Input: Task: contrast the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: Such AF2 predictions are still informed by all structures in the PDB before April 30, 2018, because these structures were used to train AF2—that is, to determine the tens of millions of parameters (“weights”) in the AF2 neural network. Machine learning methods nearly always perform better when evaluated on the data used to train them than when evaluated on other data. For this reason, we consider AF2 models only for proteins whose structures were not used to train AF2—that is, for proteins whose structures were not available in the PDB before April 30, 2018. Previous papers (including Beuming and Sherman, 2012, have shown a clear correlation between the binding pocket RMSD of a protein model and pose prediction accuracy based on that model. Our main findings are unexpected in light of these previous reports: we find that AF2 models yield pose prediction accuracy similar to that of traditional homology models despite having much better binding pocket RMSDs, and that AF2 models yield substantially worse pose prediction accuracy than experimentally determined structures with different ligands bound despite having similar binding pocket RMSDs. Reviewer 2 also correctly notes that previous papers have described AF2 models as “apo models,” because these models do not include coordinates for bound ligands. As noted by the AF2 developers (e. g. , however, AF2 is designed to predict coordinates of protein atoms as they might appear in the PDB, and AF2 models are thus frequently consistent with structures in the presence of ligands even though those ligands are not included in the models. GPCR structures in the PDB, including those used to train AF2, nearly always contain a ligand in the orthosteric binding pocket. An AF2 model of a GPCR should thus not be viewed as an attempt to predict the GPCR’s structure in the unliganded (apo) state. Finally, we did not apply flexible docking in this study because previous work has found that standard flexible docking protocols typically improve pose prediction performance only when given prior information on which amino acid residues to treat as flexible. For example, previous studies that performed successful flexible docking to AF2 models generally used prior knowledge of the ligand’s experimentally determined binding pose to identify the residues to treat as flexible. [SEP] Justify:

Output: The text contrasts the claim by explaining that while AF2 models yield certain structural predictions, they do not consistently translate to accurate predictive capabilities for protein function. The text notes, 'we find that AF2 models yield pose prediction accuracy similar to that of traditional homology models despite having much better binding pocket RMSDs,' suggesting that having a better RMSD does not guarantee better functional predictions, which undermines the assertion that properties of proteins can predict functions accurately.


Input: Task: pass the claim using the given text. Claim: Extraterrestrial signals can be easily detected from Earth. [SEP] Text: Some studies of in situ satellite observations revealed features of the plasmasphere such as “notches” (Sandel et al. 2001, 2003). A particularly long-lived (2–3 days) depleted region [magnetic local time (MLT) >1. 5–2 h) or “notch” extended out from L ~ 3 in the plasmasphere (Kotova et al. 2004). Remote sensing from ground-based magnetometers enabled the comparison of mass density and electron density between different L-shells using multiple observation stations along the 330° magnetic longitude, spanning the L-shell between 1. 5 and 3. 4 (Chi et al. 2013). It was also demonstrated that mass density decreased within a few hours by 50% or more at 0. 5 radius of the Earth or further inward of the plasmapause during moderately disturbed periods on December 10–15, 2003 (Menk et al. 2014). Measurement of electromagnetic wave data is also important to determine the electron density. For example, dispersion of electromagnetic waves originating from lighting discharge, known as whistlers (Helliwell 1965), is useful for estimating the spatial electron density profile in the plasmasphere, because the propagation velocity of whistler mode waves depends on the electron density profile around the Earth (Crouchley 1964; Singh et al. 2003). Statistical studies of whistlers have been performed using ground observatory data at Tihany, Hungary (Tarcsai et al. 1988; Collier et al. 2006; Lichtenberger et al. 2008). Another statistical study of whistlers was carried out using the data from Akebono satellite (Oike et al. 2014). These studies have provided information on the absorption effect of whistlers in the ionosphere. A recent statistical study by Zheng et al. (2016) also reported that one-to-one coincidences between whistlers observed by Probes (Storm Probes) and lightning strokes detected by Network are clearly shown in the L-shell range of L = 1–3. Because the electron density profile around the Earth changes day by day, it is important to assess the trend of this change using statistical study of electromagnetic wave propagation over several years. The intensity of whistlers, however, depends on many factors such as lightning current, location, orientation, and ionospheric attenuation. [SEP] Justify:

Output: The text does not address the claim regarding the detection of extraterrestrial signals. Instead, it focuses on in situ satellite observations, studies of the plasmasphere, and the measurement of electromagnetic waves, specifically whistlers. There is no mention of extraterrestrial signals or the ease of detecting them from Earth, making the text irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: Etnobotánica medicinal y biocidas para malaria en la región Ucayali. Folia amazónica. 2002;13(1‒2):87‒108. Pabon A, Ramirez O, Ríos A, et al. Antiplasmodial and of Extracts as Reported by People of the (in Colombia). Planta Med. 2016;82(8):717‒722. Alkaloid diversity in eleven species of Ormosia and in Clathrotropis macrocarpa (Leguminosae-Papilionoideae). Brittonia. 1994;46(4):355‒371. Sagen AL. Phytochemical and biological investigations on Clathrotropis glaucophylla (Fabaceae), an ingredient of Yanomamï curare, emphasizing on quinolizidine alkaloids. ürich, Switzerland; 2002. E. Etnobotánica de las comunidades indígenas Waunana, Chocó (Colombia). Cespedesia. 1980;9(33):115‒302. Glenboski LL. Ethnobotany of the Tukuna Indians. Amazonas, Colombia; 1975. . The healing forest: medicinal and toxic plants of the Northwest Amazonia. ís (Francia); 1990;12:236‒237. Assessment of anti-protozoal activity of plants traditionally used in Ecuador in the treatment of leishmaniasis. J Ethnopharmacol. 2010;128(1):184‒197. García Barriga H. Flora medicinal de Colombia. Bogotá DC: Instituto de Ciencias Naturales, de Colombia. 1974;3:443‒459. Gupta MPB. Plantas medicinales iberoamericanas. Bogotá DC, Colombia: Convenio Andrés Bello (CAB), de Ciencia y Tecnología (CYTED) y Universidad de Panamá. 2008. Pérez-Arbeláez E. Plantas útiles de Colombia. á, Colombia; 1996. [SEP] Justify:

Output: The text corroborates the claim by providing various references to ethnobotanical studies that examine traditional medicinal practices of indigenous cultures, specifically mentioning plants used for medicinal purposes in regions like Ucayali and by indigenous communities such as the Waunana and Tukuna in Colombia. This indicates a direct link between the use of plants for medicine and indigenous cultural practices.


Input: Task: contrast the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: However, understanding whether this unprecedented accuracy translates to better small molecule ligand pose prediction has been an open question, and this study directly addresses the question in a systematic, rigorous approach. Reviewer #2 (Public Review): While the question of 'are AlphaFold-predicted structures useful for drug design' has largely seen comparisons of AF versus experimental protein structures, this paper takes a less explored (but perhaps more practically important) angle of 'are AlphaFold-predicted structures any better than the previous generation of homology modeling tools' to the protein-ligand (rigid) docking problem. The conclusions of this work will be of largest interest to the audience less familiar with the precision required for successful rigid docking, while the expert crowd might find them obvious, yet a good summary of results previously shown in the literature. Further work, understanding the structural objectives/metrics that should be placed on future AlphaFold-like models for better pose prediction performance, would greatly expand the practicality of the observations made here. The main conclusion of the paper, that structural accuracy (expressed as RMSD) of the protein model is not a good predictor of the accuracy the model will show in rigid docking protein-ligand pose prediction, is a good reminder of the well-appreciated need for high-quality side chain placements in docking. The expected phenomenon of AlphaFold predicting 'more apo-like structures' is often discussed in the field, and readers should be cautious about drawing conclusions from the rigid (rather than flexible, as in some previous works) docking done here. The authors have very clearly communicated that the use of AlphaFold-generated structures in traditional docking might not be a good idea, and motivated that the time of a molecular designer might be better spent preparing a high-quality homology model. The visual presentation of the conclusions is very clear but might leave the reader wanting a more in-depth discussion of which structural elements of the AF models lead to bad docking outcomes. For example, Fig. 3 presents an example of a very accurate AlphaFold prediction leading to the ligand being docked completely outside of the binding pocket. Close inspection of the Figure suggests a clash of the ligand with the slightly displaced tryptophan residue in the AF model that might be to blame, as can be confirmed by comparison of the model and PDB structure by the reader themselves but has not been discussed by the authors. [SEP] Justify:

Output: The text contrasts the claim by stating that structural accuracy of protein models (as measured by RMSD) is not a good predictor of the accuracy of these models in predicting protein-ligand binding outcomes. The text emphasizes that high-quality side chain placements in docking are critical for accurate predictions, suggesting that merely relying on the properties of proteins (like their structures predicted by AlphaFold) may not be sufficient for accurate function prediction in the context of ligand docking.


Input: Task: pass the claim using the given text. Claim: Extraterrestrial signals can be easily detected from Earth. [SEP] Text: On the other hand, signals observed from artificial transmitters are worth analyzing for such purposes because these transmitters continuously broadcast signals with constant power. For this reason, it is possible to analyze the extent of change in the wave propagation. This technique has been used to estimate the ionospheric topside and bottom-side profiles with sounders (Reinisch and Huang 2001; Ganguly et al. 2001), which are capable of checking the ionospheric peak parameters such as density, height, and peak shape (Pulinets et al. 2001). Japan launched a satellite nicknamed Akebono (EXOS-D) in 1989 to observe the Earth’s magnetosphere and plasmasphere. The satellite consists of several scientific instruments (i. e. , p12. 75 kHz. The wide dynamic range amplifier (WIDA) hybrid integrated circuits (ICs) are equipped for gain control to achieve wide measurable dynamic range (Kimura et al. 1990). system was a navigation system used to provide a navigational aid not only for domestic aviation but also for oceanic air and marine shipping, and had eight ground station transmitters located in and Japan (Morris et al. 1994). The PFX observed Omega signals broadcast from these eight ground stations from 1989 to 1997. The PFX captured Omega signals at 10. 2 kHz, which is one of the common frequencies among the transmission patterns of these eight stations. In 1997, this navigation system was shut down when replaced by the global positioning system. Sawada et al. (1993) analyzed the Omega signals captured by the PFX and proposed a method to estimate global plasmaspheric electron density deduced from wave normal directions and in situ electron density along the Akebono trajectories. This method could derive a tomographic electron density profile comparing the wave normal direction and delay time (propagation time from transmission station to the observation point) of the Omega signals using 1-h data of a single satellite observation along a trajectory with the propagation paths calculated by a ray-tracing method (Kimura et al. 2001 and the 1997. To achieve this purpose, we extracted Omega signals from the enormous amount of PFX data using an automatic detection program developed by Suarjaya et al. (2016). The outline of the present paper is as follows: In the next section, we briefly introduce our detection algorithm (Suarjaya et al. [SEP] Justify:

Output: The text does not address the claim directly about the detectability of extraterrestrial signals. Instead, it discusses the analysis of signals from artificial transmitters and navigation systems without making any statements related to detecting extraterrestrial signals specifically. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: Estudio Etnobotánico sobre las especies utilizadas por la Comunidad Indígena Miraña, Amazonas-Colombia. Bogotá DC: Fund, Bogota, Colombia; 1988. p. 386. Milliken W. Traditional anti-malarial medicine in Roraima, Brazil. Economic Botany. 1997;51(3):212‒237. êa do Abordagem etnobotânica acerca do uso de plantas medicinais na Vila Cachoeira, Ilhéus, Bahia, Brasil. Acta farmacêutica bonaerense. 2002;21(3):205‒211. Ta’ta’, Huayani: Perception of leishmaniasis and evaluation of medicinal plants used by the Chayahuita in Peru. Part II. J Ethnopharmacol. 2009;126(1):149‒158. Treatment of leishmaniasis in the Oyapock basin (French Guiana): A K. A. P. survey and analysis of the evolution of phytotherapy knowledge amongst Wayapi Indians. J Ethnopharmacol. 2011;137(3):1228‒1239. Rodrigues E. Plants and animals utilized as medicines in the Jaú (JNP), Brazilian Amazon. Phytother Res. 2006;20(5):378‒391. Sanz-Biset J, Cañigueral S. Plant use in the medicinal practices known as “strict diets” in Chazuta valley (Peruvian Amazon). J Ethnopharmacol. 2011;137(1):271‒288. . Contribución al conocimiento de la Anaueria sp. Añuje moena; nuevo registro en la Amazonía peruana. Folia Amazonica. 1990;2:1‒16. Tene V, Malagón O, Finzi PV, et al. An ethnobotanical survey of medicinal plants used in Loja and Zamora-Chinchipe, Ecuador. J Ethnopharmacol. 2007;111(1):63‒81. [SEP] Justify:

Output: The text supports the claim by providing various examples of ethnobotanical studies that document the use of medicinal plants by indigenous cultures in different regions, such as the Miraña community in Colombia and the Wayapi Indians in French Guiana. These studies highlight the relationship between traditional medicine and plant use, aligning directly with the claim's assertion.


Input: Task: contrast the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: Further, the authors should discuss the commonly brought up problem of AlphaFold generating 'more apo-like structures' - are the models used here actually 'holo-like' because of the low RMSDs? (what RMSD differences are to be expected between apo and holo structures of these systems? ) How are the volumes of the pockets affected? The position on this problem taken by previous works is worth mentioning - "much higher rmsd values are found when using the AF2 models (. . . ), which reflect the difficulties in performing docking into apo-like structures" in Ref. 1 and "computational model structures were predicted without consideration of binding ligands and resulted in apo structures" in Ref. 2. Because of this 'apo problem', Ref. 2 assumed that rigid docking (as done here) would not succeed and used flexible docking where "two sidechains at the binding site were set to be flexible". In fact, the reader of this new paper will be left to wonder if it is not simply presenting a subset of the results already seen in Ref. 2, where "the success ratios dropped significantly for them because misoriented sidechains prevented a ligand from docking (Figure S14)". While this conclusion is not made as clear in Ref. 2 as it is here, a comparison of Figures 4 and S14 there will lead the reader to the same conclusion, and more -- that flexible docking meaningfully improves the performance of AF models, and more so than homology models. Finally, certain data analyses present in previous works but not here should be necessary to make this work more informative to the readers: a) Consideration of multiple top poses, e. g. , in Ref. 2, Figures 4 and S14 mentioned before, comparison of success rates in top 1 and top 3 docked poses add much context. b) Notes on the structural features preventing successful docking, see e. g. , in Ref. 1, Table 2 or in Ref. 4, Tables 2 and 4. This work has the potential to become an important piece of the puzzle, if deeper insights into the reasons for AF model failures are drawn by the authors. These could include a discussion of the problematic structural elements (clashes of side chain with ligands, missing interactions/waters, etc. ), potential solutions with some preliminary data (flexible docking, softening interactions, etc. [SEP] Justify:

Output: The text contrasts the claim by highlighting challenges related to predicting protein functions from models. It discusses issues with AlphaFold generating 'apo-like structures' and emphasizes that the results are influenced by how accurately these models can predict structures in the context of their binding states. It mentions that previous works found 'much higher rmsd values' when using AlphaFold models, which reflects difficulties in docking into these structures. Furthermore, it suggests that the models may not predict protein functions accurately due to their inability to consider binding ligands, indicating that the properties used for prediction might not align with actual functional behavior.


Input: Task: pass the claim using the given text. Claim: Extraterrestrial signals can be easily detected from Earth. [SEP] Text: (2016) is based on transmission frequency pattern, transmission time, and location of each Omega station combined with a fixed threshold, that minimizes the contamination of the VLF sources (for example, from other Omega stations). In addition, comparison of upper and lower frequencies introduced in their detection method enables exclusion of any events contaminated by whistlers. Data analysisDatasetsWe first show the number of PFX data that we have processed, as shown in Fig. 1 and Table 1. Because we applied several kinds of operation modes to PFX in changing its center frequency, we selected the PFX data when its center frequency was fixed at 10. 2 kHz to measure the Omega signal. In the figure and table, we count one event that corresponds to 10 s duration of data when the center frequency of the PFX was fixed at 10. 2 kHz. 1989 to September 1997, we measured 3,030,614 events. The number of events changes every year. We obtained the highest number of events (408,790) in 1992 and the lowest number (213,155) in 1989. We also separated the datasets of events into four sides for the analysis based on magnetic local time (MLT). In the present study, we defined dawnside, dayside, duskside, and nightside as MLT from 3 to 9, from 9 to 15, from 15 to 21, and from 21 to 3, respectively. Comparing the number of events for each MLT or year, there were no significant differences except for the data in 1989. This is because this year only contains data for three months. Therefore, the datasets coverage for each year and each MLT are reliable enough for the statistical analyses in this study. Fig. 1Number of data events processed from October 1989 to September 1997. Each event corresponds to 10 s duration of PFX dataFull size image Table 1 Number of data events processed from October 1989 to September 1997Full size table Using these datasets, we comprehensively analyzed the Omega signals broadcast from each station. For the present paper, however, we analyzed only the signals broadcast from Norway and stations located at high–middle-latitude regions because the orbital condition of Akebono was suitable to detect the signals from these stations along the ambient magnetic field lines due to its elliptical and high-inclination orbit. [SEP] Justify:

Output: The text does not provide information that specifically supports or contradicts the claim about extraterrestrial signals being easily detected from Earth. It discusses the methodology used in analyzing Omega signals and provides details on the datasets processed from specific locations without addressing the ease of detecting extraterrestrial signals.


Input: Task: corroborate the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: Sanz-Biset J, Campos-de-la-Cruz J, Epiquién-Rivera MA, et al. A first survey on the medicinal plants of the Chazuta valley (Peruvian Amazon). J Ethnopharmacol. 2009;122(2):333‒362. The rainbow hurts my skin: medicinal concepts and plants uses among the Yanesha (Amuesha), an ethnic group. J Ethnopharmacol. 2010;127(1):175‒192. de Albuquerque UP, Muniz de Medeiros P, de Almeida AL, et al. Medicinal plants of the caatinga (semi-arid) vegetation of NE Brazil: a quantitative approach. J Ethnopharmacol. 2007;114(3):325‒354. Antiviral activity of some medicinal plants. Phytother Res. 1999;13(2):142‒146. de las Heras B, Slowing K, Benedí J, et al. Antiinflammatory and antioxidant activity of plants used in traditional medicine in Ecuador. J Ethnopharmacol. 1998;61(2):161‒166. Evaluation of traditional antimalarial remedies. J Ethnopharmacol. 2005;98(1):45‒54. A search for natural bioactive compounds in Bolivia through a multidisciplinary approach. Part V. Evaluation of the antimalarial activity of plants used by the Tacana Indians. J Ethnopharmacol. 2001;77(1):91‒98. Plants used by native Amazonian groups from the (Peru) for the treatment of malaria. J Ethnopharmacol. 2011;133(2):917‒921. Antimalarials from nature. Bioorganic & medicinal chemistry. 2009;17(9):3229‒3256. Antimalarial plants used by indigenous people of the Negro in Amazonas, Brazil. J Ethnopharmacol 2016;178:188‒198. Antimalarial remedies in French Guiana: a knowledge attitudes and practices study. J Ethnopharmacol. 2005;98(3):351‒360. The classical drug discovery approach to defining bioactive constituents of botanicals. Fitoterapia. 2011;82(1):71‒79. [SEP] Justify:

Output: The text corroborates the claim by detailing the use of various plants in traditional medicine by indigenous groups, specifically mentioning studies of medicinal plants used by ethnic groups such as the Yanesha and Tacana Indians. It refers to multiple surveys and evaluations of plants utilized for medicinal purposes in regions inhabited by indigenous cultures.


Input: Task: contrast the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: A total of 17% of experts offered forecasts equal to their idealized replication, while 56% provided forecasts that were lower than their ideal, suggesting a degree of doubt about these studies and/or the RP:CB methods. Forecast accuracy None of the 5 reproducibility studies in our survey successfully replicated the original studies using either significance or effect-size criteria [17–21]. Thus, accurate forecasting would require a strongly pessimistic response pattern. Table 3 displays experts’ forecast accuracy by outcome and expertise types. Experts were extremely overconfident about the replication rate, especially for significance. The specificity of all expert forecasts was 0. 39, meaning 39% of forecasts (excluding fence-sitting 50% forecasts) were in the correct direction. The specificity of significance forecasts was 0. 20, showing that the experts were substantially overoptimistic about significance replicability. The specificity of effect size forecasts was better, 0. 64. Therefore, experts were more accurate (and pessimistic) about the replicability of effect sizes than significance levels. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageTable 3. Forecast accuracy by outcome type, identified expertise, and rank. mean Brier score was 0. 40, 95% CI (0. 38–0. 45), indicating forecasting skill was significantly worse in our expert sample than guessing 50% each time (the latter would have generated a Brier score of 0. 25) (see Fig 2). A fifth of experts (21%) had mean Brier scores less than 0. 25. Among experts, Brier scores were worse for significance than for effect-size forecasts (median = 0. 58 and 0. 25, respectively), with 11% of experts scoring better than 0. 25 (4% for significance forecasts and 30% for effect-size forecasts). Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFig 2. Brier scores by outcome type with sensitivity analysis. The gray histograms display Brier scores for the 5 studies with known results. All experts are displayed in panel A, and they are divided by outcome types in the bottom panels (B for significance and C for effect size). The green lines represent the probability density of Brier scores if the sixth study replicates each outcome, and the red line represents if it fails to replicate for each. [SEP] Justify:

Output: The text contrasts the claim by discussing the inaccuracies and overoptimism of experts in forecasting replicability, particularly focusing on effect sizes and significance levels. It suggests that forecasting skill among experts is worse than mere guessing, which implies skepticism about the reliability of predictions regarding properties of proteins and their functions.


Input: Task: pass the claim using the given text. Claim: Extraterrestrial signals can be easily detected from Earth. [SEP] Text: 3b, c, we can clearly see that the high intensities of the Omega signal from the Norway station propagated along the Earth’s magnetic field lines and that the signal reached to the opposite hemisphere (between 40° and 70° S latitude). It is also noteworthy that the Omega signal in the electric field did not attenuate as much as in the magnetic field along the magnetic field line at the center of the signal penetration point (~ 10° north of the transmitter station). Furthermore, the signal intensity in the electric field was distributed over a wider range in latitude (between 40° and 80° N), while the signal intensity in the magnetic field rapidly attenuated in latitudinal range. Fig. 3 a Duration of data processed in the magnetic and electric field with longitude restricted to ±10°. b Omega signal propagation for the Norway station in the magnetic field and c the electric field. Rectangle indicates the location of the Norway station at latitude 55. 96° N and longitude 100. 72° EFull size image Next, we show the propagation characteristics of the Omega signals broadcast from North Dakota. It is important to note that the stations at Norway and were located at the same latitude (55. 9° N) in geomagnetic coordinates, but at different latitudes in geographic coordinates. station was located at 56. 42° N, while the station was at 46. 37° N (geographic coordinates). Figure 4a shows the number of events used for the analysis just above the station from October 1989 to September 1997. The station was located at latitude 55. 98° N and longitude 34. 83° W (geomagnetic). White areas on the map indicate unavailability of PFX data, especially around the eastern part of the transmitter station. This unavailability was caused by the tracking condition of Akebono. Over the region, Akebono was tracked from the tracking station at Prince Albert, Canada (Obara et al. 1990), and the station was located southeast of Prince Albert. Because we restricted the data measured at altitude below 640 km in Fig. 4, it was not possible to track Akebono in this region. Figure 4b, c shows the averaged intensity of the signals in magnetic and electric fields, respectively, indicated by color scales given at the right of each panel. The gray color indicates no Omega signal was detected in that region. [SEP] Justify:

Output: The text discusses the propagation characteristics of the Omega signals broadcast from various stations, including detailed technical information about signal intensity and geographic coordinates. However, it does not address or support the claim regarding the ease of detecting extraterrestrial signals from Earth, making it irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: Calderon LdA, Silva-Jardim I, Zuliani JP, et al. Amazonian biodiversity: a view of drug development for leishmaniasis and malaria. J Soc. 2009;20(6):1011‒1023. Evaluation of the anti-plasmodial activity of bisbenzylisoquinoline alkaloids from Abuta grandifolia. Planta Med. 1999;65(5):413‒416. Garavito G, Rincón J, Arteaga L, et al. Antimalarial activity of some Colombian medicinal plants. J Ethnopharmacol. 2006;107(3):460‒462. Identification and evaluation of Peruvian plants used to treat malaria and leishmaniasis. J Ethnopharmacol. 2006;106(3):390‒402. de In vitro antiplasmodial activity of plants used as traditional remedies. J Ethnopharmacol. 2007;110(1):165‒170. Tabuti JR. Herbal medicines used in the treatment of malaria in Budiope county, Uganda. J Ethnopharmacol. 2008;116(1):33‒42. . Ethnopharmacological use of herbal remedies for the treatment of malaria in the District of Ghana. J Ethnopharmacol. 2010;129(3):367‒376. . Potential antimalarials from Nigerian plants: a review. J Ethnopharmacol. 2011;133(2):289‒302. Cultural categorization of febrile illnesses in correlation with herbal remedies used for treatment in Southwestern Nigeria. J Ethnopharmacol. 2003;85(2‒3):179‒185. An ethnobotanical study of antimalarial plants in Region. J Ethnopharmacol. 2011;134(1):183‒190. Antiplasmodial and antipyretic screening of Mangifera indica extract. Phytother Res. 1998;12(6):437‒438. In vitro cytotoxicity studies of 20 plants used in Nigerian antimalarial ethnomedicine. Phytomedicine. 2006;13(4):295‒298. . Screening of the Flora of for Bioactives. IJPPR. [SEP] Justify:

Output: The text corroborates the claim by providing numerous examples of research focused on the antimalarial properties of plants that have been traditionally used in various cultures, such as those in Colombia, Peru, Uganda, and Nigeria. It highlights specific studies on the pharmacological activities of these plants, indicating a strong connection between traditional medicine and the use of indigenous plant species.


Input: Task: contrast the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: Perhaps the most direct interpretation is that researchers consistently overestimated the validity of original reports. The high degree of optimism about statistical significance might reflect that experts believe effects in original studies are “real” (hence, they believe the replication results will also be positive and significant) but question the magnitude of treatment effects (hence, they show less optimism about effect sizes). Researchers may interpret the original significance levels as strong evidence that the effects are true positives, while they are more open to the possibility of type M (magnitude) error—which should be expected when samples sizes are small and/or measurements are noisy [22]. This interpretation implies researchers believe published results tend to be qualitatively valid but consistently overestimate effect sizes. A second interpretation of our findings is that researchers were overly optimistic about the ease with which the original methods could be accurately replicated by independent laboratories or, more specifically, about the ability of these replicating laboratories to perform these particular replication studies [23]. RP:CB authors have stated that obtaining original protocols and materials was challenging, and originating labs often had to reconstruct materials that were unavailable [24]. Since publication of the first RP:CB studies, there has been a vigorous discussion about whether replication attempts were faithful to original methods, especially since 2 of the replication studies were deemed uninterpretable [25]. The RP:CB methods have been criticized for being too rigidly constrained by their registered protocols, preventing adjustment to challenges that arose while implementing original protocols [24–26]. Xenograft studies—which were the focus of our forecasting exercise—have come under particular criticism [25]. The 2 RP:CB replication studies that have received the most methodological criticisms had the second and third highest mean forecasts of significance. This suggests experts could have been overly optimistic about the challenge of executing direct replications in living biological systems or about the specialized skills RP:CB researchers would need to implement novel techniques. A third interpretation is that forecasters were wrong in the specifics but right in the generalities. It is possible in each case that the original study was an overestimate of the effect size and the replication was an underestimate. As a consequence, further effort at replication might ultimately vindicate the experiments that did not successfully recapitulate effects observed in the original study. However, it is unlikely we would see the same pattern with such stark contrasts for every study. [SEP] Justify:

Output: The text contrasts the claim by suggesting that researchers are overly optimistic about the validity of original studies and the ease of replicating their results. This implies a skepticism about the predictability of protein functions based solely on their properties, which undermines the notion that such prediction is accurate. The discussion on type M error and the challenges in replicating original protocols further supports the idea that properties of proteins may not reliably lead to consistent predictions of their functions.


Input: Task: pass the claim using the given text. Claim: Extraterrestrial signals can be easily detected from Earth. [SEP] Text: The rectangle indicates the location of the station at latitude 55. 98° N and longitude 34. 83° WFull size image Magnetic local time dependenceAs the next step, we examined magnetic local time dependence of the propagation characteristics of the Omega signals from Norway and stations. We separated the data into eight sections referring to the magnetic local time (MLT) at the observation point every 3 h. We compared the results using the data obtained around the Norway station and the station. Figure 6 shows the Omega signal intensity broadcast from the Norway station from October 1989 to September 1997 in geomagnetic coordinates without any altitude data restriction. The upper eight panels show magnetic field intensity, and the lower eight panels show electric field intensity. The vertical and horizontal axes indicate geomagnetic latitude and geomagnetic longitude, respectively, and the eight panels correspond to the sections separating every three MLTs. The longitude was centered at the location of the station, with a range of 100° (±50° centered at the station). The rectangle on the map indicates the location of the Norway station, which was located at latitude 55. 96° N and longitude 100. 72° E. The transition of the intensity level demonstrates that the nightside (MLT 21–3) has a high-intensity level at approximately −265 dBT in the magnetic field and approximately −115 dBV/m in the electric field. The dayside has the lowest intensity level of approximately −270 dBT in the magnetic field and approximately −120 dBV/m in the electric field. In addition, the dayside (MLT 9–15) clearly exhibits narrow propagation with only ~50° width of range in longitude compared to the other MLT sides. Fig. 6 a Propagation of the Omega signal from the Norway station based on local time in the magnetic field and b in the electric field. The red arrow indicates the width of the map (~100°) with location of the station in the center (indicated by the rectangle)Full size image Figure 7 shows the Omega signal intensity broadcast from the station from October 1989 to September 1997 in geomagnetic coordinates without any altitude data restriction. The style of the panels is same as the one in Fig. 6. The rectangle on the map indicates the location of the station, which was located at latitude 55. 98° N and longitude 34. 83° W. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the propagation characteristics of Omega signals from specific geographical locations and does not address the detection of extraterrestrial signals or ease of such detection from Earth.


Input: Task: corroborate the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: 1993;31(4):255‒258. Antiprotozoal activities of Colombian plants. J Ethnopharmacol. 2001;78(2‒3):193‒200. Oga S, Sertié JA, Brasile AC, et al. Antiinflammatory effect of crude extract from Guarea guidonia. Planta Med. 1981;42(3):310‒312. . Analysis of the from Leaves of Specimens of Guarea guidonia (L. ) Sleumer (Meliaceae). Journal of Research. 2005;17(3):271‒273. . Terpenoids from Guarea guidonia. Phytochemistry. 2002;60(4):333‒338. . 16,17-Seco- and 2,3:16,17-di-Seco-pregnanes from Guarea guidonia. J Soc. 2008;19(6):1073‒1077. LC-ESI-MS determination of quassinoids isobrucein B and neosergeolide in Picrolemma sprucei stem infusions. J Soc. 2009;20(6):1065‒1070. de Andrade- In vitro inhibition of Plasmodium falciparum by substances isolated from Amazonian antimalarial plants. Oswaldo Cruz. 2007;102(3):359‒365. Biological activity of neosergeolide and isobrucein B (and two semi-synthetic derivatives) isolated from the Amazonian medicinal plant Picrolemma sprucei (Simaroubaceae). Oswaldo Cruz. 2009;104(1):48‒56. Struwe L, Albert VA. A monograph of Neotropical potalia aublet (Gentianaceae: Potalieae). Systematic botany. 2004;29(3):670‒701. Duke J, R Vasquez. Dictionary. FL: 1994. Roumy V, Garcia-Pizango G, Gutierrez-Choquevilca AL, et al. Amazonian plants from Peru used by Quechua and Mestizo to treat malaria with evaluation of their activity. J Ethnopharmacol. 2007;112(3):482‒489. Gentry AH. Bignoniaceae, in Flora de Colombia, IdC Naturales. [SEP] Justify:

Output: The text corroborates the claim by mentioning various studies on the medicinal properties of plants from indigenous cultures, such as Guarea guidonia and Picrolemma sprucei, which are used to treat ailments like malaria. The references to these plants and their antiprotozoal and anti-inflammatory activities underscore their use in traditional medicine.


Input: Task: pass the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: Evaluating replicability of laboratory experiments in economics. Science. 2016;351: 1433–1436. pmid:26940865 View 10. Using prediction markets to estimate the reproducibility of scientific research. Acad Sci. 2015;112: 15343–15347. pmid:26553988 View 11. Coadministration of a Tumor-Enhances the Efficacy of Cancer Drugs. Science. 2010;328: 1031–1035. pmid:20378772 View 12. -Cordero A, et al. Discovery and of of Expression Data. Med. 2011;3: 96ra77–96ra77. pmid:21849665 View 13. Melanoma genome sequencing reveals frequent PREX2 mutations. Nature. 2012;485: 502–506. pmid:22622578 View 14. BET as a to Target c-Myc. Cell. 2011;146: 904–917. pmid:21889194 View 15. -I, et al. Inhibition of BET recruitment to chromatin as an effective treatment for MLL-fusion leukaemia. Nature. 2011;478: 529–533. pmid:21964340 View 16. Willingham SB, Volkmer J- The CD47-signal regulatory protein alpha (SIRPa) interaction is a therapeutic target for human solid tumors. Acad Sci. 2012;109: 6662–6667. pmid:22451913 View 17. . Replication Study: BET bromodomain inhibition as a therapeutic strategy to target c-Myc. eLife. 2017;6: e21253. pmid:28100400 View 18. . Replication Study: The CD47-signal regulatory protein alpha (SIRPa) interaction is a therapeutic target for human solid tumors. eLife. 2017;6: e18173. pmid:28100392 View 19. . Replication Study: Melanoma genome sequencing reveals frequent PREX2 mutations. eLife. 2017;6: e21634. pmid:28100394 View 20. . Replication Study: Discovery and preclinical validation of drug indications using compendia of public gene expression data. eLife. 2017;6: e17044. pmid:28100397 View 21. . [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses various studies related to scientific research topics without addressing the relationship between protein properties and their functions. The lack of direct reference to proteins or the predictive nature of their properties means the text does not support, contrast, or provide evidence related to the claim.


Input: Task: pass the claim using the given text. Claim: Extraterrestrial signals can be easily detected from Earth. [SEP] Text: The transition of the intensity level demonstrates that the nightside had a high-intensity level at approximately −265 dBT in the magnetic field and approximately −110 dBV/m in the electric field. The dayside has the lowest intensity level of approximately −270 dBT in the magnetic field and approximately −125 dBV/m in the electric field. It is also apparent that the dayside (MLT 12–15) has narrow propagation in the magnetic field with only ~60° width of range in longitude compared to the other MLT sides. Compared with the case of the Norway station, the high-intensity regions are located around the southern part of the station at approximately latitude 45° N and longitude 34° W, although there is a similar transition in the propagation pattern between each MLT and the signals tend to propagate further on the nightside (MLT 21–3). If compared to the signals from Norway, the signals from on nightside show higher level of intensity (about 5 dB) in the electric field and about 5 dB in the magnetic field and were widely distributed. It also shows a lower level of intensity (approximately 5 dB) in the magnetic and electric fields and a narrower region on dayside. Fig. 7 a Propagation of the Omega signal from the station based on local time in the magnetic field and b in the electric field: the red arrow indicates the width of the map (~100°) with the station in the center (indicated by the rectangle)Full size image Seasonal variationIn this section, we demonstrate the results of seasonal variation of the Omega signal propagation. In the analyses, we separated the datasets obtained over eight years into four seasons approximately centered at the equinox and solstice of each year. The data range for each season is separated as follows: from February 1 to April 30 as “March equinox,” from May 1 to July 31 as “June solstice,” from August 1 to October 31 as “September equinox,” and from November 1 to January 31 as “December solstice. ”Figure 8 shows the spatial distribution of the Omega signals broadcast by the Norway station from October 1989 to September 1997. The upper four panels show magnetic intensity, and the lower four panels show electric intensity. As shown in Fig. 3, Omega signals tend to be refracted by the geomagnetic field lines and propagate from northern hemisphere to southern hemisphere. [SEP] Justify:

Output: The text is irrelevant to the claim as it primarily discusses the propagation of Omega signals and their intensity levels in different magnetic and electric fields, without addressing the topic of extraterrestrial signals being easily detected from Earth.


Input: Task: corroborate the claim using the given text. Claim: Many traditional medicines are derived from plants used by indigenous cultures. [SEP] Text: In: Forero E, Betancur J, editors. de Colombia, Bogotá DC, Colombia; 2009. p. 1‒462. . de la Amazonía Peruana. Perú: Instituto de Investigaciones de la Amazonía Peruana (IIAP), Iquitos, Peru; 1997. Cayón E, Aristizabal S. Etnobotánica Chamí. Cespedesia. 1980;9(33‒34):5‒114. Roig JT. Plantas medicinales de y su folclore. UC Rica, editor. San José, Costa Rica, 1988. p. 103‒104. Ayensu ES. of the West Indies. Algonac, Michigan, USA; 1981. p. 282. Díaz JL. Usos de las plantas medicinales de México. éxico; 1977. p. 345. Morton JF. Atlas of of Middle America: Bahamas to Yucatan. Thomas CC, 1980. p. 1448. Escobar N. Flora Tóxica de Panamá. U. Panamá, Panama. 1972. Figueroa H. Enfermedades de los conquistadores. Ibarra JdP, Antigua, Guatemala. 1983. Guzmán DJ. Especies útiles de la flora Salvadoreña. Md Educación, San Salvador, El Salvador. 1975. Barrett B. of Nicaragua’s Atlantic Coast. Economic Botany. 1994;48(1):8‒20. Agarwal K, Popli S. The constituents of Crescentia cujete leaves. Fitoterapia 1992;63(5):476. of the Popoluca, Mexico: A botanical systematical perspective. Economic Botany. 2003;57(2):218‒230. Isolation of cytotoxic metabolites from targeted peruvian amazonian medicinal plants. J Nat Prod. 2008;71(1):102‒105. . Leishmanicidal and trypanocidal activities of Bolivian medicinal plants. J Ethnopharmacol. 1994;41(1‒2):19‒37. Menachery MD. 1996. p. 269‒302. Boster JS. [SEP] Justify:

Output: The text corroborates the claim by discussing various medicinal plants utilized in different indigenous cultures across Latin America and their documented uses in traditional medicine. It indicates that knowledge about these plants has been compiled and studied, thereby supporting the claim that many traditional medicines are derived from plants used by indigenous cultures.


Input: Task: contrast the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: prediction of protein structure has been pursued intensely for decades, motivated largely by the goal of using structural models for drug discovery. Recently developed machine-learning methods such as AlphaFold 2 (AF2) have dramatically improved protein structure prediction, with reported accuracy approaching that of experimentally determined structures. To what extent do these advances translate to an ability to predict more accurately how drugs and drug candidates bind to their target proteins? Here, we carefully examine the utility of AF2 protein structure models for predicting binding poses of drug-like molecules at the largest class of drug targets, the G-protein-coupled receptors. We find that AF2 models capture binding pocket structures much more accurately than traditional homology models, with errors nearly as small as differences between structures of the same protein determined experimentally with different ligands bound. Strikingly, however, the accuracy of ligand-binding poses predicted by computational docking to AF2 models is not significantly higher than when docking to traditional homology models and is much lower than when docking to structures determined experimentally without these ligands bound. These results have important implications for all those who might use predicted protein structures for drug discovery. eLife assessment This important study presents findings with broad implications for the use of AlphaFold 2 models in ligand binding pose modeling, a common task in protein structure modeling. The computational experiments and analyses provide compelling results for the GPCR protein family data, but the conclusions are likely to apply also to other proteins and they will therefore be of interest to biophysicists, physical chemists, structural biologists, and anyone interested or involved in structure-based ligand discovery. Read the peer reviews About eLife assessments breakthroughs in machine learning have substantially improved the accuracy of protein structure prediction, to the point that some have declared the problem solved (Baek et al. , 2021; Jumper et al. , 2021; Ourmazd et al. , 2022). Indeed, in the most recent round of the of (CASP)—a blind protein structure prediction competition—AlphaFold 2 (AF2) demonstrated an unprecedented ability to predict protein structures with atomic accuracy, sometimes rivaling the accuracy of certain experimental methods for structure determination (Kryshtafovych et al. , 2021; Tejero et al. , 2022). These advances have generated tremendous excitement, focused in particular on their potential impact on drug discovery (Lowe, 2022; Thornton et al. [SEP] Justify:

Output: The text contrasts the claim by discussing the challenges in accurately predicting ligand-binding poses using machine-learning methods such as AlphaFold 2. While it acknowledges advances in protein structure prediction, it highlights that the accuracy of predicting how drugs bind to target proteins is not significantly higher than traditional methods. This suggests that while structural prediction has improved, accurately predicting protein function, specifically in drug binding, remains problematic.


Input: Task: pass the claim using the given text. Claim: Extraterrestrial signals can be easily detected from Earth. [SEP] Text: In order to evaluate their deviation and/or broadening from the geomagnetic field lines, we plotted the intensity map taking its vertical axis as invariant latitude (ILAT) of the observation point and the horizontal axis as geomagnetic longitude. The rectangle on the map indicates the location of the station. It was found that the high-intensity region deviated 10° to higher invariant latitude from the transmitter. Intensities in the high-intensity region were approximately −275 dBT for the magnetic field and approximately −117 dBV/m for the electric field. Intense signals were detected in a wider region in December solstice, while the high-intensity region became the smallest in June solstice. In addition, it is notable that the high-intensity region in the electric field was located only at 10° higher invariant latitude from the transmitter around the time of the June solstice. However, it gradually spread northward (higher latitude) in September equinox and became the widest in December solstice. The region shrunk southward again in March equinox. Fig. 8 a Seasonal propagation of the Omega signal from the Norway station in the magnetic field and b in the electric field based on invariant latitudeFull size image To understand the attenuation ratio between magnetic field and electric field based on the propagation distance from the Earth’s surface, we show the magnetic and electric intensity distributions along the magnetic field lines in Fig. 9a, b, respectively. The vertical axis indicates invariant latitude, and the horizontal axis indicates distance from the Earth’s surface along the magnetic field lines, with maximum range of 12,742 km. Small red lines indicate the latitude of the station location. Fig. 9 a Seasonal propagation of the Omega signal from the Norway station in the magnetic field and b in the electric field based on invariant latitude and the propagation distance from the Earth’s surfaceFull size image We clearly see that the magnetic intensity attenuated gradually as the propagation distance became larger, while the electric intensity did not attenuate much even in the middle at distance at ~5700 km. In addition, signals tend to propagate within the narrower invariant latitude region in June solstice, but they propagate in a wider invariant latitude region, especially toward the higher-latitude region in December solstice and March equinox. Figure 10 shows the spatial distribution of Omega signals broadcast by the station from October 1989 to September 1997. [SEP] Justify:

Output: The text discusses the evaluation of signal intensity and propagation with respect to geomagnetic fields, but does not directly address or support the claim that extraterrestrial signals can be easily detected from Earth. Instead, it focuses on the evaluation methods and seasonal patterns of signal intensity, making it largely irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: Log in or new issue alertsGet alerts Submit a your Email address: Subscribe to e4. 0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms. Research in 18(6):p 604-613, Nov–Dec 2023. | DOI: 10. 4103/1735-5362. 389948 and purpose: Pain and inflammation can be treated by various therapies that for the most part are not effective and can result in adverse effects. The current study was proposed to compare the antinociceptive and anti-inflammatory actions of curcumin and nano curcumin in rats. Experimental approach: Rats were randomly allocated into ten groups of six for formalin and tail-flick tests including the control group, curcumin and nano curcumin groups (20, 50, 100 mg/kg), morphine group (10 mg/kg), naloxone + 100 mg/kg curcumin group, and naloxone + 100 mg/kg nano curcumin group. There were nine groups for the carrageenan test. Groups 1-7 were the same as the previous division; groups 8 and 9 received 10 mg/kg diclofenac and 1% carrageenan, respectively. Findings/Results: All doses of nano curcumin significantly decreased the paw-licking time in both phases of the formalin test. In the tail-flick test, curcumin 100, nano curcumin 100, naloxone + curcumin 100, and naloxone + nano curcumin 100 showed significant analgesic effects compared to the control group. In the paw edema test, at 180 s after injection, curcumin (50 and 100 mg/kg) and all doses of nano curcumin significantly inhibited carrageenan-induced edema. Myeloperoxidase activity and lipid peroxidation decreased at doses of 50 and 100 mg/kg of curcumin but at three doses of nano curcumin (20, 50, and 100 mg/kg). Conclusion and implication: In conclusion, our results suggest that the nanoemulsion formulation of curcumin can be efficient in reducing pain and especially inflammation in lower doses compared to the native form of curcumin. [SEP] Justify:

Output: The text corroborates the claim by providing results from a study that demonstrates curcumin's effectiveness in reducing inflammation. Specifically, it states that 'curcumin significantly inhibited carrageenan-induced edema' and 'our results suggest that the nanoemulsion formulation of curcumin can be efficient in reducing pain and especially inflammation,' which supports the assertion that curcumin has anti-inflammatory properties.


Input: Task: contrast the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: Strikingly, binding pose prediction accuracy was similar when using AF2 models or traditional template-based models, despite the fact that binding pocket structures were substantially more accurate in AF2 models. Although the fraction of ligands docked correctly was slightly higher when using AF2 models (15%) than when using traditional models (9%), this difference was not statistically significant (p > 0. 5). On the other hand, binding pose prediction accuracy was far higher when docking to experimentally determined protein structures (44%), even though these structures were determined in complex with ligands different from those being docked. The docked poses analyzed above were determined with the widely used commercial docking software package Glide, run in SP mode (for ‘standard precision’) (Friesner et al. , 2004). To verify the robustness of our results, we repeated all docking experiments using a completely different docking software package—Rosetta docking (Park et al. , 2021)—as well as with Glide run in XP mode (for ‘extra precision’) (Friesner et al. , 2006). In both cases, we again found that, when used for ligand-binding pose prediction, AF2 models substantially underperformed experimentally determined structures and did not significantly outperform traditional models (Figure 2—figure supplement 2). In fact, the difference in binding pose prediction accuracy between AF2 models and traditional models was even smaller when using Rosetta docking or Glide XP than when using Glide SP. Closer look at discrepancy between structural accuracy and pose prediction accuracy The results of the previous two sections contrast sharply with one another. AF2 models nearly match experimentally determined structures—and are much better than traditional template-based models—in binding pocket accuracy, as measured by a standard structural metric. Yet AF2 models fare much worse than experimentally determined structures—do not significantly outperform traditional models—when used to predict ligand-binding poses. Figures 3 and 4 provide illustrative examples. Figure 3 with 1 supplement see all Download asset Open asset An example in which docking to an AlphaFold 2 (AF2) model yields poor results even though the model’s binding pocket has high structural accuracy. [SEP] Justify:

Output: The text contrasts the claim by discussing how AF2 models, despite their high accuracy in determining binding pocket structures, do not significantly outperform traditional models in predicting ligand-binding poses. This suggests that accurate structural properties do not necessarily correlate with accurate functional predictions, thereby undermining the claim that the properties of proteins can predict their functions accurately.


Input: Task: pass the claim using the given text. Claim: Extraterrestrial signals can be easily detected from Earth. [SEP] Text: The vertical axis indicates the invariant latitude (ILAT) of the observation point, and the horizontal axis indicates geomagnetic longitude. The rectangle on the map indicates the location of the station. We can also find that the high-intensity region of the propagation deviated ~ 10° to higher latitude from the transmitter, as in the Norway case (Fig. 8). Intensities in the high-intensity region were approximately −270 dBT for the magnetic field and approximately −115 dBV/m for the electric field. Compared with the Norway case shown in Fig. 8, however, it is obvious that the high-intensity region was almost constant throughout the year and was not widely distributed even in December solstice. Fig. 10 a Seasonal propagation of the Omega signal from the station in the magnetic field and b in the electric field based on invariant latitudeFull size image Figure 11a, b shows the magnetic and electric intensity distributions of the Omega signals broadcast by the station along the magnetic field lines. We also find that the Omega signals from tended to propagate along the ambient magnetic field lines within a limited, invariant latitude. We assume that this happened because of the different geographic latitudes even though the stations have the same geomagnetic latitude. That is, the Norway station was located at higher geographic latitude, and thus, Omega signals could propagate widely because of the longer night in December solstice. Fig. 11 a Seasonal propagation of the Omega signal from the station in the magnetic field and b in the electric field based on invariant latitude and the propagation distance from the Earth’s surfaceFull size image Annual variationFinally, we studied the annual variation of the propagation characteristics to evaluate the effects of solar activity. We separated the data and illustrated the results for each year. As shown in Fig. 1 and Table 1, there is no significant difference in the dataset coverage except for 1989, in which the available data were obtained for only three months. In addition, we selected the data measured at an altitude below 8200 km for the entire year, because the satellite’s altitude decreased every year and no data are available above that altitude in 1997. Figure 12 shows the statistical results of the Omega signal propagation pattern broadcast by the Norway station from October 1989 to September 1997 in geomagnetic coordinates. [SEP] Justify:

Output: The text discusses the propagation characteristics of Omega signals, including their intensity distributions and variations over time. It provides technical details about signal propagation near Earth's geomagnetic coordinates, but it does not directly address the claim regarding the detection of extraterrestrial signals from Earth. Therefore, the text is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: lifestyle of individuals around the world is meaningfully affected by pain and inflammation. Several treatments exist for the healing of pain and inflammation, but these treatments are not always successful and may result in experiencing adverse effects. Based on these facts, the identification of new compounds for healing pain and inflammation is an essential challenge in biomedical research (1,2). There are countless medicinal plants with possible analgesic activity, such as Artemisia herba-alba, Saliva hydrangea, Lavandula officinalis, Thymus vulgaris, Melissa officinalis, Menthe pulegium, Salvia sclarea, Moringa oleifera, Passiflora leschenaultia, Tamarindus indica Linn, Vaccinium ashei, etc. In addition to the use of new compounds, the use of strategies that can increase the effectiveness of the existing ones should also be considered. Among different strategies, using nano-sized carriers is a broadly used method to achieve acceptable bioavailability and suitable metabolism in therapeutic use (3,4). Curcumin (Curcuma longa) [1,7-bis (4-hydroxy-3-methoxyphenyl)-1,6-heptadiene-3,5-dione], also named diferuloylmethane (5), is a natural phenolic complex that can be extracted from turmeric roots (6). In recent years, a broad spectrum of exciting bioactivities has been known or attributed to curcumin, particularly antioxidant (7,8), antimicrobials (9), anticancer and antimutagenic (10) properties. This compound is bright orange-yellow thus it can be used as a food colorant (5). Recently, it has been established that most of the properties of Curcuma longa belong to curcumin with possible effects against allergies, Alzheimer's disease, diabetes, arthritis (11,12), and other chronic illnesses (13,14). Nevertheless, curcumin treatment in humans is confined by its great metabolic variability as well as low absorption and bioavailability (15). Some tactics have been adopted to increase oral bioavailability and solubility of curcumin (16,17). It has been shown that curcumin mixtures with nanop1396. 553). All the nociception tests were approved by the same visual observer. [SEP] Justify:

Output: The text corroborates the claim by mentioning that curcumin, which is extracted from turmeric, has been attributed with various bioactivities, including possible effects against arthritis, a condition characterized by inflammation. This suggests an anti-inflammatory property of curcumin as part of its broader bioactivity profile.


Input: Task: contrast the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: We predict the binding pose of the drug aprepitant to its target, the neurokinin-1 receptor (NK1R) given either the AF2 model (orange) of NK1R or the experimentally determined structure (blue, PDB entry 6E59) of NK1R bound to a different ligand, L760735. (A, B) The binding pocket of the AF2 model is more similar (lower root mean squared deviation [RMSD]) than the binding pocket of the L760735-bound structure to the binding pocket of the aprepitant-bound structure (the ‘reference structure’, white, PDB entry 6J20). Amino acid residues whose positions differ most from the reference structure are shown in sticks (see Methods). (C, D) The aprepitant binding pose predicted by docking is much less accurate (higher RMSD) when using the AF2 model than when using the L760735-bound structure. Ligand L76035 shares a scaffold with aprepitant; for completeness, we include another example with highly dissimilar ligands in Figure 3—figure supplement 1. We note that the experimentally determined L760735-bound structure is a low-resolution structure with suboptimal goodness of fit to experimental data; despite this, docking aprepipant to this structure yields an accurate pose. Figure 4 Download asset Open asset An example in which docking to a traditional template-based model yields better results than docking to an AlphaFold 2 (AF2) model, even though the AF2 model’s binding pocket has higher structural accuracy. We predict the binding pose of the psychedelic LSD to its primary target, the serotonin 2A receptor (5HT2A) given either the AF2 model (orange) or a traditional model (green) of 5HT2A. (A, B) The binding pocket of the AF2 model is more similar (lower root mean squared deviation [RMSD]) than that of the traditional model to the binding pocket of the experimentally determined LSD-bound structure (the ‘reference structure’, white, PDB entry 6WGT). Amino acid residues that differ most from the reference structure are shown in sticks. [SEP] Justify:

Output: The text contrasts the claim by illustrating that while the AF2 model shows greater structural similarity, it does not accurately predict binding poses as compared to the traditional models, indicating that the properties of proteins (as modeled by AF2) do not lead to accurate function predictions in all instances.


Input: Task: pass the claim using the given text. Claim: Extraterrestrial signals can be easily detected from Earth. [SEP] Text: The vertical axis indicates geomagnetic latitude, and horizontal axis indicates geomagnetic longitude within a range of 100° (±50° centered at the station), and nine panels corresponding to 1989–1997 are shown. The rectangle on the map indicates the location of the station. It was found that the intensity level was low between 1989 and 1992, while the average intensity level was higher, and the propagation region of the Omega signal was wider, from 1993 to 1997. Based on sunspot cycle data (NASA/Physics 2016; Usoskin 2008), the number of sunspots on the surface of the sun increased between 1989 and 1992 during the solar maximum period, while it decreased between 1993 and 1997 corresponding to the solar minimum period. We demonstrate that solar activity significantly affected the propagation and penetration of the Omega signal in the ionosphere. signal propagation intensity near the station during the solar maximum (1991) was approximately −280 dBT in the magnetic field and approximately −120 dBV/m in the electric field. During the solar minimum (1996), higher-intensity signals that propagated wider and farther from the transmitter station are apparent, approximately −270 dBT in the magnetic field and approximately −115 dBV/m in the electric field. Based on these maps, the coverage radius and intensity strength of the Omega signal that penetrated and propagated in the ionosphere changed by a few thousand kilometers every year. Fig. 12Annual propagation of the Omega signal from the Norway station in the magnetic field and b in the electric field. The red arrow indicates the width of the map (~100°) with location of the station in the center (indicated by the rectangle)Full size image Discussion and conclusionsWe studied the high–middle-latitude Omega stations located in Norway and and evaluated how widely and how far the Omega signals penetrated through the ionosphere over the station. Our analysis revealed that, for stations located at almost the same latitude in geomagnetic coordinates, the Omega signal propagated differently along the Earth’s magnetic field. Omega signals broadcast from both stations tended to propagate along the geomagnetic field lines and reached the opposite hemisphere. However, the signals from Norway propagated in the higher-latitude region compared to the ones from North Dakota. This phenomenon was a result of the stations being at different geographic coordinate latitudes: station was located at 56. 42° N and the station at 46. 37° N. [SEP] Justify:

Output: The text discusses the propagation and intensity levels of Omega signals in the ionosphere but does not address extraterrestrial signals or their detection from Earth. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: Rats were randomly allocated into ten groups of six for formalin and tail flick tests as follows: Group 1 received 10% DMSO with 90% normal saline solution by gavage (control group); group 2 received 20 mg/kg curcumin by gavage; group 3 received 50 mg/kg curcumin by gavage; group 4 received 100 mg/kg curcumin by gavage; group 5 received 20 mg/kg nano curcumin by gavagegroup 6 received 50 mg/kg nano curcumin by gavage; group 7 received 100 mg/kg nano curcumin by gavage; Group 8 received 10 mg/kg morphine intraperitoneally (IP); group 9 received 1 mg/kg naloxone IP, 30 min before being treated with 100 mg/kg curcumin; group 10 received 1 mg/kg naloxone IP, 30 min before being treated with 100 mg/kg nano curcumin. Rats were accidentally allocated into nine groups of six for the carrageenan test as follows: Group 1 received 10% DMSO with 90% normal saline solution by gavage (control group); group 2 was injected with 1% carrageenan; group 3 received 20 mg/kg curcumin by gavage 30 min before injection of 1% carrageenan; group 4 received 50 mg/kg curcumin by gavage 30 min before injection of 1% carrageenan; group 5 received 100 mg/kg curcumin by gavage 30 min before injection of 1% carrageenan; group 6 received 20 mg/kg nano curcumin by gavage 30 min before injection of 1% carrageenan; group 7 received 50 mg/kg nano curcumin by gavage 30 min before injection of 1% carrageenan; group 8 received 100 mg/kg nano curcumin by gavage 30 min before injection of 1% carrageenan; group 9 received 10 mg/kg diclofenac IP 30 min before injection of 1% carrageenan. Pharmacological tests Formalin test Based on a similar technique designed by Hunskaar and Hole (20), formalin was injected into the right hind paw of the rat (2. 5% in 0. 9% sterile saline; 50 μL/paw sub plantar) (21). [SEP] Justify:

Output: The text describes a series of experiments using curcumin on rats, where different doses of curcumin are administered prior to an injection of carrageenan—a known inflammatory agent. This setup indicates an investigation into the anti-inflammatory effects of curcumin, thus providing support for the claim that curcumin has anti-inflammatory properties.


Input: Task: contrast the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: (C, D) The LSD-binding pose predicted by docking is less accurate (higher RMSD) when using the AF2 model than when using the traditional model. To further quantify these results, we compare pose prediction accuracy for structures and models with similar binding pocket accuracy. In particular, we calculate pose prediction accuracy as a function of binding pocket accuracy (RMSD) for both experimentally determined structures and models. As expected, we find that average pose prediction accuracy increases as binding pocket accuracy increases (i. e. , RMSD to reference structure decreases). This trend holds for experimentally determined structures, AF2 models, and traditional template-based models (Figure 5 and Figure 5—figure supplement 1). Yet for the same binding pocket accuracy (RMSD from the reference structure), AF2 models yield lower average pose prediction accuracy than experimentally determined structures (Figure 3). In contrast, in cases where traditional models and experimentally determined structures have similar binding pocket accuracies, they yield similar pose prediction accuracies (Figure 5—figure supplement 1). Figure 5 with 1 supplement see all Download asset Open asset Pose prediction accuracy as a function of binding pocket structural accuracy when docking to AlphaFold 2 (AF2) models or experimentally determined structures. Docking to an experimentally determined structure generally leads to more accurate pose prediction than docking to an AF2 model with the same binding pocket root mean squared deviation (RMSD). The difference between the two curves is statistically significant for all binding pocket RMSD values below 1. 1 Å (see Methods). 5—figure supplement 1 for additional data, including results for traditional models and for various docking methods. We also considered the possibility that the improved performance of experimentally determined structures relative to AF2 models might be because, in some cases, the structure used for docking was determined with a bound ligand similar (though not identical) to the ligand being docked. Eliminating such cases from consideration does lead to decreases in both aggregate binding pocket accuracy and pose prediction accuracy of experimentally determined structures, but experimentally determined structures continue to yield significantly more accurate pose predictions than AF2 models (p < 0. 01) (Figure 1—figure supplement 1 and Figure 2—figure supplements 1 and 2). recent papers have concluded that AF2 models fall short of experimentally determined structures when used for ligand docking (Díaz-Rovira et al. , 2023; He et al. [SEP] Justify:

Output: The text contrasts the claim by discussing how the accuracy of pose prediction differs between the AF2 model and experimentally determined structures. The findings suggest that AF2 models yield lower average pose prediction accuracy compared to experimentally determined structures, indicating limitations in the predictive capabilities of the AF2 approach for protein functions. Therefore, it implies that properties inferred from these models do not match the level of accuracy claimed by some researchers.


Input: Task: pass the claim using the given text. Claim: Extraterrestrial signals can be easily detected from Earth. [SEP] Text: We suggest that effect of the attenuation ratio in the ionosphere worked differently because of this difference. According to the study by Clilverd et al. (2008), the VLF wave of higher L-shell (L > 1. 5) is highly ducted. We suggest that this fact might have affected the difference in propagation between Norway and North Dakota. However, we need to investigate further by examining the wave normal directions of Omega signals from both stations using the PFX data statistically. In the present study, we mainly focus on the magnetic and electric intensities in the northern hemisphere to evaluate how much the Omega signals penetrated through the ionosphere over the station. However, we also demonstrate that the signals tend to be refracted by magnetic field lines and propagate toward the opposite hemisphere. Further investigation of the conjugate region will be performed in future work. Next, we examined the transmittance of the Omega signals as a function of magnetic local time to evaluate the attenuation effect of the ionosphere and plasmasphere. We found that the Omega signal tended to propagate farther on the nightside, where the electron density in the ionosphere was lower, than on the dayside. This result is consistent with previous studies by Collier et al. (2006) and Oike et al. (2014), in which they studied the occurrence frequencies of whistlers. Collier et al. (2006) demonstrated that the detection frequency of whistlers on the ground was higher at night than at daytime. On the other hand, Oike et al. (2014) studied the whistlers detected in the plasmasphere and showed that the occurrence frequency was maximum after sunset. They suggested that this was caused by the combination of the frequency of occurrence of lightning and the attenuation effect of the ionosphere; that is, the occurrence frequency of lightning peaked in late afternoon but the attenuation ratio was smaller at night, so the detection peak on the spacecraft reached maximum after sunset. In the case of the ground measurement, it is necessary to penetrate the ionosphere twice, and thus, whistlers tend to be detected at night on the ground. In that sense, our statistical study is valuable for quantitatively evaluating the attenuation ratio of VLF waves in the ionosphere. [SEP] Justify:

Output: The text discusses the attenuation effects of the ionosphere on Omega signals but does not address the claim regarding the detection of extraterrestrial signals. It focuses on the technical aspects of signal propagation and attenuation rather than confirming or denying the ease of detecting extraterrestrial signals.


Input: Task: corroborate the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: Rats were spotted in the spaces with a mirror and the time spent licking and biting the injected site was considered as an indicator of pain. Reactions were evaluated five (first phase) and 15-30 min (second phase) after formalin administration (22). Curcumin, nano curcumin (20, 50, and 100 mg/kg, gavage), morphine (10 mg/kg, IP), naloxone + curcumin 100, and naloxone + nano curcumin 100 were given 1 h before formalin administration (N = 6 per group). Naloxone (1 mg/kg, IP), an opioid receptor antagonist, was injected 30 min before administration of the curcumin and nano curcumin (100 mg/kg) to evaluate the contribution of opioid receptors in the effect of the curcumin and nano curcumin. Tail flick test Tail-flick technique () was used to assess the antinociceptive reaction of curcumin and nano curcumin against thermal stimuli (23). Rats were accidentally allocated to ten groups of six. Each rat was located in a ventilated tube with the dorsal surface of the tail situated in the radiant thermal stimuli. The heating was applied to the distal part of the tail at 50 °C. The time of removing the tail in seconds was considered the response time, which was assessed automatically by a recorder joined to the equipment. A termination time of 7 s in each trial was regarded to diminish the possibility of skin damage. The tail-flick latency was evaluated before and 30, 60, and 90 min after administration of curcumin, nano curcumin (20, 50, and 100 mg/kg), and morphine (10 mg/kg, IP). Carrageenan-induced hind paw edema A paw edema model induced by carrageenan 1% (injection of 100 μL/animal into the sub-plantar section of the right hind paw of the rat) was used to study the anti-inflammatory effect of curcumin and nano curcumin (24). Rats were allocated to nine groups of six. Rats were pretreated with curcumin and nano curcumin (25, 50, and 100 mg/kg) and diclofenac 30 min before carrageenan injection. Plethysmometer apparatus (P. [SEP] Justify:

Output: The text corroborates the claim by describing an experimental setup where the anti-inflammatory effects of curcumin and nano curcumin are evaluated. It mentions a 'carrageenan-induced hind paw edema' model that is utilized to study the anti-inflammatory effects of curcumin, thus supporting the assertion that curcumin has anti-inflammatory properties.


Input: Task: contrast the claim using the given text. Claim: Certain researchers argue that the properties of proteins can predict their functions accurately. [SEP] Text: In this study, we did not limit the ligands docked to each structure or model to those that preferentially bind one specific activation state. We made this choice for several reasons: many other classes of drug targets do not have well-defined activation states; in practical applications, the preferred activation state for a given ligand may not be known when one docks it; and AF2 does not produce models in specific activation states by default. Third, we have not examined performance of the full range of available computational docking methods (Pagadala et al. , 2017). Our results are, however, consistent across the three docking methods we examined: and Rosetta docking. In each case, AF2 models yield docking accuracy similar to that of traditional models and substantially worse than that of experimentally determined structures. Our results have important implications for practitioners of structure-based drug discovery. Our findings suggest that, despite dramatic recent improvements in protein structure prediction, structural models (in particular, AF2 models) yield substantially poorer accuracy than experimentally determined structures in prediction of ligand-binding modes. Moreover, when a reasonable structural template is available—as is typically the case—AF2 models should not be expected to yield significantly better pose prediction accuracy than traditional models. Indeed, with sufficient effort, an expert may well be able to build a traditional template-based model that yields better performance than an AF2 model. Despite these findings, we believe that AF2 and other recently developed protein structure prediction methods will prove valuable in certain structure-based drug discovery efforts. Up-to-date AF2 models for any human protein are readily available for download (Tunyasuvunakool et al. , 2021; Varadi et al. , 2022). In contrast, expertise is required to build a decent template-based model, and up-to-date, downloadable repositories of such models are not available for all drug targets. Also, in the relatively rare cases when no structural template is available for a drug target, approaches like AF2 may be the only realistic option short of solving a structure experimentally. Our results also point to opportunities for developing improved computational modeling methods. Existing deep-learning methods for protein structure prediction were developed with the aim of maximizing structural accuracy for models. We find that the RMSD of a model—a classic structural accuracy metric—is not a good predictor of the accuracy that model yields for pose prediction. [SEP] Justify:

Output: The text contrasts the claim by stating that the AF2 models, which are part of protein structure prediction methods, yield substantially poorer accuracy than experimentally determined structures in predicting ligand-binding modes. This suggests that while researchers may hope for accurate predictions based on protein properties, the findings indicate significant limitations in current predictive models, specifically AF2, highlighting that traditional methods may outperform these new techniques.


Input: Task: pass the claim using the given text. Claim: Extraterrestrial signals can be easily detected from Earth. [SEP] Text: As for the propagation characteristics in the plasmasphere, we showed that the signal intensity in the magnetic field gradually decreased along the propagation path, while the attenuation ratio in electric field was lower; the signals could propagate more widely and farther (to the other hemisphere) from the original transmission station. We also studied the seasonal variation of Omega signals to evaluate the trend of propagation characteristics. We found that intense signals from the Norway station were detected in a wider region in December solstice, while the high-intensity region became the smallest in June solstice. However, the signals from were not widely distributed and tended to propagate in a narrower region along the ambient magnetic field. This is probably because the Norway station was located at higher geographic latitude, and thus, the night was longer than at the station during the December solstice. Thus, the signals from the Norway station were not attenuated at that time and propagated widely in the higher-latitude region. Finally, we studied the annual variation of the propagation characteristics of the Omega signals to evaluate the effects of solar activity. We found that in 1991, when solar activity was at a maximum, the Omega signal propagated at a lower intensity. In contrast, when solar activity was at minimum in 1996, the Omega signal propagated at a higher intensity and reached farther from the transmitter station. We assumed that plasmaspheric electron density and temperature affected the propagation of the Omega signal. As described in the introduction, quantitative study of Omega signals using eight years of PFX data from October 1989 to September 1997 is quite important to evaluate the attenuation ratio of VLF waves propagating in the ionosphere and plasmasphere as a function of magnetic local time, season, and annual solar activity. In the future, extensive studies of the delay time and wave normal direction are necessary to quantitatively clarify the global features of the ionosphere and plasmasphere. AbbreviationsIC: integrated circuit CDF: common data format PFX: Poynting flux analyzer VLF: very low frequency WIDA: wide dynamic range amplifier MLT: magnetic local time 1682. doi:10. 1029/JZ068i006p01675 3086. doi:10. 1002/jgra. 50274 4211. doi:10. 1029/2007JA012602 1060. doi:10. 1029/2002RS002603 996. doi:10. [SEP] Justify:

Output: The text discusses the propagation characteristics of signals, particularly Omega signals, in the Earth's atmosphere and does not directly address whether extraterrestrial signals can be easily detected from Earth. It explores factors like signal intensity, seasonal variations, and the impact of solar activity on signal propagation, which are somewhat tangential to the claim. Therefore, the text is not relevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: test The duration of pain reaction in the early stage (0-5 min) was meaningfully diminished in nano curcumin (20, 50, and 100 mg/kg), naloxone + curcumin 100, naloxone + nano curcumin 100, and morphine-treated groups in comparison with the control group. The duration of pain reaction in the late stage (15-30 min), was meaningfully declined by two doses of curcumin (50 and 100), and three doses of nano curcumin (20, 50, and 100 mg/kg), naloxone + curcumin 100, naloxone + nano curcumin 100 and morphine compared to the control group. Moreover, nano curcumin at two doses (50 and 100 mg/kg) was meaningfully better than curcumin (Fig. 1). Fig. 1. : Comparative graphical representation of analgesic effects of curcumin (20, 50, and 100 mg/kg), nano curcumin (20, 50, and 100 mg/kg), and morphine in formalin-induced paws licking test. Reactions were evaluated after (A) 5 min (first phase) and (B) 15-30 min (second phase) after formalin administration. Each point represents the mean ± SEM. * P < 0. 05, ** P < 0. 01, and *** P < 0. 001 indicate significant differences compared to the control group; $$ P < 0. 01 and $$$ P < 0. 001 comparisons between curcumin and nano curcumin at the same dose. Tail flick test Curcumin 100, nano curcumin 100, naloxone + curcumin 100, and naloxone + nano curcumin 100 showed significant analgesic effects (prolongation of the reaction time) compared to the control group. Curcumin and nano curcumin (20 and 50 mg/kg) displayed non-significant results as compared with the control group, whereas morphine showed significant analgesic effects as compared to the control group) (Fig. 2). Fig. 2. : Comparative graphical representation of analgesic effects of curcumin (20, 50, and 100 mg/kg), nano curcumin (20, 50, and 100 mg/kg), and morphine in tail flick test. Each point represents the mean ± SEM. * P < 0. [SEP] Justify:

Output: The text supports the claim as it describes experiments that demonstrate the analgesic effects of curcumin, indicating its potential anti-inflammatory properties. It mentions that curcumin significantly reduced the duration of pain reaction in various test groups compared to the control group, providing evidence for its effectiveness in alleviating pain, which relates to its anti-inflammatory qualities.


Input: Task: contrast the claim using the given text. Claim: Some argue that all GMOs are entirely safe and have no ecological impact. [SEP] Text: Введение Прошло более 30 лет с тех пор как людьми были получены первые трансгенные растения (Herrera-Estrella et al. , 1983; et al. , 1984). Однако с появлением первых коммерческих линий ГМО встал вопрос об их экологической безопасности. Ситуация усложняется тем, что площади посевов, занятые ГМ культурами неуклонно растут, а подавляющее большинство трансгенных линий растений являются устойчивыми к гербицидам и/или насекомым (ISAAA, 2012). [SEP] Justify:

Output: The text contrasts the claim by raising concerns about the ecological safety of GMOs, indicating that the area cultivated with GM crops is steadily increasing and that the majority of transgenic plant lines are resistant to herbicides and/or insects. This suggests potential ecological impacts that contradict the assertion that all GMOs are entirely safe.


Input: Task: pass the claim using the given text. Claim: Extraterrestrial signals can be easily detected from Earth. [SEP] Text: 1186/BF03351796 2201. doi:10. 1029/2008JA013467 34. doi:10. 1051/swsc/2014030 1. Information Service, Springfield, p 434 764. doi:10. 1002/2014RS005523 74. doi:10. 14569/. 2016. 071009 1. 4 and 3. 2 deduced from whistlers. J Phys 50(7):07–611. doi:10. 1016/0021-9169(88)90058-X 10. 12942/lrsp-2008-3 2079. doi:10. 1002/2015JA022010 4. 0 ( which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the license, and indicate if changes were made. Reprints and permissionsAbout this 10. 1186/s40623-017-0684-5Download citationReceived: 17 February 2017Accepted: 14 July 2017Published: 25 July 2017DOI: this 3. Space science Language editing for authors Scientific editing for authors Leave feedback Terms and conditions Privacy statement page Springerpage By using this website, you agree to our Terms and Conditions, Your US state privacy rights, Privacy statement and Cookies policy. Your privacy choices/Manage cookies we use in the preference centre. © 2024 BioLtd unless otherwise stated. Part of Springer Nature. [SEP] Justify:

Output: The text is irrelevant to the claim regarding the detection of extraterrestrial signals from Earth. It consists mainly of references, DOIs, and publication information without any discussion on the topic of extraterrestrial signals or their detection.


Input: Task: corroborate the claim using the given text. Claim: Curcumin, found in turmeric, has anti-inflammatory properties. [SEP] Text: 05, ** P < 0. 01, and *** P < 0. 001 indicate significant differences compared to the control group. Carrageenan-induced hind paw edema was applied as an edema inductor (Fig. 3), after 60 min, curcumin (100 mg/kg) and nano curcumin (50 and 100 mg/kg) significantly inhibited carrageenan-induced edema compared to the carrageenan group. Also, at 180 min after injection, curcumin (50 and 100 mg/kg) and nano curcumin (20, 50, and 100 mg/kg) significantly inhibited carrageenan-induced edema compared to the carrageenan group. However, at 120 min after injection, no significant effect was observed. In addition, the control drug, diclofenac, showed significant inhibition of edema volume over 3 h. Fig. 3. : Comparative graphical representation of anti-inflammatory effects of curcumin (20, 50, and 100 mg/kg), nano curcumin (20, 50, and 100 mg/kg), and diclofenac in carrageenan-induced paw edema test. Each point represents the mean ± SEM. * P < 0. 05, ** P < 0. 01, and *** P < 0. 001 indicate significant differences compared to the carrageenan group. activity is indicative of the polymorphonuclear leukocyte recruitment in the organ following any damage. MPO activity was meaningfully higher in the carrageenan-treated group as compared to the control group. Curcumin decreased the MPO activity at doses of 50 and 100 mg/kg but nano curcumin reduced the MPO activity at three doses (20, 50, and 100 mg/kg) in comparison with the carrageenan (Fig. 4). Fig. 4. : Comparative graphical representation of curcumin (20, 50, and 100 mg/kg), nano curcumin (20, 50, and 100 mg/kg), carrageenan, and diclofenac on MPO test. Each point represents the mean ± SEM level. ### P < 0. 001 indicate a significant difference compared to the control group; * P < 0. 05, and *** P < 0. 001 compared to the carrageenan group; $ P < 0. [SEP] Justify:

Output: The text supports the claim by providing evidence of the anti-inflammatory effects of curcumin as demonstrated through the inhibition of carrageenan-induced edema. It specifies that both curcumin and nano curcumin significantly inhibited edema compared to the control group, which suggests their anti-inflammatory properties.


Input: Task: contrast the claim using the given text. Claim: Some argue that all GMOs are entirely safe and have no ecological impact. [SEP] Text: В литературе появляется все больше работ связанных с исследованием экологических рисков ГМ-растений. Суммируя данные исследования (on Trials, 2008; Dunfield, Germida,. [SEP] Justify:

Output: The text contrasts the claim by indicating that there are increasing works in literature that involve research into the ecological risks of GM plants, which suggests that there are potential concerns about their safety and ecology.


Input: Task: pass the claim using the given text. Claim: Extraterrestrial signals can be easily detected from Earth. [SEP] Text: AbstractThe global terrestrial water storage (TWS), the most accessible component in the hydrological cycle, is a general indicator of freshwater availability on Earth. The global TWS trend caused by climate change is harder to detect than global mean temperature due to the highly uneven hydrological responses across the globe, the brevity of global freshwater observations, and large noises of internal climate variability. To overcome the climate noise and small sample size of observations, we leverage the vast amount of observed and simulated meteorological fields at daily scales to project global TWS through its fingerprints in weather patterns. The novel method identifies the relationship between annual global mean TWS and daily surface air temperature and humidity fields using multi-model hydrological simulations. We found that globally, approximately 50% of days for most years since 2016 have climate change signals emerged above the noise of internal variability. Climate change signals in global mean TWS have been consistently increasing over the last few decades, and in the future, are expected to emerge from the natural climate variability. Our research indicates the urgency to limit carbon emission to not only avoid risks associated with warming but also sustain water security in the future. Similar content being viewed by others Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation 2. In regions experiencing frequent water scarcity, TWS often provides the last critical buffer against extreme droughts through natural water storage systems such as underground aquifers, glaciers, and wetlands. TWS also regulates Earth’s energy budget, affects biogeochemical cycles, maintains freshwater ecosystems, and enables socioeconomic development3. The global TWS is affected by climate change and exacerbated by multi-faceted human activities. Climate change impacts TWS because it accelerates the hydrological cycle through enhancing evapotranspiration and altering precipitation patterns across the globe. The climate-induced variations in the global TWS pose multiple risks to human and natural systems worldwide, in particular in the vulnerable regions where changes in the hydrological cycle on people and ecosystems are observed4. On the other hand, human activities, such as the impoundment of fresh water in reservoirs and groundwater mining, exacerbate the TWS variations in time and space as these activities contribute to changes in water and energy budgets which are tightly coupled through changes in phase. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses global terrestrial water storage and its relation to climate change, with no mention of extraterrestrial signals or their detection from Earth.