Here, we review these and other experimental approaches in common use for identification and characterization of lncRNAs, particularly those involved in different types of cancer, with focus on merits and demerits of each technique.Long non‐coding RNAs (lncRNAs) comprise a vast repertoire of RNAs playing a wide variety of crucial roles in tissue physiology in a cell‐specific manner. Despite being engaged in myriads of regulatory mechanisms, many lncRNAs have still remained to be assigned any functions. A constellation of experimental techniques including single‐molecule RNA  In the post‐genomic era, the ‘junk’ moniker is giving way to the understanding that most of the genome is fully functional 6 adenosine methylation (m6A) Most lncRNAs are transcribed by RNA polymerase II LncRNAs play a diversity of regulatory functions due to their modular structures and RNA–RNA or RNA–DNA base pairing ability HOXD gene by binding two enzymes (PRC2 and LSD1) involved in chromatin modification HOXD gene, where PRC2 deposits the H3K27me3 modification needed for repression and LSD1–CoREST–REST erases the H3K4me2 modification involved in activation By combining their modularity and base‐pairing ability, lncRNAs act as guiding molecules, directing proteins to other RNA or DNA molecules PCDH10, PCDHB5 and JAM2) LncRNAs, now being emerged as master regulators of gene expression, have been shown to be involved in a variety of malignancies In addition, lncRNAs have been proven as important diagnostic and prognostic biomarkers of cancer and other disorders Thanks to advances in increasing the depth of RNA sequencing techniques, thousands of novel lncRNAs have been discovered in recent years. However, the task of characterizing newly discovered lncRNAs is an arduous one, contingent on the power of technologies at our disposal.In this review, we strive to shed light on the ever‐expanding toolkit of techniques employed in lncRNA research. The methods are classified based on methodology as techniques used to visualize lncRNAs, determine their structure, map their interactions with other cellular components and elucidate their functions. Each method is described briefly, with their attributed pros and cons being discussed and summarized.Most of the genomic sequence is transcribed, and the majority of such transcripts do not code for proteins As with other molecules, our knowledge of the subcellular localization of lncRNAs opens up new vistas to their potential cellular roles et al., made use of two pools of probes labelled with different fluorophores and co‐localizing the signals obtained using the two probe sets. If the signals co‐localize, then they are construed as true ones indicating the lncRNA localizations, otherwise at least some of the signals are considered to be due to off‐target hybridizations A common obstacle in revealing the subcellular localization of lncRNA molecules is the off‐target hybridization of probes to nuclear aggregations, generating blob‐like signals like that of true lncRNA signals. Cabili RNA FISH and immunofluorescence have been used in order to show the co‐localization of Urothelial carcinoma associated 1 (UCA1(and phosphorylated hnRNP1 in the perinuclear regions to confirm that the phosphorylated form of hnRNP1 is able to interact with UCA1 RNA tracking methods have been developed that take advantage of green fluorescent protein fused to MS2 coat protein (MCP) and the MS2 binding sequence inserted into the RNA molecule to be analysed. The RNA molecule containing the MS2 binding site and the GFP‐MCP fusion protein are expressed inside the cell. The localization of RNA molecules is revealed through GFP‐MCP binding to the MS2 site The GFP fluorophore, 4‐hydroxybenzylidene imidazolinone (HBI) does not show fluorescence in the absence or denaturation of the GFP protein. RNA mimics of GFP are aptamer molecules that can bind HBI or other GFP like fluorophores and enable them to fluoresce The CRISPR/Cas9 system is considered as a type of adaptive immunity in bacteria and archaea The RNA‐binding capability of Cas9 protein has spurred the development of technologies for tracking the subcellular localization of RNA molecules Despite being tested on few mRNA molecules, the CRSPR‐based RNA tracking technology has the potential to be utilized in studies aimed at revealing the subcellular localization of RNAs including lncRNAs.Unlike RNA detection technologies based on RNA–protein interactions, the CRSPR‐based RNA tracking technique does not require laborious genetic engineering procedures, as target recognition is based on RNA–RNA interactions LncRNAs are capable of folding on themselves and therefore taking a wide variety of secondary and tertiary structures, enabling them to perform their functions SHAPE is among the key techniques commonly used to unravel the secondary structure of lncRNAs in vivoin vitro to in vivo in icSHAPE(in vivo click SHAPE) Despite being a powerful technique in unravelling the single and double‐stranded regions of lncRNA molecules, SHAPE is not able to determine the range of such base paring interactions An array of chemical probing techniques including SHAPE has been employed to characterize HOTAIR in structural terms in vitro, subjected to RNase treatment, ligated to adaptors and sequenced. Finally, a PARS score is obtained as the log ratio of in a double‐ or single‐stranded conformation. The log ratio between the number of sequence reads obtained for each nucleotide in the V1 (cleaving double‐stranded RNA) and S1 (cleaving single‐stranded RNA) experiments. A nucleotide with a higher log ratio, or PARS score, thus indicates a higher probability of being in a double‐stranded conformation  is a modification of ChIRP (described in 4.1.1) that allows simultaneous mapping of RNA–RNA, RNA–DNA and RNA–protein interactions at the level of individual domains In this technique, the cells are subjected to cross‐linking agents to preserve protein–nucleic acid interactions and then sonicated to shear the nucleic acids. Specific biotinylated oligonucleotides are used to tile individual domains. Streptavidin magnetic beads are then added to capture specific interactions and non‐specific interactions are washed away. The material recovered from dChIRP is finally fractioned into protein, DNA and RNA parts for extraction and analysis. The parts can be subjected to real‐time PCR using primers for the lncRNA domain of interest and other RNAs suspected to be in its interaction. The protein content can be analysed by Western blotting or mass spectrometry to reveal any protein interacting with different domains. Recovered DNA can be also sequenced, revealing any binding sites on genome that may become occupied by a given lncRNA domain Unlike other techniques used to map lncRNA interactome, dChIRP is capable of revealing lncRNA multivalent interactions with other RNA, DNA and protein molecules in a single reaction Using dChIRP, Rox lncRNA was indicated to have interaction with MSL proteins through its D1, D2 and D3 domains. The Rox binding sites on X‐chromosome  were also clearly determined. dChIRP has the potential to be applied to other lncRNAs with important implications in cancer, on the way to revealing their interactions in a domain by domain manner The traditional approach for gene discovery called forward genetics relies on finding aberrant phenotypes in a model organism and then unravelling the genes behind such phenotypes. In reverse genetics, however, a given gene of interest is perturbed and the resulting phenotypic change is observed, helping to find the gene function. Reverse genetics are particularly important in delineating the important roles of lncRNAs in cancer, as gene ablations can clearly depict their contributions to cancer phenotype or transformation of normal cells. Here, we look at the techniques utilized in lncRNA reverse genetics Several technologies for genome editing based on programable proteins including Zinc‐finger nucleases (ZFNs),transcription activator like effector nucleases (TALENs) and Cas9 have emerged over the past 10 years Making use of two gRNAs, the dual CRISPR system is suited for perturbing lncRNAs in contrast to conventional methods, which may lead to insertions or deletions, not enough to eliminate the function of lncRNAs The applicability of the all‐in‐one system strategy in perturbing lncRNAs was illustrated by ablating urothelial carcinoma‐associated 1 (UCA1), lncRNA‐21A and AK023948 in various human cell lines While the knockout techniques eliminate gene expression by deleting the genes, RNAi suppresses expression by sequestering and then cleaving RNA molecules Any RNAi experiment has to be accompanied by standard controls Involved in aggressive prostate cancer, second chromosome locus associated with prostate‐1 (SChLAP1), is an lncRNA that inhibits the tumour‐suppressive activity of the SWI/SNF complex. The role of SChLAP1 in contributing to aggressiveness of prostate cancer was assayed by performing siRNA‐mediated knock‐down experiments. Remarkably, the SChLAP1 knock‐down dramatically decreased cell proliferation and invasiveness.RNAi has been successfully applied to many loss‐of‐function studies involving lncRNAs GFP in HEK293 cells and endogenous genes including CD71, CXCR4 in HeLa cells The versatility of CRISPR/Cas9 has enabled repurposing of its utility from genome editing to genome regulation Acting at the DNA level, CRISPRi can be a useful tool to target non‐coding transcripts including lncRNAs as well as microRNAs and products of RNA polymerase III in vitro transcription in the presence of labelled UTPs can be performed for the generation of RNA FISH probes. In vitro transcription followed by RNase III digestion can be implemented for the production of esi‐RNAs. c‐KLAN combines the power of RNA FISH and RNAi for characterizing lncRNAs through loss‐of‐function studies and subcellular visualization RNA‐FISH is utilized to localize RNA transcripts inside the cell c‐KLAN has been efficiently utilized to reveal the lncRNAs involved in pluripotency Despite being highly effective devices in loss‐of‐function studies, siRNA and shRNAs cannot be used effectively in depleting nuclear lncRNAs, although the RNAi machinery also exists in the nucleus 2′‐O‐methoxyethylribose (2′‐MOE)) on their termini, intervened by a central ‘gap’ of unmodified DNA, 8‐10 bases in size As effective tools for silencing nuclear lncRNAs, ASOs are modified or unmodified single‐stranded deoxyribonucleotides, with the ability to hybridize to their targets among a population of transcripts present in the cell. Knock‐down experiments using ASOs are based on the ability of RNase H to degrade the RNA part of a DNA–RNA duplex MALAT1 was also observed in systematic MALAT1 depletion using ASOs Several groups have used ASOs successfully in loss‐of‐function studies of nuclear lncRNAs. For instance, ASOs were utilized in an attempt to knock‐down the nuclear‐retained MALAT1, systemically. Two gapmers against different parts of MALAT1 were used, and systemic knock‐downs using ASOs were shown to recapitulate the same results observed in knockout studies. Besides, the same reduction in metastasis happening upon genetic loss of Cell function is governed by a complex network of interactions involving different cellular components Conventional methods of chromatin precipitation commonly make use of antibodies against proteins associated with DNA ChIRP, which can be considered as an analogue of ChIP, has been used by different research groups hitherto to map the genomic binding sites of different lncRNAs RNA immunoprecipitation (RIP) is a technique which can be employed to unravel all lncRNAs that interact with specific proteins of interest Like other protein‐centric pull‐down assays, RIP is dependent on antibodies previously produced against the suspected counterpart proteins In a study of the role of the lncRNA, UCA1, in breast cancer promotion, RIP was employed to indicate that UCA1 interacts with hnRNP1 and suppresses the p27 protein level by competitive inhibition To investigate the role of MALAT 1 in splicing of pre‐mRNAs, antibodies against SRSF1 splicing factor, and primers specific to MALAT1 were used to reveal a specific interaction between them, using the RIP technique Further refinement of RIP has led to cross‐linking and immunoprecipitation (CLIP) technique, which is capable of revealing a more accurate picture of lncRNA–protein interfaces with single nucleotide resolution In contrast to other CLIP variants, which makes use of cross‐linking with 254 nm UV light, PAR‐CLIP takes advantage of 4‐thiouridine to facilitate the cross‐linking process, allowing it to occur at a higher UV wavelength (365 nm) irCLIP and eCLIP are newly introduced versions of CLIP techniques developed to increase reverse transcription efficiency and decrease RNA loss and sequencing backgrounds The advantages and disadvantages of each of the CLIP techniques have been reviewed in Table .In a genome‐wide analysis of lncRNA binding sites on different RBPs, CLIP‐seq was employed to show the interaction of Ezh, a PRC2 complex subunit, with 35 lncRNAs including Tsix, Meg3, Rian and Pvt1 Using PAR‐CLIP, TUG1, DLEU2 and GAS5 lncRNAs were also shown to bind at least two of the three RNA‐binding proteins HuR, Ago2 and MOV10 at identical binding sites Moreover, CLIP has been employed to show air interactions with H3K9 histone methyl‐transferase G9a Over the past 20 years important efforts have been made allowing the research to be directed at transcriptome‐wide analysis of RNAs and changes in their global patterns of expression Several methods have been developed for global or single‐molecule mapping of local primary and secondary structures of RNA molecules in vitro cross‐linking Previous attempts have been made to map miRNA–mRNA interactions in RNA induced silencing complexes Some lncRNAs are shown to function through interaction with other RNA molecules Deamination of Adenosine to inosine is a common RNA modification, which plays important regulatory roles and has been implicated in several disorders including cancer N1‐cyanoethylinosine adduct halts the cDNA extension process and allows identification of A‐to‐I editing points. The procedure is carried out with or without CE. In CE− conditions both I and A positions recognized in sequencing. However, under CE conditions the RNAs undergoing A‐to‐I modifications stop to extend beyond the edition point. Therefore, the G band (I is read G in sequencing process) is erased, and a shaper A band is detected and that point is identified as a true modification site ICE‐seq makes use of Inosine cyanoethylation with Acrylonitrile. The resulting Caenorhabditis elegans poly (U) polymerase (PUP‐2) Despite being effective in determining RNA–protein interactions, RIP and CLIP can only unravel protein‐RNA interactions when specific antibodies against the protein of interest are already available These techniques have the potential to be extended to lncRNA research, shedding light on all the interactions a given protein of interest may have with the population of lncRNAs inside the cell and depicting probable interruptions in such interaction networks that may lead to cancer.A global understanding of genomic regions undergoing active transcription can provide valuable information for discovery and functional analysis of lncRNAs. Global run‐on assay sequencing (GRO‐seq) is a technique based on NGS technologies that provides valuable insights into of the location, orientation and density transcripts undergoing active transcription by RNA polymerase II. In this technique, the RNA polymerase is allowed to function in the presence the UTP analogue Bromodeoxyuridine (BrdU). The nascent RNAs are captured using anti‐BrdUTP antibodies and subjected to deep sequencing. The resulting sequence reads are aligned across the genome to map the genomic positions undergoing active transcription The technique, however, is limited to cell culture and other artificial systems due to its dependence on incorporation of Bromodeoxyuridine (BrdU). New initiation events that may happen and introduction of artefacts during preparation of nuclei are among other demerits of the technique Using this method, several studies have indicated that transcription by RNA pol II often occurs divergently and leads to production of lncRNAs et al. The result of many studies has shown that there is an intimate relationship between mRNA half‐life and its function, which implies an understanding the half‐life of lncRNAs can provide useful information about their functions The method involves pulse labelling of cells with 5′‐bromo‐uridine and then quantifying the decrease in labelled RNA levels that occurs over time making use of deep sequencing. The result of this study indicated that RNA molecules with half‐lives <4 hrs include the majority of regulatory and lncRNAs in situ hybridization allows simultaneous visualization of cellular location of a small number of transcripts RNA sequencing provides valuable insights into global quantitative and qualitative changes in transcripts but does not picture the spatial distribution of transcripts in vitro quantitative measurement of transcripts to in vivo and allows spatial organization of gene expression to be revealed globally FISSEQ extends the applicability of RNA‐seq beyond FISSEQ has the potential to reveal the global spatial changes in lncRNA expression in disease conditions including cancer. However, the technique needs to be refined regarding its read length, sequencing depth and coverage and library preparation The complexity of cells is better appreciated with this emerging view that most of the genome is functional and ubiquitously transcribed into a repertoire of coding and non‐coding RNAs. LncRNAs are highlighted in the new transcriptional landscape replete with transcripts of unknown function. They play vital roles in various cellular processes and disease conditions including cancer.. Therefore, considering their important regulatory roles, lncRNAs are among the missing parts of the puzzle in the long‐lasting fight against cancer and have to be scrutinized comprehensively so as to enhance our current understanding of this disease. The boundaries of our capability to understand how lncRNAs can contribute to cancer prevention or progression are contingent on power of the techniques available.in vitro. To overcome the single‐molecule limitation of SHAPE, global structural analysis of the complete RNA reservoir or structurome has been now possible by PARS and Fraq‐seq. icSHAPE has extended the applicability of lncRNA structural studies by SHAPE to the realm of in vivo. LncRNA interaction networks have been clearly delineated using RNA‐centric approaches comprising ChIRP, CHART, RAP and protein‐centric methods including CLIP. dChIRP has enabled domain by domain interrogation of lncRNA interactions. CLIP has been refined regarding its throughput and resolution to iCLIP and PAR‐CLIP. Recently, further refinement of CLIP has led to irCLIP and eCLIP which allow more accurate and rapid determination of lncRNA–protein interactions. RNAi has allowed the knock‐down experiments employed in functional studies of lncRNAs and CRISPRi can increase the precision with which we can suppress lncRNA expression in reverse genetic investigations. TRIBE‐seq enables global mapping of lncRNA–RNA interaction network, without any pre‐existing antibody for affinity purification required in CLIP techniques. ICE‐seq allows the research to be directed at depicting a global picture of lncRNA epitranscriptome and is not confounded by individual variations due to SNPs. The half‐life of lncRNAs can be screened in real time using BRIC‐seq. GRO‐seq provides a picture of transcriptionally active genomic regions as it can capture nascent RNA molecules.High‐throughput sequencing has accelerated the pace at which new lncRNAs are being discovered and allows global analysis of lncRNAs. However, our ability to characterize the expanding catalogue of unknown lncRNAs is also dependent on other techniques enabling us to map lncRNA interactions, their structure and function. For instance, the subcellular location of lncRNAs can be determined using FISH and further clarified by the combination of FISH and esi‐RNA technology (cKLAN). Compared to RNA FISH which can localize few transcripts in a single reaction, FISSEQ allows the research to be directed at quantitative global and spatial analyses of lncRNA expression. New technologies developed based on CRISPR‐Cas system can now be a complement to the current RNA visualization techniques as they may be better applied to non‐coding transcripts. Structural studies of lncRNAs have become more feasible using SHAPE. But SHAPE is limited to single‐molecule analyses carried out As aberrations in abundance, subcellular localization and interaction networks of lncRNAs are among key contributors to cancer progression, the technological toolkit described throughout this review is central to a deeper understanding of lncRNAs not yet characterized, revealing their likely widespread roles in cancer disease and opening new perspective for therapy.The authors confirm that there are no conflicts of interest.


In the original article, there were mistakes in Figures *p < 0.05, **p < 0.001.Figure *p < 0.05, **p < 0.01, ***p < 0.001.Figure *p < 0.05, **p < 0.01, ***p < 0.001.Figure In the original article, the standardized Beta value was reported in the text where the unstandardized b value should have been reported.Parenting by Lying and the Frequency of Lying to Parents, paragraph one:A correction has been made to the Results section, R2 = 0.08, ΔF = 4.33, p = 0.043. Thus, as exposure to parenting by lying in childhood increased, the frequency of lying to parents during adulthood also increased, bparent lying = 1.86, SE = 0.89, t(49) = 2.08, p = 0.043, 95% CI , rpart = 0.29.We conducted a simple linear regression to determine whether parenting by lying is associated with the frequency of lying to parents. Parenting by lying was entered as the predictor variable and lying to parents served as the dependent variable. Parenting by lying significantly predicted lying to parents, explaining 8% of the total variance, ΔThe authors apologize for these errors and state that this does not change the scientific conclusions of the article in any way.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.


Sound RNA Sampling Card  is a device that enables specimens or isolates to be applied to a card, whereby viruses are inactivated, while RNA is preserved and purified RNA can also easily be eluted. To evaluate this card, we applied influenza virus cell culture isolate supernatants to either the RNASound card or Whatman Grade No. 1 filter paper  and compared the preservation to that of material stored in liquid form. Preservation was tested using influenza A and B viruses at two different storage temperatures [cool (2–8°C) or room temperature (18–22°C)] and these were compared with control material stored at -80°C, for 7, 14, or 28 days. The quality of the RNA recovered was assessed using real time RT-PCR and Sanger sequencing. The RNASound card was effective in preserving influenza RNA at room temperature for up to 28 days, with only a minor change in real-time RT-PCR cycle threshold values for selected gene targets when comparing between viruses applied to the card or stored at -80°C. Similar results were obtained with filter paper, whilst virus in liquid form performed the worst. Nevertheless, as the RNASound card also has the capability to inactivate viruses in addition to preserving RNA at room temperature for many weeks, this makes it feasible to send samples to laboratories using regular mail, and thus avoid the need for expensive shipping conditions requiring biohazard containers and dry ice. Moreover, the quick and simple RNA recovery from the RNASound card allows recipient labs to obtain RNA without the need for special reagents or equipment.Shipping influenza virus specimens, isolates or purified RNA is normally conducted at ultra-low temperatures using dry ice to ensure minimal degradation of the samples but this is expensive and requires special packaging and shipping conditions. Therefore, alternative methods for shipping influenza viruses or RNA at ambient temperatures would be desirable. The RNA Viruses that infect humans and animals can have a devastating impact on morbidity and mortality and therefore rapid analysis of specimens to determine the identity of causative viruses is important. Molecular-based assays, such as real-time RT-PCR, are rapid, sensitive and specific and are now widely used in diagnostic laboratories around the world . HoweverRecently, several new products, such as RNAstable , GenTegra  and RNAshell  have been developed for the purpose of preserving RNA at room temperature based on the principle of anhydrobiosis . HoweverThe Whatman FTA card  is another filter paper system that differs from regular filter paper, as it contains chemicals that can inactivate viruses and stabilize nucleic acids. However, these appear to have been designed specifically for long-term preservation of DNA at room temperature, as the manufacturer recommends that RNA be processed as soon as it reaches the laboratory or be kept frozen . NeverthSound card  is similar to the Whatman FTA card, but with a simpler RNA extraction/elution process. Virus samples are inactivated once applied to the disks of the RNASound card and easily eluted by pushing-out the disks and shaking them in RNase-free water. In comparison, special reagents, equipment and techniques are required to isolate RNA from the Whatman FTA cards pdm09 virus  and a type B (B/Victoria/02/1987-lineage) virus (B/Brisbane/60/2008), were collected as part of the WHO Global Influenza Surveillance and Response System and cultured in Madin-Darby canine kidney (MDCK) cells. These viruses were handled in a PC2 facility to comply with biohazard requirements. Both viruses were diluted in phosphate buffered saline (PBS) to a titre of 32 haemagglutination units (per 25 μl). These were then also used to prepare purified RNA in a 1:1 volume ratio.Sound card are summarized in Figure 1. Briefly, virus was applied to either the RNASound card or Whatman Grade No. 1 filter paper , or kept in liquid form, and all were stored at either room temperature (18–22°C) or in a fridge , for either 7, 14, or 28 days. Purified RNA was also stored under the same conditions following either application to filter paper or being kept in liquid form. Unless otherwise indicated, all RNA purifications/extractions were performed using the QIAamp Viral RNA kit . Ten microliters of virus or purified RNA (for filter paper only) was applied onto each of the two disks of the RNASound card or onto each of two similarly sized disks of filter paper. All disks were left to air-dry for an hour at room temperature, then stored in individual sealed plastic bags containing a desiccant, as per manufacturer’s instructions. For the liquid form, virus (cell culture isolate supernatant diluted in PBS) or RNA (in RNase-free water) was stored in 20 μl aliquots. To recover RNA from virus applied to the RNASound card, the two push-out disks per sample were placed into a 1.5 ml microtube containing 100 μl pre-heated (75°C) RNAase-free water, shaken for 5 min using a vortex, and then the disks were removed. For RNA recovery of virus applied to the filter paper, the two disks were placed into a 1.5 ml microtube containing AVL buffer + carrier RNA , shaken for 5 min using a vortex, and then RNA was extracted as per manufacturer’s protocol, but with a final elution volume of 100 μl using RNAse-free water. RNA recovered from virus stored in liquid form, including the control virus stored at -80°C, was eluted in 100 μl RNAse-free water. For the purified RNA that was applied directly to filter paper, the same method to that used for eluting from the RNASound card was used, where two disks were placed into a 1.5 ml microtube containing 100 μl pre-heated (75°C) RNAase-free water, shaken for 5 min, and then the disks were removed. Purified RNA stored in liquid form (20 μl), including the -80°C control purified RNA, was made up to a total volume of 100 μl with RNase-free water, to ensure the dilution factor was equivalent to the other methods. With the exception of the -80°C controls, all eluted RNA was used immediately on the same day for real-time RT-PCR analysis and Sanger sequencing, thus eliminating any possible freeze-thaw effects on the RNA.The different storage conditions used to assess the RNACt) value for each sample held under various conditions was compared with the mean Ct value for the respective control virus or purified RNA stored at -80°C (considered the gold standard for storage of viruses and nucleic acids). Analysis of variance and post hoc Tukey test were used to compare mean Ct values and generate 95% confidence intervals for the difference in mean Ct (ΔCt) to the -80°C control. All analyses were performed using Stata14  according to the manufacturer’s protocol with 4 μl of RNA used per reaction. Primer/probe sets targeting the matrix (MP) segment of the influenza A virus (FluA) and the non-structural (NS) segment of the influenza B virus (FluB) were kindly provided by the Influenza Division at CDC, Atlanta, USA ,b. Therm Stata14 .In addition to real-time RT-PCR analysis, the preservation of RNA was also assessed by Sanger sequencing. Conventional RT-PCR was performed using the MyTaq One-Step RT-PCR kit  using in-house subtype-specific HA primers according to the manufacturer’s protocol. Thermocycling conditions were 45°C for 40 min, 95°C for 1 min, followed by 40 cycles of 95°C for 10 s, 60°C for 10s and 72°C for 1 min, with a final hold at 72°C for 2 min. RT-PCR products were visualized on an E-Gel  and purified by ExoSAP-IT . A sequencing reaction was then conducted using Big Dye Terminator Reaction Mix  and purified with Big Dye Xterminator  before being run on the ABI 3500xL sequencer. Sequence data was analyzed using the SeqMan  software.Figure 2 summarizes the difference in mean Ct values (ΔCt) between the Ct values of RNA eluted from the RNASound card (and other storage media) compared with the ‘gold standard’ of virus stored at -80°C for the equivalent amount of time. The preservation of influenza A virus on the RNASound card for 7, 14, or 28 days at room temperature was highly effective with Ct values within <0.5 cycles of virus stored at -80°C and extracted using standard techniques . No additional benefit was observed if the RNASound cards were kept cool rather than at room temperature. The preservation of influenza A virus on Whatman Grade No. 1 filter paper (followed by standard RNA extraction) yielded Ct values that were ≈1 Ct value higher than the virus stored at -80°C across all time points and temperatures, indicating only a minor loss in RNA quantity . The addition of purified RNA to Whatman Grade No. 1 filter paper also showed a minor loss in quantity compared to the purified RNA control stored at -80°C. As expected, virus stored in liquid form showed the worst deterioration at room temperature with increases of ≈3 Ct values after 7 and 14 days, and ≈4 Ct values after 28 days, compared to virus stored at -80°C . However, purified RNA in liquid form (RNase-free water) appeared very stable at both cool and room temperatures for up to 28 days, yielding highly similar Ct values (within <0.5 cycles) to purified RNA stored at -80°C for the equivalent amount of time .Data presented in Ct value) following preservation of the influenza B virus on the RNASound card for 7, 14, or 28 days at cool or room temperature, compared to virus stored at -80°C. Interestingly for short-term (7 days) storage, virus on filter paper appeared to perform better than the RNASound card, although there was no significant difference between the two at 14 or 28 days. Purified RNA on filter paper behaved similarly to virus on the RNASound card with a minor loss in quantity. Influenza B virus stored in liquid form appeared more stable than influenza A virus, with increases of ≈1 Ct value at 7 and 14 days, and ≈2 Ct values at 28 days, compared to virus stored at -80°C. Purified RNA (in RNase-free water) was again very stable at cool or room temperature, with only a slight increase of <1 Ct value when stored at room temperature for 28 days, compared to purified RNA stored at -80°C for the equivalent amount of time.There was a minor loss of RNA quantity . Subsequent sequence analyses of the RT-PCR products showed that the electropherogram and sequence quality were of a high standard for all samples except for the influenza A virus stored in liquid form at room temperature for 28 days (data not shown).Conventional RT-PCR of the HA gene was conducted on RNA from both the influenza A and B viruses preserved under the various conditions outlined above. Amplicons of a similar intensity to that obtained from the -80°C controls were successfully generated for all samples, as visualized following gel electrophoresis, except for the influenza A virus stored in liquid form at room temperature for 28 days, where the amplicon was faint on the E-Gel  or frozen (-80°C) conditions promptly, then the virus and its nucleic acid can rapidly degrade, potentially impacting on the capability of laboratories to achieve a diagnosis.Sound card in this study due to its ease-of-use in preserving RNA at room temperature, its ability to inactivate viruses when applied to the card, and the simple RNA extraction process. Although this is the first reported use of the RNASound card for preserving influenza virus RNA, there has been an established protocol of its use for West Nile Virus RNA preservation as part of a dead bird surveillance program , which could occur during sample shipment, and the effect of varying virus concentrations to determine the quantity of RNA that can be eluted from the card, may be worthwhile. Furthermore, while the inactivation of viruses upon application to the RNASound card can, in certain circumstances, be advantageous as it reduces the biohazardous nature of infectious viruses, it has the disadvantage that the specimen is no longer viable for culture in the laboratory. Although RNA alone is sufficient for diagnostic tests, a more detailed antigenic characterization of influenza viruses requires an egg- or cell-cultured isolate. Another concern is that the inactivation may be dependent on the amount of virus added to the card. An interesting side observation from this study was that RNA eluted in RNase-free water was extremely stable at room temperature and therefore may indicate that purified RNA in RNase-free water does not need to be shipped on dry ice.In this study, we evaluated the capability of the RNASound card was effective in preserving influenza RNA when cell culture isolates of influenza A and B viruses were applied to the card, although the effectiveness differed slightly depending on the virus used. Future studies that test additional influenza A and B viruses may confirm, or otherwise, the differences between viruses of the two types for the RNASound card vs. filter paper on day 7. Despite also observing a similar performance with virus applied to filter paper, we conclude that the main benefit in using the RNASound card lies in its ability to inactivate viruses (due to the presence of lysis buffer) and its simple RNA recovery method . As the RNASound card can inactivate viruses and preserve RNA at room temperature for up to 28 days, this makes it feasible to send RNA using regular mail. There will be no need for expensive shipping conditions requiring biohazard containers and dry ice. Moreover, the quick and simple RNA recovery from the RNASound card allows recipient labs to extract the RNA for testing without the need for special reagents or equipment.Overall, we observed that the RNAAH and HL conceived the study, conducted the experiments, then drafted, revised and approved the manuscript.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.Sound RNA Sampling cards free-of-charge for use in the evaluation. FortiusBio did not provide any funding for the study, and had no input into the experimental design, analysis of results or the preparation of the manuscript.FortiusBio LLC, San Diego, CA, USA provided the RNA


Perceptual decision-making is biased by previous events, including the history of preceding choices: observers tend to repeat  their judgments of the sensory environment more often than expected by chance. Computational models postulate that these so-called choice history biases result from the accumulation of internal decision signals across trials. Here, we provide psychophysical evidence for such a mechanism and its adaptive utility. Male and female human observers performed different variants of a challenging visual motion discrimination task near psychophysical threshold. In a first experiment, we decoupled categorical perceptual choices and motor responses on a trial-by-trial basis. Choice history bias was explained by previous perceptual choices, not motor responses, highlighting the importance of internal decision signals in action-independent formats. In a second experiment, observers performed the task in stimulus environments containing different levels of autocorrelation and providing no external feedback about choice correctness. Despite performing under overall high levels of uncertainty, observers adjusted both the strength and the sign of their choice history biases to these environments. When stimulus sequences were dominated by either repetitions or alternations, the individual degree of this adjustment of history bias was about as good a predictor of individual performance as individual perceptual sensitivity. The history bias adjustment scaled with two proxies for observers' confidence about their previous choices (accuracy and reaction time). Together, our results are consistent with the idea that action-independent, confidence-modulated decision variables are accumulated across choices in a flexible manner that depends on decision-makers' model of their environment.SIGNIFICANCE STATEMENT Decisions based on sensory input are often influenced by the history of one's preceding choices, manifesting as a bias to systematically repeat  choices. We here provide support for the idea that such choice history biases arise from the context-dependent accumulation of a quantity referred to as the decision variable: the variable's sign dictates the choice and its magnitude the confidence about choice correctness. We show that choices are accumulated in an action-independent format and a context-dependent manner, weighted by the confidence about their correctness. This confidence-weighted accumulation of choices enables decision-makers to flexibly adjust their behavior to different sensory environments. The bias adjustment can be as important for optimizing performance as one's sensitivity to the momentary sensory input. It has been known for almost a century that people's judgments of sensory stimuli do not only depend on the current sensory input, but also on their preceding choices . SeveralComputational models posit that choice history biases result from the temporal accumulation of signals from past decisions . Such a Perceptual decisions often have to be made under uncertainty due to weak or ambiguous evidence. This uncertainty (or its complement: confidence) might be important for controlling behavior under conditions, in which the decision-maker receives no immediate external feedback. Indeed, fluctuations of confidence play a key role in a normative model, which postulates the accumulation of the internal decision variable over time . The decOur current study addressed three questions. First, do choice history biases originate from signals in motor or action-independent formats? Second, can these signals be accumulated in a sufficiently flexible manner, so as to adjust history biases to repetitive as well as alternating environments? Third, is the strength of such bias adjustment scaled by confidence? We modeled human choice behavior under experimental manipulations tailored to answering these questions.We analyzed data from 28 participants and two experiments (referred to as Experiments 1 and 2) in total. All participants gave their written informed consent.Six healthy participants  took part in the experiment, which was approved by the ethics committee of the Department of Psychology of the University of Amsterdam (reference number 2011-OP-1588).Twenty-six healthy participants  took part in the experiment, which was approved by the local ethical review board . Four participants were excluded from the data analysis, so that 22 participants remained for the data analysis. Three of the excluded participants did not complete all sessions and one exhibited substantially worse performance than the rest of the group .The data from both experiments allowed for quantifying choice history biases during a random dot motion discrimination (up vs down) task. We used large random dot motion patterns in both experiments, so as to minimize stochastic fluctuations in the effective motion energy across trials .A) were composed of 785 (average) white dots on a black screen. The dots were moving within a circular aperture of 9.1° radius. A red fixation cross of 0.4° × 0.4° was centered in the middle of the circle. The dot density was 12.07 dots/deg2. The population of dots was split into “signal dots” and “noise dots”. The signal dots moved either upward or downward with a velocity of 2.6°/s. The noise dots changed position randomly from frame to frame. The percentage of signal dots defined the motion coherence, a measure of motion strength. On each trial, three different sequences of dot motion (at the same coherence and direction) were presented in an interleaved fashion, making the effective speed of signal dots 0.87 °/s. One of six different levels of motion coherence  and one of six different viewing durations  were chosen randomly, under the constraint that they occurred equally often within a block of 144 trials. Stimuli were presented on a 22 inch CRT monitor with a resolution of 800 × 600 pixel and a frame rate of 100 Hz at a viewing distance of 68 cm. The participants were instructed to maintain their gaze on the red cross throughout the trial and judge the net motion direction. The motion viewing interval was followed by a variable delay (uniform distribution ranging from 200 to 400 ms), after which the observers had to report their choice by pressing one of two buttons on a computer keyboard, with either the left or the right index finger. Participants received auditory feedback after incorrect responses (a 1000 Hz tone of 100 ms). Perceptual choices (“up” vs “down” motion direction) were decoupled from motor responses (left vs right button press) by varying their mapping from trial to trial. This mapping was instructed before motion viewing in one condition (“Pre” condition) and after motion viewing in the other (“Post” condition), by means of a visual cue that presented each direction (as an arrow) on the left or right side . This mapping cue was randomly selected on each trial. Conditions alternated across blocks. Observers 1–5 participated in both conditions. Observer 6 participated only in the Post condition. The analyses of participants 1–5 presented here were collapsed across both conditions. We obtained the same pattern of results when analyzing the data from both conditions separately (data not shown).The following description summarizes the aspects of the experimental design that were most important to the current paper; a comprehensive description can be found in . Random Fig. 1B). Stimuli, task, and procedure for Experiment 2 were identical to Experiment 1, with the following exceptions. The circle within which the dots were moving had an outer radius of 12° and an inner radius of 2°. The density of dots was 1.7 dots/deg2 and each dot had a diameter of 0.2°. The dots moved with a velocity of 11.5°/s. Signal dots had a maximum lifetime of six frames. We used the following coherence levels: 0, 5, 10, 20, 40, and 60% . A red bullseye fixation target at the center of the screen as well as randomly moving dots (0% coherence) were presented throughout each block. The first trial of each block started with a baseline interval of 5 s. A beep  indicated the onset of the evidence interval with variable coherence levels and directions after a fixed duration of 0.75 s. A second beep indicated the offset of the evidence interval and prompted the observers' response. Observers reported their perceptual choices by pressing one of two keyboard buttons, with the index finger of the left or right hand. After button press or a response deadline of 3 s, the intertrial interval started. Intertrial intervals were uniformly distributed between 1 and 5 s. Observers received auditory feedback during the training sessions, but no feedback during the subsequent six sessions of the main experiment. The motion viewing duration of 0.75 s was selected because previous work in monkeys , or “Alternating” environments B. Stimul monkeys  and huma monkeys  found liB, right). Specifically, the probability of a repetition was defined as follows:n indexes trials. The repetition probability was held constant within each session, but varied across the main experimental sessions between the following values: 0.5 in the Neutral condition, 0.8 in the Repetitive condition, and 0.2 in the Alternating condition. The Neutral condition allowed for quantifying observers' intrinsic choice history bias, which we used as a baseline for quantifying their adjustment to the biased sequential statistics of the Repetitive and Alternating conditions.Critically, the transition probabilities between the two alternative stimulus categories  over trials were manipulated across experimental sessions B, right.During the training session, the motion direction on each trial was chosen randomly and independently. All participants started with the Neutral condition in Session 1 of the main experiment, which was repeated in Session 4. Half of the participants then performed the Repetitive condition in Sessions 2 and 5 and the Alternating condition in Sessions 3 and 6 and conversely for the other half of participants.Observers were instructed to maintain stable fixation and perform the motion discrimination task as accurately as possible. They were informed that the sequential statistics of the stimulus identities would change from session to session, but stay constant within each session. To this end, we told them that the stimulus sequences could be “as if produced by a coin flip” , “more likely repeating than alternating” (Repetitive), or “more likely alternating than repeating” (Alternating). Observers were not informed about (1) the order of these conditions, (2) the exact transition probabilities, and (3) the use of this information for optimizing their behavioral performance.We used logistic regression to model observers' choice history biases under the different experimental conditions. The basic approach consisted of adding a linear combination of different components of trial history (which depended on the experiment), as a bias term to a logistic function model of the choice probability . We heretr = 1  on trial t, given the signed stimulus intensity ts̃  was described by the following:tr = 1 and tr = −1, and g(x) = The probability of making one of the two choices D), we separated the trials from Neutral into two subsets, conditioned on the choice from the previous trial, and fitted the psychometric function separately to the observed proportion of upward choices in both subsets. Results from three example observers are shown in Figure 1D and discussed in Results.For visualizing the effect of previous on current choice D, we sephist (th) = Σk=114ωkhkt consisted of the sum of the preceding seven responses tr−1 to tr−7 and the preceding seven stimulus categories tz−1 to tz−7, each multiplied with a weighting factor ωk. The vector ht was written as follows:ht were coded as −1 or 1, with the exception of terms coding for stimuli with zero coherence, which were set to 0. The weighting factors ωk thus modeled the influence of each of the seven preceding responses and stimulus categories on the current choice. Positive values of ωk indicated a bias to repeat the choice or stimulus category at the corresponding lag, and negative values of ωk indicated a tendency to alternate. In this and all subsequent analyses, the parameters of the logistic regression model were fit by maximizing the log-likelihood L = Σt log P using an expectation maximization algorithm .In Experiment 1, perceptual choices and motor responses were further decoupled through a mapping that varied from trial to trial. Thus, we could independently estimate the relative contribution of previous choices and motor responses to the current choice bias. We added the last seven choices Experiment 1 contained not only trial-to-trial variations in motion direction and coherence, but also in the duration of the dot motion stimulus. To assess the effect of this manipulation, we first fitted the psychometric functions separately for each of the six different motion-viewing durations  and compared the resulting weights within each observer. The viewing duration had only negligible impact on the history weights (data not shown), indicating that the history contributions were invariant across viewing durations. Consequently, we fitted the psychometric functions to the data from all trials, and analyzed the history weights, regardless of viewing duration.Experiment 1 also contained two conditions (Pre and Post) in which observers were instructed about the required mapping between choice and response either before or after the presentation of the sensory evidence. The analyses presented in Results collapsed across both conditions, but we also verified that there were no differences between these conditions when analyzing them separately (data not shown).The weights for previous correct and incorrect choices were estimated by recombining the weights for previous stimuli and choices estimated by means of dv), which is computed as a transformation of sensory input, corrupted by noise. A choice is made by comparing dv to a criterion c. Confidence is a function of the distance between dv and c. When dv is far from c, the choice is likely to be correct; the probability of the choice being correct approaches chance as dv approaches c. Specifically, iconfidence = f(|idv − c|) where f(x) = x on the probability of making a correct choice , we restricted the model to the immediately preceding trial (Lag 1), at which the bias adjustment was expected to be strongest, but we now estimated the weights separately for each of the different levels of previous motion coherence. This enabled us to control for the trial-to-trial variations of stimulus strength, thus isolating the impact of internal trial-to-trial fluctuations of confidence.Modeling the contributions of past correct (and incorrect) choices to current bias.In our analysis of the impact of choice accuracy, separate predictors coded for the choice or stimulus categories for each level of (non-zero) previous motion coherence. Because choice accuracy was undefined at 0% coherence, we estimated a single choice weight for previous trials where no decision-relevant sensory evidence was presented. Specifically, we included six regressors in the model that each coded for the previous choice at a given coherence level (zero elsewhere) and we included five regressors that each coded for the previous stimulus category at a given non-zero coherence level (zero elsewhere). To assess the impact of choice accuracy, the stimulus and choice weights were transformed into weights for correct and incorrect choices by recombining the stimulus and choice weights as described in the section z denoted z-scoring per individual and condition. This transformation was only applied to simplify the interpretation of the corresponding history terms in terms of confidence-weighting. Without this transformation, the resulting weights were qualitatively identical but sign-flipped, thus reflecting the complement to confidence, decision uncertainty (data not shown).To assess the effect of RTs, we first normalized RT to make it scale positively with confidence, because of its negative scaling with decision confidence  and five regressors for previous stimulus category multiplied by previous RTconf (1 for each non-zero coherence level), and a nuisance covariate Σk=16ω″k RTconfkt for the main effect of RTconf. The full bias term in this model was as follows:We added a modulation by the above-defined We performed two sets of simulations to ensure that the context-dependent shifts in the history weights exhibited by participants in Experiment 2 were not just passively “inherited from” the correlated stimulus sequences in the Repetitive and Alternating conditions. The rationale of these simulations was to fit the behavior of synthetic observers. These were matched to the behavior of each of our participants in all parameters, except for the history weights displayed in the biased conditions.hist (ht) set to 0; it allowed us to compute the probability of making an “up”-choice (tr = 1) for any given stimulus intensity in the absence of any influence of past events. To simulate the model's performance in the two biased experimental conditions (Alternating and Repetitive), we used the original sequences of stimuli (motion coherences times directions) seen by each observer in these two conditions, and computed the choice probability for each trial by putting the model parameters and stimulus categories in In the first set of simulations, we constructed observers, who based their decisions only on the current stimulus. For each participant, we estimated the parameters of the psychometric function described by The second set of simulations was as the first set of simulations, with the exception that the synthetic observers had the same (non-zero) history weights estimated for the real participants in the Neutral condition, but did not adjust these biases to the biased environments. Again, this enabled us to simulate choice patterns of the synthetic observers exposed to the stimulus sequences used in our actual experiment, and to use these choice patterns to estimate the simulated observers' choice and stimulus weights, as described for the first set.In both sets of simulations, we presented the same stimulus sequence 50 times, to average out the effect of binomial noise that was needed to generate choices from the logistic function. This yielded more precise estimates of the model parameters than was possible in the human observers.t tests for all statistical comparisons of regression weights reported in this paper. The rationale was that we could then also provide Bayes factors (Bf), to quantify the posterior belief in the null hypothesis given the evidence , false discovery rate correction  against zero, we first Fisher r's test  for compFinally, we used circular statistics, specifically Rayleigh's test, to assess the clustering of orientations of the lines connecting the weights from Neutral with those from either Repetitive or Alternating conditions, respectively. A Hotelling test  was usedN = 10,000 permutations.The results from all regression weights and individual adaptivity indices (correlation coefficients) in Experiment 2 were analogous when replacing the parametric tests with nonparametric permutation tests  with N =C and D, illustrates behavioral patterns generated by choice history biases in example observers from the Neutral condition of Experiment 2 . Figure 1C shows, for one observer, a “streak” of eight repeats of the same choice, followed by five repeats of the other choice. These streaks occur in the face of trial-to-trial variations of the direction of the random stimuli. Critically, such apparent biases toward one or the other choice emerge only locally in time. Choice history biases are therefore distinct from the “global” biases toward one particular choice that result from uneven probabilities of the two stimulus categories or uneven payoffs for the two options  with an intrinsic bias to repeat  or to alternate choices (right), or no bias (middle). A more comprehensive approach is to explicitly model the relative contribution of previous choices, or other experimental variables from previous trials, to current choice bias (We here report results from two experiments (referred to as Experiments 1 and 2) quantifying choice history biases during the random dot motion discrimination task that is widely used in neurophysiological studies of perceptual decision-making . The twoFigure 1 options . One wayOur analyses pursued two main objectives. First, we aimed to disentangle and compare the contribution of decisional and motor processing stages to the history biases. Second, we aimed to quantify the adjustment of choice history biases to the environment, as a function of varying levels of decision confidence, in the absence of external feedback.In laboratory tasks, perceptual choice and motor response used for reporting the choice are typically coupled, but can be decoupled with little effect on performance on the current trial . AlthougA). The effect of the previous choice on current choice was positive and stronger than the effect of the previous motor response (A). The response weights did not differ significantly from zero for any lag . Preceding stimulus categories (up/down) exhibited negative, albeit not statistically significant, weights at longer lags (B), possibly reflecting the impact of long-lasting, repulsive effects of direction-selective sensory adaptation mechanisms (Observers showed a significant tendency to repeat their previous choices (indicated by positive choice weights), but not their motor responses A. The efresponse A. The reger lags B, possibchanisms  on choicThese results indicate that the commonly observed choice repetition biases are specifically due to previous choices and not the motor responses used to the report them, which has implications for their neural bases (see Discussion). We next investigated the adjustment of choice history biases (under fixed mapping) to varying environmental statistics to gain deeper insights into their functional origin and adaptive utility.B; Materials and Methods). Importantly, observers received no external feedback about the correctness of their choices. This enabled us to study the impact of their decision confidence on the adjustment of their choice history biases to environmental statistics.In laboratory tasks used to study perceptual choice, it is common to generate random sequences of the two alternative stimulus categories. But the states of natural environments, and hence the sensory signals generated by them, often exhibit significant autocorrelations across time, so that it might be beneficial for decision-makers to adjust their choice history biases to this correlation structure . In ExpeFig. 1A). Thus, the strongest effects were expected for events from the preceding trial .The manipulation of the environmental statistics had robust effects on observers' history biases. We visualized those in two complementary ways focusing on different aspects of the data. Both our approaches were guided by the statistical structure of the Repetitive and Alternating conditions, which yielded characteristic profiles of the probability of stimulus repetitions as a function of lag: for both Repetitive and Alternating conditions, repetition probability was most strongly biased  at Lag 1, and progressively approaching 0.5 for larger lags A. Thus, B, dashed diagonal line). If observers adjusted their choice patterns to the Repetitive and Alternating environments, their history weights should have shifted in the corresponding directions. This is what we observed . The weights were close to zero in the Neutral condition ; weights shifted toward repetition in the Repetitive condition , and alternation in the Alternating condition , respectively. The vector angles of the shift from Neutral were significantly different from uniform , and the shift angles were significantly different between Repetitive and Alternating  = 60.28, p < 0.0001, Hotelling test). The adjustment of choice history bias was also evident when fitting the psychometric function conditioned on the previous choice (as in D). Both conditions were characterized by a history-dependent shift, in opposite directions  = 3.21, p = 0.0042). By contrast, previous choice had no effect on the slope of the psychometric function (difference in history-dependent change in the slope between Repetitive and Alternating: t(21) = −0.60, p = 0.5532, 10Bf = 0.2627).Our first approach, therefore, focused on the weights for Lag 1. When plotting the choice weights against stimulus weights, data points located in the upper-right triangular part indicated a tendency to repeat the previous choice or stimulus categories (up/down), whereas data points in the lower-left triangular part indicated a tendency to alternate  that corresponds to equal weights for previous stimuli and choices. Thus, the bias adjustment was largely driven by correct choices . We thus used the weight of previous correct choices  in all subsequent analyses as a single metric of the bias adjustment. The importance of previous correct choice for the bias adjustment was indicative of the role of decision confidence, an aspect that we elaborate on in the section Modulation of choice history bias adjustment by decision confidence.It is noteworthy that the direction of the shift of history weights between the different environmental statistics was largely along the positive diagonal B that coA). The correlation between both time courses for Repetitive and Alternating conditions was negative. In what follows, we refer to these time courses as “history templates”, to indicate that these characterize the statistical structure of the environment.Our second approach focused on an assessment of the full time courses of the history weights. The temporal profiles of the stimulus repetition probabilities in the two biased conditions exhibited markedly different patterns: in the Repetitive condition the temporal profile exhibited a monotonic decay toward 0.5, whereas it exhibited a damped oscillation ∼0.5 in the Alternating condition A. The coD, A). We use the term “history kernel” to refer to the individual courses of the weights for correct choices as a function of lag. We quantified their similarity with the corresponding history templates by means of temporal correlation (E). These correlations were significant in both conditions (Repetitive: t(21) = 2.57, p = 0.0179; Alternating: t(21) = 4.83, p < 0.0001). Thus, participants adjusted their history biases to the statistical structure of their environments with a time course matched to the full environmental statistics. In what follows, we refer to this similarity metric as adaptivity index.Indeed, participants' history weights exhibited profiles that were similar to those of the history templates .One concern might be that even an observer who only discriminates the current sensory evidence, without any active accumulation of past experimental events, might exhibit similar shifts in the history weights between the Alternating and Repetitive conditions, by virtue of the stimulus statistics propagating into the history weights without any active adjustment of the observer. To address this concern, we simulated the performance of two types of synthetic observers, which were constructed individually for each of our participants. These had the same perceptual sensitivity as each participant, but without any adjustment of stimulus and choice weights to the different environmental conditions . The first set of synthetic observers had stimulus and choice weights of zero. The second set of synthetic observers had the same history biases  as our participants in the Neutral condition, but did not adjust these to the changing environmental statistics. The choice and stimulus weights obtained for both these models were not significantly different from zero . In other words, the systematic deviations of the history weights between Repetitive and Alternating conditions evident in the real observers were not just passively inherited from the correlations evident in the stimulus sequences, but rather due to an active adjustment of their biases.E). We correlated the individual adaptivity indices with the proportion of correct choices to assess their predictive value for overall task performance (A). The more strongly observers adjusted, the more successful they were in both, the Repetitive  and Alternating (middle) condition. We found no evidence for such an effect in the Neutral condition . As expected, perceptual sensitivity  was also strongly predictive of individual performance in all three conditions . In both biased environments the adaptivity index was similarly predictive of performance as perceptual sensitivity , while sensitivity was a better predictor in the Neutral environment . In other words, the adjustment to the environmental statistic can be about as important for maximizing reward rate as sensitivity to the momentary sensory evidence.Although the bias adjustment was highly consistent across participants, individuals differed in the extent to which they shifted their history biases between conditions . The scaling of RT with motion coherence exhibited the same characteristic signature as uncertainty  as reported in previous studies . Linear regression revealed an opposite-signed relationship between motion coherence and RT, separately for correct  and error trials .We used two experimental variables consistent with this definition of confidence: accuracy and RT. Correct choices are overall associated with higher confidence for all non-zero evidence strengths . There was a significant effect of previous correct choice at all of the previous coherence levels, whereas there was no such effect for previous incorrect choices at any of the previous coherence levels .As predicted, the leverage of the preceding choice on bias adjustment  was larger when the previous choice was correct than incorrect, even when controlling for the level of previous motion coherence B,C. TherC; Repetitive: t(21) = 2.58, p = 0.0174; Alternating: t(21) = −4.42, p = 0.0002). Again there was no such effect for previous errors  = −0.13, p = 0.8985, 10Bf = 0.22; Alternating: t(21) = 0.35, p = 0.7309, 10Bf = 0.24). The weights were significantly larger for correct than incorrect previous choices in the Repetitive (t(21) = 3.06, p = 0.0060) and the other way around in the Alternating condition (t(21) = −5.19, p < 0.0001; Fig. 6C). Please note that although the weights were averaged across previous coherence levels for visualization in Figure 6C, they were first estimated separately for each previous coherence to factor out effects of trial-to-trial fluctuations in sensory evidence strength . These results were qualitatively identical after random subsampling of the correct trials, so as to match the smaller number of incorrect trials for each previous coherence level (data not shown), ruling out the concern that the stronger bias adjustment after correct choices may have been due to the larger number of correct than error trials. In sum, these results were consistent with the idea that the weight of choices in the across-trial accumulation process depended on internal  fluctuations in decision confidence.When pooled across previous coherence levels, the weights for previous correct choices deviated significantly from zero in both conditions . Again, we split trials by their motion coherence to assess the modulatory effect of RTconf on the impact of correct choices , over and above variations in evidence strength.To assess the modulatory effect of the second confidence proxy, RT, on the bias adjustment, we built on an extension of the statistical model by multiplicative interaction terms. This quantified the degree to which the impact of previous correct choices on current bias was modulated by previous RT . In these model fits, we transformed RT to scale positively with decision confidence, a variable we refer to as RTconf were associated with a stronger impact of the previous (correct) choice on the current bias , an effect that was robust even when we evaluated each previous coherence level separately (E). When pooled across previous coherence levels, the interaction weight was significantly larger than zero in the Repetitive condition  = 3.84, p = 0.0009), indicating a confidence-dependent enhancement of the tendency to repeat correct choices in that condition. Conversely, the interaction weight was significantly smaller than zero in the Alternating condition  = −3.71, p = 0.0013), indicating a confidence-dependent enhancement of the tendency to alternate correct choices. Thus, even within the correct choices, evidence-independent fluctuations in the associated confidence (indexed by RTconf) boosted their impact on future choice bias.Larger values of ent bias E,F, an eparately E. When pTogether, two independent proxies of decision confidence, choice accuracy and reaction time, both supported the conclusion that decision confidence boosted the adjustment of choice history biases to the structure of the environment.Choice history biases are a pervasive phenomenon in perceptual decision-making . Here, wAn important novel contribution of our study is the discovery of a confidence-weighted adjustment of choice history biases to changing environments. We propose that this was due to a context-dependent accumulation of decision variables across trials. A similar accumulation process has been proposed to explain sequential effects under strong and unambiguous evidence . ConsequSuch a context-dependent across-trial accumulation of decision variables has been postulated by a recent normative account , and shoOne recent study provided similar evidence for an effective adjustment of human observers to changing environmental statistics . Our curThe interpretation provided above as well as the normative framework by A (B). A possible explanation is that choice accuracy was less closely coupled to the decision variable than postulated by the confidence model from Figure 6A. For example, some errors will be caused by noise downstream from the decision variable and consequently not affect the bias adjustment. Thus, motor errors will counteract the dependence of history bias adjustment on correctness. Because misperception of the true stimulus category becomes less likely with stronger evidence, the relative contribution of motor errors to incorrect choices will increases as a function of evidence strength. This might explain why the effect of previous correctness on history bias adjustment did not increase as a function of previous evidence strength in our data. Similar considerations hold for our second confidence proxy, reaction time.In our account the strength of history bias adjustment depends on the magnitude of the decision variable, which is also the sole source of variations in confidence in the confidence model from Figure 6A . AccordiA B. A possOur analyses revealed that the contributions of previous stimuli, perceptual choices, and motor responses were dissociable in terms of their strength, sign, and time course. Importantly, the dominant and consistent bias in standard conditions with random stimulus sequences was to repeat preceding choices, rather than motor responses. Two recent studies similarly decoupled perceptual choice and motor response . One of We conclude that human observers accumulate action-independent, graded decision variables across trials toward biases for upcoming choices in a context-dependent manner. This process enables observers to adjust their choice behavior to environmental statistics in the absence of unambiguous information about choice outcome. Our findings are in line with normative theory and constrain the candidate neural sources of choice history biases.


The present study aim to design a liposomal electrochemical sensor using 1, 2-dioleoyl-3-trimethylammoniumpropane (DOTAP) and dioleoylphosphatidylethanolamine(DOPE), chimeric probes and p19, it has been considered as a caliper molecule as well. Also the competitor structural hybrid (RNA) was used to detect three types of miRs in one screen printed electrode modified by gold nanoparticle (SCPE/GNP). In this purpose, the sensor signal stabilized when the cationic DOTAP-DOPE with hybrids of the chimeric probes  sandwiched in order to detect 221–124a miRs. Given the lack of accessibility to RNA-miRs segments of chimeric probes, p19 inhibited the electrochemical reaction and shifted signal to off. After that p19 connected with the free hybrid of T-linear/21miR (just RNA) as competing for structure and the signal was shifted to ON, again. In this study, the electrochemical measurements were performed between the potentials at −0.4 V and +0.4 V with 1 mM [Fe(CN)6]-3-/4 which DOTAP-DOPE acted as an enhancer layer in the electrostatically reaction. This sensor determines as low as 0.4 fM of miRNA with high selectivity and specificity for sequential analysis of 124a-221-21 miRs in just 2 h. The initiation and progression of human cancers relies on alterations in miRs expression2. Circulating miRNAs seems as package in exosomes that derived from multivesicular bodies, or to be exported in the presence of RNA-binding proteins  or shed into micro vesicles within membrane blabbing3. According to recent literature on this field, circulating miRNAs have diagnostic and prognostic significance in cancer and many other diseases4. There are two other important considerations regarding to dynamic range and multiplexing capability for detection methods6. In this regard, an effective method with easy and rapid experimental protocols as well as a high specificity and sensitivity with a large measurement dynamic range from subfemtomolar to nanomolar should use to miRNA profiling and detection with a minimum sample quantity7. Traditional assays are cloning, Northern blotting, microarray or RT-PCR as well as next-generation sequencing8. The properties of such methods including low throughput; low sensitivity or they involve laborious sample handling and detection protocol11Micro RNAs as a class of endogenous small (18–25 nucleotides) noncoding RNAs play important roles in various cellular processes and intercellular space13. So far, extensive studies have been carried out on the detection of electrochemical micro RNAs15. The recent work on electrochemical sensor for miRs was about ultrasensitive electrochemical detection of Dicer1 3′UTR for the fast analysis of alternative cleavage and polyadenylation in role in miRNA pathways by Zhao16. Detection of micro RNAs with equal length has been considered as an important challenge for electrochemical methods17. Regarding to design innovative strategies for detection of the multiple miRs, this progress will be boosted for rapidly expanding in the field of miRNA diagnostics. The double-tagged p19 fusion can be used as a general miRNA detection method because of the sequence-independent binding. The best RNA probes for them are 19–20 nucleotides long and have a 5′ phosphate and form one blunt end when hybridized to miRNAs18.The last study about p19, the combined three-mode sensor (HPD-SENS) was done to detect the miR-122 and miR-21 in 4 mM K3[Fe(CN)6] and 10 mM [Ru(NH3)6]Cl319. Different combinations of liposomes as dioleoylphosphatidylethanolamine (DOPE) and 1,2-dioleoyl-3-trimethylammoniumpropane (DOTAP) have been used in sensor applications. The various combination arranged separately on the surface which can take two different of probes on one electrode and a suitable mediator for electrochemical reactions21. In the recent studies, properties of DOPE were reported along with other compounds. These properties were reported as DOPE, transmembrane profiles of electron density, lateral pressure, electric field and dipole potential22. According to the possible enhancement due to the combination of DOTAP/DOPE liposomes and stronger connections with RNA structure in electrochemical reactions, they can be used as a suitable intermediate layer which can take two different of probes on one electrode. So these novel spherical cationic liposomes have been used to fix two chimeric probes with different structures (stem & M-linear). Then a hybrid compound of miRs-RNA formed by connecting 124a-221miRs in the stable situation. Indeed, these hybrids cause less access of 5′ phosphate for p19 connection and reduce the exchange of electrons and convert the unstable situation of DOTAP/DOPE/hybrids/p19. In the following, T-linear/miR-21 is added as competitive structure  with the same concentration. In this time, the real performance of p19 used to separate from sandwiched hybrids on the sensor and to connect with the T-linear/21miR hybrid with the stabled system, again. Finally, the stability of the sensor in situation of DOTAP/DOPE/hybrids (segments of miRs-RNA probe of hybrids) contributes to the unstable situation of DOTAP/DOPE/hybrids/p19. Then the model to determine 124a-221-21 miRs has been shown with respect to these important roles in various cancer and diseases23.Electrochemical nanosensors used as suitable devices for POC diagnostics and multiplexed platforms because of their sensitive, specific, fast, simple, low-cost characteristics−3/−4 in PBS buffer in the potential window −0.4 V to +0.4 V at a scan rate 50mVs 1. The impedance measurement used at frequency ranged from 100 kHz to 1 Hz of [Fe(CN)6]−3/−4 in PBS pH = 7.4. The EIS spectra were analyzed with the help of equivalent circuit using ZSimpWin 3.22 (Princeton Applied Research), and the data were presented in Nyquist plots. FTIR spectra were recorded using Perkin Elmer NicoletIS 10 in the frequency ranged from 4000 to 400 cm−1. AFM images in the non-contact mode were acquired using Veeco declaimer. TEM images were acquired usingTecnaiG2 20 instruments of FEI Company, Hillsboro, USA. Particle sizes and zeta potentials were obtained from Horiba nanoparticle size analyzer, Malvern nano SZ-100 which uses a green laser light at wavelength 532 nm. Analytical grade potassium ferrocyanide, potassium ferricyanide, sulfuric acid, sodium chloride and potassium chloride were purchased from Chemical Arax, Iran. N-[1- propyl]-N,N,N-tri methyl ammonium methylsulfate (DOTAP) and 1, 2-dio-leoyl-sn-glycero-3-phosphoethanolamine (DOPE) were procured from Sigma-Aldrich, USA. Deionized water (DI) was used for preparing all experimental solutions. Hydrogen Tetrachloro Aurate (III) were purchased from Alfa Aesar, Thiolated DNA short- RNA chain 21-mer synthetic oligonucleotides were synthesized by MW GE biotech, Ebersberg, Germany, without any purification. The following sequences were used for RNA sensing experiments.In this study all electrochemical measurements, including electrochemical impedance spectroscopy (EIS) and differential pulse voltammetry (DPV), were used by SP-300 Instruments (SP-300) Texas, USA. SPCEs functionalized with gold nanoparticles on the ceramic substrate (L 34 mm × W 10 mm × H 0.5 mm) were purchased from DropSens Inc . The disposable electrode consisted of a GNP-carbon working electrode; a carbon counter electrode and a silver reference electrode. DPV measurements were performed in presence of 1 mM [Fe(CN)6]Stem probe: 5p’-GGCATCACGCCAT2′p(AAAGAGACCGGUUCACUGUGA)ATGGCGTGATGCC - HS-3′(124-a), M-linear probe: 5p’-GGCATC 2′p (AAAUCUACAUUGUAUGCCAGGU)GGCAT- HS- 3′ (221), T-linear probe: 5p’-ACAACAUCAGUCUGAUAAGCUA-HS-3′ (21), mir 124a: 5′-UCACAGUGAAUCCGGUCUCUUU-3 (RNA), mir 21: 5′- UAG CUUAUCAGACUGAUGUUGA −3′(RNA), mir 221 5′-ACCUGGCAUACAAUGUAGAUU −3′(RNA), mir 124-a: 5′-ACTCTGAGTTACCGGACACAAA-3′(DNA), mir 221: 5′-TCCAGGCTATCTTAGATGTAA-3′ (DNA), mir 124a: 5′- UGAGAGUGAAUGGGGUGUGUUU −3, (mismatch RNA), p19 was purchased from New England Bio Labs Inc. and used without further purification. p19 siRNA Binding Protein (10 units/ml) was stored at −20 °C.24. Also to determine the effect of electrochemical changes on DOPE-DOTAP liposomes, each of the liposomes (DOPE and DOTAP), were used on the separate electrodes as control cases. In all stages of the construction of the liposomes were carried out in two stages26: At first, DOTAP and DOPE liposome were prepared by dissolving in chloroform at the ratio1:3, dried, rehydrated with buffer (pH = 7.4) and sonicated for 15 min and kept at 4 °C until use. On the other, (DOTAP-DOPE) liposomes at the ratio 2:3 were separately prepared by dissolving in chloroform at the ratio1:3, dried, rehydrated with buffer (pH = 7.4) and sonicated for 15 min and kept at 4 °C until used. The gold nanoparticles were made by the citrate reduction used to examine the effects of gold nanoparticles on the different electrochemical reactions of DOTAP-DOPE liposomes27. Thus prepared DOTAP, DOPE, DOPE-DOTAP liposomes and AuNP solutions were mixed at 1:1 ratio and sonicated for 15 min to form liposome–AuNP composites in solution. 1.2 ml of this mixture was dropped on the surface and stored at 4 °C for 1 h. Then, the electrochemical tests have been done on the separate electrodes.In this study, the entire processes were done on the (DOTAP-DOPE) liposomal composition as the sandwich layer in GNP-SCPEThe thiolated (Stem-T-M-linear) probes  were dropped onto the DOPE–DOTAP-AuNP on the individual electrodes and left for at 4 °C. The surfaces were washed with the blank buffer for removing the non-reacted probes. Micro-RNA sensing experiments were hybridized 1 mM of 2 ml target RNA  for 4 h on the different surfaces  under similar experimental conditions. To determine the behavior of p19 in the presence of different structural hybrids, ten ml of 1:20 (v/v) diluted p19 protein solutions were dropped on the each electrode and were mixed for 10 s afterward. The interactions between the p19 protein with probes and targets of 124a, 221, 21 miRs were preceded at 37 °C for 1 h under dark conditions. To determine the behavior of p19 in the presence of free RNA-miR hybrid (T-probe/miR-21 hybrids in this study) was dropped on different electrodes. At first, 6 mg/mL T-linear probe and 3 mg/mL miR21 were mixed inside a vial containing TEB. The hybridization mixture was then put into the thermal shaker which was set to 65 °C and 250 rpm mixing speed and kept there for 1 h. Then, 1 mM of 2 ml hybrid of miR-21, was added on the surface of the electrode and incubated at 37 °C for 2 h in a dark without shaking. Finally, the electrochemical measurements were performed between the potentials at +0. 4 V and −0.4 V in PBS.μM of the Stem-probe (for detection miR-221) with 1 μM of the DNA to assess the specificity of the sandwiched sensor, and one electrode was used as bare which incubated in the buffer for 24 h at 4 °C. Subsequently, the electrodes were incubated with 0.1 mM of 2 M mercaptoethanol in ethanol for 5 min. Similarly, two electrodes were incubated for detecting miR-124a with the 1 μM of the DNA and mismatch RNA (G/C) and one electrode was prepared as bare. Also two electrodes were incubated with 1 μM of the M-linear probe (for detection miR124a) with the 1 μM of the DNA and mismatch RNA (G/C) in the incubation buffer for 24 h at 4 °C used to determine p19 function to the double-stranded miRs in the electrochemical reactions. Then 10 ml of 1:20 (v/v) diluted p19 protein solutions were dropped on the each electrode and were mixed for 10 s and kept at 37 °C for 1 h in a dark. Finally, the EIS was performed in the PBS solution. For sensitivity test of miRs; prior to titration experiments, aliquots containing different concentrations of the miR-124a (10 fM to 100 pM) and miR-221(500 aM to 1pM) and miR-21 from 1 nM to 100 fM in 30 μL of the incubation buffer that they were incubated with their probes on the GNPs-SPCE at 37 °C for 1 h in a dark humidity chamber. After washing with deionized nuclease-free water, 10 μgmL−1of p19 proteins (30 μL) was added to the electrodes and incubated at 37 °C for 1 h in a dark humidity chamber. DPV was performed at each concentration. To investigate the separation behavior of p19 from sandwiched hybrids on the sensors and binding to the free hybrids of different structure, the same concentration (6 mg/mL) of each hybrid is used.One electrode was incubated with 1 According to the results shown of electrochemical changes of the p19 to different structure of hybrids  in the separate electrodes, the overall strategy sensors were designed to detect three miRs in one electrode, in the following manner: prepared M-linear and Stem probes solutions were mixed at 1:1 ratio and sonicated for 15 min. Then, 2 mM of 4 mix- probes were dropped on the DOPE-DOTAP liposome, left for 24 h under cold condition. The surface was washed with the blank buffer for removing the non-reacted probes and TWIX to fill the empty pores. Then 1 mM of 2 ml mir-221 RNA was hybridized for 4 h on the sensor. Sensor washed with the blank buffer, again. And ten ml of 1:20 (v/v) diluted p19 protein solutions were added and sonicated at 37 °C for 1 h. The PBASE was used for removing non-specific binding protein. Then, 1 mM of 2 ml mir-124a RNA was added for 4 h on the sensor and 10 ml of 1:20 (v/v) diluted p19 protein solutions were dropped on and washing process and PBASE solution had been done, again. Then, 1 mM of 2 ml hybrid of T-linear/miR 21 was added on sensor and incubated at 37 °C for 2 h in a dark without shaking. At each stage, DPV and EIS testing have been conducted.6]−3/−4. The [Fe (CN)6]−3/−4 redox probe exhibited a reversible behavior on the bare gold electrode with ΔE(Epa − Epc) 68 mV with an IPC/IPA peak ratio 0.6. The electrochemical behavior of DOPE due to the increased surface area showed the peak currents decreased from 9.3 to 8.2 µA and the ΔEp increased from 72.5 to 75 mV. But in another electrode, attachment of DOPE–AuNP hexagonal particle by drop casting on the GNP-SPCE caused, the unchanged ΔEp and the peak current decreased from 9.3 to 8.9 µA. In comparison, Fig. p decreased from 85 to 78 and peak current decreased from 10.8 to 9.1 µA by comparison with DOTAP, alone. In a previous study, an effect of organic substrate and amount of charges was fixed in the electrochemical behavior15. In this study, Branched–charged of DOTAP structure occupies more surfaces, and mixing gold nanoparticles and more change in the electrochemical peak compare to the neutral charge of DOPE, too. The results of the pervious study showed, DOPE along with other lipids was only marginally altered in dramatic effects for the lateral pressure, electric field, and dipole potential profiles16. In our result, the combination of both DOPE-DOTAP lipids leads to more placements as redox sties for attachment of gold nanoparticle or probe, on the (DOPE-DOTAP) liposome. So, DOPE-DOTAP sandwiched with AuNP in GNP-SPCE, in addition to having the positive charge, causing a dramatic shift change from negative territory to zero. Due to the same charge of Cationic liposomes  as compared to neutral lipid (DOPE), the inverted hexagonal structure can play an important role in the shifted of peak potential and electrochemical exchanges and increased redox reactions along with other lipids Actually, the combination of both DOPE-DOTAP lipids leads to more placements for gold nanoparticle on the (DOPE-DOTAP) liposome. Also increased surfaces and changed the more negative shift are more suitable in electrochemical reactive. ΔEp increased from 64 to 91 and peak current decreased from 13.3 to 12.1 µA. To identify the modified electrode surface properties, the EIS was used. The impedance data are modeled using the equivalent circuit [Rs(QCPE RCT)W]28.Upon formation of DOPE–DOTAP-AuNP on the GNP-SPCE modified surface, the peak current decreased 35% and only 20% by comparison with DOPE-AuNP, DOTAP-AuNP, respectively. This can suggest the presence of more pinholes in the DOPE–DOTAP-AuNP layer than others.Figure Ipa was decreased from 9.80 to 6.12 µA for stem-linear, from 9.54 to 8.2 for T-linear, from 9.1 to 7.3 for M-probes) in Fig. 6]−3/−4 compared to previous studies15. Hybridization of 221–124 a-21 miRs with their probes increased the peak currents from 6.12 to 10.9, 8.2 to 9.7, and 7.3 to 8.6.These results were obtained by the electrostatic repulsion between the double strand nucleic acid probes and [Fe(CN)6]−3/−4, in addition to the additive effect of DOTAP-DOPE liposome, Fig. ΔEp to 580 mV and RCT to 1.35 × 104 Ω cm−2 Fig. 13. In the current study, unavailability of stem and M-linear probes with 221 and 124a miRs cause an inappropriate connection of p19 which lead to the inhibitory caliper in the electrostatic repulsion between the nucleic acid probes and [Fe(CN)6]−3/−4 in the DOTAP/DOPE/hybrids. The connection of p19 with a duplex of Stem/M probes and miRs is likely to cover more pores of liposomes and decrease in electrostatic repulsion. Since probe of T-linear is just RNA, it can form stronger compound for binding with p19 and the current decrease in the [Fe(CN)6]−3/−4 solution. The hybrid of T-linear probe and 21-mir was added to show the electrochemical changes of p19 and also the availability of probe-miRs duplex by comparison with other different structures of sandwiched hybrids on the sensor. The progress of the modified sensors (Stem and M-linear) was shown in Fig. The result of immobilization of stem and M-linear/T-linear probes on the DOTAP/DOPE–AuNP showed to decreased the peak currents  and it cause to decrease the current peak in the electrochemical reactions and shift the signal ON, as the mode of stable of DOTAP-DOPE/probes/miRs sensor. In the Table The AFM image of the p19 attachment on the DOTAP/AuNP + Stem probe + 221 miR showed that p19 did not connect properly with the Stem probe + 221 miR and left a large open space on the electrode with the rough surfaceFig. . The intμAcm−2), respectively. Hybridization with mismatch RNA of 221 and 124a miRs caused a 22.9%, 18.5% increase in the j value . These calculated percentages compared with the buffer treatment alone  and 10 pM of the fully matched miR-221, miR124a . The results showed that the non-complementary DNA causes a larger reduction in electron transfer rate than mismatch RNA. The mismatch of RNA/RNA sequences (for 124a miR) was used to show the behavioral changes of p19 function to miRs. The result shows that the attachment of p19 to mismatch of RNA cause a 12.8% increase in the j value (1075.1 μAcm−2) and not change in the j value (897.7) for 1 μM DNA sequence by comparison with 10 pM of the fully matched miR-124a, Fig. 18. So, p19 connect to the mismatch of miR124a (as RNA) with not stable interaction and different behavior by comparison with the hybrid of match miR124a, in EIS test.In Fig. 12. In Fig. R2 = 0.976) was obtained, where y is the j value in μA cm−2 and x is the logarithmic concentration of miR124a in fM.In this study, the design of different probe structures made it possible to differentiate between electrochemical behaviors between two miRs. In the case of DNA, binding to p19 not occur and not change in the electrochemical behavior. To check out, the effects of hybrids with different structure in the p19 performance, similar concentrations of them are used in the connection and disconnection stages. In the previous study, the presence of free hybrids of miR-probe in the solution with a more concentration than another hybrid caused the release of p19 and connected to free hybridsSb/m), where Sb is the standard deviation of the measurement signal for the blank and m is the slope of the analytical curve in the linear region. The result showed miR-221 in Fig. R2 = 0.986) was obtained, and the relative standard deviation (RSD) values were between 7% and 8.3%. Also an16.6% increase in current density (1660.1 μAcm−2) and also, 21.6% decreased in the j value (897.4 μAcm−2) observed in comparison with concentration of miR-124a in Fig. μl of the incubation buffer of the hybridization product of miR 21 and its T-linear probe were incubated with the sensor at 37 °C for 1 h in a dark humidity chamber , as shown in Fig. As shown in Fig. ber Fig. . As showμgm−1of p19 protein, there was a decrease in resistance (curve c).Then, detection for miR 221 was done by incubation of its sequence with stem probe on the sandwiched sensor. It was observed an increased in resistance, again (curve c). In the following, incubation with 10 μgmL−1of p19 protein, made to decrease in resistance, again (curved). Finally, incubation with the free T-linear/21 miR hybrid caused an increased in resistance (curve d). EIS was carried out in a parallel manner  based on the accessibility of p19 to the different structure of RNA-miR hybrids. In literature, different probes should be added at every stage to formation hybrids for p19 function. Because of presence and absence of hybrids in solution, the accuracy, sensitivity, and repeatability of results doubted31. So, the spherical liposome because of their structure can provide to connect different probes (Stem and M probe) in one electrode. So, it can be clearly achieved to the function of the p19 protein in the electrochemical changes by comparison with the different structure of miRNAs-RNA. Designed structures of probes can provide the different availability of phosphates in RNA-RNA sequences for p19 function (in connection and separation stages). This liposomal/p19/GNP SPCE sensor shows the high sensitivity as 5 fM miRNA with the broad dynamic range of measured concentrations (from 500 aM to 1 nM) in only 2 h. In addition, the sensor can detect miRNA selectively for miRNAs and DNA. However, in order to confirm this sensor, it is suggested future studies performed on real examples. In total, this biocompatible sensor design allows to identify three miRs. It also can be a window for a significant direction to explore the use of mild bifunctional ways for the attachment of the biomolecules on the surface of the nanostructure.The properties of the electrochemical biosensor such as unique and attractive strengths are extremely promising for improving the efficiency of diagnostic testing and therapy monitoring micro RNA RNASupplementary Information