ratios as indicated. The experiment was performed twice with similar results. Significance compared to the PBMC control was tested with a T-test. \*P \< 0.05. \*\*P \< 0.01. **a** All P \< 0.05; **b** buffalo and Mariakani were not significant different from PBMC, all other P \< 0.05; **c** all P \< 0.01

### Immunized A18+ cattle vary in their CTL response to the Tp1 epitope {#Sec14}

The pattern of killing of autologous infected cell lines suggested that animals sharing the A18 MHC haplotype differ in their CTL specificity, even when the animals are haploidentical. We examined this further by determining if there were differences in the CTL recognition of the Tp1~214--224~ epitope, previously shown to be presented by the A18 haplotype. This was assessed on two naturally occurring variants of the epitope, present in the *T. parva* Muguga and Marikebuni parasites, respectively, plus autologous cell lines infected with these parasite strains. There was a clearly different pattern of reactivity among the three A18+ animals (Fig. [2](#Fig2){ref-type="fig"}). BE017 appeared to recognize both variants of the Tp1~214--224~ epitope, plus the infected cell lines. Neither of the haploidentical animals BE033 and BE043 lysed the peptide-pulsed targets. We have previously shown that animals expressing either the allele BoLA-6\*01301or BoLA-6\*01302 recognize the Tp1~214--224~ epitope \[[@CR26]\], so the lack of recognition of the peptide by BE033 and BE043 is not due to the variant A18 allele. Another difference was the lack of recognition by BE043 of the Marikebuni-infected cell line, which was well recognized by the haploidentical BE033 CTL. The results underscore the difference in the CTL specificity exhibited by haploidentical individuals.Fig. 2Peptide-specific CTL responses (cytotoxicity) in three A18+ cattle. BE017 (**a**), BE033 (**b**) and BE043 (**c**) and one control calf BE029 (**d**). CTL from the cattle were tested for killing on autologous cell lines infected with Muguga or Marikebuni (e.g. BE017-Mug or BE017-Mar) or autologous PBMC pulsed with the Tp1~214--224~ peptide from *T. parva* Muguga (Tp1 Mug) or *T. parva* Marikebuni (Tp1 Mar), as indicated. The experiment was performed twice with similar results. T-test was used for testing statistical significance. The highest E:T ratio was tested against the PBMC control. \*P \< 0.05, \*\*P \< 0.01, \*\*\*P \< 0.001. Significance between killing of Muguga and Marikebuni was also tested and found to be significantly less (for Marikebuni) with at least P \< 0.05 for the animals BE033, BE043 and BE029 but not for BE017

Tetramer staining was performed on PBMC from the four animals at the optimal time point 15 days after challenge \[[@CR27]\], and co-stained with Tp1~221--224~/BoLA 6\*01301 tetramers and an anti-CD8 antibody. As shown in Fig. [3](#Fig3){ref-type="fig"}, cells from BE017 reacted very strongly with the tetramer, with 7.01% of CD8^+^ cells (or 1.12% of the total PBMC population) being positive. There appeared to be a very small percentage of positive cells in BE033 (0.23% of the total population), although when expressed as a percentage of the CD8^+^ cells (1.14%), there was no difference between BE033 and the control animal BE029 (1.43%). There was no difference between BE043 and the control animal. This experiment was repeated 6 months later with similar results but a lower level of tetramer positive cells in BE017 (data not shown). These results were corroborated by IFN-gamma ELISPOT assay (Additional file [2](#MOESM2){ref-type="media"}). Overall, these results support those observed in the cytotoxicity assays described above.Fig. 3Muguga derived Tp1~214--224~ tetramer staining of PBMC from the three A18+ animals. BE017, BE033, BE043 and the control animal (BE029), isolated at day 15 after immunization. PBMC were co-stained with anti-CD8 Ab-PerCP and Tp1~214--224~-tetramer-PE. Initial gating was performed on the live lymphocyte fraction (not shown). Staining of the CD8^+^ cells by the tetramer is seen in the upper right quadrant (Q2). The animals from which the CD8^+^ cells were derived are indicated in the figure. The experiment was performed twice

Discussion {#Sec15}
----------

CTL are believed to be the major mechanism of protection using the Muguga cocktail and during natural immunity, which underscores the importance of analyzing the CTL response induced by the vaccine. Our aim in the current study was to test whether a mixture of parasite stabilates (Muguga cocktail) consistently induces CTL capable of killing cell lines infected with a broad array of parasite types. The results presented here suggest that this is not always the case.

CTL from BE017 killed all different infected cell lines, although there were differences in the efficiency of lysis. The BE017 CTL recognized the Tp1~214--224~ epitope, which is known to be relatively conserved among different *T. parva* strains, with only four different variant epitopes found in field samples thus far \[[@CR28]\]. It is known that CTL cross-react with these variant epitopes \[[@CR19]\] and the present results confirm this observation.

Surprisingly, the CTL response in both BE033 and BE043 showed no reactivity to the Tp1~214--224~ epitope. This may be due to the other MHC haplotype (A12) since it has been shown that the CTL response can be dominated by one haplotype \[[@CR29]\].

While BE043 efficiently lysed all *T. parva* strains tested, except *T. parva* Marikebuni, BE033 showed a variable response among the different strains and BE043 didn't kill the Marikebuni strain, so the CTL in this calf must be dominated by a specificity that is not cross-reactive with the Marikebuni strain, presumably through the presentation of a non-crossreactive epitope. This difference between Muguga and Marikebuni has been studied previously, mostly in context of strain-specific clones \[[@CR13], [@CR30]\]. While this is interesting from an immunological point of view, it is the overall polyclonal response which is more important from a vaccine perspective because this will inform if the immune response has the potential to cross-protect between strains. Unfortunately, there are few of these studies which would provide valuable information for improvement of a live vaccine. The Muguga and the Marikebuni strains have obviously some differences and a Marikebuni strain could be considered for inclusion in a live vaccine.

BE033 had the most variable CTL response of the three animals with regards to strain specificity. Such variability may potentially lead to breakthrough in the field, i.e. incidences of ECF despite vaccination, for certain combinations of host MHC haplotypes and infection with some *T. parva* strains.

In summary, these findings suggest that the specificity of the CTL response following immunization with a live vaccine against *T. parva* varies among animals sharing the same MHC haplotype, including a pair of haploidentical individuals, and that certain strain/MHC haplotype combinations could possibly lead to break through of the vaccine. Further, the variable immune responses found in MHC class I haploidentical cattle most likely translate to other species as the mechanisms in generation of CTL responses are very similar across species.

Limitations {#Sec16}
-----------

The animal number is small. It would be preferable to have more haploidentical animals in the study.

Additional files
================

 {#Sec17}

[**Additional file 1.**](https://doi.org/10.1186/s13104-018-3145-8) Table showing sequence-specific primer sequences used for BoLA Class I typing. [**Additional file 2.**](https://doi.org/10.1186/s13104-018-3145-8) IFN-γ release from CD8^+^ cells derived from the three A18+ cattle. BE017, BE033 and BE043 and one control calf (BE029) in response to (A) autologous Muguga 4230 infected cell lines and (B) Tp1~214--224~ peptide derived from Muguga. The relative numbers of spots compared to added cells are shown (frequency). A positive control cell line was included (CTL line) which reached higher values than the maximum on the Y-axis. The maximum was diminished to visualize the important results. Statistical significance was tested with a *T* test, (\*) P \< 0.05. (\*\*) P \< 0.01.

CTL

:   cytotoxic T-lymphocyte

ECF

:   East Coast fever

MHC

:   major histocompatibility complex

ITM

:   infection and treatment method

BoLA

:   bovine leucocyte antigens

PBMC

:   peripheral bovine mononuclear cells

IFN

:   interferon

**Electronic supplementary material**

The online version of this article (10.1186/s13104-018-3145-8) contains supplementary material, which is available to authorized users.

LS designed and supervised the experiments, participated in the cellular experiments, analyzed and interpreted the data and co-wrote the manuscript. NS performed the MHC typing work and interpreted the data. EA and RS performed the cellular experiments and partially analyzed the data. PT co-wrote the manuscript with LS. All authors read and approved the final manuscript.

Acknowledgements {#FPar1}
================

We also wish to thank Thomas Njoroge and Stephen Mwaura for immunizing and monitoring the cattle.

Competing interests {#FPar2}
===================

The authors declare that they have no competing interests.

Availability of data and materials {#FPar3}
==================================

Detailed data and material can be obtained by contacting the corresponding author.

Consent to publish {#FPar4}
==================

Not applicable.

Ethical approval and consent to participate {#FPar5}
===========================================

The animal experiments were approved by the Institutional Animal Care and Use Committee at International Livestock Research Institute (ILRI)---IACUC No.: 2009.10. There was no involvement of humans in the study.

Funding {#FPar6}
=======

This work received support from the CGIAR Research Program on Livestock and Fish, led by the International Livestock Research Institute (ILRI). We also acknowledge the CGIAR Fund Donors (<http://www.cgiar.org/who-we-are/cgiar-fund/fund-donors-2>). The National Science Foundation (NSF) contributed to this project by Grant No.: NSF 0965346.

Publisher's Note {#FPar7}
================

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.