Graphene, owing to its inherent chemical inertness, biocompatibility, and mechanical flexibility, has great potential in guiding cell behaviors such as adhesion and differentiation. However, due to the two-dimensional (2D) nature of graphene, the microfabrication of graphene into micro/nanoscale patterns has been widely adopted for guiding cellular assembly. In this study, we report crumpled graphene, i.e., monolithically defined graphene with a nanoscale wavy surface texture, as a tissue engineering platform that can efficiently promote aligned C2C12 mouse myoblast cell differentiation. We imparted out-of-plane, nanoscale crumpled morphologies to flat graphene via compressive strain-induced deformation. When C2C12 mouse myoblast cells were seeded on the uniaxially crumpled graphene, not only were the alignment and elongation promoted at a single-cell level but also the differentiation and maturation of myotubes were enhanced compared to that on flat graphene. These results demonstrate the utility of the crumpled graphene platform for tissue engineering and regenerative medicine for skeletal muscle tissues. A technique that introduces instabilities onto normally flat graphene can enhance the engineering of muscle fibers. Researchers have recently found that applying cyclic electric stimuli to conductive graphene films promotes the growth of tubular myoblast cells that comprise muscle tissue. SungWoo Nam at the University of Illinois at Urbana-Champaign in the United States and colleagues have now developed a ‘crumpled’ form of graphene to further control the morphology of myoblasts. The team transferred graphene film onto a pre-stretched elastomeric tape, and then gradually released the tape’s tension. Microscopy revealed graphene’s transformation into an accordion-like surface featuring nanoscale ridges and valleys. Comparisons with flat graphene showed the new material improved the assembly of myoblasts into longer myotubes by promoting growth along the direction of the crumpled valleys. For example, skeletal muscles have longitudinally aligned myofibrils presenting directional contractile functions in response to stimuli2. Ligaments and tendons have unidirectionally aligned collagen fibers and thus absorb sudden mechanical forces by the shearing mechanism of the protein matrix3. In addition to those muscular tissues, the hippocampus in brain tissue has directionally sprouting neuronal networks, allowing a unidirectional signal transfer through the CA1-CA3 neural circuit4. Because geometrical directionality has a close relationship with function, the recapitulation of anisotropic orientation has been conceived as a key factor in the fabrication of in vitro tissue models6. One simple yet robust method is the fabrication of anisotropic structures and the seeding of tissue-specific cells on top of tissue scaffolds. Using this method, cells recognize the orientation and surface materials of the underlying substrates and adapt their behaviors based on physicochemical cues. To prepare directional micro/nanostructures, various microfabrication methods, such as photolithography, soft lithography, and electrospinning, have been developed9.Native human tissues possess inherent anatomical directionality, and such directionality endows tissue-specific functions12. Even in the absence of electrical stimuli, simply cultivating C2C12 mouse myoblast cells and neurons on conductive materials enhances differentiation13. These results clearly show the importance of the electrically conductive nature of the matrix in the development of electrically active tissue models. In this regard, graphene has substantial potential in the recapitulation of physiological electrical properties because it is a very thin material with high electrical conductivity14. Furthermore, graphene shows promise in the regulation of cell functions, such as promoting cell adhesion and enhancing stem cell differentiation17 because the adhesion of growth factors on a graphene film is promoted by interactions with π–π stacking18 and enhanced graphene-plasma membrane interaction, which regulates downstream cell signaling pathways19.In the fabrication of in vitro tissue models, the material properties are also an important issue. Skeletal muscle, heart, and brain tissues have electrical stimuli-responsive characteristics. The introduction of cyclic electrical stimuli during the culture period can promote the differentiation and functional maturation of C2C12 mouse myoblast cells20. As a different approach, a suspended graphene sheet was fabricated by transferring a graphene film on top of engineered nanogrooves21. On the graphene film, human mesenchymal stem cells showed an aligned morphology due to the nanogrooves beneath the graphene film, and the morphology promoted neurogenic and osteogenic differentiation. The transfer printing of graphene oxide flakes on the substrate allowed the fabrication of strip and grid graphene oxide patterns and demonstrated the graphene-specific adhesion and controlled differentiation of adipose-derived stem cells on the graphene patterned substrates22. A graphene-nanofiber hybrid scaffold created by electrospinning polycaprolactone nanofibers on a graphene oxide film was used to explore the potential of this material in oligodendrocyte differentiation23. Micrometer-scale graphene oxide wrinkles fabricated by an unconventional fabrication method were shown to be useful in their system in guiding cell alignment24. A microgroove-patterned methacrylated gelatin substrate showed enhanced differentiation capabilities compared to a nonpatterned methacrylated gelatin substrate25. Moreover, recent research has demonstrated that conductive three-dimensional graphene foam bioscaffolds improve the growth and differentiation of C2C12 myoblasts into functional myotubes26. Although previous approaches showed the potential of graphene-based tissue engineering platforms, they usually adapted complex and multistep fabrication techniques for topographically patterned graphene substrates. To utilize novel material properties in tissue engineering applications, a simpler yet robust fabrication method is required.To utilize the characteristics and topographical effect of graphene in tissue engineering, a variety of approaches have been introduced. As a straightforward approach, rectangular graphene patterns with a large area of 150 × 1500 μm were fabricated using standard photolithography methods, and myogenic differentiation of C2C12 mouse myoblast cells was demonstrated on the patternsIn this study, we report a tissue engineering platform that can utilize the topographical features and material properties of graphene by inducing mechanical instability in a graphene film. For this purpose, we transferred graphene onto a prestretched elastomer film and subsequently released the stretch so that the film could spontaneously form anisotropic geometrical features via wrinkling phenomena. We then cultured C2C12 mouse myoblast cells on the crumpled graphene and observed myotube formation and maturation in response to the anisotropic geometrical features. On the crumpled graphene substrate, C2C12 myoblasts showed a highly aligned morphology following the wrinkled structures and exhibited enhanced myotube formation compared to those on the flat graphene substrate.x-direction and y-direction depending on the orientation to induce anisotropic mechanical instability. The major axis was stretched by 150–300%, while the minor axis was stretched by 50% , whereas the amplitude (displayed as the root mean square (RMS) height) increased in response to increased prestrain   intensity remained constant as the prestrain increased -grown graphene onto a prestretched elastomeric substrate (VHB tape) using a polydimethylsiloxane (PDMS) block as a temporary stamp. The stretchable substrate was prestretched by different amounts in the 50% Fig. . We applly) Fig.  and S2. ly) Fig. . Raman ssed Fig. . Further32, showing contact guidance in response to the underlying surface topography.To demonstrate the utility of crumpled graphene in skeletal muscle tissue engineering, C2C12 mouse myoblast cells were seeded on various crumpled graphene platforms Fig. . Here, tp-value indicates that the angular distribution is significantly different from the ‘uniform’ distribution, with given statistical reliabilities corresponding to the p-values33. In the 150 and 300% prestrain cases, p-values smaller than 0.01 indicate a significantly different distribution of angle values from the uniform distribution. The Mardia–Watson–Wheeler test was further used to confirm the equality of the two angular populations34. A sufficiently small p-value indicates that the angular populations of two data sets are significantly different with p-value-specific statistical reliabilities. The Mardia–Watson–Wheeler test between the data sets, such as flat:150% and flat:300%, showed significantly small p-values, indicating a significant difference between the cases in terms of the angular populations. These statistical analysis results consistently showed the utility of the anisotropically crumpled graphene platform for the unidirectional alignment of C2C12 cells.To compare the differences in those cell alignment behaviors, we conducted a statistical analysis Table . The cir36. In this regard, the higher amplitude in the case of 300% prestrain is more beneficial than that for 150% prestrain, and thus, cell alignment and elongation were promoted in the 300% prestrain case.The morphological indices, including the cell length, cell width, and aspect ratio, were different depending on the various platforms Fig. . For exap < 0.01). The Mardia–Watson–Wheeler test demonstrated significant differences between the angular populations on various samples, such as flat:150% and flat:300% (p < 1e−12). The morphological indices of myotubes were also quantified. The length, width, and aspect ratio of myotubes were larger in the case of the crumpled graphene substrates than the flat substrates . These four indices were higher for crumpled graphene substrates (150 and 300%) than for flat substrates. Similar to the results of the morphological indices of the myotubes, there were no significant differences in those four indices between the 150 and 300% prestrain cases. According to previous studies, neither too large (>20 μm)37 nor too small (<70–80 nm)29 size patterns affect myotube fusion, implying the limited effect of feature size control over C2C12 differentiation.The myogenic differentiation efficiency was evaluated with the fusion index, maturation index, myotube fraction, and myotube density Fig. . The fus38, such stiffness-dependent elongation was not observed in our study, presumably because of the small difference in stiffness.To examine the change in stiffness with respect to the applied prestrain and ultimately to the cultured cell behaviors on the crumpled graphene substrates, we measured the elastic modulus of the crumpled graphene using a nanoindenter Fig. . As the From the quantification, we found that at the single C2C12 mouse myoblast cell level, crumpled graphene with a uniaxial topography increases the cell length while decreasing the width. Furthermore, as the prestrain increases from 150 to 300%, the length and aspect ratio of the individual cells tend to increase due to the increased height of the surface texture. However, after myotube formation , such morphological differences between the 150 and 300% prestrain samples decreased.40. As reported in previous studies41, an ultrathin membrane of a rigid material has a quite limited effect on the overall mechanical properties when layered on a soft substrate. Therefore, we believe that the similarities in the mechanical properties of VHB and graphene on VHB resulted in marginal differences in the morphological indices of C2C12 mouse myoblast cells before and after differentiation.Furthermore, C2C12 mouse myoblast cells and differentiated myotubes on bare VHB and flat graphene on VHB Figs.  do not s31. However, in this study, we fabricated a nanoscale  topography using a CVD-grown monolayer graphene. Although, as shown in Fig. 29 support that the imperfections of crumpled graphene have a negligible effect on cell behaviors. The micron-scale topography is known to have the ability to align cells towards a topographical orientation but not to effectively guide cell differentiation because the feature size is much larger than that of focal adhesions42. Conversely, the nanoscale topography can control both alignment and differentiation because the sizes of the features and focal adhesions are comparable43. Second, although previous studies reported the superior properties of graphene in the myogenic differentiation of C2C12 cells20, the synergistic role of the surface topography and the material properties of graphene have not been clearly demonstrated.Our crumpled graphene platform is a significant departure from previous approaches for the following reasons. First, the geometrical size (wavelength and amplitude) of our platform is much smaller than that of the platforms used in previous studies, and our platform thus can stimulate cell behaviors and functions more precisely. For example, previous studies fabricated wrinkled graphene oxide films with a wavelength and amplitude of a few micrometers to a few tens of micrometers due to the thick graphene oxide film44. Such morphology-controlled cell behaviors are also commonly observed in other cell types, such as immune cells and human mesenchymal stem cells46. Therefore, we believe, although further in-depth studies are needed, that the morphology control can control the differentiation and maturation of mouse myotube cells. As reported in previous studies, culturing mouse myoblast cells  on a nanotopography upregulates multiple genes related to myogenic differentiation, such as Myf5, MyoD, and MyoG. The enhanced gene expression of myogenic differentiation was evident irrespective of the surface characteristics, including the gelatin-coated poly(lactic-coglycolic acid) (PLGA)6, sphingosine-1-phosphate-conjugated PLGA47, and gold-coated polyurethane acrylate (PUA) substrates13. In addition, microgroove patterns also upregulated the expression levels of focal adhesion-related, actin cytoskeleton-related, and MAPK signaling-related genes48. Furthermore, on multiscale micro-patterns and nano-patterns, aligned nanofibers on top of microgrooves with orientations perpendicular to each other, C2C12 cells preferentially aligned following the nanofibers rather than the microgrooves49. These results indicate, at least in adhesion and alignment aspects, C2C12 cells prefer nanoscale patterns over microscale patterns. Based on these earlier findings, future investigations on the upregulation of various myogenic genes induced by the crumpled graphene substrate will provide further evidence of the impact of the crumpled topography on myogenic differentiation. The observation of cross-striation will also provide evidence of myotube maturation. In addition to gene expression, the effect of extracellular matrix components on differentiation and subsequent production by the cells can be studied in the future. Previous researchers reported that the laminin protein significantly promotes cell adhesion and differentiation of C2C12 cells51. Furthermore, we expect that these electrically active, nanotopographic crumpled graphene substrates can electrically stimulate cells. According to previous studies, consistent electrical stimulation can enhance the differentiation and maturation of skeletal muscle cells54. Although, in this work, there was no significant difference in the experimental results between ‘bare’ and ‘flat’ substrates due to the absence of electrical stimulation and the similarity of the elastic moduli  foil  by a chemical vapor deposition (CVD) system . Under a hydrogen (H2) gas environment (50 sccm) at 150 mTorr, the chamber was heated to 1050 °C. After annealing at 1050 °C for 2 h, methane (CH4) and H2 gases (CH4: 100 sccm and H2: 50 sccm) were introduced into the chamber at 520 mTorr for 2 min. Then, the chamber was cooled down to room temperature slowly under an argon (Ar) gas environment (500 sccm) at 330 mTorr. After the synthesis of graphene, a polydimethylsiloxane (PDMS) block was attached on the graphene side of the Cu foil, and then Cu was etched with 1 M FeCl3 solution. For a flexible substrate, a very high bond (VHB) substrate  was used. After stretching the VHB substrate in biaxial directions, with a larger prestrain applied to one direction  to induce uniaxial deformation, the graphene on the PDMS block was transferred onto the stretched VHB substrate. Due to the mechanical limitation of the VHB substrate, the stretching of the VHB substrate was controlled to be less than 400%. After transfer, the stretched VHB substrate was released, and the crumpled graphene structure was obtained. The surface structure of the crumpled graphene was monitored with a scanning electron microscope  and an atomic force microscope , and the integrities of the crumpled graphene at various tensile strain conditions between 0 and 300% were evaluated with a Raman spectroscope  using a 633 nm wavelength laser. Nanoindentation was carried out with the same AFM system used for imaging.The crumpled graphene structure was fabricated by modifying the protocols of previous studiesεxpre, : 300 and 150%) and a flat graphene substrate (50% prestrain). The prepared substrates were sterilized with alcohol and ultraviolet (UV) light. Then, mouse skeletal myoblast C2C12 cells were seeded at a density of 5000 cells/cm2 on sterilized graphene/VHB substrates. The cells were maintained in growth media  in a humidified atmosphere with 5% CO2 at 37 °C. The GM was replaced every 24 h. After 3 days of cell culture, the morphology and angular orientation data of the cells were analyzed using cytoskeleton staining. The cells were fixed with 4% paraformaldehyde, permeabilized with 0.1% Triton X-100, and stained with TRITC-phalloidin  and DAPI . The actin filaments and nuclei were observed using a fluorescence microscope . From the obtained fluorescence images, cell width, length, aspect ratio, and angular orientation data were analyzed with ImageJ software. We analyzed 5 different samples from four kinds of cell substrates and monitored over 100 cells from each sample. We conducted Rao’s spacing test to evaluate the uniform distribution of angular orientation data of cells and the Mardia–Watson–Wheeler test to evaluate the identical distribution of the angular orientation data of cells.Three types of cell substrates were prepared: two crumpled graphene substrates  and a flat graphene substrate were prepared and sterilized with alcohol and UV. Mouse skeletal myoblast C2C12 cells were seeded at a density of 5000 cells/cm2 on sterilized graphene/VHB substrates. The seeded cells were grown in GM at 37 °C and 5% CO2. GM was replaced every 24 h. When the cells covered 80% of the substrate, GM was replaced with differential media . The cells were incubated at 37 °C and 5% CO2, and the DM was replaced every 12 h. After 7 days of differentiation, cells were fixed, permeabilized and blocked with 4% paraformaldehyde, 0.1% Triton X-100 and 1% bovine serum albumin. For immunostaining, cells were incubated with the primary antibody MF20 (anti-myosin heavy chain (MHC)), Developmental Studies Hybridoma Bank ((DSHB), University of Iowa) overnight at 4 °C, followed by incubation with the secondary antibody (fluorescein isothiocyanate (FITC)-conjugated goat anti-mouse IgG, Thermo Fisher Scientific) and DAPI (Thermo Fisher Scientific) for 2 h at 37 °C. Myotube formation and alignment were observed using a fluorescence microscope  and analyzed with ImageJ software. We analyzed 5 different samples from four kinds of cell substrates and monitored over 100 myotubes from each sample. To evaluate the uniform distribution and identical distribution of myotube alignment data, Rao’s spacing and Mardia–Watson–Wheeler tests were conducted. To evaluate the myogenic differentiation efficiency, we analyzed the fusion index (the ratio of the nuclei number in myocytes with two or more nuclei), maturation index (the percentage of myotubes having five or more nuclei), myotube area fraction and cell density from each sample.Two types of crumpled graphene substrates (p-values smaller than 0.05 were considered to be significant.All of the quantitative data are expressed as the mean ± standard error of the mean. Statistical analysis was performed by means of one-way analysis of variance. For the determination of statistical significance, Supplementary Information


Saline soil is one of the most crucial problems of arid and semiarid regions because it reduces growth of plant and microorganisms. In Thailand, the inland saline soils are found mostly in the northeastern part especially in Maha Sarakham Province where 85% of the province has geological characteristics as rock salt beds. Saline soil often experiences low soil fertility problems which multiply the adverse effects on plant growth. Interestingly, the Na Si Nuan Secondary Forest, Kantharawichai District, Maha Sarakham, is not affected by salinity although almost the entire province of Maha Sarakham is salt-affected area. Saline soil is a habitat of halophilic bacteria. Bacteria are the most important microorganisms contribute to soil fertility and soil health. Thus data regarding the density of culturable halophilic bacteria and soil properties in this forest soil is useful for reclamation of saline soil and helping to sustain the forest ecosystem. Main physical and chemical properties of soil collected in three seasons  from Na Si Nuan Secondary Forest, Kantharawichai District, Maha Sarakham Province, Thailand, are summarized in The density of non-, slightly-, and moderately halophilic bacteria of soil collected in three seasons from the study site are summarized in 22.1The sampling area, Na Si Nuan Secondary Forest at Maha Sarakham Province, Thailand, is situated between latitude 16°20′N and longitude 103°12′E with a total area of approximately 19.2 ha. The sampling sites were divided into 14 plots .Fig. 1Ma2.2Soil samples were collected seasonally during June 2017 to March 2018. The samples were randomly taken from three subplots for each sampling site at a depth of 30 cm using a hand auger. Samples from the same sampling site were mixed thoroughly to obtain the composite sample. Then a portion (one kilogram) of the composite soil samples was collected and stored at 4 °C for further examination.2.2.1The pH, electrical conductivity (EC), soil texture class, organic matter, total nitrogen, available phosphorus and available potassium of the soil samples were determined seasonally. Details of the methods of physical and chemical analysis are given elsewhere on Page et al. ,5 and Di2.2.2−1) were used for enumeration of non-, slightly-, and moderately halophilic bacteria, respectively. The NaCl concentrations used were chosen from the level of salt requirements for the growth of each group of halophilic bacteria [−1 of dry soil. Different colonies grown on media were selected and purified for further characterization.The number of non-, slightly-, and moderately halophilic bacteria in soil samples were enumerated using a spread plate technique. The halobacteria medium  containibacteria . After i2.2.3The values of soil physical and chemical properties and density of halophilic bacteria of each plot were averaged from its subplots. Data obtained from three seasons were compared by one-way analysis of variance (ANOVA) and the significance of mean difference among the three seasons was done by multiple comparison tests (Tukey's HSD Post Hoc Test). Statistics analyses were performed using the SPSS version 17.0 .


Spectrophotometer measurements recorded at ten US monitoring sites were used in this analysis, and over 71,000 total UVR measurement scans of the sky were collected at those 10 sites between 1998 and 2000 to assess the RAF value. This UVR dataset was examined to determine the specific impact of clouds on the RAF. Five de novo modeling approaches were used on the dataset, and the calculated RAF values ranged from a low of −0.80 to a high of −1.38.A generally accepted value for the Radiation Amplification Factor (RAF), with respect to the erythemal action spectrum for sunburn of human skin, is −1.1, indicating that a 1.0% increase in stratospheric ozone leads to a 1.1% decrease in the biologically damaging UV radiation in the erythemal action spectrum reaching the Earth. The RAF is used to quantify the non-linear change in the biologically damaging UV radiation in the erythemal action spectrum as a function of total column ozone (O The Radiation Amplification Factor (RAF) is defined as the measured percentage change in ultraviolet (UV) irradiance for each one-percent change in total column ozone . UnderstThe Brewer instruments were calibrated for biologically damaging UV radiation in the erythemal action spectrum at each of the 21 sites using a secondary (travelling) standard lamp traceable to a primary (stationary) National Institute of Standards and Technology (NIST) 1000-W lamp. The calibrations were performed by scientists at the University of Georgia at Athens (UGA) National UV Monitoring Center (NUVMC) on an annual basis. The calibrated Brewer data used a daily temporal response (estimated) based on the annual calibration. In addition, independent quality assurance audits of the Brewers were performed by scientists from the National Oceanic and Atmospheric Administration (NOAA) Central UV Calibration Facility (CUCF). Quarterly checks on the transfer of the calibration standard from the NIST 1000-W lamp to the traveling secondary standard were performed at the NUVMC. The response function of each instrument was calculated daily from a linear interpolation between the two  closest response functions. Brewer data were corrected for dark count, dead time, and stray light.3) and solar zenith angle (SZA) are the most important parameters in determining the biologically damaging UV radiation in the erythemal action spectrum reaching the Earth’s surface. Five modeling approaches, labelled A, B, C, D, and E, were used to estimate the impact of clouds on the biologically damaging UV radiation in the erythemal action spectrum.Clouds affect the relative absorption/reflectance of UVR. Transmittance of UVR through clouds is shown to be wavelength dependent, ranging from 45% in the UV-A region to 60% in the UV-B region as stated in Chapter 4, page 105 of . Cloud fIn the early 1990s, the EPA’s Office of Research and Development (ORD) originally designed a UVR monitoring network of five to seven sites principally in urban areas, with a few “pristine” rural sites for monitoring background UVR levels. The EPA’s role in UVR research was to monitor in urban areas. The United States Department of Agriculture (USDA) was responsible for monitoring UVR in rural areas. The focus of the EPA’s original UVR network design was shifted in 1996. In September 1996, the US EPA and US National Parks Service (NPS), of the US Department of the Interior (DOI), signed an Interagency Agreement (IAG) to cooperate on a program of long-term monitoring of environmental stressors, including UVR, at 21 separate locations throughout the United States. When the NPS sites were added to the network, it greatly expanded the EPA’s UVR monitoring program. The EPA’s UVR Monitoring Network facilitated research on the observed effects that environmental stressors, including UVR, pose on various ecosystems and on human health. The 21 EPA UVR monitoring sites  designed to reduce the amount of greenhouse gases in the stratosphere, and increase the amount of stratospheric ozone.Serve as a component of the EPA’s National Environmental Monitoring Strategy.During the development phase of the EPA’s UVR Monitoring Network, the experimental design and site selection were planned to test specific hypotheses, which fulfilled the stated research objectives listed above. Sites were selected which provided UVR data for a variety of conditions . The EPA decided that the network would consist of spectral UVR monitors so that researchers could determine what key factors caused changes in UVR levels, e.g., changes in stratospheric ozone composition, tropospheric changes like cloud cover or pollution , etc. A secondary benefit of spectral UVR data is that the data on the UV spectrum can be compared with data on human and ecological disease incidence and geographic distribution.The first  site in the EPA’s UVR Monitoring Network at Research Triangle Park, North Carolina, began initial operation in 1992. The UVR data collected from the EPA’s UVR Monitoring Network was processed through a Level-1 data quality assurance algorithm to ensure proper characterization of biologically damaging UV radiation intensities at each measured wavelength (for each instrument), and the data in this study is designated as Level-1 corrected data . The Lev2) per day ). UVR data collected by the instruments is important because it helps us understand the implications of increased UVR associated with decreasing stratospheric ozone concentrations. The instruments provide accurate UVR measurements of known quality in assessing the effectiveness of the EPA’s stratospheric ozone policies. The data allows scientists to evaluate the “climatology” affecting UVR in the environment. The EPA’s quality-assured UVR data is posted to a publicly accessible web site: https://www.epa.gov/hesc/rsig-data-inventory (Last Accessed: 4 August 2017).The instrument computer controls the azimuth tracker which rotates the entire Brewer, allowing it to track the sun. Brewer software has an ephemeris algorithm, which calculates both the azimuth and zenith angles of the sun as seen from its (current) location. Brewers accomplish this using its latitude and longitude placement along with its GMT time and date. Angles calculated by the ephemeris algorithm along with latitude and longitude are transmitted to both the zenith tracker and azimuth tracker systems to properly position the Brewer towards the sun. Brewers measure biologically damaging UV radiation at each wavelength  in the instrument’s measurement range during each scan of the instrument. Spectral irradiance is expressed as power density per unit wavelength . A Brewer’s schedule for scanning the local sky was programmed based on zenith angle of the sun at its particular location. The first UV spectrum scan recorded each day by a Brewer occurred at a local solar zenith angle (SZA) of 85 degrees . The instrument is programmed to make subsequent spectral scans at 5-degree increments after that point, since the SZA is changing rapidly. Near local noon, when the local SZA does not change rapidly, the scanning schedule was programmed to occur at intervals of approximately 20 min. On a typical summer day at mid-latitudes, approximately 30 UV spectral scans were recorded. The raw UV spectral data from each Brewer in the network was collected daily and processed through a data correction algorithm, which performed numerous quality control checks. The algorithm corrected the data for known systematic biases caused by temporal drift in Brewer calibration, non-ideal cosine response, and temperature dependence.To determine the dependence of the RAF on cloudiness, the parameter “cloudiness” must first be defined. Most Brewer sites had no additional instrumentation to independently measure clouds or broadband solar radiation, but general sky conditions were manually recorded in site operator logs. Therefore, Brewer UV spectral measurements were used to derive the cloudiness, or percent “clearness”  indicator, where the sum of percent clearness and cloudiness equals 1.0. The selected indicator of percent clearness was based on the amount of light received with clouds compared to the amount of light received when the sky is cloudless. The percent clearness indicator was selected to be (1) independent of total column ozone, and (2) able to be determined as closely to the biologically damaging UV radiation measurement temporally as possible. Furthermore, the percent clearness indicator needed to be a value derived entirely from the recorded UV spectral data, rather than from the output of a radiative transfer model. The measurement of UV spectral irradiance is not an instantaneous measurement. The Brewer records UV spectral irradiance, progressing from shorter to longer wavelengths, while its internal diffraction grating is physically rotated. An entire UV spectral scan, from 286.5 nm to 363 nm, takes approximately six min. This yields a rate of approximately 13 nm/min of wavelength scan progression.Although Brewers are capable of measuring total column ozone, the Brewer instruments in the EPA’s network were never initialized or calibrated to measure total column ozone. For that reason, NASA’s Total Ozone Mapping Spectrometer (TOMS) satellite provided total column ozone, in Dobson Units (DUs), from its daily overpass for each of the 10 sites analyzed in this study. Since only one daily satellite overpass was accomplished per site, the recorded daily total column ozone values were constant for each site. The biologically damaging UV radiation is largely determined from energy in wavelengths less than 320 nm . The effective UV wavelength band range for ozone impacts occurs at wavelengths from 290 nm to 325 nm . Changes3) measurement from TOMS; (c) a biologically damaging UV radiation (Brewer) measurement; (d) an unweighted, integrated Brewer UVR measurement taken between the 325 nm and 330 nm wavelength segment (designated UV325). Using the data collected at the 10 selected UVR monitoring sites from 1998 through 2000, a plot of UV325 (in mW/m2) versus SZA, shown in The UV spectral data scanned and recorded by the Brewers between 325–330 nm was used as the indicator for percent clearness. This particular wavelength segment was chosen because it lies above the wavelengths that are affected by total column ozone. The rational for selecting this wavelength segment (325–330 nm) was to ensure that any changes observed could be attributed to clouds and not to any potential impacts from total column ozone. This portion of the electromagnetic spectrum also provides a stable measurement basis. This wavelength segment is temporally close (within two min) to the wavelength segment which provides the major contribution to biologically damaging UV radiation. Given that the peak biologically damaging UV radiation contribution occurs at approximately 310 nm, the following calculation illustrates the temporal resolution (difference) between the wavelengths unaffected by total column ozone and those contributing to maximum biologically damaging UV radiation  = 1.538 min, yielding approximately 1.5 minutes’ temporal difference). The wavelength segment between 330–363 nm was also used, which is minimally affected by clouds, to ensure that a consistent definition of cloudiness could be determined at each site using the appropriate UV wavelength segment least impacted by clouds based on local site conditions. The rational for selecting this particular wavelength segment (330–363 nm) was to attribute observed changes to total column ozone and to remove impacts from clouds. For each of the 10 selected sites, a data set was generated with each observation consisting of four pieces of data including: (a) SZA measurement; (b) a total column ozone (O95 = {cos(SZA)}3 + {cos(SZA)}2 + {cos(SZA)}, (0). The parameter CLR1 is a line which represents a boundary indicating where most (95%) of the UV measurements between 325 nm and 330 nm are found based on SZA at each particular site. CLR1 is the parameter describing a cloud free day, according to the maximum range of UV irradiance values, which would not occur on a cloudy or partially cloudy day. CLR1 tends to approach the upper limit of UV325 values at each SZA, but some values can exceed CLR1 values plotted along the 95th percentile line by up to 20 percent, most likely due to cloud reflections. The generated data set for each site could now be supplemented with an additional parameter (CLR1) derived from the UV325 versus SZA plots: CLR1 = UV325/(95th percentile of measurements at each SZA). The ten sites selected for the analysis are provided in ™ statistical software.Examination of the UV325 versus SZA plots for the 10 selected sites led to the determination of CLR1  which was added to the datasets, containing (a) through (d) above, from an SZA-dependent polynomial approximation of the 95th percentile of the UV325 measurements for each site {as shown by the black lines in The vertical lines shown in It is preferable for conditions to remain constant during a scan, but that was not always the case. The temporal gap between the bulk of the contribution to the biologically damaging UV (at 310 nm) and the UV325 wavelength segment introduced some variability in the data. The variability appeared to be systematic, and can be illustrated through the following two examples. Hypothetical Situation: A day with widely scattered cumulus clouds; Example 1: At one point during the day, the sun is exposed  at the beginning of an instrument spectral scan. Then, at the 320 nm wavelength portion of a spectral scan, a cloud passes in front of the sun. The calculated UV325 will be lowered to approximately 50% of the previous CLR1 value, and the measured biologically damaging UV radiation value will be higher than the UV325 value. Example 2: At another point during the same day, the sun is hidden in the early stages of a spectral scan and then emerges at approximately 320 nm, the UV325 will record nearly 100% clear, and will be higher than the previous CLR1 value, and the measured biologically damaging UV radiation value will be lower than the UV325 value. The frequency of such systematic variations tends to diminish as the sky becomes either heavily overcast (0% clear) or cloud-free (100% clear).3], biologically damaging UV radiation in the erythemal action spectrum, UV325), and the derived CLR1 parameter. These parameters were then used to plot the biologically damaging UV radiation in the erythemal action spectrum versus total column ozone (O3), for different values of CLR1 and SZA. The biologically damaging UV radiation values were then normalized for the seasonal change in Earth–sun distance. Finally, although the polynomials defining “clear” (sky) UVR are approximately the same, there should be some systematic differences based on altitude, topographic obstruction, and haze/pollution at each site. For this analysis, the biologically damaging UV radiation values were normalized between sites to produce a nearly identical definition of “clear” sky. The data from all ten sites were then combined to produce the four plots shown in 3) for percent clearness PCLR of 25% (black), 50% (blue), 75% (green), and 100% (red) ±3% and SZA from 25 to 30 degrees. The curved line relationship for the RAF = −1.1 is based on the power law: 3), approximately 350 Dobson Units (DU).Data sets were compiled for the ten selected sites in the UVR network containing the measured parameters  and  as would be expected from sudden appearance or disappearance of direct sun due to cloud configuration/movement, as discussed in two hypothetical examples described above. This skewing affected the regression analyses designed to determine the RAF theoretically.3) increases, biologically damaging UV radiation in the erythemal action spectrum decreases in a consistent manner. Clouds may have a systematic effect in altering the generally accepted value of a 1.1% decrease in the biologically damaging UV radiation in the erythemal action spectrum (–1.1%) for each 1.0% increase in total column ozone, as measured in Dobson Units (DUs).3), cloudiness/percent clearness of the sky, and solar zenith angle was determined using the experimental setup. The RAF is a parameter which is designed to answer the question, “If total column ozone increases by one percent, what is the percentage change in the biologically damaging UV radiation ”? If the assumption is that the RAF is a reasonable concept, an experiment must be designed to determine if there is a relationship between the RAF and cloudiness. The idea is to isolate the changes due to atmospheric ozone and minimize the impact of clouds when measuring changes in UVR at different wavelengths.An initial description of the relationship between cloud coverage and its effect on the RAF was obtained from 71,000 total UV measurement scans taken between 1998 and 2000 at ten Brewer sites in the EPA’s UVR Monitoring Network. The range of solar zenith angles for which measurements were taken was less than 60 degrees (60°). The relationship between the biologically damaging UV radiation, total column ozone :3] levels  at each fixed SZA.Measure the total column ozone [OMeasure the biologically damaging UV radiation levels  at each fixed SZA at measured:Percent clearness = 0% [100% cloud cover] to Percent clearness = 100% [0% cloud cover]Percent clearness = 100% to 120% [accounting for cloud “reflections”]—Note: enhancement of UVR by cloud reflections has been measured at up to 30 percent [3] was measured, in DUs, from the TOMS satellite. The biologically damaging UV radiation is measured, in mW/m2, from the ground using Brewers. The computerized Brewer scan schedule does not accommodate measuring the biologically damaging UV radiation at fixed SZAs for long periods of time. There were no independent or reliable measurements or estimates of cloud cover either from ground-based measurements or from satellites at either Brewer site. However, operator logs at each site recorded the general sky condition and amount of cloudiness . This left the question of how to determine percent clearness (cloudiness) unanswered. Since there was no instrument-based measurement of cloudiness (percent clearness) available at either of the Brewer sites, a theoretically determined methodology for assessing percent clearness (cloudiness) was used as described below.The total column ozone , SZA = 0 is directly overhead, and SZA = −90 degrees [the local horizon at sunset].3 = total column ozone (in Dobson Units)—from TOMS satellite measurements.OBiologically Damaging UV Radiation = Brewer spectrophotometer measurements.CLR2 = percent clear (percent clear sky measurement at a selected SZA)—calculated value, derived from the polynomial representing the 95th percentile of all UVA measurements, between 330–363 nm, as a function of SZA.To ensure that all potential confounding parameters are eliminated from the calculation and only RAF versus percent clear curves are generated for each modeling approach, the following steps were taken:The UVR calculations were normalized with respect to the distance between the sun and the Earth during the year. Note: Earth is closest to sun on 5 January. The formula used to calculate the normalized UVR values is:where jday = 1, 2, …, 365, with jday = 5 being 5 January, .The UVR values were normalized with respect to systematic differences due to site altitude, topography, pollution, aerosol, haze, etc.The data from all ten sites was combined into curves of RAF versus percent clear sky for each of the five modeling approaches, Model A through Model E, (as shown in 3) measurement from TOMS; (c) biologically damaging UV radiation (Brewer measurement); (d) an unweighted, integrated Brewer UVR measurement taken between the 330 nm and 363 nm wavelength segment (designated UV330). Using the data collected at the 10 selected UVR monitoring sites from 1998 through 2000, a plot of UV330 (in mW/m2) versus SZA, shown in For each of the 10 selected sites, a data set was generated with each observation consisting of four pieces of data including: (a) solar zenith angle (SZA) measurement; (b) a total column ozone (OExamination of the UV330 versus SZA plots for the 10 selected sites led to the determination of the derived “clear” (CLR2) parameter added to the datasets, (containing a through d above), from an SZA-dependent polynomial approximation of the 95th percentile of the UV330 measurements for each site {as shown in 3], (2) percent (%) clear sky {i.e., percent clearness/cloudiness} [CLR], (3) SZA; Model B—(1) total column ozone [O3], (2) “clear” ; “iclear” is the parameter describing cloudiness (as discrete percentage levels grouped into different classes), based on the maximum range of UV irradiance values, (3) SZA; Model C—(1) total column ozone [O3], (2) “iclear*” , (3) SZA—Note: This is the same as Model B, except with the tails of the biologically damaging UV radiation distribution removed; Model D—(1) total column ozone [O3], (2) CLR^ [replaces CLR with a linear function in percent clearness {“classes” of CLR} between 40% and 100% clear skies], (3) SZA; Model E—(1) total column ozone [O3]/cos(SZA), and (2) cos(SZA): This is an empirical relationship known as Beer–Lambert’s Law. At the 10 UVR monitoring sites selected for the analysis, the NASA Total Ozone Mapping Spectrometer (TOMS) satellites were used to measure total column ozone. This provided the benefit of an independent measurement source for determining atmospheric  ozone.The vertical lines shown in Each model is based on the 71,000 total UVR measurements taken at the ten sites listed in Model A: The average RAF value from Model A for all 10 sites and for all sky conditions  and solar zenith angles less than 60° is −1.167. Model A is the base model from which Models B, C, and D are derived.Model B: The average RAF value for all 10 sites and for all sky conditions and solar zenith angles less than 60° is −1.1936. This model performed a regression on the discrete “classes” of the parameter CLR and replaced it with the result . This model produced the highest average RAF value of the five models.Model C: The average RAF value for all 10 sites and for all sky conditions  and solar zenith angles less than 60° is −1.105. This model is identical to Model B, except data censoring was applied .^) and solar zenith angles less than 60° is −1.087. The parameter representing the percentage of clear sky (CLR^), was assumed to be a linear function between 40% and 100% clear skies. This model provided the lowest average RAF value of the five models.Model D: The average RAF for all 10 sites and for all sky conditions  and solar zenith angles less than 60° is −1.119. Model E is based on a physical/empirical model (Beer–Lambert’s Law).The overall average RAF value from the five methods used for the ten selected network sites was −1.134, with the RAF values for individual methods ranging from a low of −0.80 to a high of −1.38, as shown in 3]; (2) CLR ; (3) solar zenith angle [SZA], is given as follows : The relationship between the biologically damaging UV radiation and the following parameters: (1) total column ozone  to 15% clear sky radiation [transmitted]). This behavior is expected, as an increase in cloudiness (decrease in percent clear sky radiation transmitted) tends to reduce the amount of UV radiation reaching the Earth’s surface for each 1% change in total column ozone. At 45% clear sky radiation, where the lowest RAF value (−1.38) is found, there is an inflection point, after which RAF values tend to increase in general, with negligible decreases (between 55% to 65% clear sky radiation and between 105% to 115% clear sky radiation).3]; (2) “iclear” ; (3) solar zenith angle [SZA], is given as follows: The relationship between the biologically damaging UV radiation and the following parameters: (1) total column ozone  to 15% clear sky radiation [transmitted]). This behavior is expected, as an increase in cloudiness (decrease in percent clear sky radiation transmitted) tends to reduce the amount of UV radiation reaching the Earth’s surface for each 1% change in total column ozone. At 45% clear sky radiation, where the lowest RAF value (−1.375) is found, there is an inflection point, after which RAF values tend to increase in general, with a constant region between 85% to 95% clear sky radiation and a decreasing region between 105% to 115% clear sky radiation.The Model B residuals versus the natural logarithm of the total column ozone value in Dobson Units (LOZ), for clear sky radiation between 90–100% , may indicate some biologically damaging UV radiation well below the expected values as shown in The Model B residuals versus the natural logarithm of the total column ozone value in Dobson Units (LOZ) for sky clearness percentages of 40–50% (iclear = 45) may indicate some biologically damaging UV radiation well above the expected values, as shown in The residuals for the for sky clearness class 90% to 100% (iclear = 95), The distributions of the biologically damaging UV radiation as shown in The distributions of the biologically damaging UV radiation as shown in The distributions of the biologically damaging UV radiation as shown in 3]; (2) “iclear” , is identical to Model B (using the same equations) except the tails of the biologically damaging UV radiation distributions are removed (data censoring).The relationship between the biologically damaging UV radiation and the following parameters: (1) total column ozone  to 15% clear sky radiation [transmitted]). This behavior is expected, as an increase in cloudiness (decrease in percent clear sky radiation transmitted) tends to reduce the amount of UV radiation reaching the Earth’s surface for each 1% change in total column ozone. Between 25% and 45% clear sky radiation, there is no visible change in RAF value. This may be a result of the removal of the “tails” of the biologically damaging UV radiation distributions, which would be expected to drive the values of the distributions closer to the mean value. This is the only model without an inflection point at 45% clear sky value, which seems reasonable given the censoring of the tails of the biologically damaging UV radiation distributions. The lowest RAF value (−1.18) occurs at 95% clear sky radiation, which again might be attributable to the data censoring used in this model. The residuals for Model C censored data are provided in 2 value, as shown in 2 value for Model C can be attributed to the fact that extreme values were removed by data censoring. The R2 values for the residuals of the other models are lower than Model C and display more scatter.The Model C residuals versus the natural logarithm of the total column ozone value in Dobson Units (LOZ) for sky clearness percentages of 90–100% (iclear = 95) indicate that biologically damaging UV radiation mostly clusters around the expected values, with a high R2 value, as shown in The Model C residuals versus the natural logarithm of the total column ozone value in Dobson Units (LOZ) for sky clearness percentages of 40–50% (iclear = 45) indicate that these biologically damaging UV radiation measurements have a larger spread than those at sky clearness percentages of 90–100% (iclear = 95), with a relatively high RAt first glance, the residuals for the for sky clearness class 90% to 100% (iclear = 95), 3]; (2) CLR^ [assuming a linear function in percent clearness {“classes” of CLR} for skies between 40% clear and 100% clear]; (3) solar zenith angle [SZA], is given as follows: ^ represents a linear function in percent clearness for 40–100% clear skies.The relationship between the biologically damaging UV radiation and the following parameters: (1) total column ozone  to 15% clear sky radiation [transmitted]). This behavior is expected, as an increase in cloudiness (decrease in percent clear sky radiation transmitted) tends to reduce the amount of UV radiation reaching the Earth’s surface for each 1% change in total column ozone. At 45% clear sky radiation, where the lowest RAF value (−1.3) is found, there is an inflection point, after which RAF values increase, with one exception between 85–95% clear sky radiation. The RAF values between 40–60% clear sky radiation could possibly indicate an isolated cloud over the sun during a scan.3]/cos(SZA), and cos(SZA), based on Beer–Lambert’s Law is shown in 3/cos(SZA)}): The functional relationship between the biologically damaging UV radiation and the following parameters: total column ozone  to 15% clear sky radiation [transmitted]). This behavior is expected, as an increase in cloudiness (decrease in percent clear sky radiation transmitted) tends to reduce the amount of UV radiation reaching the Earth’s surface for each 1% change in total column ozone. At 45% clear sky radiation, where the lowest RAF value (−1.28) is found, there is an inflection point, after which RAF values increase, with exceptions between 75% and 85% clear sky radiation, and between 105% and 115% clear sky radiation, consistent with .Although Model A and Model B have average RAF values closer to −1.2, while Model D has an average value of nearly −1.1 (−1.087), Model A, Model B, and Model D behave in a similar fashion, as they each display the relationship where RAF decreases as clear sky increases (percent cloudiness decreases) between the 100% to 120% clear sky values. Each of these three models displays the lowest RAF values (−1.3 to −1.38) at the 45% clear sky value. Due to the censoring of the tails of the biologically damaging UV radiation distribution, understandably, Model C has a “flattened” RAF versus clear sky response curve. Model E, like Model A, Model B, and Model D, also has its lowest RAF value (−1.28) at the 45% clear sky value. The average RAF value of Model E is −1.119 (less than Model A), and it displays the relationship where RAF increases as clear sky increases (percent cloudiness decreases) between the 85% to 105% clear sky values, unlike Models A, B, and D.This research project utilized a large dataset of UVR measurements from ten monitoring sites that were diverse with respect to spatial location, geography, climate, altitude, and ecology to calculate RAF using four hypothetical approaches and one empirical model. This research project developed a consistent definition of cloudiness, independent of total column ozone, and temporally close to biologically damaging UV radiation measurements to facilitate direct and consistent comparisons between each of the approaches for modeling RAF. Model C, which censors the tails of the biologically damaging UV radiation distribution, should not be used to assess RAF, since the RAF value is artificially driven to a mean value (−1.1). While Models A, B, and D are consistent and comparable in the relationship between RAF and clear sky radiation between 100% and 120%, the empirically-based model, Model E, behaves differently in that range.The results show that for all models except Model C (censored tails), in the 35% to 65% range of clear sky radiation (65% to 35% cloudiness), as cloudiness decreases, RAF increases, ranging from −1.2 to −1.4, where it reaches its highest level before decreasing. Between 15% and 25% clear sky radiation (85% to 75% cloudiness), there is an increase in RAF for all models. In general, RAF tends to increase as the sky conditions change from high to moderate cloudiness. Clouds block biologically damaging UV radiation in this range and the behavior is qualitatively the same as if stratospheric ozone was increased. UVR can experience a 4.3% increase per kilometer of altitude, from 0 km to 6.2 km, and is also affected by atmospheric pressure and aerosol density . It is n


Singapore used to report an annual average of 14 cases of Japanese encephalitis, but ever since the abolishment of pig farms in the early 1990s, the local incidence rate for Japanese encephalitis virus (JEV) infections has reduced drastically. Studies done in the early 2000s demonstrated the presence of JEV-specific antibodies in animals such as wild boars, dogs, chickens and goats on the offshore island and peripheral parts of the Singapore, indicative of prior JEV exposure. A JEV wildlife and sentinel chicken surveillance system was initiated in 2010 through to 2017 to study the animal host seroprofiles.A total of 12/371 (3.23%) of resident bird samples, 24/254 (9.45%) of migratory bird samples and 10/66 (15.16%) of wild boar samples were positive for the presence of JEV antibodies. Seroconversions in sentinel chickens were observed at two time points. Through this study, two sites with active transmission of JEV amongst avian or porcine hosts were identified.JEV transmission in animal hosts has continued despite the phasing out of pig farming nearly thirty years ago; however, the public health risk of transmission remains low. Environmental management for mosquito population remains key to keeping this risk low. Japanese encephalitis is endemic in many Asian countries and contributes to a large disease burden, with approximately 30,000 to 50,000 reported cases, and 10,000 deaths annually , 3. JEV Culex tritaeniorhynchus as the primary vector, and humans as the accidental dead-end host [Sus scrofa Linnaeus), which were once thought to be extinct in Singapore have re-colonized areas such as the Central Catchment Nature Reserve (CCNR) and the western catchment areas in the past decade. It is estimated that over 500 wild pigs inhabit the CCNR. Small population clusters are also found on the eastern side of Singapore [Singapore used to report an annual average of 14 cases of JEV until the abolishment of pig farms in 1992 –11. JEV end host . After 1end host . JEV-speend host . These aend host , 17. Theingapore . The expEgretta garzetta) and herons (Nycticorax nycticorax) from the family Ardeidae are particularly susceptible to JEV infection, and are known to develop high viral titers [A plausible source of JEV is migratory birds which can serve as viral reservoirs. Over 90 bird species have been identified as amplifying and reservoir hosts of JEV. Among them, egrets  houses a variety of resident birds, and is also visited by both long- and short-distance migratory birds. NR has an existing bird ringing programme to collect bio-data from the migratory birds that visit this pit-stop. Tagging onto this programme that has been on-going since 1990, 254 blood samples were taken from the migratory birds that were caught during the migratory session (every September to March) from 2010 to 2017. Jugular vein blood samples of not more than 1% body weight of birds were drawn aseptically into EDTA tubes by avian veterinarians. After sampling, an equivalent volume of 10% glucose was injected for replenishment. Blood samples were transferred on ice to the Environmental Health Institute, a public health laboratory under the National Environment Agency of Singapore. The plasma was separated by centrifugation at 4000 rpm for 4 min and kept at − 80 °C until further processing.Through a donor bird programme at the Avian Sanctuary (AS) where the public can submit injured birds found elsewhere in the country, 372 bird serum samples were obtained during the same period. The collection also included 1024 dead bird carcasses. These carcasses were dissected, and their organs  were stored at − 80 °C for bio-banking purposes.Sixty-six wild boar blood samples were collected as part of wild boar population management programme in Central Catchment Nature Reserve (CCNR) in 2014, where wild boar activity was previously documented. Animals’ physical characteristics such as size and weight were recorded. Blood was kept and transferred to the laboratory on ice. The plasma was separated by centrifugation at 4000 rpm for 4 min and kept at − 80 °C until further processing.A total of 1024 bird brain samples were each homogenized in 500 µl of virus transport media  using a Mixer Mill MM 400 . A volume of 140 µl of viral RNA was extracted from each brain specimen and blood sample by using a QIAamp viral RNA mini kit  according to the manufacturer’s instructions.A duplex JEV and West Nile (WN) real-time reverse transcription polymerase chain reaction (RT-PCR) protocol was optimised based on protocols by Scherret et al.  and SantGallus domesticus) were deployed at NR for monitoring of specific zoonotic diseases, particularly arboviruses (arthropod-borne viruses). As mosquito-borne viruses such as JEV utilize birds in their transmission cycles, chickens are good sentinels and can act as an early warning system [From 2013 to 2018, a sentinel chicken surveillance was established at NR. As part of this surveillance, three to five sentinel chickens  was cultured in Vero cells (ATCC CCL-81) in the biosafety level 3 (BSL3) laboratory at the Environmental Health Institute. Immunofluorescence slides were made, inactivated and transferred out of the BSL3 to BSL2 where the IFA was performed. Animal plasma was diluted 1:50 in 5% skim milk  and applied onto the JEV IFA slides. Incubation was performed in a humidifier at 37 °C for 30 min before washing with 1× PBS. Secondary antibody anti-bird Ig-FITC  or anti-pig Ig-FITC (Bethyl Laboratories) was applied onto the slides, depending on the animal sera tested. Incubation and washing were repeated before visualization of fluorescence was performed.2. Subsequently, each well was fixed with formaldehyde (20%) for 30 min and stained with napthol blue black stain solution. PRNT80 was used to differentiate any cross-neutralizating antibodies from the same JEV serocomplex. The PRNT80 titre was calculated by counting plaques and reporting the titre as the reciprocal of the last serum dilution to show 80% reduction of control plaques (≤ 4 plaques) based on approximately 20 pfu of virus added to each sample.Samples that were positive in the IFA were subjected to plaque reduction neutralization assay (PRNT). PRNT, adapted from Nemeth et al. –28, was 1–103  registered JEV neutralizing antibodies, with an end point titre ranging from 10Besides ardeid birds , which are the typical avian reservoirs of JEV, raptors  also showed JEV neutralizing antibodies. The common birds in this collection  are considered as part of the native bird community.Charadrius mongolus; Mongolian plovers, Pluvialis fulva) and common redshanks (Tringa tetanus). Out of this, 24 (9.45%) samples collected from 2010 to 2012 registered neutralizing antibodies towards JEV  plasma samples had JEV neutralizing antibodies, with an end point titre ranging from 101 to 102 , a flavivirus in the JEV antigenic complex . It is i raptors . AlternaCharadrius mongolus) and the rest were common red shanks (Tringa totanus). Interestingly, JEV seropositive birds were only detected between 2010 and 2012, during which notable JEV outbreaks in this region occurred in East Asia, namely China and Korea [Out of the 24 migratory birds that had neutralizing antibodies towards JEV, six were Mongolian plovers  in Singapore involving avian and porcine hosts, nearly thirty years after the abolishment of pig farming. Further risk assessment studies will focus on identifying spatial risk of JEV in Singapore through surveillance of vector and animal hosts.


To examine the effects of shared genetics and prenatal environment, we compared McGurk susceptibility between MZ and DZ twins. Both twin types had significantly greater correlation than unrelated pairs (r = 0.28 for MZ twins and r = 0.21 for DZ twins) suggesting that the genes and environmental factors shared by twins contribute to individual differences in multisensory speech perception. Conversely, the existence of substantial differences within twin pairs (even MZ co-twins) and the overall low percentage of explained variance (5.5%) argues against a deterministic view of individual differences in multisensory integration.Multisensory integration of information from the talker’s voice and the talker’s mouth facilitates human speech perception. A popular assay of audiovisual integration is the McGurk effect, an illusion in which incongruent visual speech information categorically changes the percept of auditory speech. There is substantial interindividual variability in susceptibility to the McGurk effect. To better understand possible sources of this variability, we examined the McGurk effect in 324 native Mandarin speakers, consisting of 73 monozygotic (MZ) and 89 dizygotic (DZ) twin pairs. When tested with 9 different McGurk stimuli, some participants never perceived the illusion and others always perceived it. Within participants, perception was similar across time ( This illusion, first described by Humans have the remarkable ability to combine information from the mouth of a conversation partner with information from their voice in order to facilitate communication . The intOne surprising fact about the McGurk effect is that even though humans are experts in audiovisual speech perception, the illusion is not universal: even among healthy young adults, some participants never perceive the illusion, while others always do . The orin = 150) were retested 2 years after the original test.In order to determine the influence of genes and early environment on the McGurk effect, we examined perception of the McGurk effect in 324 healthy twins (mean age ± SD = 16.8 ± 2.1 years). 73 pairs of twins were monozygotic (MZ) and 89 pairs were same-gender dizygotic (DZ). To assess the stability of the McGurk effect, some of the participants . The McGurk stimuli consisted of nine digital audiovisual recordings, each ∼2 s long . Each stSubject responses were classified into four categories: auditory (responses corresponding to the auditory syllables), visual , McGurk  with a sample of native English speakers from the United States . Using tt-test assessing the null hypothesis of no linear relationship between the two variables being correlated.To assess the consistency of individual differences, we tested both within-test reliability  and test-retest reliability (Pearson’s correlation) for the proportions of McGurk responses. For assessing the statistical significance of individual Pearson correlations, we report the associated 95% confidence interval and the results of the To assess the similarity of McGurk illusion perception between cotwins, we separately calculated intraclass correlations for MZ and DZ pairs using the packge “irr” in R and report the corresponding analysis of variance (ANOVA). To compare these correlations, we used Fisher’s r-to-z transform to test the null hypothesis that the correlations are equal.As a secondary measure of similarity, we determined how accurately we could predict each subject’s McGurk illusion perception (root mean squared error across stimuli) using the co-twin’s illusion perception. As a comparison, we also used the mean value across all subjects (except the subject being predicted) to predict each subject’s illusion perception. To compare error rates between these methods, we used a non-parametric Wilcoxon signed–rank test.We conducted additional control analyses to assess the robustness of our presented results. First, we used bootstrapped simulations to calculate the expected intraclass correlation between unrelated pairs of individuals for both illusion percepts and auditory percepts . Next we used a linear mixed-effect model to assess the relationship between illusion perception and the collected demographic variables , with random effects of subject and stimulus. Finally, we looked for mean differences in the percentages of response types  between MZ and DZ twins.Different McGurk stimuli vary in efficacy, so we presented nine different McGurk stimuli in order to obtain a more generalizable estimate of each participant’s susceptibility to the illusion. Seven of the stimuli consisted of pairings of auditory “ba” and visual “ga” and two of the stimuli consisted of pairings of auditory “pa” and visual “ka” . Particit(322) = 68.1, p < 10–16; t(148) = 7.9, p = 10–13; As suggested by the large standard deviations in the response percentages, there was substantial variability across participants. We defined the McGurk susceptibility for each subject as the mean proportion of McGurk fusion reports across all presentations of all stimuli. A plot of the susceptibility values showed a broad range, with some subjects never reporting the effect and others always reporting it . This brGiven that individual differences in McGurk susceptibility were reliable, we next examined the effect of twin status. For some pairs of twins, there were substantial differences between twins  = 1.79, p = 0.007) and DZ twins . The intraclass correlation was not significantly different between MZ and DZ twins . The rate of auditory percepts also showed a positive intraclass correlation for both MZ twins  and DZ twins  with no significant difference between MZ and DZ twins .To visualize these relationships, we calculated the mean susceptibility to the McGurk effect of each twin pair and plotted the distance from the mean for each co-twin for both MZ  and DZ tr = 0.23  corresponds to only 5.5% of variance explained. As another way to understand this relatively low correlation, we estimated how well one twin pair’s response to a particular stimulus could predict their co-twin’s response to the same stimulus. Across subjects, prediction error (root-mean squared error) was 44 ± 17% for a given stimulus. Strikingly, if we instead use the mean value for a given stimulus across all subjects (except the subject being predicted), prediction error improved to 35 ± 10% for a given stimulus .While the twin correlations were significantly different than zero, they were low in absolute terms. An r = 0.25 and 0.17 for McGurk and auditory percepts, respectively) were higher than would be expected for randomly selected non-twin pairs for both McGurk illusion percepts  and auditory percepts .First, we verified that the intraclass correlations between actual twins .Second, we examined demographic explanations for individual differences in McGurk susceptibility. Age, gender, birth order, and their interactions failed to explain a significant portion of the variance in McGurk susceptibility  = −0.06, p = 0.95; auditory: 23 ± 22% vs. 26 ± 22%, t(322) = 0.96, p = 0.34; visual: 13 ± 13% vs. 12 ± 11%, t(322) = −0.97, p = 0.33; other: 16 ± 15% vs. 15 ± 13%, t(322) = −0.56, p = 0.58.Finally, we verified that there were no mean differences between MZ and DZ groups in any percept category: McGurk, MZ vs. DZ, 48 ± 23% vs. 48 ± 25%, in utero, approximately two-thirds of MZ twins share placentas, while no DZ twins share placentas. Since most MZ co-twins are exposed to exactly the same concentration and temporal variation in developmentally active biochemical factors in their shared circulation, MZ twins have much more similar prenatal environments than DZ twins, invalidating the equal environment assumption.Twin studies have a long and troubled history of being used to support unjustified conclusions that human behavior is strongly genetically determined, reviewed in r2) was only 5.5% (averaged across MZ and DZ twins) and there was no significant difference between MZ and DZ twins. Put another way, for both MZ and DZ twins, knowing how often one co-twin perceived the McGurk effect provided little information on the McGurk perception of the other co-twin.Keeping these caveats in mind, we found that the degree of susceptibility to the McGurk effect in MZ and DZ twins was significantly more similar than chance, demonstrating that shared genes and environment play some role in determining McGurk susceptibility. However, the percent variance explained  and speech rate (fast vs. slow) may contribute to the efficacy of a given McGurk exemplar  that is an order of magnitude larger than most published studies of the McGurk effect. This is important because in a phenomenon with high inter-subject variability, large sample sizes (>100) are necessary to accurately estimate differences between groups  with a sample of native English speakers from the United States (n = 145)   using thThe datasets analyzed during the current study are included as This study involving human participants were reviewed and approved by all subjects gave written informed consent to participate in an experimental protocol which was carried out in accordance with relevant guidelines and regulations and was approved by the Institutional Review Board at Institute of Psychology, Chinese Academy of Sciences. Parental informed consent was obtained for subjects under 18 years of age. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.MB conceived the study. MB and WZ designed the study. GF and BZ performed the testing and data collection. GF and JM performed the data analysis and interpretation under the supervision of WZ and MB. All authors contributed to the writing of the manuscript and approved the final version of the manuscript for submission.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Ribes stenocarpum Maxim (RSM) fruits at different stages of maturity were investigated, and the extraction process of polyphenols from RSM was also optimized using Box-Behnken design method. Results showed that the content of the nine phenols varied considerably at different ripening stages; catechin, chlorogenic acid, coumaric acid, and ferulic acid were abundant in immature fruits but decreased with fruit ripening, whereas the levels of rosemary acid and querctin acid were low in immature fruits and increased with time, reaching the highest value after the fruit was completely mature. The phenols extracted from RSM fruits possessed good antioxidant activities for effective and rapid scavenging of DPPH and ABTS free radicals, as well as intracellular ROS. Analysis of the phenols content at different maturity stages indicated that the unripe fruits had significantly higher polyphenols content than mature fruits. Consequently, unripe fruits possessed higher antioxidant activities. According to the overall results of the extraction process optimization, the selected optimal conditions for extracting polyphenols from RSM were as follows: extraction time, 95 min; solvent concentration, 60%; ratio of sample to solvent, 1:25.Differences in the content of nine phenols and the antioxidant capacity of  Ribes stenocarpum Maxim , i.e., the ratio of sample to solvent was the most significant variable for the model, followed by solvent concentration and extraction time. The empirical second-order polynomial model for the designs of extraction is shown in the following equation:To obtain optimal extraction conditions, a Box–Behnken design was used to optimize the significant variables , as well as to further investigate interactions between these variables. The experimental design for extraction process is shown in Based on the optimal conditions, three-dimensional response surfaces cf. a–c were Results showed that gallic acid, catechin, chlorogenic acid, vanillic acid, syringic acid, coumaric acid, ferulic acid, rosemary acid, and quercetin were the main types of phenols in the fruits of RSM. These nine phenols were separated completely within 35 min with high resolution and symmetrical peaks by HPLC a–c. The The optimized method was validated for linearity, limits of detection (LODs), limits of quantification (LOQs), precision, and accuracy. Linearity data was generated by plotting the peak areas versus concentrations for the nine phenols standards, and are summarized in The established method and the optimal conditions were further applied for analyzing the nine phenols of RSM fruits from different stages of maturity. The composition of the nine phenols in dry materials were expressed as mean ± SD (n = 3) and are summarized in The results showed that the content of the nine phenols in the RSM fruits at different stages of maturity differed significantly. Catechin, chlorogenic acid, coumaric acid, and ferulic acid were abundant in immature fruits but decreased with maturity. Currently, studies on phenols in RSM are limited. The reliable quantitative and qualitative determination of phenols composition and content determined in this study may lay a foundation for further investigation.According to The toxic effects of RSM fruits at different stages of maturity on HepG2 cells were evaluated at concentrations ranging from 20 to 100 μg/mL to determine the safe dose for subsequent experiments. As shown in As shown in Overall, we concluded that antioxidant capacity was highest in the extracted phenols in the order No. 1 > No. 3 > No. 4 > No. 2 > No. 6 > No. 7 > No. 5. The antioxidant activity of RSM fruits decreased gradually with maturity, which may be due to the decrease in phenol content with the increase in fruit ripening. More importantly, all studies of antioxidant activity have shown that phenols in RSM fruits have good antioxidant activity and have the potential to develop into new antioxidants.Ribes stenocarpum Maxim were collected from Huzhu in Qinghai province, China at different stages of maturity in 2017 . HPLC-grade acetonitrile and methanol were purchased from CLINC High Purity Solvents Co., Ltd. . Ultra-pure water was supplied by Watsons . All other reagents used were of analytical grade unless otherwise stated.−3 mol/L), each of which contained dilutions of the stock solutions of the nine phenols with acetonitrile. All solutions were stored at 4 °C in the dark until analyzed.The stock solutions of the nine phenols were prepared in 90% acetonitrile, which were then used to prepare the mixed standard solution for HPLC separation , solvent concentration (X2) and ratio of sample to solvent (X3) were selected as the variables. In this experiment, the phenols extraction process was optimized taking the No. 5 sample as an example. The extraction of phenols from the other samples was undertaken using the selected optimal conditions. The experimental data was analyzed using Design Expert software .A Box-Behnken design was used for the optimization of extraction experiments, as a three-factor-three-level containing 17 experimental runs and total content of the nine phenols was considered as response values. Extraction time  and adsorbed for 1 h. The column was eluted with acidified 1% ethanol at a flow rate of 2 mL/min and non-phenols substances were removed. The phenols were eventually eluted using acidified ethanol and concentrated in a vacuum at 45 °C, followed by freeze-drying to obtain phenol powders. The Sephadex LH20 dextran gel column (1.8cm × 80 cm) was equilibrated with phosphate buffered saline (PBS) pH 7.0. Then, 50 mg of the extracted phenols was eluted with PBS and the eluent was concentrated in vacuum, followed by freeze-drying to obtain the final extracted phenols samples. The samples were stored at 4 °C in the dark until analyzed.sample1 is the absorbance of samples and DPPH solution mixture, Ablank1 is the absorbance of the testing sample and absolute ethanol mixture, and Acontrol1 is the absorbance of DPPH solution and solvent  mixture.The DPPH-free radical scavenging activity of the extracts was based on a previously described procedure . Vitaminsample2 is the absorbance of testing sample, Ablank2 is the sample background absorbance, and Acontrol2 is the absorbance when sample is not present .ABTS free radical scavenging activity: This assay was performed as described previously  and abso2. The medium was replaced every other day until the cells were 80−90% confluent.Cell preparation: HepG2 cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM)-containing 10% fetal calf serum (FCS) at 37 °C in a humidified incubator containing 5% CO4 cells per well in DMEM containing 10% FCS and incubated for 24 h. The cells were then treated with various concentrations of phenols for another 24 h. Thereafter, 10 μL MTT solutions (5 mg/mL) were added to each well and the cells were further incubated at 37 °C = b. After 4 h of incubation, the medium was removed and 150 μL dimethyl sulfoxide (DMSO) was added to dissolve the resultant formazan product. Absorbance was detected at 570 nm using a multifunctional enzyme-linked immunosorbent assay (ELISA) detection platform [Cell toxicity assay: HepG2 cells in 150 μL growth medium were seeded in 96-well plates at 8 × 10platform .4 cells/mL for 24 h and treated with various concentrations of phenols for another 24 h. Then, the medium was replaced with 200 μL HBSS  containing 25 μmol/L of 2′-7′-dichlorodihydrofluorescein diacetate (DCFH-DA) and further incubated for 1 h under the same condition. After that, the fluid was removed and the cells were washed thrice with HBSS solution. Then, the cells were treated with 100 μL AAPH  dihydrochloride) (0.6 mol/L) for 30 min in the CO2 incubator. The fluorescence intensities were measured using a multifunctional ELISA detection platform with the excitation and emission wavelengths of 485 and 530 nm, respectively [Intracellular ROS detection: HepG2 Cells were seeded in 96-well plates at a cell density of 8 × 10ectively .Ribes stenocarpum Maxim resources, that are widely distributed in the Qinghai-Tibet plateau, for example, for the development of RSM-based functional food or medicine.In this study, an efficient method was developed for the rapid extraction and separation of nine phenols from RSM fruits at different stages of maturity. The optimum extraction conditions were as follows: extraction time, 95 min; solvent concentration, 60%; ratio of sample to solvent, 1:25. Analysis of the nine phenols from RSM fruits at different stages of maturity revealed that the content of these phenols varied considerably at different ripening stages. Catechin, chlorogenic acid, coumaric acid, and ferulic acid were abundant in immature fruits, but their levels decreased with fruit ripening; in contrast, the levels of rosemary acid and querctin acid were low in immature fruits and increased with time, reaching the highest value after the fruit was completely mature. In addition, the contents of gallic acid, vanillic acid, and syringic acid reached the highest values in different semi-mature periods. The antioxidative activities of these compounds were also investigated. Overall, analysis of phenol content at different maturity stages indicated that the unripe fruits had significantly higher levels than mature fruits. Consequently, unripe fruits possessed higher antioxidant activities, as observed in terms of the DPPH and ABTS free radical and intracellular ROS activities scavenging. However, our study has some limitations. As coumaric acid and ferulic acid were abundant in unripe fruits, we speculated that these acids contributed mainly to the antioxidant activity of polyphenols in RSM fruits. However, the phenols extracted from RSM fruits were not sufficiently pure, and antioxidant activity might improve with further purification of these phenols. Thus, the relationship between phenol species from RSM fruits and their antioxidant activities warrants further study. Overall, our work suggests that phenols from RSM fruits may act as new raw materials for the development of natural antioxidants. Our observations may further promote the use of


Development of patient-specific CT imaging phantoms with randomly incorporated lesions of various shapes and sizes for calibrating image intensity and validating quantitative measurement software is very challenging. In this investigation, a physical phantom that accurately represents a patient's specific anatomy and the intensity of lung CT images at the voxel level will be fabricated using fused deposition modeling (FDM) 3D printing. Segmentation and modeling of a patient's CT data were performed by an expert and the results were confirmed by a thoracic radiologist with more than 20 years of experience. This facilitated the extraction of the details of the patient's anatomy; various kinds of nodules with different shapes and sizes were randomly added to the modeled lung for evaluating the size-accuracy of the quantification software. To achieve these Hounsfield Units (HU) ranges for the corresponding voxels in acquired CT scans, the infill ratios of FDM 3D printing were controlled. Based on CT scans of the 3D printed phantoms, the measured HU for normal pulmonary parenchyma, ground glass opacity (GGO), and solid nodules were determined to be within target HU ranges. The accuracy of the mean absolute difference and the mean relative difference of nodules were less than 0.55 ± 0.30 mm and 3.72 ± 1.64% (mean difference ± 95 CI), respectively. Patient-specific CT imaging phantoms were designed and manufactured using an FDM printer, which could be applied for the precise calibration of CT intensity and the validation of image quantification software. These structures can be used to identify the early onset of lung diseases such as lung cancer, emphysema, and diffuse infiltrative diseases. In addition, due to the high dependence of diagnosis on imaging, better reliability of pulmonary CT is necessary. In addition, the development of CT phantoms that can be used to evaluate the accuracy and reliability of pulmonary CT quantification software is also a challenge. Although many patient-specific chest phantoms can now be created due to recent advances in 3D printing technology, the ability to simulate sections of the phantoms is limited because of the limitations associated with the available printing materials.,6Chest CT scans show diverse anatomic structures with a wide variety of CT intensities ranging from -1024 to 3072 Hounsfield Units (HU) including the airway, pulmonary parenchyma, diseased imaging patterns, fat, soft tissue, and bone.The purpose of this study is to simulate the shape and CT values of pulmonary parenchyma and lesions of various sizes using 3D printing technology and to verify the accuracy of CT software. Lungs, in particular, have a wide range of HU (-1024 to 400 HU) because of the presence of air, water, fat, and nodules. We investigated the HU of various 3D printing materials with various infill ratios with the goal of reproducing the HU range of chest CT images obtained from human subjects. In addition, a section of the lung from a patient's CT data was used to extract the details of their anatomy and lesions of different shapes and sizes were randomly incorporated into the modeled lung to evaluate the size-accuracy of the quantification software.2This study was approved by the Asan Medical Center Institutional Review Board with a waiver of a written informed consent to a patient due to a retrospective study without any additional harm.,8 to evaluate HU.To confirm the HU of a 3D printed phantom, samples with a specific size (radius 20 mm and height 30 mm) and different amounts of infill were outputted for various kinds of FDM materials including acrylonitrile butadiene styrene (ABS), thermoplastic polyurethane (TPU), and polylactic acid (PLA). For each sample, CT scans were performedChest CT data of a patient were acquired and segmentation and 3D modeling were performed. Data for the regions of interest (ROI) including lung parenchyma and pulmonary vessels were converted to stereolithography (STL) files. FDM 3D printing was used to fabricate phantoms for the parenchyma and lesions. Then, the final phantoms and STL files were compared Fig. .2.1An anonymous patient, various kinds of material samples for fabricating phantoms, and 3D printed lung phantoms were scanned using a dual-source CT  with a standard protocol of 120 kVp and 1.0 mm slice thickness. In addition, these scan data were reconstructed to 0.6 mm in the axial section using software (Syngo CT 2012B).2.23 using 3-matic software .–12 For CT scanning, the model was fixed to a self-manufactured plate so that each model could maintain a constant alignment. The HU for each model with various kinds of materials including ABS, TPU, and PLA, clear resin (Form lab.), white resin (Form lab.), general resin (Carima), general resin (Projet), Acryl resin, PXL clear powder was then confirmed with a CT scan . The obtained chest areas were exported to the 3-matic software  for post-processing. The various well-known shapes and sizes of lung diseases including ground glass opacity (GGO) and solid nodules were artificially modeled and inserted in the images. Each phantom was designed and manufactured by one type of material and printer without need of assembly. Based on the HU measurements in Figures 2.4,14To evaluate the HU range and to compare the sizes of the designed STL model and the actual model, the 3D printed phantom was scanned using the same dual-source CT equipment and scan protocol used for the initial study. Several ROIs of the designed STL model including normal parenchyma, GGO, and solid nodules were selected for size measurements. In CT images of the 3D printed phantom, the HU and size of each corresponding ROI were measured five times using a RadiAnt DICOM viewer . The measurement error of HU between reference and scanned CT values of GGO and solid nodule were evaluated by applying median and lower bound values as −350 and −100 HU, respectively. The absolute value means, and standard deviation were listed in Table 33.1We evaluated the HU from sample CT images for various types of 3D printers and materials at 100 percent infill ratio Fig. . These w3.2CT scans were obtained for the ABS, TPU, and PLA samples with various amounts of infill ratios from 10% to 100% in 10% increments. The average HU for the same size ROI along the axial section of each sample were evaluated. 3D printed models with lower infill ratios have higher porosity and gradually less HU  of ABS and TPU are GGO: 0.55 ± 0.30 mm, solid nodule: 0.33 ± 0.08 mm and GGO: 0.19 ± 0.18 mm, solid nodule: 0.22 ± 0.21 mm, respectively Fig. .4 However, there are several notable studies based on the application of 3D printing for the fabrication of CT imaging phantoms. For example, Hernandez-Giron et al used multi-jet 3D printing technology to fabricate an anthropomorphic lung phantom. However, this method is very expensive. Zhang et al, fabricated a lung phantom using 3D printing technology and tissue equivalent materials. This phantom has a realistic human anatomy and radiation attenuation property. Abdullah et al developed an organ-specific insert phantom using a 3D printer to investigate cardiac CT protocols. This phantom exhibited human-like chest and Hounsfield Unit (HU) characteristics that were comparable to that of a human subject, but the cardiac structure was non-anthropomorphic.Up to now, phantoms are primarily used for the evaluation and maintenance of medical devices.On the other hand, in this study, we developed patient-specific CT imaging phantoms with randomly incorporated lesions with various shapes and sizes for calibrating image intensity and validating quantitative measurement software. This physical phantom was scanned using CT to evaluate HU using different materials including ABS, TPU, and PLA for FDM 3D printing, which yields a range of HU between 0 and 200. To overcome this limitation, we attempted to achieve a lower HU range of −1000 to 0 HU by controlling the infill ratios, which can be one of the setting values of 3D printing via FDM. The emphysema, normal parenchyma, and nodules have HUs of less than −950, −800 to −600, and more than −200, respectively. The measured HU for normal pulmonary parenchyma, GGO, and solid nodules were within target HU ranges of a normal chest CT. The error of the measurement accuracy was determined to be submillimeter using quantitative measurement software. or Yaoyao et al, using PVC and 3D printing. Additionally, Aldosari et al, produced a 3D-printed pulmonary artery model for simulating peripheral pulmonary embolism and confirmed that the shape is very similar to the patient anatomy.,22 However, this model was limited in the choice of materials for the pulmonary embolism simulation and used an anonymous elastoplastic material with flexible features. Therefore, the CT imaging phantom was produced but did not reflect the HU well. To overcome the limitation, they proposed soaking the phantom to the contrast agent. Unlike previous other studies, we could use only one FDM printer to fabricate the lung imaging phantom without assembly. This 3D printing technology was able to implement a wide range of HU. Moreover, FDM printers are the most economical 3D printers, which is advantageous for future clinical application.The advantage of the method proposed in this paper is that it would implement realistic morphology, and it shows that the application of 3d printing technology in various medical fields could help overcome the limits of current physical phantom by making imaging phantom. In line with our study, several 3D printed imaging phantoms have been developed with different methods, for example, Altermatt et al, by using agar gel doped with contrast agent polyvinyl chloride (PVC) and 3D printing,25 The performance of software in difficult setting such as a complex anatomic lesion, that is branching area of the airway, cannot be evaluated corrected using the commercial phantom with the typical anatomic model. Generating the phantom with similar complex anatomy of the human body and similar CT density profile would be useful to validate software because the real dimension of the physical phantom can be controlled easily. The second potential application is for the education, having realistic physical phantom along with CT images would enhance the efficiency of training image interpretation skills to medical students and radiology residents. Finally, this patient-specific model will be useful to the clinician to communicate with the patient explaining the specific disease condition and discussing the treatment plan and so on.There could be various kinds of clinical applications of this patient-specific imaging phantom. One important application is the validation of quantification software. Various kinds of measurements on airway dimension and tumor diameter using different software with the various algorithms are well-known issues need to be overcome. The other limitation includes that the texture of the lung parenchyma is unnatural. CT image of the phantom showed the regular infill pattern of walls in the parenchyma, which are characteristic of FDM 3D printing. It is very difficult to remove these walls. We think that this limitation can be overcome by using the characteristics, which were generally regarded as disadvantages of FDM technology.,28 FDM 3D printing is a method of squeezing filaments made of polymer material from a printing head, and laminating layer by layer. As the temperature of the printing head is high and the moving speed is slow, string-like structures appear on the surface. This could be used to implement the form of alveoli. Another method is to use foamed silicone, where the degree of foaming depends on negative pressure.,31There are several limitations in our current prototype phantom study. The proposed method has a limitation to print bone structures. Most commercially available chest phantoms include the chest wall and bones such as ribs and the spine. To incorporate spine and bony structures using 3D printing, the CT value of bone can be replicated using color-jet printing (CJP) materials, which have HUs of 1000 or more, by assembling with an FDM lung model. For further investigation, a higher range up to +1000 HU can be obtained using contrast agents with different concentrations by injecting them into voids inside 3D printed parts.In summary, the CT values of different 3D printed materials were evaluated and CT imaging lung phantoms were fabricated using FDM 3D printing based on a patient's CT data, to include anatomical details. The generation of patient-specific lung imaging phantom using only 3D printing is difficult. However, this study demonstrates that a wide range of CT values can be achieved by controlling the internal filling of the 3D printing material. In addition, a variety of lesions of different shapes and sizes were randomly incorporated into the lung phantom to evaluate the size-accuracy of quantification software.We would like to thank Younghwa Byeon for his excellent technical assistance and English editing.Conceptualization: Sangwook Lee, Namkug Kim, Joon Beom Seo.Data curation: Dayeong Hong.Investigation: Dayeong Hong.Methodology: Dayeong Hong, Sangwook Lee, Guk Bae Kim, Namkug Kim.Project administration: Dayeong Hong, Namkug Kim.Resources: Namkug Kim.Software: Dayeong Hong, Sangwook Lee.Supervision: Guk Bae Kim, Sang Min Lee, Namkug Kim, Joon Beom Seo.Validation: Dayeong Hong, Sang Min Lee, Namkug Kim, Joon Beom Seo.Visualization: Dayeong Hong.Writing – original draft: Dayeong Hong, Namkug Kim.Writing – review & editing: Dayeong Hong, Guk Bae Kim, Namkug Kim, Joon Beom Seo.Dayeong Hong orcid: 0000-0002-6270-9643.