Bacteroides thetaiotaomicron has developed a consortium of enzymes capable of overcoming steric constraints and degrading, in a sequential manner, the complex rhamnogalacturonan II (RG-II) polysaccharide. BT0996 protein acts in the initial stages of the RG-II depolymerisation, where its two catalytic modules remove the terminal monosaccharides from RG-II side chains A and B. BT0996 is modular and has three putative carbohydrate-binding modules (CBMs) for which the roles in the RG-II degradation are unknown. Here, we present the characterisation of the module at the C-terminal domain, which we designated BT0996-C. The high-resolution structure obtained by X-ray crystallography reveals that the protein displays a typical β-sandwich fold with structural similarity to CBMs assigned to families 6 and 35. The distinctive features are: 1) the presence of several charged residues at the BT0996-C surface creating a large, broad positive lysine-rich patch that encompasses the putative binding site; and 2) the absence of the highly conserved binding-site signatures observed in CBMs from families 6 and 35, such as region A tryptophan and region C asparagine. These findings hint at a binding mode of BT0996-C not yet observed in its homologues. In line with this, carbohydrate microarrays and microscale thermophoresis show the ability of BT0996-C to bind α1-4-linked polygalacturonic acid, and that electrostatic interactions are essential for the recognition of the anionic polysaccharide. The results support the hypothesis that BT0996-C may have evolved to potentiate the action of BT0996 catalytic modules on the complex structure of RG-II by binding to the polygalacturonic acid backbone sequence.The  The human gastrointestinal tract houses a densely populated microbial community from almost all kingdoms of life . This coBacteroides thetaiotaomicron, from the Bacteroidetes phylum  (One of the most common carbohydrate-active bacteria found in the human gut is the Gram-negative s phylum . In B. ti (PULs) , which di (PULs) . CAZymesi (PULs) .d-galacturonic acid  residues and four structurally well-defined oligosaccharide side chains (A-D) , which is present at the cell wall throughout the plant kingdom, is the most structurally complex dietary carbohydrate known, containing a wide diversity of monosaccharides and glycosidic linkages  O'Neill. RG-II ins (A-D)  (Pellerins (A-D) . RG-II ins (A-D) .B. thetaiotaomicron, Ndeh and colleagues demonstrated that three different PULs are upregulated using RG-II as substrate (“RG-II degradome”)  . These e enzymes .exo-cleavage stage of RG-II deconstruction (d-glucuronidase (GH2) and β-l-arabinofuranosidase (GH137) target RG-II chains A and B, respectively, in a coordinated manner by cleaving monosaccharide decorations from the terminal regions of each chain. The role of BT0996 is in the early stages of the degradation process, being the first enzyme to cleave the RG-II side-chain B and the second on the RG-II side-chain A. The BT0996 GH137 module does not need an upstream enzyme for removing the RG-II side-chain B terminal arabinose but BT0996 GH2 needs the early removal of l-galactose from side-chain A by BT1010 before cleaving of the glucuronic residue from this same side-chain  and leads to the disassembly of the RG-II dimer. After this event, steric constraints are released, and other enzymes can continue with the RG-II degradation (In one of those PULs (PUL 92), a modular enzyme (BT0996) with bi-functional activity was identified as being involved in the initial truction . BT0996 truction A. The BTde-chain . The remradation .Fig. 1ExAlthough abundant information concerning the action of the two catalytic modules of BT0996 exists, not much is known about the putative CBM modules and their roles in the RG-II degradation. These non-catalytic domains are frequently found attached to enzymes and operate as substrate-binding modules. CBMs are reported to mediate the specific targeting and recognition of the carbohydrate substrate, enhancing enzyme proximity and substrate degradation efficiency . Here, wN-terminal His-tag and further re-cloned with a C-terminal His-tag   backbone chain  , which she_2811) C.The quantitative analysis of the interaction of BT0996-C with homogalacturonan polysaccharides and oligosaccharides was initially investigated using isothermal titration calorimetry (ITC). The attempt was unsuccessful due to the low heat release (data not shown). This suggests that there is a significant entropic contribution, enough for cancelling the enthalpic contribution and the heats not being observable by ITC. To circumvent this problem, we used microscale thermophoresis (MST) which, contrary to ITC, does not rely on heat measurements for quantifying biomolecular interactions. Here, we labelled BT0996-C with a fluorescent dye and used the fluorescence changes observed as a direct result of the non-fluorescent ligand increasing concentrations to determine the dissociation constants . The comTo confirm the role of ionic interactions in mediating the interaction of BT0996-C with a backbone sequence of α1,4-linked GalA, we analysed the binding of BT0996-C to pectin polysaccharides using two buffers with different ionic strength (HEPES pH 7.5 and Tris-HCl pH 8.5) and with increasing concentrations of salt concentrations . BT0996-C showed binding to PGA samples at low ionic strength, while an abrogation of interaction was observed at higher salt content . Tris-HCSome carbohydrate-binding proteins specifically recognise complex charged carbohydrates through electrostatic interactions . This seN-terminal His-tag was determined at 1.65 Å resolution by molecular replacement using, as phasing model, the preliminary 2.3 Å resolution structure of the C-terminal His-tag construct, solved by Se-SAD , representing almost 20 % of the protein composition, resulting in a theoretical isoelectric point (pI) of 9.43. This feature confers a prominent broad positive patch to the electrostatic surface of the BT0996-C protein B, which β-sheets 3 and 4, near the loop region (β3-L1loop-β4 region (Lys33-Thr44) was highly disordered in the BT0996-C Se-Met derivative structure, where electron density from residues 11 to 39 was missing due to disorder (data not shown). This stretch of disordered residues included the calcium coordination region. The presence of the MPD molecule stabilised this region and consequently the calcium ion coordination region.To target the putative binding site of BT0996-C, the protein was incubated with different monosaccharides present in the RG-II structure  and co-cp region B. This βThe observation of an MPD molecule in this region suggests a putative binding site, as the binding sites of BT0996-C homologues are also located in the extended loops that connect the two β-sheets. A PDBeFold search for structurally similar proteins resulted in several CBMs belonging to family 35 with binding specificity for uronic acids, but also CBMs from family 6 and one from family 36  Table S, Fig. 3.A close inspection of common carbohydrate-interacting aromatic residues like tryptophan and tyrosine present on CBMs and other carbohydrate-binding proteins and known to mediate the recognition with sugar residues through π-CH stacking interactions, showed that these are absent from BT0996-C’s putative binding site. Instead, His36 and Phe43 were found, which are more electron-poor aromatic amino acids and then less prone to make CH–π interactions with sugar residues . Notably1 and D2  is also found in region D2 of BT0996-C. Finally, Region E also displays a high degree of variation and contributes to ligand specificity among CBM35 and CBM6 family members. In CBM35, an Asparagine is frequently found in this region, near a basic path . Both features are absent in the BT0996-C structure. Instead, a Lys46 can be found in region E near Met78.The diverse specificities observed for CBM members from families 35 and 6 seem related to the structural diversity in the surface shape of their binding sites . For CBM1 and D2 . BT0996-BT0996-C has structural similarity to CBM modules from families 35 and 6, characterised for having a variety of specificities that may not entirely match to their adjacent catalytic modules – a direct consequence of the variety of their binding-sites topologies . DespiteBT0996-C gene was amplified from Bacteroides thetaiotaomicron genome and cloned into the pHTP1-A53 vector by NZYTech company established protocols  and antibiotic resistance to kanamycin. A second construct (BT0996-C-His) was designed to improve the probability of obtaining protein crystals. To generate the second construct, the recombinant DNA from the HTP construct was re-cloned into a NcoI- and XhoI-restricted pET28 vector with a C-terminal His-tag. The functional and structural studies of CBM BT0996-C were performed using these two protein constructs in different steps. The oligonucleotides used for cloning and re-cloning of BT0996-C are listed in The rotocols . The HTPE. coli strain. Cell culture was incubated in Luria-Bertani (LB) medium with 50 µg/mL kanamycin at 37 °C, with shaking. The induction was carried out with 0.2 mM isopropyl-β-d-thiogalactopyranoside (IPTG) when cells were at mid-exponential growth phase (OD600nm = 0.6), and cell cultures were incubated at 37 °C, for 3 h. Then, cells were harvested by centrifugation at 6000×g for 15 min (4 °C). For selenomethionine-labelled BT0996-C-His production, SelenoMet™ Medium from Molecular Dimensions Limited was used, following the instructions provided by the supplier. BT0996-C-His construct was transformed in methionine auxotroph E. coli B834 (DE3) strain. Expression of BT0966-C-His was induced by the addition of 1 mM IPTG at OD600nm = 0.6, and cells were incubated at 37 °C for 5 h. Cells were collected by centrifugation.His-BT0996-C was expressed in Tuner (DE3) 2+, coupled to the chromatograph ÄKTA START . The cells pellet was resuspended in their respective Start Buffer (2 and Lysozyme (300 µg/mL). Cells were disrupted by sonication  and the crude extract centrifuged at 13,000×g for 30 min . The supernatant was loaded into the column, and the first wash with 50 mM imidazole was applied. Protein was eluted using an imidazole gradient from 50 to 500 mM. All fractions were analysed by SDS-PAGE and pooled together. Proteins were buffer-exchanged to an appropriate storage buffer  using a HisTrap™ column (5 mL) with Nit Buffer  containie buffer  with no 2O  and 5 µL of milli-Q-H2O/Buffer 4× was added and mixed. The plate was sealed and centrifuged . TSA was performed in a StepOnePlus Real-Time PCR system (Applied Biosystems) with ROX  filters. The temperature was scanned from 25 to 95 °C, at 1 °C/min. Data was exported, and each melting curve and respective melting temperatures (Tm) were analysed.To improve protein stability and sample homogeneity, a storage buffer optimisation was performed using Thermal Shift Assay . For thidl-Glu, Ala, Gly, Lys, Ser), 0.1 M Buffer system 3  and 37.5 % Precipitant Mix 4 . Both protein crystals were harvested after 2 months and flash-frozen in liquid nitrogen using Paratone-N oil as cryoprotectant.Crystallisation experiments were conducted using an automated crystallisation nanodrop robot  on 96-well crystallisation plates, where 0.67 µL of protein was mixed with 0.33 µL of reservoir solution. Commercial crystallisation screens were used: JCSG-plus, Structure 1 and 2, and Morpheus at two different temperatures (4 °C and 20 °C). For selenomethionine BT0996-C-His, crystals grew in a drop with 16.6 mg/mL of protein in Sodium Citrate buffer against a reservoir containing 50 µL of 40 % (w/v) polyethylene glycol 300, 0.1 M sodium cacodylate pH 6.5 and 0.2 M calcium acetate, at 20 °C. To obtain His-BT0996-C structure in complex with a monosaccharide present in RG-II, co-crystallisation trials were tried with a mix of monosaccharides (MonoS) . For thiP4122 with cell constants a = 49.14 Å, b = 49.14 Å, and c = 282.89 Å. Matthews Coefficient calculations suggested the presence of 2 copies of BT0996-C-His in the asymmetric unit, with VM = 2.84 Å3Da−1 and an approximate solvent content of 57 %. Se-phasing was successfully achieved using AutoSol  using phenix.refine  data set was collected, to a maximum resolution of 2.43 Å on beamline ID30B at the European Synchrotron Radiation Facility , using 0.97937 Å wavelength radiation. Experimental values of the anomalous-scattering factors, f′ = −7.75e and f″ = 5.76e, were derived from the X-ray fluorescence scan using Chooch . The BT0 AutoSol , impleme AutoSol . The besx.refine .P212121 space group with cell constants a = 34.98 Å, b = 45.94 Å, and c = 85.82 Å and processed using autoPROC software package  to a maximum resolution of 1.65 Å and using radiation of 0.976 Å wavelength. The diffraction data were indexed in  package  from thePhaserMR , using aplatform , using px.refine , alternane , with a backbone of α-1,4 Galacturonic acid ; rhamnogalacturonan I, with a mixed-linked α-1,4-GalA and α-1,2 Rhamnose (Rha) backbone and galactan, with a β-1,4 galactose  backbone. All these pectic polysaccharides have ramifications with diverse monosaccharide composition. PGA and Galactan polysaccharide probes are from diverse sources. The Plant-related polysaccharide array covered a diversity of sequences used in previous works . PolysacCtCBM35, Cthe_2811) and four commercial monoclonal antibodies  of known specificity were used as control proteins in the microarray assays. These proteins are detailed in CtCBM35 was analysed at a final concentration of 5 µg/mL. The CBMs were pre-complexed with mouse monoclonal anti-polyhistidine  (Ab1) and biotinylated anti-mouse IgG antibodies  (Ab2) at a ratio of 1:3:3 (by weight). The CBM-antibody complexes were prepared by preincubating Ab1 with Ab2 for 15 min at 20 °C, followed by the addition of the CBM and further incubation for 15 min. The binding was detected by Alexa Fluor-647-labeled streptavidin at 1 μg/ml  diluted in the blocking solution. Binding assays were conducted at room temperature.The microarrays were analysed with His-BT0996-C, following described protocols . In paraAll microarray slides were scanned with GenePix® 4300A fluorescence scanner, and the fluorescence was quantified using GenePix® Pro Software (both from Molecular Devices). Microarray data analysis was performed using dedicated software developed by Dr. Mark Stoll from the Glycosciences Laboratory  .2, 5 mM TCEP with Tween®20 0.05 % (v/v) at a final concentration of 66 nM. The oligosaccharides' dilution series was prepared in the buffer of the labelled BT0996-C . BT0996-C was mixed with each ligand solution. The mixtures were incubated for 15 min at room temperature and then loaded into standard treated capillaries. The experiments were recorded at 22 °C (40 % Excitation Power and 40 % MST Power) using the MO.control software v1.4. The quenching of the initial fluorescence, instead of the thermophoresis, was used to calculate the binding dissociation constant of the interaction. An SDS-denaturation test was performed to confirm that the quenching resulted from the specific interaction of the galacturonic oligosaccharides with the BT0996-C protein. The replicates of independent measurements were analysed with M.O.Affinity Analysis Software v2.3.Microscale thermophoresis experiments were carried out on a Monolith NT.115 (red/blue) instrument . The purified CBM BT0996-C-His was labelled with Monolith NT™ Protein Labeling Kit RED-NHS, following the manufacturer's protocol. The experiments were performed with BT0996-C in HEPES pH 7.5, 100 mM NaCl, 5 mM CaClALC, ASP and BAP designed and supervised the work. The experiments were conducted by FT, VGC, FL, DR and BAP. FT, VGC, BAP, ALC and ASP prepared and revised the manuscript.Filipa Trovão: Investigation, Formal analysis, Visualization, Writing – original draft, Writing – review & editing. Viviana G. Correia: Investigation, Formal analysis, Writing – review & editing. Frederico M. Lourenço: Investigation. Diana O. Ribeiro: Investigation. Ana Luísa Carvalho: Conceptualization, Supervision, Writing – review & editing. Angelina S. Palma: Conceptualization, Supervision, Funding acquisition, Writing – review & editing. Benedita A. Pinheiro: Conceptualization, Supervision, Investigation, Formal analysis, Writing – original draft, Writing – review & editing.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Viral DNA and RNA polymerases are two kinds of very important enzymes that synthesize the genetic materials of the virus itself, and they have become extremely favorable targets for the development of antiviral drugs because of their relatively conserved characteristics. There are many similarities in the structure and function of different viral polymerases, so inhibitors designed for a certain viral polymerase have acted as effective universal inhibitors on other types of viruses. The present review describes the development of classical antiviral drugs targeting polymerases, summarizes a variety of viral polymerase inhibitors from the perspective of chemically synthesized drugs and natural product drugs, describes novel approaches, and proposes promising development strategies for antiviral drugs. Viruses have a relatively simple life structure which causes them to be hard to eliminate but also quick to mutate, and infect hosts again and again . There aAccording to the Baltimore Classification, viruses can be divided into seven groups based on the source of the viral mRNA: (1) Double-stranded DNA viruses (dsDNA) such as herpesviridae, cytomegalovirus, adenoviruses, and poxvirus; (2) Single-stranded DNA viruses (ssDNA) such as parvoviruses; (3) Double-stranded RNA viruses (dsRNA) such as reoviruses; (4) Positive-strand RNA viruses (+ssRNA) such as coronavirus, the Hepatitis C virus, Flavivirus, and Norovirus; (5) Negative-strand RNA viruses (−ssRNA) such as the Influenza virus, filovirus, respiratory syncytial viruses, and rhabdoviruses; (6) Single-stranded RNA retroviruses (ssRNA RT) such as human immunodeficiency virus, leukemia virus, and sarcoma virus; and (7) Double-stranded RNA retroviruses (dsRNA RT) such as hepadnaviridae and Caulimoviridae. We focus on the viruses which have mature antiviral drugs targeting DNA/RNA polymerase. Therefore, the selection criteria focus on those viruses for which there are marketed antiviral drugs that target the viral synthase. Thus, we searched the literature for records which have been reported up until August 2022; the keywords mainly included “Viral DNA/RNA polymerase”, “Antiviral drugs”, and “Antiviral natural products”. We excluded drugs that were terminated, non-progressive, and withdrawn, and selected antiviral drugs that target the DNA/RNA synthases of four common RNA viruses that have been approved for marketing by the FDA, EMA, NMPA, PMDA, etc., or had clinical trial results in CTGOV, CTR, WHO, and were reported in the literature in PubMed.The tiny DNA virus known as HBV primarily causes viral hepatitis B disease by infecting host hepatocytes . HBV repSince cccDNA is stable, as of now HBV infection can only be controlled and it cannot be cured . The priHIV, as a retrovirus in the lentivirus family, can cause acquired immunodeficiency syndrome and T-cell immunological insufficiency resulting in infection (AIDS) . HIV RT Another key target, HIV integrase, is responsible for the integration of the full-length linear HIV DNA genome into host chromatin, as well as for 3’-end processing and catalytic activity for strand transfer . The catHCV is a positive-sense, single-stranded, enveloped RNA virus of the flaviviridae family that can lead to acute hepatitis or chronic disease . HCV hasThe influenza virus is an enveloped single-stranded negative-sense RNA virus of the family orthomyxoviridae that causes seasonal influenza and is spread by droplets ,38. It cCoronaviruses are a type of single-stranded positive-sense RNA viruses with envelopes in the family coronaviridae, which are transmitted in the air as droplets . Seven tAfter the virus enters the host cell, the host cell is used to synthesize the virus’ own nucleic acid and protein . Most ofThe replication for most viral RdRp is processed within the host cells. Influenza virus RdRp consists of three subunits encoded by the virus: PB1, PB2, and PA . The nakAt present, the PA inhibitor baloxavir marboxil, jointly developed by Shionogi and Roche, is used for the treatment of influenza A and B in individuals over the age of 12 . Since tAmong the PB1 inhibitors, ribavirin and favipiravir have entered the clinical research stage due to their good antiviral activity . AlthougPimodivir, also known as VX-787, is a typical representative of the PB2 cap-binding domain inhibitors . Based o50 values were 32 µmol/L and 35 µmol/L, respectively, and they had no cytotoxicity at the concentration of 250 µmol/L. These two compounds became potential PPI inhibitors [The three subunits of RdRp are non-covalently combined into a functional complex, so blocking the interaction between the subunits can effectively inhibit the activity of RdRp . The polhibitors .The NS5B polymerase encoded by the non-structural gene NS5B is an enzyme of RdRp . Its strSofosbuvir is a uridine analog prodrug, which can specifically inhibit HCV NS5B polymerase activity and is used for antiviral therapy in patients with chronic hepatitis C. The mechanism of action involves sofosbuvir being converted into the active uridine triphosphate under the action of intracellular phosphokinase, which competes with intracellular nucleotide phosphate as a substrate for NS5B polymerase and is incorporated into newly synthesized RNA chain, terminating the elongation of the HCV RNA chain, thereby inhibiting the replication of HCV . SofosbuNNIs bind to the allosteric site of NS5B polymerase, resulting in a change in enzyme conformation, thereby inhibiting the activity of NS5B polymerase and exerting an antiviral effect ,81. CompThe HCV nonstructural protein NS5A is one of the components of the viral RNA replication complex . It has After retroviruses such as HIV-1 enter cells, they first synthesize RNA-DNA complex strands under the action of reverse transcriptase, and then the RNA strands are hydrolyzed to synthesize double-stranded DNA . Under tNRTIs are analogs of deoxynucleotides, the DNA RT substrates for the synthesis of HIV-1. In vivo, NRTIs are converted into active nucleoside triphosphate derivatives, which compete with the natural deoxynucleoside triphosphate to bind HIV-1 RT to inhibit RT activity or terminate the RNA chain ,93. CurrNNRTIs can directly combine with the p66 hydrophobic region of HIV-1 RT to change the conformation of the enzyme protein and inhibit the enzyme’s activity ,95. UnliHIV-1 integrase catalyzes the integration of the HIV-1 virus reverse transcription product cDNA into the human host genome . HIV-1 iThe structure of the polymerase complex of SARS-CoV-2 includes one NSP12, one NSP7, and two NSP8 subunits, which are required to complete the replication process of the coronavirus RNA . The corDue to the increasing cost of drug research and development, traditional drug random screening strategies and blind optimization of lead compounds consume a lot of resources and time. In recent years, some new research strategies have been developed, which are listed as follows:Ribonuclease targeting chimera (RIBOTAC) technology converts RNA-binding molecules into RNA-degrading molecules to degrade the viral genome by combining RNA-binding molecules with a small molecule and activating ribonuclease L (RNase L) . Haniff Targeting protein degradation chimera  molecules can target degradation of proteins . PROTAC RNA interference (RNAi) refers to the specific gene expression silencing mediated by double-stranded RNA . ARC-520The HBV capsid protein assembly regulator can inhibit the replication of the HBV virus by destroying the function of the capsid . The HBVStudies have found that many natural products can inhibit the activities of integrase, RT, and protease to achieve antiviral activity; these natural products include flavonoids, polyphenols, alkaloids, coumarins, terpenes, peptides, etc. Most of these antiviral natural products are flavonoids and polyphenols, followed by terpenoids (mainly diterpenes and triterpenes), and there are fewer alkaloid inhibitors . SeveralThis present review mainly focused on the recent progress and development of classical antiviral drugs targeting polymerases, supplemented with a variety of viral polymerase inhibitors from the perspective of chemically synthesized compounds and natural products, and also introduced novel approaches based on characteristic of viral polymerase. In recent years, the treatment of chronic viral diseases such as HIV and HBV has been greatly improved by the intervention of antiviral drugs. Unfortunately, a complete cure of these viral diseases has not yet been achieved, and there is still the possibility of recurrence or outbreak, and long-term medication is required. In addition, drug resistance is the biggest challenge faced in antiviral therapy ,143. Dif


T) of the viral RNA by RT-PCR significantly varied according to the sequences of the primer and probe sets with in vitro transcript (IVT) RNA or viral RNA as templates, whereas the copy number of the viral RNA by ddPCR was effectively quantified with IVT RNA, cultured viral RNA, and RNA from clinical samples. Furthermore, the clinical samples were assayed via both methods, and the sensitivity of the ddPCR was determined to be equal to or more than that of the RT-qPCR. However, the ddPCR assay is more suitable for determining the copy number of reference materials. These findings suggest that the qPCR assay with the ddPCR defined reference materials could be used as a highly sensitive and compatible diagnostic method for viral RNA detection.The World Health Organization (WHO) has declared the coronavirus disease 2019 (COVID-19) as an international health emergency. Current diagnostic tests are based on the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) method, which is the gold standard test that involves the amplification of viral RNA. However, the RT-qPCR assay has limitations in terms of sensitivity and quantification. In this study, we tested both qPCR and droplet digital PCR (ddPCR) to detect low amounts of viral RNA. The cycle threshold (C Coronaviruses have caused several notable respiratory disease outbreaks in humans, such as severe acute respiratory syndrome (SARS). The SARS coronavirus was the first fatal pathogenic human coronavirus to be identified and caused 8,096 infections and 774 deaths in 26 countries in 2003 . Prior tAccording to the World Health Organization (WHO), the WHO China Country Office was informed of cases of pneumonia of unknown etiology in Wuhan City, Hubei Province, on December 31st, 2019 . The novIn the present case of SARS-CoV-2, virus isolates or samples from infected patients have yet to be made available to the international public health community. In this study, we concluded that the optimized conditions are required to increase the precision of ddPCR to develop reference materials with matrix conditions.2O . Quantitation of the RNAs was performed spectrophotometrically at 260 nm. The measurement of the RNA concentrations was performed in duplicate, and the concentration was then converted to the molecule number [Full-length N and E genes of SARS-CoV-2 (GeneBank: MN908947) were synthesized and cloned in the pET21a plasmid. The plasmids were amplified with the T7 promoter primer (5’-TAATACGACTCACTATAGGG-3’) and T7 terminator primer (5’-GCTAGTTATTGCTCAGCGG-3’). The amplicons were spectrophotometrically quantified at 260 nm. A total of 200 ng of the PCR product was used for the in vitro transcription , which was performed at 37°C overnight in a 20 μl reaction mixture containing 2 μl of reaction buffer, 2 μl of each nucleoside triphosphate, and 2 μl of enzyme mix. The template DNAs were removed by digestion with 2 U of Turbo DNase I for 15 min at 37°C. The RNAs were precipitated by adding 6 μl of 3 M sodium acetate and 150 μl of 98% ethanol, which was followed by a subsequent incubation at -20°C for 30 min. After 15 min of centrifugation at 17,000 rpm, the supernatant was removed and 200 μl of 70% ethanol was added. After another 10-min centrifugation at 17,000 rpm, the supernatant was removed, and the pellet was dissolved in 20 μl of RNase-free He number .2 incubator unless described otherwise.The human cell lines were obtained from the relevant culture collections Vero E6 cells (ATCC CRL-1586) and MRC-5 cells (ATCC CCL-171) were obtained from the American Type Culture Collection (ATCC), and Huh-7 cells (JCRB 0403) were obtained from the Japan Cell Research Bank (JCRB). The cells were cultured at 37°C in a 5% CO2 incubator. HCoV OC43 (ATCC VR1588) was obtained from the ATCC and inoculated into the MRC-5 cells. The culture media of the MRC-5 cells were Gibco Minimum Essential Media  supplemented with 10% heat-inactivated Fetal Bovine Serum (FBS), 1% Sodium Pyruvate, 1% penicillin, and 1%non-essential amino acids. The inoculated cells were cultured with virus growth medium  at 33°C. The supernatant of the culture medium was stored at -80°C until RNA extraction. The viral RNAs of SARS-CoV-2, MERS-CoV and HCoV-OC43 were extracted using the QIAamp Viral RNA Mini Kit  according to the manufacturer’s instructions. The viral RNA of SARS-CoV was extracted from the culture medium using the MagMAX-96 viral RNA isolation kit (Thermo Fisher Scientific) according to the manufacturer's instructions.The clinical isolate SARS-CoV-2 (NCCP 43326) was obtained from the National Culture Collection for Pathogens (NCCP). The strains were introduced into the Vero E6 cells (ATCC CRL-1586) and maintained in Dulbecco’s modified Eagle medium (DMEM) supplemented with 2% (v/v) fetal bovine serum (FBS) and 1%antibiotic-antimycotic solution (Thermo Fisher Scientific). The SARS coronavirus HKU-39849  was inoculated into the Vero E6 cells. Cytopathic effects were observed two days after inoculation and the viral titer was determined via a plaque assay. The patient-derived isolate MERS-CoV strain KNIH/002_05_2015  was obtaThe clinical samples used in this study were collected from subjects according to registered protocols approved by the Institutional Review Board (IRB) of Jeonbuk National University Hospital with all patients having signed written informed consent forms (IRB registration number: CUH 2020-02-050-008). The clinical characteristics of the patients are shown in The primer-probe sets used in this study are listed in The cDNAs of the clinical and cultured  viral RNA genomes were synthesized using the LunaScript RT SuperMix Kit . The reaction mixture had a volume of 20μl and consisted of 4μl of 5X LunaScript RT Supermix, 1μl of RNA template, and 15 μl of distilled water. The reactions were carried out according to the manufacturer’s instructions. The synthesized cDNAs were serially diluted with distilled water and used as templates for qPCR and ddPCR without purification.The templates were serially diluted to a few copy numbers/μl. To remove the bias from different reverse transcription steps, the same cDNAs from the viral RNA were used as templates for both qPCR and ddPCR. RT-qPCR analysis was performed on the StepOne and StepOnePlus Real-Time PCR system (Thermo Fisher Scientific). The reaction mixture had a volume of 25μl and consisted of 12.5μl of maxima Probe/ROX qPCR master mix (2X) (Thermo Fisher Scientific), 1μl of cDNA template, 1μl of 10μM forward primer, 1μl of 10μM reverse primer, 1μl of 5 μM probe labeled with FAM, and 8.5 μl of distilled water. The ddPCR analysis was performed using a QX200 system . The reaction mixture had a volume of 20μl and consisted of 10μl of ddPCR supermix for probes (BioRad Laboratories), 1μl of cDNA template, 1 μl of 10μM forward primer, 1μl of 10μM reverse primer, 1μl of 5 μM probe labeled with FAM, and 6 μl of distilled water. All valid copy numbers were selected according to the manufacturer's instructions .i.e., the fluorescence values for Ct) were exported from the StepOne software to Microsoft Excel 2016. A series of diluted templates were used to determine the Ct value, which can establish a standard curve for evaluating the reaction efficiency. Droplet fluorescence data were initially analyzed using the QuantaSoft software (BioRad Laboratories). Raw data  were exported from the QuantaSoft software to Microsoft Excel 2016. Depending on the separation of positive and negative droplets, an objective separation value k was automatically calculated.The qPCR data were initially analyzed using the StepOne software (Thermo Fisher Scientific). Raw data  targeting the HKU-N and E-sarbeco primer-probe sets were positive with both SARS-CoV and SARS-CoV-2 genomic RNA. The results showed that both qPCR and ddPCR reactions using the N primer-probe sets are specific to the SARS-CoV-2, and the sarbecovirus targeting primer-probe sets are also specific to SARS-CoV and SARS-CoV-2.To assess the specificity and sensitivity of the five SARS-CoV-2 specific N gene targeting primer-probe sets . The qPCR and ddPCR reactions using the N gene targeting primer-probes sets were positive in the SARS-CoV-2 genomic RNA in triplicate . The rea2 values of the viral RNA and IVT RNA (N genes) standard curve from the RT-qPCR assays were calculated as 0.9973 and 0.9987, respectively, whereas the R2 values of the viral RNA and IVT RNA (E genes) standard curve from the RT-qPCR assays were calculated as 0.9956 and 0.9993, respectively  for detecting acute infections of SARS-CoV-2 is the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) method . MultiplIn this study, SARS-CoV-2 RNA concentrations were measured using the qPCR and ddPCR methods. The qPCR results showed that the Ct value of a given template was greatly dependent on the individual primer-probe sets. However, the copy numbers determined by ddPCR were relatively stable and reliable in the quantification of viral RNA samples, regardless of the primer-probe sets. A previous study reported that qPCR and ddPCR results were consistent for 95 positive samples and that there was a high correlation between the Ct values of qPCR and the copy number values of ddPCR among patient samples . AlthougThe qPCR method requires the use of a standard curve to obtain quantitative measurements of an unknown sample . HoweverThe Coronavirus Standards Working Group led by the Joint Initiative for Metrology in Biology (JIMB) is conducting international collaborative experiments to develop guidelines for the purpose of evaluating and establishing the availability of common and appropriate standards, diverse reference materials, validation tests, and reference measurement protocols that can enable reliable COVID-19 testing , 61. OurOur study demonstrated that the Ct values of samples from qPCR assays were significantly variable depending on the sequences of primer and probe sets, whereas the copy numbers of the samples from the ddPCR assays were hardly affected by the sequences of the primer and probe sets. These results indicate that ddPCR can be performed with sub-optimal primer-probe sets without the loss of sensitivity. A comparison of the standard curves of viral RNA and IVT RNA showed that the IVT RNA quantified by ddPCR could be used as a standard for the absolute quantification of the qPCR assays. The results from the clinical samples showed that the ddPCR method could be used as a sensitive and quantitative diagnostic assay. Although the qPCR produced different Ct values using different primer-probes sets, the ddPCR results obtained using different primer-probe sets were compatible with each other. However, the narrow dynamic range and high cost of ddPCR are drawbacks for its use a clinical diagnostic method. Therefore, the deployment of qPCR assays with ddPCR-based reference materials could produce highly sensitive and quantitative results that are compatible between different laboratories.http://jmb.or.kr.Supplementary data for this paper are available on-line only at


N = 270) performing a computerized version of the IGT, and adult outbred male Lister Hooded rats (N = 72) performing the rGT. Both group and individual data were explored by normative scoring approaches and subgroup formations based on individual choices were investigated. Overall results showed that most humans and rats learned to favor the advantageous choices, but to a widely different extent. Human performance was characterized by both exploration and learning as the task progressed, while rats showed relatively consistent pronounced preferences for the advantageous choices throughout the task. Nevertheless, humans and rats showed similar variability in individual choice preferences during end performance. Procedural differences impacting on the performance in both tasks and their potential to study different aspects of decision-making are discussed. This is a first attempt to increase the understanding of similarities and differences regarding decision-making processes in the IGT and rGT from an explorative perspective.Decision-making requires that individuals perceive the probabilities and risks associated with different options. Experimental human and animal laboratory testing provide complimentary insights on the psychobiological underpinnings of decision-making. The Iowa gambling task (IGT) is a widely used instrument that assesses decision-making under uncertainty and risk. In the task participants are faced with a choice conflict between cards with varying monetary reinforcer/loss contingencies. The rat gambling task (rGT) is a pre-clinical version using palatable reinforcers as wins and timeouts mimicking losses. However, interspecies studies elaborating on human and rat behavior in these tasks are lacking. This study explores decision-making strategies among young adults ( Decision-making is a process involving a choice between two or more different alternatives, which requires that individuals perceive the probabilities and risks associated with each option and estimate the consequences of each option in the short, medium, and long term . DecisioThe Iowa gambling task (IGT)  is a widDuring the first part of IGT, participants have insufficient knowledge about the risks and benefits associated with each option. The participants acquire information on the relative risks and benefits based on the reinforcer and punishment feedback obtained as the task progresses . Early rThe rat gambling task (rGT) is loosely based on the IGT and uses sucrose pellets as reinforcers and timeout periods as punishment, mimicking monetary losses in the IGT . In contThe rGT was originally developed to specifically assess gambling-like decision-making processes. It was designed to be suitable for experiments testing the effects of different manipulations, including pharmacological, on decision-making. In the rGT, rats perform repeated daily testing in order to reach stability in choice preferences . The outStudies investigating inter-individual variability in decision-making using various versions of rodent gambling tasks found subpopulations of decision-makers , suggestStudies assessing and comparing interspecies data on the IGT, and rodent analogs are scarce. Therefore, the aim of this study was to explore individual decision-making strategies in experimental gambling settings among humans and rats. Initially, the choices of the IGT and rGT were investigated using the grouping method that is similar for both tasks, where scores are calculated by subtracting disadvantageous from advantageous choices . Furthern = 1,644)] of young adults, born in 1997 and 1999. Data were collected during an experimental session at Västmanland County Hospital, Västerås, Sweden. Eligible participants, based on criteria required for the experimental session, were consecutively included until the final sample was reached  across 100 trials in both tests, and 25 days in the rGT. To investigate changes in patterns of decision-making during the tasks, choice scores were calculated for each 20-trial block across 100 trials in both tasks, and for each week (5 days) in the rGT. To standardize, block-wise scores in the IGT were multiplied by 5 to approximate the choice scores in rGT. Human and rat decision-making performance were also assessed according to their end performance. In the IGT, choice scores were obtained during the last 40 trials of the task  which is commonly termed decision-making under risk  in the ANOVA models were assessed according to Statistical analyses were performed using IBM SPSS Statistics version 26 and Microsoft Excel. Figures were created in SPSS and GraphPad Prism 9. The significance threshold was set at der risk . Correspt-test. To explore whether participants decision-making could be explained by the loss-frequency decision-making strategy, scoring was obtained by taking the number of choices from the low-loss frequency decks (deck B + D) minus the high-loss frequency decks (deck A + C). The loss-frequency-based scoring approach was only explored in the human sample.Analyses based on various personality characteristics within the human sample were performed using independent samples N = 147, 55.7%) showed a preference for the advantageous decks (C + D) across 100 trials, although a large proportion  did not.Choice scores were calculated according to the standard scoring approach assessing long term decision-making, taking the number of advantageous choices (deck C + D) minus the number of disadvantageous choices (deck A + B) across 100 trials. Using a cutoff of choice scores >0 most of the subjects , although a large proportion of the participants did not   .t-tests were performed to investigate differences in choice scores across the task  based on participants sex and self-reported symptoms on the ASRS-18, DSRS, AAS-15, and the PGSI. Results revealed no significant differences in performance related to sex or any of the self-reported symptoms. However, there was a numerical difference in mean choice scores between females and males. Individuals above the cutoff for self-rated symptoms of depression had lower mean choice scores, but the difference was not significant  showed a preference for the advantageous choices (P1 + P2) across all 25 days of the rGT.Choice scores [(P1 + P2%)–(P3 + P4%)] were calculated across all 25 days in the rGT. Using a cutoff of choice scores >0, all subjects  = 30.454, p < 0.001, ηp2 = 0.10). Post-hoc test with Bonferroni corrections revealed a significant increase in choice scores from block 1 to block 3 (p < 0.001). There was no significant difference between block 3 and 4 (p = 0.387) or blocks 4 and 5 (p = 0.382), indicating an overall stabilization of performance during the final two blocks .To explore learning during the task, choice scores were calculated [number of advantageous choices (deck C + D) minus the number of disadvantageous choices (deck A + B)] for each 20-trial block . The ranF = 31.183, p < 0.001, ηp2 = 0.106), but not for sex  = 0.900, p = 0.334, ηp2 = 0.003). Post-hoc tests with Bonferroni corrections showed no significant differences in choice scores between males and females in blocks 1, 2, 3, or 4. However males had higher choice scores in block 5 (p = 0.040).Sex differences in choice score progression was explored using a two-way repeated measures ANOVA with Huynh-Feldt corrections. Results revealed a significant main effect of block  = 1.230, p = 0.298, ηp2 = 0.005).Block-wise choice scores were also calculated according to the loss-frequency approach . A repeaF = 7.626, p < 0.001, ηp2 = 0.09). Post-hoc tests with Bonferroni corrections revealed a significant increase in scores from block 1 to 2 (p < 0.001), but there were no increases in scores between blocks 2, 3, 4, and 5.Average choice scores were calculated during the first 100 trials for each 20-trial block of the rGT. Since the rats performed different number of trials each day of testing, additional trials from day 2 were added for the rats that did not reach 100 trials during day 1. The range of possible choice scores was −100 to +100 for each block . A repeaF = 12.690, p < 0.001, ηp2 = 0.15). Post-hoc test with Bonferroni corrections revealed a significant increase in choice scores from week 1 to week 2 (p < 0.001). However choice scores were numerically higher in week 3 compared to week 5 but did not reach a significant difference (p = 0.069).Average choice scores were also calculated for each week that the rats underwent testing in the rGT . Since pF = 19.571, p < 0.001, ηp2 = 0.05) and group  = 115.044, p < 0.001, ηp2 = 0.256). Post-hoc tests with Bonferroni corrections determined a significant difference in choice scores between humans and rats for all blocks (p < 0.001) (Differences in choice score progression between humans and rats were tested using a two-way repeated measures ANOVA with Huynh-Feldt corrections. There was a significant main effect of both block (< 0.001) .t-test were also conducted to explore sex differences in each separate choice option per block. Results revealed higher mean choices of B during the last block among females compared to males (p = 0.038). No differences were found in mean choices of A, C, or D across the blocks.Independent samples N = 166, 62.9%) using a cutoff of >0. However, a noteworthy proportion of participants did not, thus failed to develop a preference for the long-term advantageous decks .Based on previous analysis ”) indicating stabilization in overall choice scores during the final two blocks, end performance was assessed by calculating choice scores across trials 61–100. Results revealed that most participants had developed a preference for the advantageous decks  based on participants’ sex and self-reported symptoms of ADHD, depression, anxiety, and problem gambling. Results revealed no significant differences in performance related to sex or any of the self-reported symptoms during this phase  using a cutoff of >0. The remaining four subjects preferred the disadvantageous choices .Calculating choice scores [(P1 + P2%)–(P3 + P4%)] across the last 5 days of the task, i.e., the last week, revealed that most individuals had developed a preference for the advantageous choices (N = 38 (14.4%), B: N = 31 (11.7%), C: N = 27 (10.2%), and D: N = 37 (14.0%). Individuals below the threshold of +1 SD in all choices were considered intermediates N = 129 (48.9%). Two individuals had a high frequency of choice in both A and B and were categorized accordingly. Subgroups were then plotted for visualization (lization . The meaN = 7 (10.0%), P2: N = 11 (15.7%), P3: N = 9 (12.9%), and P4: N = 9 (12.9%). Individuals below the threshold of +1 SD in all choices were considered intermediates N = 32 (45.7%). Two individuals had a high frequency of choice in both P1 and P3 and were categorized accordingly  are shown in ordingly . The meaN = 64 (24.2%), intermediate: N = 129 (48.9%), and poor: N = 71 (26.9%). The proportion of individuals in each subgroup of the rGT was as follows: good: N = 18 (25.7%), intermediate: N = 34 (48.6%), poor: N = 18 (25.7%). A one-way ANOVA was used to compare choice scores between groups during end performance. Results showed a significant main effect of group (F(5) = 179.846, p < 0.001, η2 = 0.733). Post-hoc tests with Bonferroni corrections showed no differences in choice scores between the subgroup of good decision-makers in the IGT and good decision-makers in the rGT (p = 0.872), as well as intermediates in the rGT (p = 1.000). Intermediates in the IGT had significantly lower choice scores than intermediates in the rGT (p < 0.001). Poor decision-makers in the IGT also had significantly lower choice scores that the poor decision-makers in the rGT (p < 0.001)  .This study explored decision-making strategies among humans in the IGT and rats in the rGT, using similar approaches to compare both group and individual behavioral data, highlighting differences and similarities in the two tasks. Both the IGT and rGT results are based on large sample sizes. Differences were evident on a group level, in terms of overall performance and changes in average choice preferences across the tasks. On average, rats showed relatively consistent pronounced preferences for the advantageous choices throughout the entire task, while human performance was characterized by both exploration and learning as the task progressed. This confirms the typical performances of humans and rats previously reported , and higMost human participants increasingly preferred the advantageous choices, consistent with the assumption that most healthy participants learned to choose the advantageous options . A distiIn contrast, all rats in the rGT showed a pronounced overall preference for the advantageous choices across all sessions, consistent with studies showing that a majority of rats learn and maintain a stable choice of P2 , others The differences in choice progression between humans in the IGT and rats in the rGT may be attributed to four procedural differences: (1) effects of rGT pre-training, (2) the number of trials administered during the two tasks, (3) the probabilistic schedule of the tasks, and (4) the win/loss frequency and magnitude. In the IGT, the present results reveal that trial-and-error learning occurred during the first 60 trials, consistent with the assumption that participants explore the different options during the first part of the task (decisions under ambiguity) and progressively develops a stable preference during the later phase of the task (decisions under risk). In the rGT, the rats undergo training in the operant chambers prior to the rGT. The first, most time-consuming part of the training only teaches them to make responses and collect pellets and gives no information about the choices and their respective pellet/punishment contingencies. However, the subsequent seven-session forced choice training requires the rats to choose all four options to make sure that all options have been explored with regard to number of pellets delivered and duration of punishing timeouts. As pointed out by Additionally, humans performed 100 trials in one session while the rats performed 25 sessions. The rGT procedure, with testing across multiple sessions, enable the rats to reach stability in their choice preferences. Hence, humans and rats likely rely on different memory systems to guide their choices. While humans must rely on working memory during one session, the rats likely use their long-term memory to determine their strategy after repeated testing. Consequently, different neural systems might be active during task performance in humans and rats. Several researchers have shown that a large proportion of healthy participants in the IGT fail to progress from the initial exploration phase and develop a stable preference after 100 trials, but that many were able to achieve a better final performance when the number of trials were increased to 200 trials . TherefoFurthermore, the IGT and rGT also differ in terms of their probabilistic schedules. In IGT, the decks are stacked in a fixed order, and the large losses associated with the disadvantageous options occur after several trials . This may prompt an initial preference for the disadvantageous choices that switches to a learned preference for the advantageous choices throughout the session. However, in the rGT the losses occur randomly. Previous research found that changing the order of the decks in the IGT, so that the large losses of the disadvantageous decks are presented on earlier trials, lead participants to favor the advantageous decks from the first block  . The effThe rGT is often presented as the rat analog of the IGT, but the win/loss frequency and magnitude associated with each option differ between the tasks. It is mainly P1 in the rGT that differs from the options available in the IGT. Choosing P1 will give rise to frequent small wins and infrequent small losses, which may reflect risk averse decision-making . It is uHowever, previous research has shown that some individuals in the IGT may apply a decision-making strategy where they seek to minimize the frequency of losses, rather than maximizing the long-term gains of the different choices. Several studies report this strategy among healthy individuals . The losGiven that the magnitude and frequency of the choices in the IGT and rGT differ, they do not entirely correspond in terms of their risk/gain potential in the short- and long-term. Hence, there may be a discrepancy in terms of the way they are perceived and processed. To our knowledge, this has not been addressed in previous research, but is relevant from a translational perspective since it begs the question of what defines individuals as good or poor decision-makers in each of the tasks. Another version of the rGT has been developed to specifically measure IGT-like decision-making during only one session, in order to track individual choices and ongoing decision-making processes, that more closely resemble the IGT paradigm . Hence, The individual choices during end-performance were also examined in both the IGT and rGT, by the formation of subgroups including the most extreme individuals in each choice. Despite differences in terms of the overall level and distribution of choices, there were also similarities in terms of subgroup variability in choice preferences. In both tests, extreme individuals were found in each of the different options and the two advantageous options did not seem to correspond with each other, i.e., individuals preferred either one of the advantageous options, but not both. The choice score comparisons of good, intermediate and poor decision-makers also revealed similar level of performance among the good decision-makers in IGT and rGT. However, there was a slightly different pattern for extreme individuals of the two disadvantageous options between the tasks. For individuals in the IGT with the highest choice frequencies of A and B, choices were somewhat evenly distributed between the other options, while extreme individuals in P3 and P4 still had an overall preference for P2. Hence, poor decision-makers in the rGT performed considerably better than poor decision-makers in the IGT. In addition, the level of performance of intermediates were also higher in the rGT than IGT due to the contrasting levels of developed preferences by the end of the tasks. These results once again highlight differences in the level of performance between the tasks, but also interesting variations in combinations of choice preferences beyond choice score performances. This type of subgroup variability, including the relationships between the different choices, is not generally displayed, or discussed in either IGT or rGT studies, so it is unclear whether this is a universal finding or if other groups would find a different relationship between the options. Furthermore, aggregating advantageous and disadvantageous choices only allows two groups of “advantageous” or “disadvantageous” individuals based on positive or negative scores and fails to identify variations in choice behavior, as well as underlying neurobiological mechanisms. In both tasks, the groups that are formed with the standard scoring approaches evidently consist of individuals with highly contrasting choice patterns. In the rGT, the overall low preference for any of the disadvantageous options results in very few individuals that are classified as disadvantageous. However, when looking at the individual choice data there are several individuals with a much higher preference for these options compared to the rest of the population. Hence, analysis of individual choice preferences in favor of the choice score approach, may reveal widely different strategies guided by various underlying decision-making processes.Some rGT studies discuss individual differences in choice behavior without aggregating advantageous and disadvantageous choices. One study found that animals with high and low motor impulsivity differed in their preference of the different choices; animals in the low motor impulsivity group chose P2 more, animals in the high motor impulsivity group chose P1 and P4 more, while choice of P3 did not differ . This reAnother factor that may contribute to why the rats are able to clearly distinguish between the advantageous and the disadvantageous choices early on concerns the modeling of “wins” and “losses” which remains a major challenge in animal models. Money is a secondary reinforcer, and its incentive value is highly subjective. However, food, and especially palatable food, is a primary reinforcer influenced by factors such as hunger and satiety, as well as rewarding properties . Cabeza This study compared a population-based sample of humans with outbred male Lister Hooded rats and complement a previous comparative study in which inbred mice and a different version of gambling task were used . The ratThe overall results confirmed the typical decision-making patterns usually reported separately in both humans and rats. Most healthy humans and rats learn to favor the advantageous choices associated with small losses and larger long-term gains, in favor of the immediate large reinforcers. However, to what extent humans and rats reach this level of performance during the tasks differ considerably. Consequently, the procedural differences between the tasks makes them suitable to study different aspects of decision-making. The IGT procedure can be used to track ongoing decision-making processes from exploration to exploitation as the task progresses, while the rGT with repeated daily sessions allows the identification of stable choice preferences in decision-making.Despite the procedural differences between the two tasks, both the IGT and rGT revealed individual variability in choice preferences during end performance, as both humans and rats formed preferences for a single option or a combination of options. Consequently, the formation of different combinations of choice preferences may reflect widely different underlying mechanisms that drive decision-making on an individual level. In order to make inferences regarding the underlying mechanisms operating during these tasks, both human clinical, and pre-clinical research would benefit from more detailed analyses on individual variations in decision-making. Moreover, future research is needed to address the correlations between the separate choices in IGT and rGT, and whether they tap into similar processes (reward maximization or loss aversion) during reinforcement-based decision-making in humans and rats. This is a first attempt to increase the understanding of similarities and differences in the IGT and rGT and their respective strengths and limitations from an explorative perspective on decision-making processes, but further studies are needed.The raw data supporting the conclusions of this article will be made available by the authors upon request.The studies involving human participants were reviewed and approved by Ethical Review Board of Uppsala. The patients/participants provided their written informed consent to participate in this study. The animal study was reviewed and approved by Uppsala Animal Ethical Committee.CH and NT: investigation, data collection, formal analysis, visualization, write the first draft of the manuscript, and review and editing. SV: investigation, data collection, supervision, conceptualization, methodology, and review and editing. MR: investigation, formal analysis, visualization, and review and editing. KN: funding acquisition, supervision, and review and editing. ER and CÅ: funding acquisition, supervision, conceptualization, methodology, and review and editing. All authors contributed to manuscript revision, read, and approved the submitted version.


Plant organellar RNA metabolism is run by a multitude of nucleus-encoded RNA-binding proteins (RBPs) that control RNA stability, processing, and degradation. In chloroplasts and mitochondria, these post-transcriptional processes are vital for the production of a small number of essential components of the photosynthetic and respiratory machinery—and consequently for organellar biogenesis and plant survival. Many organellar RBPs have been functionally assigned to individual steps in RNA maturation, often specific to selected transcripts. While the catalog of factors identified is ever-growing, our knowledge of how they achieve their functions mechanistically is far from complete. This review summarizes the current knowledge of plant organellar RNA metabolism taking an RBP-centric approach and focusing on mechanistic aspects of RBP functions and the kinetics of the processes they are involved in. Arabidopsis thaliana; Selaginella uncinata  chloroplasts, at least 139 nuclear-encoded RBPs from the PPR  polymerases triggers exonucleolytic degradation , which iKD values have been measured, recombinant P-class PPRs bind to their cognate RNA in the picomolar–nanomolar range. For example, the equilibrium KD values of PPR10 and HCF152 are 10 and 40 pM, respectively  proteins, which are known for their propensity to form protein–protein interactions. However, some TPR proteins have evolved to bind RNA, including members of the half-a-tetratricopeptide (HAT) subfamily . MoreoveThe immediate outcome of the action of helical repeat proteins, the most abundant P-class PPR proteins, is the baffling complexity of transcript isoforms, which exceeds bacterial and nuclear transcript heterogeneity. The production of shorter, often monocistronic, forms from longer precursor RNAs has long been assumed to be beneficial for protein production. Chloroplast operons contain genes with very different functions, and separating individual cistrons was speculated to contribute to adjusting individual transcript amounts and improving translation. The results of experiments with in vitro translation systems supported this idea, where the translational output of some mRNAs was strongly influenced by the processing state of the UTRs . HoweverThe half-lives of chloroplast transcripts, determined by blocking transcription and measuring RNA quantities over time, is in the range of hours or even days . Noninvarps12 mRNA halves, supporting the trans-splicing of rps12  family of RBPs is more specialized, with all but 1 member involved in RNA splicing in chloroplasts and mitochondria . The besF intron . In vitrF intron . Whetheri mutant .trans-splicing  proteins or the DUF794 protein family  of mRNAs is common in mitochondria and chloroplasts, although the functional impact of this is not yet clear  genes, which block their expression and restore pollen production and plant fertility by reducing their deleterious effects  genes (orf29 in Arabidopsis (Rfo/PPR-B protein was demonstrated to suppress the expression of the CMS transcript (orf138) by impeding its translation via ribosome blockage rather than by inducing its cleavage  genes . MoleculL) genes . HoweverL) genes . PRORP rbidopsis , but thebidopsis . The secbidopsis . The Rfocleavage .Rf gene candidates in rye and barley were found to encode members of the mTERF family , specific genomic loci constantly spawn novel family members , suggestf interacts with and induces the degradation of MCA1, an RNA stability factor for the petA mRNA encoding cytochrome f  make an excellent “chassis” for synthetic biology due to their small, well-understood genomes, and prodigious production potential . Most chpsbD mRNA  efforts that have been put into cataloging the numerous RBPs involved need to be complemented by equivalent efforts at understanding the processes mechanistically. There are several particular areas that we would encourage researchers to focus on. Our understanding of the kinetics of RNA maturation in organelles is still rudimentary. A much better understanding of the rates of the different processes (and the rate-limiting steps within them) are needed to discover which have regulatory potential. New labeling techniques that can provide high-throughput pulse-chase analysis appear to offer a way forward . With reThe following materials are available in the online version of this article.. Gene and RBP numbers of selected species, supports Fig. 1.. PPR proteins involved in plant organellar RNA splicing, supports Chapter 4.1koad049_Supplementary_DataClick here for additional data file.


Introduction: Surgical databases are useful for examining outcomes and case volume to improve care, while public interest data has the potential to track the supply and demand of medical services in specific communities. However, the relationship between public interest data and case volume from surgical databases, specifically during disruptive instances like the coronavirus pandemic, is unknown. Therefore, the purpose of this study is to determine how public interest data is related to the case volume of coronavirus and other surgical procedures performed during the coronavirus pandemic.Methods: This retrospective study included a review of appendectomy, total hip arthroplasty (THA), and total knee arthroplasty (TKA) cases from the National Surgery Quality Improvement Project and relative search volume (RSV) of hip replacement, knee replacement, appendicitis, and coronavirus from Google Trends from 2019 to 2020. T-tests were used to compare surgical caseload and RSV data before and after the COVID-19 surge in March 2020, while linear models were used to determine relationships between confirmed procedures and relative search volumes.2 = 0.931) and THA (R2 = 0.940).Results: The RSV for knee replacement  and hip replacement  had a large dip during the coronavirus pandemic, while the RSV for appendicitis had a smaller dip . Linear models showed very strong linear relationships between surgical RSV and surgical volume for TKA (RConclusions: There was a significant reduction in the number of elective surgeries, which correlated to drops in public interest during COVID-19. The strong correlations between RSV, surgical volume, and coronavirus cases indicate that public interest can be used to track and predict surgical case volume. Our findings allow for greater insight into the use of public interest data to gauge surgical demand. Large databases like the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) and the Center for Disease Control (CDC) COVID tracker are useful for examining national caseloads and patient outcomes . HoweverOther studies have used Google Trends to track public interest in surgeries and medical procedures. Mohty et al. used Google Trends to analyze public interest in elective hand surgery , while oTherefore, in this investigation, we measure the effect of the first COVID-19 peak on the public interest in emergent and elective surgical cases, identify the relationships between the public interest in surgical cases to the public interest in coronavirus and the number of coronavirus cases, identify how emergent and elective surgical case volume changes with public interest before and over the course of the COVID-19 pandemic, and evaluate the feasibility and limitations of using public interest data and national databases for tracking surgical demand and volume.Data acquisitionGoogle Trends, ACS NSQIP, and the CDC COVID Tracker were queried to measure public interest, surgical case volume, and coronavirus case volume, respectively.Google TrendsGoogle Trends was queried to determine the general interest in knee replacement, hip replacement, appendicitis, and coronavirus from January 2019 to December 2021 . Knee reAmerican College of Surgeons National Surgical Quality Improvement ProgramACS NSQIP ,12 was qCDC COVID TrackerThe CDC COVID Tracker provides a daily count of new coronavirus cases beginning from January 2020 . The daiData analysisMatlab (Mathworks) and its statistics package were used to plot and analyze the data from Google Trends, ACS NSQIP, and the CDC COVID Tracker.Changes in Public Interest Before and After the COVID-19 PeakRaw weekly averages for RSV data were plotted with confirmed case counts to observe the trends over the course of 2019 and 2020. The RSV for knee replacement, hip replacement, appendicitis, and coronavirus during the five weeks preceding and following the March 14 peak in coronavirus RSV were compared using a T-test with a significant threshold of p = 0.05 [Relationship Between Coronavirus and Emergent and Elective Surgical RSVsKnee replacement, hip replacement, and appendicitis RSVs were plotted against coronavirus RSV and the actual CDC new coronavirus case count. A linear model was fit to the data, and root mean square (RMS) error was calculated . The linRelationship Between Public Interest and Actual Case CountWhen comparing the RSV data with the number of cases from ACS NSQIP, quarterly data was used by taking the mean RSV over each quarter in 2019 and 2020. When comparing the RSV data with CDC data, weekly data was used by taking the sum of new coronavirus cases for each week in 2019 and 2020. Similar to the relationships between coronavirus and other surgical RSVs, the best linear model fit was calculated.Qualitative observations of surgical and COVID-19 case volume and RSVTKA and THA surgical case volume decreased after the first COVID-19 surge in March 2020  and after (post-peak) this peak using a T-test  and weakly correlated to new coronavirus cases . Lastly, appendicitis RSV is moderately correlated with coronavirus RSV  and new coronavirus cases . There were poor linear relationships relating surgical RSV to both coronavirus cases and coronavirus RSV, with R2 values all being less than 0.5; however, all of these linear models were statistically significant compared to a constant model.As the RSV for coronavirus increases, the RSV for surgical procedures decreases Figure . SimilarRelationship between RSV and actual case count2 = 0.931, p < 0.001; Hip: R2 = 0.940, p < 0.001). . Coronavirus RSV showed a poor relationship and no correlation to the coronavirus case counts .Knee replacement RSV and hip replacement RSV showed strong linear relationships and correlations to the TKA and THA case counts, respectively (Knee: RTracking demand and incidence of medical procedures is important for ensuring adequate access to care throughout the community. Demand and interest in care can fluctuate based on geographic region, time, population, racial disparities, and current events . Our invAs expected, we found that emergent surgeries showed smaller changes in surgical volume and RSV in comparison to elective procedures before and after the COVID-19 peak in RSV. Notably, there was still a decrease in emergent surgical volume and RSV during the COVID-19 outbreak in March 2020. These reductions may be a result of decreased emergency surgical operations and admissions to hospitals due to fear and anxiety about the coronavirus. Mulita et al. reported that patients in need of emergent surgeries presented with delayed onset of symptoms compared to before the COVID-19 outbreak, which resulted in longer hospital stays and operation durations . These rWe also found that there were strong correlations between search volume and surgical volume both before and after the COVID-19 peak for all elective surgical procedures evaluated. This suggests that while elective surgery RSV is primarily used as an indicator of interest, it could also be used to gauge demand, idempotent to the presence of acute, disruptive events. The findings that the drop in demand for elective surgeries after the COVID-19 peak on March 14, 2020, caused significant decreases in search volume ,17 is suInterestingly, after the March 2020 surge, despite a continued increase in coronavirus cases through the end of 2020, public interest and caseloads of surgical procedures recovered Figure , suggestIn the future, national medical datasets like ACS NSQIP can be used alongside public interest data like Google Trends for predictive analytics, with approaches utilizing tools like deep learning or Bayesian inference. This system would also be able to adjust and make predictions for acute, disruptive events by integrating disturbances to the model such as public interest data. The ability of Google Trends to be multilayer filtered by geographic region such as city and state  allows fSome limitations of our study include the lack of data from January 2019 to December 2021. However, other studies examine and highlight how some of the public interest in surgery changed before the coronavirus pandemic. Furthermore, there may be omissions from both the ACS NSQIP database and CDC Coronavirus Tracker, which may slightly change some of our findings. Lastly, our search queries were based on terms used in prior studies, but there could be additional or alternate terms in which people are interested that can change throughout an emergent scenario like the COVID-19 pandemic. Because of this, our study does not fully detail every term that could result in changes in caseload or medical interest. For instance, interest in the term "vaccine" may have increased later in 2022, which could have changed the demand for surgeries as it became safer for patients to return to hospitals. However, there would likely be similar results since many of these grouped search terms show strong correlations [Our investigation showed that strong correlations exist between public interest data from Google Trends and national databases like ACS NSQIP and the CDC COVID-19 Tracker. We also found decreases in RSV and case volume for emergent surgeries during the COVID-19 pandemic, which reflects serious consequences for patients who may have delayed their treatment due to fear and anxiety about the coronavirus. Because of these strong relationships, forecasting and understanding demand stratified by race, time, geography, and more could be done with the fusion of these data streams to evaluate public health. Future work could go into creating specific predictive models to see how geopolitical events change the demand as well as further stratification of the data to assess specific regions or populations.


The presence of RNA in the extracts was confirmed using 2% agarose gel electrophoresis. Statistical analyses were conducted using R language.  In a comparative experimental cross-sectional study, RNA was extracted from oral swabs and blood samples from 25 healthy individuals at the Department of Molecular Medicine, KNUST. RNA was extracted by the manual AGPC extraction method and commercial RNA extraction kits. The quantity (ng/p < 0.0001). However, the purity of RNA extracted by the manual AGPC method from blood was significantly lower than the commercial methods (p < 0.0001). Moreover, the purity from oral swabs using the manual AGPC method was significantly lower compared to QIAamp (p < 0.0001) and the OxGEn kits method (p < 0.001).  The yield of RNA extracted from blood and oral swab samples using modified AGPC was significantly higher compared to the commercial methods ( The modified manual AGPC method has a very high yield of RNA extracts using blood samples, which could serve as an alternate cost-effective method for RNA extraction in resource-limited laboratories; however, its purity may not be suitable for downstream processes. Moreover, the manual AGPC method may not be suitable for extracting RNA from oral swab samples. Future investigation is needed to improve the purity of the manual AGPC RNA extraction method and also confirmation of the obtained results by PCR amplification and RNA purity verification by sequencing. Ribonucleic acid (RNA) is a significant macromolecule that is required for a variety of biological functions, including protein synthesis and catalysis of biological reactions. As a result, extracted RNA is commonly employed in molecular biology tests such as gene expression profiling using reverse-transcription quantitative polymerase chain reaction (RT-qPCR) arrays and next generation sequencing . For effRNA extraction is usually performed using one of two methods: phenol-chloroform extraction or commercially available silica spin column extraction. The use of acid guanidinium thiocyanate-phenol-chloroform to induce phase separation of biological mixtures and subsequent selective isolation of molecules of interest is the basis for phenol-chloroform-based RNA extraction , 5, 6. TIn recent years, commercially available RNA extraction kits have largely replaced conventional RNA extraction approaches. Among them are TRIzol, manufactured by Thermo Fisher Scientific in Waltham, MA, and QIAzol, manufactured by QIAGEN in Hilden, Germany , QIAamp®This comparative experimental cross-sectional design was carried out on 25 physiologically healthy individuals who consented to participate in the study, from July to October 2022. Blood and oral swab samples were collected for RNA extraction at the Research and Development Unit at the Department of Molecular Medicine, Kwame Nkrumah University of Science and Technology (KNUST). The Department of Molecular Medicine is under the College of Health Sciences at the School of Medicine and Dentistry.Ethical approval was sought from the Committee on Human Research, Publication and Ethics, School of Medical Sciences, Kwame Nkrumah University of Science and Technology (CHRPE/SMS/KNUST) before the commencement of the study. Study protocol was thoroughly explained to subjects before sample collection. Written informed consent was also sought from participants before sample collection.μl of phosphate buffered saline (PBS) and stored at 4°C. RNA was extracted from each sample using three different methods; a modified manual acid-phenol chloroform RNA extraction method, standard protocol for QIAamp® Viral RNA Mini Kit  and OxGEn RNA Kit . Agarose gel electrophoresis was performed to visualize the various RNA extracted.Blood and oral swab samples were collected from participants for RNA extraction. 2 ml of venous blood sample was drawn from each participant into ethylene diamine tetraacetic acid (EDTA) tube and stored at 4°C until assayed. Oral swabs were collected into Eppendorf tubes containing 200 2O) was added to make 100 ml. The components were mixed by stirring at room temperature until completely dissolved (30–60 mins).The reagents involved were prepared in our laboratory under optimum conditions. In the preparation of a 100 ml TRIzol reagent, 38 ml of water saturated phenol (pH 4.3), 5 ml glycerol, and 3.33 ml sodium acetate  were measured into a falcon tube. This was followed by the addition of 11.82 g guanidine thiocyanate and 7.61 g ammonium thiocyanate, making a final concentration of 0.8 M and 0.4 M, respectively. Water  was added to the mixture and mixed by vortexing for 15 seconds. The mixture was centrifuged at 13,000 rpm for 10 mins at 4°C. The upper phase was transferred into a new Eppendorf tube, after centrifugation. Equal volume of cold isopropanol was added to the upper phase and inverted to mix. The mixture of the upper phase and isopropanol was placed in a −20°C freezer for 30 mins to enhance precipitation, followed by centrifugation at 13,000 rpm for 10 mins at 4°C. The supernatant was discarded, and 500 μl of ice-cold 75% ethanol was added to the pellet and vortexed and allowed to stand for 10 mins to rinse the pellets (75% ethanol was prepared with RNAse-free water and stored at −20°C). This was followed by centrifugation at 13,000 rpm for 10 mins at 4°C. The supernatant was discarded, and the pellets were air dried for 10 mins. 20 μl of RNAse-free H2O was added to the RNA pellet for elution. The RNA was quantified using IMPLEN NanoPhotometer® N60.To 200 μl of the sample  was transferred to 560 μl buffer AVL-carrier RNA in a microcentrifuge tube. This was followed by addition of 560 μl of ethanol (96–100%) after 10 mins of incubation. 630 μl of the solution was transferred to the QIAamp Mini column followed by centrifugation at 6000 ×g (8000 rpm) for 1 minute. The QIAamp Mini column was placed into a clean 2 ml collection tube. This step was repeated until all of the lysate had been loaded onto the spin column. 500 μl of wash buffer AW1 was added to the QIAamp Mini column and centrifuged at 6000 ×g (8000 rpm) for 1 minute. The collection tube was discarded and replaced with a clean 2 ml collection tube. 500 μl of wash buffer AW2 was added to the QIAamp mini column and centrifuged at full speed  for 3 minutes. 60 μl of buffer AVE was used for the elution of the RNA.The QIAamp kit is designed for the purification of viral RNA from body fluids. In brief, 140 μl Solution A was transferred into a 1.5 ml microcentrifuge tube, 5 μl of RNA carrier was added, 140 μl of the sample was added to the tube and mixed by pulse-vortex for 15 s, followed by incubation at room temperature. 560 μl of ethanol (96–100%) was added to the mixture. 650 μl of the lysate was transferred onto the G-spin column and centrifuged at 8000 rpm for 1 minute. This step was repeated with the remaining lysate until the entire lysate had passed through the G-spin column. The column was washed with 600 μl of solution W1 and centrifuged at 8000 rpm for 1 min. The column was washed with 600 μl of solution W2 followed by centrifugation at 13000 rpm for 1 minute, and the collection tube was replaced with a new one. The residual wash buffer was removed by centrifuging at 13000 rpm for 2 minutes, and the column was transferred onto a new 1.5 ml microcentrifuge tube. 50 μl of solution E was added onto the column, followed by incubation for 3 min at room temperature, RNA was eluted by spinning down at 8000 rpm for 1 minute, and RNA was quantified using the IMPLEN Nanophotometer.The OxGEn kit is a spin column-based RNA extraction kit. 560 μl, followed by analysis on a 2% agarose gel electrophoresis.Both the concentration and absorbance ratio at A260/280 nm were measured using the IMPLEN NanoPhotometer® N60. The concentrations were estimated in ng/p value of <0.05 was considered statistically significant.Data from the study was entered into Microsoft Excel 2019. Statistical analyses were performed on R language for statistical computing . Distribp = 0.525) . Moreover, the purity of RNA was slightly higher in blood compared to oral swabs, although the purity of RNA between these two samples was not statistically significant (p = 0.740) (= 0.525) . Moreove= 0.740) .p < 0.0001). In a post-hoc test, the yield using modified manual acid phenol chloroform was significantly higher compared to the two commercial methods (QIAamp method and OxGEn kit) (p < 0.0001). Moreover, the yield between the QIAamp method and the OxGEn kit was also significantly different (p < 0.0001)  .p < 0.0001). However, the purity between the manual AGPC and OxGEn kit was similar (p > 0.05). The QIAamp kit also produced significantly higher purity of RNA extracts from that of the OxGEn kit method (p < 0.0001)  .p < 0.0001) using the oral swabs. In addition, the yield produced using the QIAamp kit was significantly higher compared to the concentration of RNA extracted using the OxGEn kit method using the oral swabs. However, the yield using either the manual AGPC method or the QIAamp kit method was proportional (p > 0.05)  .p < 0.0001) and the OxGEn kit method (p < 0.001). However, the RNA extracted using the QIAamp kit method was significantly pure than using the OxGEn kit method (p < 0.0001)  .Following agarose gel electrophoresis, there were strong bands for RNA extracted from blood samples by each of the three methods; manual AGPC method, QIAamp kit, and OxGEn . VisibilRNA extraction is usually conducted using one of two methods: phenol-chloroform extraction or commercially available silica spin column extraction. In recent years, commercially available RNA extraction kits have largely replaced conventional RNA extraction approaches . Howeverμl compared to that of QIAamp (20.4 ng/µl) and OxGEn kit (5.32 ng/μl). However, the purity (A260/280 ratio) of RNA extracted from blood by QIAamp and OxGEn was purer (≥1.8) compared to that of the modified manual AGPC method (≤1.8). Although the QIAamp and OxGEn kit produced high purity of RNA extracts, both kits do not meet the demands of cost effectiveness, costing $314 and $113.04, respectively, to extract 50 samples each [μl and 140 μl, respectively. Interestingly, similar volumes of oral swabs were used, but comparable concentrations were produced by both the manual AGPC and QIAamp kits. As a result, the difference in RNA concentration recovered by each method cannot be explained solely by the volumes used. However, the high concentration observed with the modified manual AGPC method can be explained by the fact that it extracts total RNA from the samples, whereas the QIAamp and OxGEn kits are designed specifically for viral RNA extraction. Extracted RNA was verified by 2% agarose gel electrophoresis. For blood samples, RNA recovered by either the manual AGPC or QIAamp method produced comparable visible RNA bands on the gel, despite the differences in concentrations. By contrast, none of the RNA from oral swab RNA extracts by the manual AGPC method and OxGEn produced bands on the gel. RNA extracts by the QIAamp method had faint bands on the gel.In this study, RNA recovered from twenty-five blood samples using the manual AGPC method had the highest concentration of RNA with a median value of 114.40 ng/les each , 13. ForIn agreement with the findings of this study, the manual AGPC RNA extraction method has been demonstrated to yield high quantity of RNA compared to column-based kits including the QIAamp and OxGEn kit using different samples , 14, 15.Furthermore, the lack of significance in comparing yield and purity of RNA extracts in the aforementioned studies may validate the idea that traditional methods, when modified and carefully monitored, will be of great use in RNA extraction from blood and oral swabs, particularly in resource-constrained settings where there is a need to reduce cost but with high efficiency. One major limitation of this study is the lack of confirmation of the RNA extracts by PCR or sequencing. The study could not confirm the RNA obtained by the manual AGPC method by either PCR or sequencing due to limited financial resources.The modified manual AGPC method has a very high yield of RNA extracts using blood samples, which could serve as an alternate cost-effective method for RNA extraction in resource-limited laboratories; however, its purity may not be suitable for downstream processes. Moreover, the manual AGPC method may not be suitable for extracting RNA from oral swab samples. Future investigation is needed to improve the purity of the manual AGPC RNA extraction method and also confirmation of the obtained results by PCR amplification and RNA purity verification by sequencing.