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]


Overview and Current Status of mIRNA Expression in AD and PrD
=============================================================

Recent miRNA array-, Northern-, quantitative RT-PCR, and/or RNA-sequencing-based analyses have uncovered a small group of inducible, pathogenic microRNAs (miRNAs) significantly up-regulated in degenerating central nervous system (CNS) tissues, and these appear to be involved in the coordinate down-regulation of disease-relevant messenger RNA (mRNA) targets ([@B16]; [@B7]; [@B12]; [@B23]; [@B25],[@B28]; [@B2]; [@B4]; [@B22]). This small family of up-regulated miRNAs include miRNA-9, miRNA-34a, miRNA-125b, miRNA-146a, and miRNA-155; for example their 1.7- to 5.8-fold up-regulation in AD neocortex targets a set of degeneration-relevant mRNAs involved in the regulation of gliosis, glial cell proliferation, the innate-immune response, inflammatory signaling, deficits in neurotrophic signaling, synaptogenesis, and amyloidogenesis. One prominent Aβ42 peptide and related amyloid clearance pathway affected in neurodegenerative processes in the CNS appears to be an inducible miRNA-34a-regulated TREM2 mRNA circuit ([@B12]; [@B26]; [@B3]; [@B25]; [@B29]; [@B18]; [@B21]). Briefly, TREM2, the triggering receptor expressed in myeloid/microglial cells and encoded by a ∼2700 nuc*l*eotide (nt) mRNA at chr 6p21.1, yields a ∼26 kDa (230 amino acid) variably glycosylated type 1 transmembrane glycoprotein of the immunoglobulin gene superfamily highly expressed in MG cells, the '*resident immune cells'* of the CNS. As a rather recently recognized myeloid/microglial cell surface amyloid sensor-receptor, TREM2 appears to play a critical function in innate-immune surveillance, the sensing of amyloid and phagocytosis throughout the CNS, including the recognition and ingestion of neurotoxic Aβ42 peptides and related extracellular amyloidogenic debris ([@B29]; [@B18]; [@B21]). The TREM2 mRNA 3′-untranslated region (3′-UTR; 299 nt) contains an unusually strong recognition feature for miRNA-34a; the energy of association (E**~A~**) between hsa-miRNA-34a (encoded at chr 1p36.15) and the TREM2 mRNA-3′UTR sequence is ∼16.2 kcal/mol; hence gene products on chromosome 1 and 6 orchestrate a biologically relevant TREM2 expression that impacts phagocytosis ([@B29]; [@B18]; [@B21]). TREM2 signaling is in part mediated through a MG membrane-associated tyrosine kinase-binding protein/DNAX activation adaptor protein of 12 kDa (TYROBP/DAP12), however, no deficit in TYROBP/DAP12 in AD or PrD has yet been identified, and we cannot exclude deficiencies in other phagocytic proteins at the present time ([@B23]; [@B29]). On the other hand significant TREM2 deficits have been reported during inflammatory neurodegeneration of the human CNS including sporadic AD and age-related macular degeneration (AMD; [@B26]; [@B29]; [@B2]; [@B18]). It is not clear what role TREM2 plays in amyloidogenic processes associated with prion infected human brain in Creutzfeldt-Jakob disease (CJD) or Gerstmann-Straussler-Scheinker (GSS), although markers of MG activation are down-regulated in prion-infected TREM2-/- mice suggesting TREM2 involvement in prion-induced MG-activation ([@B18]; [@B21]). In this brief report, we for the first time provide data on the up-regulation of these five inducible miRNAs, and prominently miRNA-34a, in two rare human prion diseases: the transmissible spongiform encephalopathies (TSE) sporadic CJD (incidence ∼1 per million) and GSS syndrome (incidence ∼1--10 per 100 million), and compare them to their levels in sporadic AD ([@B12]; [@B23]). We further provide evidence that wild type MG cells can effectively phagocytose Aβ42 peptides while miRNA-34a-treated MG cells (compared to scrambled miRNA-treated controls) exhibit both a significantly attenuated TREM2 signal and a reduced ability to ingest and clear Aβ42 peptide from the extracellular space. Using miRNA array-based analytical approaches, recent findings further indicate that miRNA-9, miRNA-34a, miRNA-125b, miRNA-146a, and miRNA-155 exhibit similar up-regulation in sporadic AD and in PrD brain (**Table [1](#T1){ref-type="table"}**), that miRNA-34a induces a deficiency in the expression of MG cell TREM2, and a defect in the ability of MG cells to phagocytose (**Figure [1](#F1){ref-type="fig"}**; [@B27]; [@B2]).

###### 

Relative expression of AD-relevant miRNAs in the prion diseases sJCD and Gerstmann-Straussler-Scheinker (GSS) indicate a similar up-regulation of these inducible, NF-kB-regulated miRNAs; clinical parameters including age and gender of these human PrD cases (both JCD and GSS) have been described in detail elsewhere ([@B12]).

                  Control   AD      sCJD    GSS     Fold increase AD/control   Fold increase CJD/control   Fold increase GSS/control
  --------------- --------- ------- ------- ------- -------------------------- --------------------------- ---------------------------
  N               9         12      3       2       \-                         \-                          \-
  miRNA-9-5p      15657     38661   48529   46969   2.5                        3.1                         3
  miRNA-34a-5p    261       1176    1410    1875    4.5                        5.4                         7.2
  miRNA-125b-5p   15310     26424   32150   35213   1.7                        2.1                         2.3
  miRNA-146a-5p   304       1756    1915    2463    5.8                        6.3                         8.1
  miRNA-155-5p    370       968     1182    1222    2.6                        3.2                         3.3

Numbers under

Control

,

Alzheimer's disease (AD)

,

sCJD

or

GSS

are the means of each sample's miRNA signal as indicated; briefly the average ages of sCJD (

n

= 3) and the controls (

n

= 6) were 66 ± 8 years and the mean ages of the GSS (

n

= 2) and controls (

n

= 6) were 61 years; there were no significant differences in total RNA yield or purity between any AD or control, or prion-affected brain samples (

Lukiw et al., 2011

;

Zhao and Lukiw, 2015

;

Bhattacharjee et al., 2016

); due to their extreme rarity and limited availability, only sCJD and GSS small RNAs, and no brain tissue protein extracts were available for the current investigation; in AD, sCJD, and GSS miRNA-34a exhibited one of the highest up-regulations ranging from 4.5- to 7.2-fold over relevant controls.

![**TREM-2 mediated phagocytosis of Aβ42 peptides in murine microglial (MG) cells - control or a scrambled-miRNA-34a (**+miRNA-34a-sc**)-treated MG cells efficiently phagocytose Aβ42 peptides; miRNA-34a-treated MG cells do not; **(A)** C8B4 MG cells (ATCC CRL-2540) cultured for 3 days (**control**) were treated with 5 μM of Aβ42 peptides (American Peptide Company, Sunnyvale, CA, cat \# 62-0-80A) for 24 h before staining;** briefly, Aβ42 peptide was completely dissolved in hexafluoroisopropanol (HFIP; Fluka Chemical, cat\# 52512; Sigma--Aldrich, St. Louis, MO), lyophilized and stored at -20°C; HFIP films were re-suspended to 5 mM with DMSO then diluted to 5 μM and introduced into C8B4 MG culture medium ([@B19]; [@B24]; [@B2]); cells were incubated with either a scrambled miRNA-34a sequence **(+miRNA-34a-sc) (B)** or with a locked nucleic acid (LNA) protected miRNA-34a **(+miRNA-34a) (C)** (each at 30 nM); treatments were for 24 h before incubation with 5 uM of Aβ42 peptides for another 24 h before assay; MG cells were subsequently stained with **(a)** a murine amyloid beta MABN10 (red fluorescence λ~max~∼650 nm; anti-Aβ antibody, clone W0-2; Millipore, Billerica, MA); **(b)** a TREM-2 antibody (M-227; sc-48765; green fluorescence; λ~max~∼510 nm; Santa Cruz, CA); or **(c)** a DAPI nuclear stain (blue fluorescence; λ~max~∼470 nm); **(d)** represents a merged view of all three fluorescent stains**;** we note a decreased TREM2 presence in miRNA-34a treated MG cells (bottom row, panel **b**) and a consistent decrease in ingested Aβ42 peptides within C8B4 MG cells **(C)**; bottom row, panel **(d)** magnification 20×. These and previous results together indicate a miRNA-34a-mediated down-regulation of TREM2 and an inability to ingest Aβ42 peptide from the surrounding medium; note **(i)** the rapid self-aggregation of Aβ42 peptides into 'clumps'; **(ii)** affinity of Aβ42 peptides for TREM2 containing MG cells (leftmost panels); and **(iii)** internalization of Aβ42 peptides (yellow merge; λ~max~∼580 nm; rightmost panels); Aβ42 peptide analysis and quantification was performed using SlideBook 5.0 (Intelligent Imaging Innovations) and ImageJ (NIH) software; under control conditions approximately 40--45% of Aβ42 peptides were cleared from the extracellular medium after 24 h; this was reduced to less than 8% in miRNA-34a treated MG cells. These results are consistent with other recent reports of an elevated miRNA-34a down-regulating TREM2 expression in MG cells, and defective miRNA-34a-TREM2-mediated signaling pathways in *cellular* models of inflammatory neurodegeneration ([@B26]; [@B8]; [@B2]; [@B21]).](fnagi-08-00140-g001){#F1}

Concluding Remarks
==================

Our understanding of the highly specialized functions for small, ∼18--25 nt non-coding RNAs such as miRNAs in the CNS continues to evolve, and their abundance and patterns of expression underscore our recognition of the complexity of miRNA-mRNA-mediated genetic regulatory networks in the human CNS in health and disease ([@B11]; [@B15]; [@B5]; [@B3]; [@B27]; [@B29]; [@B1]). While the importance small non-coding RNAs in human CNS neurodegeneration including AD have been recognized for at least a quarter century ([@B13]), specific pathogenic miRNAs, their expression patterns, regulatory actions and their participation in development, aging and diseases of the CNS are all relatively new discoveries within the last decade. Indeed, it has almost been 10 years since the first description of selective miRNA alterations in AD brain and in related neurological conditions ([@B11]; [@B14]; [@B15]; [@B5]; [@B17]; [@B10]; [@B3]; [@B27]; [@B29]; [@B1]). One truly remarkable finding is that a significant up-regulation of inducible, pro-inflammatory pathogenic miRNAs such as miRNA-34a and/or miRNA-146a are shared by AD ([@B9]; [@B10]; [@B25],[@B28]; [@B1]), PrD and murine scrapie in the CNS ([@B12]; [@B3]) and in aging and AMD of the human retina ([@B17]; [@B10]; [@B2]; data not shown). Common patterns of miRNA abundance, speciation and/or complexity in the degenerating brain and retina are particularly interesting because: **(i)** both the brain and retina are commonly derived during development from the neural ectoderm; **(ii)** both brain and retina exhibit basic alterations in the innate-immune response, inflammatory signaling and amyloid generation and clearance during neurodegeneration (such as seen in AD, PrD and AMD); and **(iii)** dys-homeostasis of beta-amyloid precursor protein (βAPP) and amyloid-beta (Aβ) peptides generated from βAPP and their associated βAPP cleavage enzymes (PS1, α-secretase, β-secretase) and βAPP-docking and membrane-associated proteins (such as TSPAN12 and caveolin-1) confined to βAPP-enriched lipid raft domains accompany both age-related brain and retinal degeneration (AD, AMD, PrD; [@B10]; [@B27]; [@B1]; [@B2]). It is therefore tempting to speculate and our evolving opinion: **(i)** that a specific subfamily of pathogenic, CNS-abundant miRNAs (such as miRNA-34a and miRNA-146a) appear to be involved in common amyloidogenic aspects of selective forms of brain and retinal inflammatory neurodegeneration; **(ii)** that commonly altered mechanisms of βAPP, Aβ42, prion amyloids, other forms of amyloid and/or amyloid-derived fragment generation and clearance appear to be integral to the onset, pathogenesis and/or propagation of CNS diseases with a progressive amyloidogenic component; **(iii)** that poorly understood mechanisms of core pathogenic processes involving the homeostatic balance between pro-inflammatory miRNA signaling and the generation and clearance of Aβ42- and/or prion-based amyloids are a common unifying feature of AD and PrD; and **(iv)** that a more in depth knowledge of selective molecular-genetic components of these amyloidogenic mechanisms and pro-inflammatory pathways should provide additional targets for pharmacological intervention and the more effective clinical management of these enigmatic neurodegenerative proteinopathies ([@B20]; [@B6]).

Author Contributions
====================

All authors listed, have made substantial, direct and intellectual contribution to the work, and approved it for publication.

Conflict of Interest Statement
==============================

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

**Funding.** Thanks are also extended to the many neuropathologists, physicians and researchers of the USA, Canada, and Europe who have provided high quality, short post-mortem interval (PMI) human CNS and retinal tissues or extracted total brain and retinal RNA for scientific study. Research on miRNA in the Lukiw laboratory involving the innate-immune response, neuroinflammation and amyloidogenesis in AD, PrD, AMD, and in other neurological or retinal diseases was supported through an unrestricted grant to the LSU Eye Center from Research to Prevent Blindness (RPB); the Louisiana Biotechnology Research Network (LBRN) and NIH grants NEI EY006311, NIA AG18031, and NIA AG038834.

This work was presented in part at the Society for Neuroscience (SFN) Annual Meeting October 17--21, 2015, Chicago, IL, USA and at the Association for Research in Vision and Ophthalmology (ARVO) Annual conference May 1--5, 2016 in Seattle WA USA. These studies utilized total RNA and other nucleic acid fractions extracted from short post-mortem human brain and retinal tissues; no live human subjects or animals were involved; sincere thanks are extended to Drs. E. Head, W. Poon, H. LeBlanc, F. Culicchia, C. Eicken and C. Hebel for short PMI human brain and/or retinal tissues or extracts, miRNA array work and initial data interpretation, and to D Guillot and AI Pogue for expert technical assistance in the preparation of this manuscript for publication.

[^1]: Edited by: *Aurel Popa-Wagner, University of Rostock, Germany*

[^2]: Reviewed by: *Yu-Min Kuo, National Cheng Kung University, Taiwan; J.R. Walton, University of New South Wales, Australia*