It appears that shortening the vertical gate distance is a better and safer way to reduce speed in Super-G than increasing the gate offset.In Super-G alpine ski racing mean speed is nearly as high as in Downhill. Hence, the energy dissipated in typical impact accidents is similar. However, unlike Downhill, on Super-G courses no training runs are performed. Accordingly, speed control through course design is a challenging but important task to ensure safety in Super-G. In four male World Cup alpine Super-G races, terrain shape, course setting and the mechanics of a high-level athlete skiing the course were measured with differential global navigation satellite systems (dGNSS). The effects of course setting on skier mechanics were analysed using a linear mixed effects model. To reduce speed by 0.5 m/s throughout a turn, the gate offset needs to be increased by + 51%. This change simultaneously leads to a decrease in minimal turn radius (− 19%), an increase in impulse (+ 27%) and an increase in maximal ground reaction force (+ 6%). In contrast, the same reduction in speed can also be achieved by a − 13% change in  Including overuse injuries and injuries sustained off season, the rates are even higher5. Accordingly, alpine ski racing is recognized as having one of the highest injury risks of all Olympic winter sports8.In each World Cup (WC) alpine ski racing competition season, approximately one third of all athletes suffer an injury10. Since speed is the driving factor for forces that are dissipated during crashes and collisions with the surroundings11, impact injuries are frequent in these two competition disciplines12. Consequently, spill zones and impact protective equipment such as netting along the race courses are commonly used countermeasures13. Additionally a reduction of speed in general, and before potential injury hotspots in particular, may be helpful in preventing impact injuries14. An earlier study of Downhill races assessed whether speed, as a key driver for impact injuries, could be reduced by changes in ski geometry and binding plates. The study, however, revealed that equipment alterations have only small effects on speed and that lower speed does not substantially increase the time athletes have to anticipate and prepare for technically difficult situations in Downhill15. Similar changes in equipment did not have substantial effects on speed in Giant Slalom (GS), but did positively affect the skiers' motion patterns and kinetics17. Hence, studies suggest it is difficult to adequately increase ski–snow friction forces via changes in equipment properties, particularly in the speed disciplines of Super-G and Downhill.In Super-G and Downhill speed is high compared to the other disciplines18, turn entrance speed18 and course setting21 are measures that have an effect on skier speed in technical disciplines. For GS it was found that increasing the gate offset or reducing the vertical gate distance both reduced speed18. However, increasing the gate offset to reduce speed caused an increase in injury risk through increased impulse , reduced minimal turn radius and increased maximal force, while a reduction in the vertical gate distance did not lead to such increases in injury risk18. It is, however, unknown whether speed can be controlled in Super-G in a similar manner to that demonstrated for GS, and it would be beneficial if similar quantitative recommendations could be generated for Super-G. It would also be helpful to determine the negative side effects of course-setting manipulations on other injury risk factors, such as turn radius, impulse and ground reaction forces. Therefore, this study aimed to: (1) assess whether course-setting characteristics, entrance speed and terrain incline influence speed through a turn; and (2) assess whether changes in course-setting aimed at reducing speed have negative consequences on turn radius, impulse and turn forces in Super-G.An alternative approach to reducing speed in Super-G or Downhill is course design. Recent studies have shown that terrain inclineDuring two winter seasons, data was captured at four male Super-G World Cup races in Kitzbühel (AUT), Hinterstoder (AUT), and twice in Crans Montana (SUI). The races were chosen to cover the range of typical World Cup Super-G courses. A forerunner, testing the course directly prior to competition, was tracked using a differential high-end global navigation satellite carried by the skier. For each location a different forerunner was chosen to ski the course. The forerunners were athletes competing at European Cup level. The study was approved by the Ethics Committee of the Department of Sport Science and Kinesiology at the University of Salzburg. Each subject provided written informed consent prior to taking part in the study and the methods were carried out in accordance with the relevant guidelines and regulations.2 were measured. At terrain transitions this number was substantially increased and was reduced in uniform terrain10.Start, turning gate positions, finish line and the terrain were captured prior to the respective race using static dGNSS: Alpha-G3T receivers with GrAnt-G3T antenna  and Leica TPS 1230 + . To reconstruct the snow surface in enough detail, on average 0.3 points per m22. A GPS/GLONASS dual frequency (L1/L2) receiver  collected antenna position at 50 Hz. The antenna  was mounted on the forerunner’s head. To calculate the carrier phase double difference position solutions, two (for redundancy) base stations were located at the start of the course and equipped with GNSS antennas  and Alpha-G3T receivers .Athlete tracking during skiing was conducted using a high-end differential global navigation satellite system (dGNSS) carried by the athlete on the back and helmet10. To calculate skier antenna position data, double difference carrier phase solutions were processed from GPS and GLONASS satellites and frequency L1/L2 using the geodetic software’s  KAR algorithm22. Turns for which the geodetic solution ambiguities failed to be solved were excluded from the study.Static dGNSS measurements on the terrain surface to represent the snow surface, and gate positions to represent the course, were calculated in a post-processing procedure, using the geodetic GNSS software Justin 10. The local incline of the terrain was geometrically derived using the local terrain surface normal vectors. To represent the average slope incline of a turn, the local incline vectors associated with a turn were averaged over the area of each turn10. The average turn incline was named TerrainINCLINE and expressed as the angle to the horizontal10.The shape of the snow surface was surveyed using static dGNSS. A digital terrain model was generated from the point cloud captured by dGNSS by triangulation of the point cloud, using the Delaunay method, and gridded on a rectangular gridGateVERTICAL) and the gate offset (GateOFFSET), also named horizontal gate distance in other studies  to the projection of gate (i) onto the vector between (i − 1) and (i + 1), as shown in Gilgien et al.10. GateOFFSET for gate (i) was calculated as the normal projection of gate (i) on the vector from gate (I − 1) to gate (i + 1). When two consecutive gates formed a delay turn (a long turn marked with two gates) the gate with the larger GateOFFSET was selected as the one to represent the turn10.Courses in alpine skiing are marked with gates, with a turning gate and a gate on the outside of the line skiers take. The setting of the course is characterized by two gate distances; the vertical gate distance  when the CoM turn radius was below 75 m14. The speed at which an athlete entered a turn (SpeedIN) was defined as the instantaneous speed at the point when the turn radius dropped below 75 m prior to the gate passage. Exit speed was the instantaneous speed at the point when the turn radius exceeded 75 m for the first time after the gate passage. The change in speed through a turn (∆Speed) was computed as the difference of SpeedIN and Exit speed. The minimal turn radius through a turn (RadiusMIN) was also considered as an injury proxy and was defined as the smallest radius in the turn20. The maximal ground reaction force (GRFMAX) was defined as the highest instantaneous ground reaction force during a turn24. To measure the effort athletes excerpt to the surrounding over the time of the course impulse was calculated as the time integration of the external forces. Impulse might also serve as an approximation of accumulated fatigue since both duration and the intensity of the physical effort are reflected in this measure. Impulse as a proxy of fatigue was defined as the integral of ground reaction force and air drag (in body weight) through the turn time and expressed in body weight seconds (BWs)25.The position of the dGNSS antenna that was mounted on the helmet of the athlete was filtered using bi-cubic spline functions. To better estimate the center of mass (CoM) position, a mechanical pendulum model was attached to the antenna position with a global position accuracy of 9 ± 12 cmThe data from all four races were pooled together to create a dataset of 192 turns. To characterize the central tendency and variability of the course setting and athlete mechanical parameters, mean and standard deviation (SD) were calculated.SpeedIN, TerrainINCLINE, GateOFFSET and GateVERTICAL. The mixed model was run for each outcome variable: RadiusMIN, ∆Speed, GRFMAX and Impulse. To generate comparable results between the different outcome variables, the fixed effects of the model were adjusted by division by two SD. The results of this intermediate step calculation can be found in the GateVERTICAL is required to change ∆Speed by two standard deviations?".To determine the relationship between course setting and adjustments in course setting and their effect on skier mechanics, a linear mixed effects model was established ). Since snow conditions were not quantified and the forerunners were different in each race location, the model contained the random variables “Skier ID” (3 different athletes), and “Skier ID*Race ID”. As model predictors we included the variables: SpeedIN, TerrainINCLINE, GateOFFSET and GateVERTICAL) to result in a reduction in speed of 0.5 m/s (∆Speed = − 0.5 m/s) from turn start to turn end. The effect that this change in the predictors (to reduce speed by 0.5 m/s) had on the other outcome variables, RadiusMIN, GRFMAX and Impulse, was also determined.The mixed model was re-run on all turns to calculate the adjustment required for each predictor variable (GateOFFSET has much higher variability than GateVERTICAL or linear gate distance.Table SpeedIN have on ∆Speed (reduction in speed induced by the given adjustments through a turn). All model predictors have a significant effect on speed.Table GateOFFSET needs to be increased by 51% of the existing GateOFFSET, or an average of 6.84 m. For the same decrease, GateVERTICAL would need to be shortened by − 6.31 m, which is − 13% of the existing GateVERTICAL.. Further, if course setting and terrain is held constant, but skiers enter the turn at 2.2 m/s or 9% higher entrance speed (SpeedIN), due to the phenomenon of the "velocity barrier" (i.e. a skier’s voluntary control of speed in order to avoid mistakes), they would lose 0.5 m/s speed throughout the turn. And, for a given course setting and SpeedIN, a 3.68° steeper TerrainINCLINE would result in a speed reduction through the turn of 0.5 m/s compared to a turn with the given TerrainINCLINE.To achieve a reduction in speed of 0.5 m/s throughout a turn, (∆Speed) caused by an increase in GateOFFSET by + 6.84 m .The data in Table  m Table  typicallAL Table  leads toGateOFFSET of + 6.84 m (Table GRFMAX of + 0.13 BW (i.e. + 6%). No increase in GRFMAX is found if GateVERTICAL is shortened by − 6.31 m to reduce speed by − 0.5 m/s.Moreover, an increase in  m Table  to reducGateOFFSET is increased by + 6.84 m to reduce speed by − 0.5 m/s. In contrast, impulse is actually decreased by − 0.07 BWs (i.e. − 2%) if GateVERTICAL is shortened by − 6.31 m to reduce speed by − 0.5 m/s.Finally, impulse increases by + 0.87 BWs (i.e. + 27%) if GateOFFSET to reduce speed by − 0.5 m/s throughout a turn  simultaneously leads to a decrease in RadiusMIN (− 19%), an increase in Impulse (+ 27%) and an increase in GRFMAX (+ 6%). To reduce speed by − 0.5 m/s with a change in GateVERTICAL, compared to GateOFFSET, a much smaller percentage change is required . Further, shortening GateVERTICAL to reduce speed by − 0.5 m/s causes a much smaller reduction in RadiusMIN (− 4%) and Impulse (− 2%), and no increase in GRFMAX.The main findings of this study were: increasing GateOFFSET and decreasing GateVERTICAL lead to a reduction of speed; however, for the same speed reduction (− 0.5 m/s) the required percentage changes are almost four times higher for GateOFFSET (+ 51%) than for GateVERTICAl (− 13%), while the absolute changes are similar  in terrain incline reduced speed by 0.5 m/s, which is in line with previous observations in other disciplines28. However, as entrance speed and terrain are only indirectly modifiable by course setting for a specific race venue, they must be considered as important confounders rather than manipulatable prevention approaches.Similar to the findings of earlier studies in slalom and giant-slalom, higher entrance speed led to a higher speed reduction (energy dissipation) throughout the turn. This finding further supports the presence of a so called "velocity barrier"; the idea that skiers need to dissipate energy (control speed by braking) at certain points along the course in order to avoid making mistakesGateOFFSET or decreasing GateVERTICAL. However, the different percentage-wise impact on speed-reduction (larger for decreasing GateVERTICAL) is not the only relevant aspect in the decision of whether to control speed by adjustments in GateOFFSET or GateVERTICAL. As shown in this study, the increase in GateOFFSET to reduce speed by 0.5 m/s resulted in an adverse decrease in minimal turn radius, an increase in maximal ground reaction forces and an increase in impulse  appear much higher than those achieved with modified ski equipment15. To date, it has not been scientifically investigated whether a clothing-induced increase in air drag could adequately reduce speed in the speed disciplines31. Additional padding and use of race suit fabrics with higher air drag coefficient would increase air drag and are likely to reduce speed. Padding might also improve crash impact absorption. Snow properties may also have substantial impact on speed32, but these are only partly in the race organizers’ hands, especially in SG and downhill, where courses are long and environmental factors play an important role in the generation of snow properties.The results of this study show that course setters can control and reduce speed by either increasing se Table . As thes10 and consequently the impact energy in impact accidents is only slightly lower than in Downhill; (2) courses are technically more challenging; and (3) skiers do not have training sessions on the courses prior to competitions as is the case in Downhill. More specifically, Super-G courses are steeper, include more turns with smaller radii and more frequent and more pronounced terrain transitions10. Ground reaction forces are higher and the total physical load (impulse) of a competition is only 13% lower than in downhill25. Super-G courses also include an average of 2.3 jumps (4.2 for downhill), with jump length being only 21% and airtime being only 6% shorter than in Downhill14. Hence, jumps in Super-G can be as challenging as in Downhill, since a given rotation impulse at take-off can cause nearly the same off-balance rotation as in Downhill14.Preventing injuries in Super-G is challenging, since (1) mean speed is only slightly lower (− 2 m/s) than in Downhill33; mostly on easier and shorter slopes than in competition. In this connection, the findings of the current study may help course setters to develop a better understanding of how to set safe courses and adequately control speed in Super-G.In Downhill it is a safety requirement that athletes need to participate in at least one official training run on the course prior to competition to become familiar with the course. In Super-G athletes only have the opportunity to inspect the course some hours prior to competition and need to anticipate their skiing strategy and find a balance between performance and safety. Preventing injuries in Super-G is not only difficult for skiers, but also for organizers and course setters. In Downhill, course setting is kept similar from year to year, which allows organizers to learn and improve courses over the years, while Super-G courses are set differently by different coaches each year and change accordingly. Hence, course setters and the race directors of the International Ski Federation FIS, who carry the ultimate responsibility for course safety, have no opportunity to test the Super-G course for safety prior to competition. Therefore, experience in course setting is important. However, this might take years to build, since WC coaches only set about 40 Super-G training courses per yearThere are some limitations to be aware of when interpreting the study findings:18. This leaves us with the problem that we cannot provide information on how adjustments in course setting depend on terrain incline. Second, the study analysis did not look at the interaction of consecutive turns or entire course sequences and hence, experimental course set testing for a given situation seems indicated. Third, the applied dGNSS methodology did not provide direct data describing the influence of course setting on the mode of ski–snow interaction. Thus, we can only speculate as to why speed is reduced as a function of ski–snow interaction. Future studies should investigate the effect of course setting on skidding and the underlying ski–snow interaction in more detail. For the four races, three different athletes were employed as forerunners. The effect of forerunner however was compensated for in the mixed model.First, the number of turns was not sufficient to split the analysis into terrain incline sub-groups as shown in a similar study on GSSupplementary Information.


This research developed an effective and efficient approach for improving the slow convergence in the scattering analysis of a one-dimensional graphene grating, made of a periodic array of parallel graphene strips, illuminated by a TM-polarized plane wave. Specifically, the electric fields over the graphene strips and slit regions in a unit cell are individually expressed as an expansion of local basis functions inherently satisfying edge conditions. Interestingly, convergence rate is highly improved compared to the customary and modified Fourier modal method. Additionally, with the aid of local basis functions, the Gibbs phenomenon occurring at both edges of graphene strip can be removed. Moreover, graphene-based grating composed of graphene sheet has been a continued research interest14 in both theoretical studies and practical applications in recent years.The plane wave scattering by a one-dimensional (1D) grating made up of dielectric or metallic mediums has been intensively and extensively studied. Some numerical methods such as the rigorous coupled-wave analysis (RCWA)1 is known to be slowly converging for 1D metallic gratings in TM polarization . Fortunately, the inverse rule, by invoking adequate Fourier series of the permittivity and reciprocal permittivity functions of a periodic medium to reformulate the eigenvalue problem, was developed to achieved a highly improved convergence rate for the scattering analysis of a metallic grating in TM polarization18. Additionally, the Floquet modes in a periodic medium with the unit cell composed of a dielectric slab and a metal layer having finite conductivity can be determined by solving the dispersion equation19. However, finding their complex roots is a difficult task. Consequently, use of Fourier series expansion to calculate Floquet modes in a periodic medium, in general, is the most reliable and effective approach in handling a diffraction grating problem.In the RCWA method, both the permittivity function of a periodic medium and electromagnetic fields are expanded into Fourier series and Floquet-Fourier series, respectively. Therefore, the electromagnetic boundary-value problem can be converted into an eigenvalue problem. Such an approach is efficient in handling the grating with an arbitrary profile and a finite stack of multiple gratings, as well. However, the RCWA methodnm); therefore, the electromagnetic fields are merely in the upper and lower homogeneous mediums, as shown in Fig. x-axis, electric and magnetic fields can be presented in the standard form of Floquet-Fourier series (or Rayleigh expansions). Moreover, the electrical property of graphene strips can be modeled with a surface conductivity  throughout this paper.In this paper, we aimed at studying the numerical convergence of plane wave scattering by a graphene grating in TM polarization. Here, the structure under study is a 1D periodic array of graphene strips (ribbons) deposited on a dielectric substrate. The graphene sheet is assumed to be near-zero thickness  that takes into account the effective conductivity due to the displacement current in slit region without graphene. The effective conductivity is non-zero everywhere; therefore, the inverse rule can be successfully applied. Although FMM with ABC convincingly achieves numerical convergence, the convergent value varies in accordance with the enclosed-loop height (h), shown in Fig. h.Unfortunately, the poor convergence occurs in conventional FMM for the scattering analysis of periodic arrays of graphene ribbons reported in the literatureIn this research, the respective local basis functions (LBFs) taking into account the electric-field edge conditions over the graphene-strip and slit regions in a unit cell are developed to replace the global basis functions (Floquet–Fourier series in a homogeneous medium). As will become clear later on, the tangential electric-field expanded by the local basis functions exhibits the fidelity of discontinuous behaviour, which is not seen in the conventional FMM, enabling a fast convergence in the scattering analysis of graphen-strip gratings in TM polarization.This paper is organized as follows. We begin with the mathematical formulation using the conventional FMM that is taken as a general framework for theoretical analysis. Moreover, ABC is employed to reformulate the FMM by invoking the inverse rule. Additionally, the present approach, namely, FMM incorporating LBFs, will be comprehensively elaborated. Finally, convergence behaviour will be examined for the three aforementioned methods. Specifically, electric field distribution on graphene grating surface will be demonstrated for various incident conditions.y-axis and the electromagnetic fields have no variation along that direction. The strip width and period along the x-axis are denoted as Figure 11:e is the electron charge, T is the ambient temperature.Incidentally, graphene conductivity (x-axis can be represented by Rayleigh expansions (or Floquet–Fourier series) in the form5z-axis In a homogeneous medium, the electric and magnetic field components of TM polarization in the presence of periodicity 16 and equaling the same Fourier coefficient corresponding to the same harmonic on both sides, one obtains the system of linear equationsm is running from negative to positive infinity.Owing to the zero thickness approximation of the graphene grating, discontinuity in the tangential component of magnetic fields at the interface (graphene grating surface) between two uniform mediums equals to the conduction current induced on the graphene strips array, yieldingy in Eq.  and condn in Eq. . Using Lm, n) entry Equation  can be en in Eq. ; the \do5. Equation ,,\documenough Eq. . One obtwith Eq. , one obtNotably, for a graphene grating incident by a single plane wave, the wave vector via Eqs.  and 18)\documentz-axis over a grating period is defined asMoreover, the time average Poynting power along the n runs from − N is denoted as truncated order. The total number of space harmonics is then designated as Notably, the mathematical formulation in FMM is rigorous and the result is exact when the space harmonic index 16, the slow convergence in the RCWA for TM polarization is not caused by the Fourier series expansion but the form where the Fourier series of the permittivity and the reciprocal permittivity functions are utilized. The same problem also occurs in graphene gratings with thickness of almost zero. Nevertheless, the inverse rule16 is not applicable in the graphene grating because 20 in slit region. In doing so, the reciprocal function H) on the graphene grating between two uniform mediums equals to the sum of conduction- and displacement-current. At the left-hand side of Fig. x-axis; while it equals to the displacement current filled in the rectangular box at the right-hand side figure. Combining these two results, Eq.  entry of Now, the reciprocal function mentclasspt{minimah is still a core factor affecting the value of convergence, as will be demonstrated in the next section. Moreover, the criterion for determining the appropriate h remains to be studied in detail. So far, we have implemented a computer program based on FMM with ABC for calculating the scattering characteristics of a graphene grating as well as the electric-field  to use only a few basis functions to approach the correct solution, and (2) to have closed forms in the overlap integral between the local basis functions and the space harmonic in Eq. .n is ranging from 1 to More specifically, the 22. They are expressed as follows:n runs from 0 to On the other hand, in the slit region, we have the singular basis functions with singularities at its two edges, which are commonly used to approximate the current parallel to the edges in a micro-strip linely, Eqs.  and 24)22. They In a unit cell on the graphene grating surface (at m is ranging from -N to +N. The notation of a(x) and b(x) in the range of sinc(x) is the unnormalized sinc function defined as n is the index of the local basis function.Due to electromagnetic boundary condition,  of Eqs.  and 25)\documentG]] and [[S]] have the size 19, therefore, we have round[.] rounds a real number towards the nearest integer. In doing so, we have a square matrix Equation x-axis, one obtainsSubstituting of Eqs.  and 25)25) into  and Eq. , the sysAfter performing matrix operations with Eqs.  and 34)34), we oHere, we obtain a totally different admittance matrix while the input-output relation in Eq.  remains _ in Eq.  can be rFurthermore, the power dissipated on the graphene strips array can be directly determined byA free-standing graphene-strip grating is taken as an example to examine the convergence behaviour for the three approaches. The parameters of graphene are N running from 1 to 200. In Fig. h) in FMM with ABC are considered: 20, the conventional FMM (green dotted curve) indeed runs into the serious problem of oscillating convergence behaviour. On the other hand, the FMM with ABC can improve the convergence rate; however, the convergent value changes with h accordingly. Interestingly, the result with We first calculate the absorptance against the truncated order N) are used to examine the performance of numerical convergence. It is obvious to see that FMM with ABC (yellow solid curve) and our approach (purple solid curve) agree very well for the case of Additionally, the absorption versus frequency for both convincing methods including the FMM with ABC and our approach are demonstrated in Fig. x in a unit cell on the graphene grating surface. The red dotted curve is calculated based on FMM with ABC, while the solid curve in blue colour is obtained using FMM incorporating LBFs. The region for x-direction. Therefore, the induced current exhibits the first normal mode (standing wave) pattern. It is very similar to the current induced on a radio-frequency (RF) dipole antenna excited at its first resonant frequency.Figure  in Eqs.  and 24)\documentx-axis was demonstrated for the five cases with different incident angles including 0°, 15°, 30°, 45°, and 60°, respectively. Fig. 13, the resonance effects are in connection with the leaky plasmonic modes existing in individual graphene strip but with weak coupling between strips. Such a normal mode is a source-free solution; therefore, its mode pattern is almost independent of the incident angle. Contrarily, the asymmetric distribution is observed in the slit region for oblique incidence, which maybe caused by unbound waves with continuous spectrum.Since the approach of FMM incorporating LBFs can effectively remove the Gibbs phenomenon, it should be in a good position to observe the effect of incident angles on the electric field  in conventional FMM disappears. Furthermore, the convergence rate of the present approach is superior to the other two methods. Additionally, a new admittance matrix is obtained in the present approach while the whole formulation can still fit into the standard procedure of FMM. Significantly, the inverse rule and ABC for FMM are no longer needed. Such an approach can drastically reduce the required number of space harmonics and is more efficient for scattering analysis of stacked multiple graphene gratings.


Redundancy analysis identified specific conductivity, dissolved oxygen, agricultural land, ammonium, urban land, and water transparency as the dominant environmental factors influencing the bacterioplankton communities in the Pearl River. Variation partitioning analysis indicated that both physicochemical factors and land use had direct effects on the bacterioplankton community, and that land use may also shape bacterioplankton communities through indirect effects of physicochemical factors on riverine ecosystems. This study provides fundamental information on the diversity, spatial patterns, and influencing factors of bacterioplankton communities in the Pearl River, which should enhance our understanding of how such communities change in response to environmental gradients and anthropogenic activities.River ecosystems are critical for human and environmental health, with bacterioplankton playing a vital role in biogeochemical cycles. Unveiling the spatial patterns of bacterioplankton communities in relation to environmental factors is important for understanding the processes of microbial variation and functional maintenance. However, our understanding of the correlations among bacterioplankton communities, physicochemical factors, and land use, especially in large rivers affected by intensive anthropogenic activities, remains relatively poor. Here, we investigated the bacterioplankton communities in July 2018 in three main tributaries of the Pearl River, i.e., Beijiang, Xijiang, and Pearl River Delta, based on 16S rRNA high-throughput sequencing. Results showed that the most dominant phyla, Proteobacteria, Actinobacteria, Cyanobacteria, and Planctomycetes accounted for 33.75%, 22.15%, 11.65%, and 10.48% of the total abundance, respectively. The bacterioplankton communities showed remarkable differences among the three tributaries in terms of composition, structure, diversity, and predictive functional profiles. Mantel and partial Mantel tests revealed that the bacterioplankton communities were affected by physicochemical variables ( The microbial community is a key component of aquatic ecosystems and plays an important role in biogeochemical cycling processes such as ammonia oxidation, nitrification, sulfate reduction, and methane production ,2,3,4. URiver ecosystems are critical for human and ecological health. They are a major source of drinking water and provide irrigation for agriculture, habitat for fish, and space for recreation. Rivers also offer important freshwater habitats for microorganisms. Bacterioplankton communities exhibit complex responses to environmental stresses and disturbances, as manifested by changes at both the population and community levels ,13. Many9 m3, including 7 × 109 and 2 × 109 m3 of domestic and industrial wastewater, respectively [The Pearl River is the largest river in southern China, stretching some 2400 km in length . The rivectively . Such waectively . Althougectively ,23,24,25In this study, we analyzed the bacterioplankton communities in three main tributaries of the Pearl River in July 2018, a typical flood season, using 16S rRNA high-throughput sequencing. We aimed to (1) characterize the composition, diversity, and spatial patterns of bacterioplankton communities in the Pearl River and (2) elucidate the roles of physicochemical factors and land use in shaping these communities. To the best of our knowledge, this is the first study to report on the effects of land use and physicochemical factors on bacterioplankton communities in the Pearl River, which should enhance our understanding of how aquatic ecosystems change and function in response to environmental gradients and anthropogenic activities.A total of 30 water samples were collected in July 2018 from 15 sites ; SK, YD, LF, QY, LB for Beijing River (BJ); and SH, GM, JJ, WH, ZZ for Pearl River Delta (PRD)  along th4-N), nitrate (NO3-N), nitrite (NO2-N), total phosphorus (TP), phosphate (PO4-P), chlorophylla, and suspended solids (SS), were measured in the laboratory following standard protocols [Physicochemical variables, including dissolved oxygen (DO), temperature, salinity, pH, total dissolved solids (TDS), specific conductivity (SpC), and oxidation-reduction potential (ORP), were measured in situ with a YSI multiparameter probe . Water transparency (cm) was measured by a Secchi disk  (20 cm diameter). Ammonium  (2016–2018) were used to determine land use cover. The satellite images were corrected and stitched in ENVI 5.3 , and then they classified into land use types using knowledge-based supervised and maximum likelihood classification methods. Land use was classified into agricultural land, forestland, grassland, urban land, highway, and bare soil. The 1:100,000 scale map of land use was then interpreted. ArcGIS 10.2.2  was applied to extract land-use percentages using a 10 km × 2 km buffer zone upstream of the sampling points.Satellite datasets from the Landstat 8 OLI database . The 16S rDNA V3-V4 hypervariable region was amplified using primers 341F (CCTACGGGNGGCWGCAG) and 806R (GGACTACHVGGGTATCTAAT). After being quantified with QuantiFluorTM fluorometer, purified amplicons by PCR were pooled in equimolar amounts and paired ends were sequenced (2 × 250) on an Illumina HiSeq2500 platform according to the standard protocols at Gene Denovo Biological Technology Co. Ltd. . The 16S high-throughput sequencing raw data was uploaded in the NCBI Sequence Read Archive with accession no. PRJNA579235.The raw reads were filtered using FASTP. Paired-end clean reads were then merged using FLASH v. 1.2.11 . Noisy sPhysicochemical factors and land use were analyzed by principal component analysis (PCA) to identify potential spatial patterns in the different tributaries.p < 0.05).Alpha diversity, including Good’s coverage, Abundance-based Coverage Estimator (ACE), Chao1, Simpson, and Shannon indices, were calculated via QIIME. Differences in diversity indices among the different tributaries were examined with Kruskal–Wallis tests for global comparison and Wilcoxon tests for pairwise comparisons (http://huttenhower.sph.harvard.edu/lefse/).Nonmetric multidimensional scaling (NMDS) and analysis of similarity (ANOSIM) were performed to compare bacterioplankton communities based on the Bray–Curtis dissimilarity index using the Vegan package in R . Linear The Mantel test was used to examine the correlation between the environment  and bacterioplankton communities, and a partial Mantel test was used to determine the relationship between a certain type of factor  and bacterioplankton community, controlling for the effects of other factors . The Mantel and partial Mantel tests were conducted with the Vegan package . RedundaFunctional changes in the bacterioplankton communities among the different tributaries were predicted using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) . Rarefie4-N. Axis 2 was highly positively correlated with highways and forests, and negatively associated with agricultural land.Spatial variations in 15 physicochemical factors and six land use types were analyzed by PCA to identify differences among tributaries . The fir4N were relatively higher in BJ than in XJ and PRD, whereas DO and ORP were relatively higher in XJ than in BJ and PRD. PRD had relatively higher values for agricultural land, urban land, SS, and NO2N, but lower values related to water transparency, forests and highways.Both XJ and PRD were close to each other, but distant from BJ A. BJ washgcI_clade, CL500-29_marine_group, Planctomyces, Synechococcus, Aquabacterium, Ideonella, Exiguobacterium, CL500-3, Polynucleobacter, and Acinetobacter, which accounted for 10.81%, 6.03%, 3.84%, 3.71%, 3.25%, 1.92%, 1.86%, 1.74%, 1.33%, and 1.23% of total bacterioplankton community, respectively  among the three tributaries, whereas diversity indices (Shannon and Simpson) showed significant spatial variation . The Shap < 0.01). The BJ group was separated from the other groups, whereas XJ and PRD demonstrated partial overlap. These spatial patterns were consistent with environmental factors , and Dechloromonas (genus), were identified as potential biomarkers for PRD , Methylophilaceae (family), Candidatus for PRD . Genera r = 0.638; p = 0.001). Partial Mantel tests revealed that the bacterioplankton communities were affected by both physicochemical variables  and land use . Forward selection and Monte Carlo permutation (499 iterations) of RDA showed that environmental variables SpC , DO , agricultural land , NH4-N , urban land , and water transparency  significantly influenced the Pearl River bacterioplankton communities . The conditional effect of physicochemical variables was 42.6% . The conditional effect of land use was 8.9% . The shared effect of these two groups was 6.1%. In total, 42.4% of variation remained unexplained. The Mantel tests indicated that environmental factors significantly shaped the bacterioplankton communities , multifunctional diversity also increased, but when OTU diversity approached 8, multifunctional diversity reached saturation, indicating functional redundancy within the bacterioplankton communities , and Dechloromonas (genus) were mainly restricted to PRD . NO2-N, TP, and PO4-P are essential nutrients for primary production and microbial growth [Anthropogenic factors such as agricultural and urban land use significantly contributed to the variability in the bacterioplankton communities among the three tributaries. This result may be explained by both direct and indirect anthropogenic influences on bacterioplankton community compositions. Firstly, bacteria may enter riverine waters directly through a variety of point and non-point sources such as urban runoff, wastewater treatment plant outflows, and agricultural areas ,55. The l growth ,61. SuspThis study investigated the bacterioplankton communities in July 2018 in three main tributaries of the Pearl River, i.e., Beijiang, Xijiang, and Pearl River Delta, based on 16S rRNA high-throughput sequencing. We revealed that the three tributaries formed distinct bacterioplankton communities in relation to the environmental gradients. Both physicochemical factors and land use had direct effects on the bacterioplankton communities, and land use may shape bacterioplankton communities through indirect effects of physicochemical factors on the riverine ecosystem. However, physiochemical factors outweighed land use in structuring bacterioplankton communities in this large subtropical river. This study provided fundamental information on the diversity, spatial patterns, and influencing factors of bacterioplankton communities in the Pearl River, which should enhance our understanding of how bacterioplankton change in response to environmental gradients and anthropogenic activities. However, as the current study only covered one season, future studies are needed to provide insight into microbial communities and functions at both the spatial and temporal scale, including biological factors and other physicochemical variables.


The results obtained in the course of development and the results of testing of the graphene-based sensor for detection of protein molecules are also presented. The biosensor was fabricated by the technology previously developed for the gas sensor. The working capacity of the biosensor was tested with an immunochemical system constituted by fluorescein and monoclonal antibodies (mAbs) binding this dye.This work is devoted to the development and optimization of the parameters of graphene-based sensors. The graphene films used in the present study were grown on semi-insulating 6H-SiC substrates by thermal decomposition of SiC at the temperature of ~1700 °C. The results of measurements by Auger and Raman spectroscopies confirmed the presence of single-layer graphene on the silicon carbide surface. Model approach to the theory of adsorption on epitaxial graphene is presented. It is demonstrated that the Green-function method in conjunction with the simple substrate models permit one to obtain analytical results for the charge transfer between adsorbed molecules and substrate. The sensor structure was formed on the graphene film by laser. Initially, a simpler gas sensor was made. The sensors developed in this study demonstrated sensitivity to the NO The discovery of graphene and the study of its properties is one of the brightest pages in the development of solid-state physics over the past 15 years. This discovery sparked the emergence of a whole class of two-dimensional structures, of which graphene is still the most-studied material. The exfoliation method, used by K. Novoselov and A. Geim in their first work on the preparation and study of graphene, is reduced to the separation of a one-atom-thick flake from a graphite crystal. Until now, graphene samples obtained by this technology have had the best structural perfection. It was on these samples that the most important results were obtained, which confirmed the two-dimensional nature of this material. However, their small size and irregular and unpredictable geometrical shape in advance do not allow the exfoliation method in industry.Graphene films obtained by thermal destruction of the surface of silicon carbide are the second in terms of structural perfection. Thus, it is possible to obtain structures up to industrially important dimensions; in this case, the dimensions are limited only by the initial SiC substrate, i.e., up to 6 inches (150 mm) in diameter.High mobility of charge carriers in combination with their low concentration;The maximum possible ratio of surface area to volume;Low noise level.Theoretical and experimental studies show that graphene has a unique set of electrophysical properties:The combination of these properties leads to the fact that the addition of a minimal amount of impurity to the graphene surface can noticeably change the conductivity of the graphene film. Thus, graphene is a very promising material for the manufacture of various types of sensors.In this work, we discuss the technology of forming a biosensor based on a graphene film obtained by thermal destruction of the surface of silicon carbide. A brief review of the model approach to the theory of adsorption on epitaxial graphene is presented. New results obtained by detecting various types of biological molecules with a graphene sensor are analyzed.After appearing in a previous paper , where iWe begin with the adsorption on single-layer free-standing graphene. As far as we know, the first corresponding model was put forward in ,16. In tgiven in ,16).At zero temperature the occupation number or ω<−3t . If initNow turn to the epitaxial graphene (epigraphene) model description. The simplest approach is described in . The fir3a) . Such a (ω) from ,16.General expression for the epigraphene DOS is given byHere given in .There are two limiting regimes for the graphene–substrate interaction: Strong coupling, when given in . It is cIt is easy to understand now that for the DOS of particle adsorbed on epigraphene, formula (1) has to be rewritten in the formshown in  that thee is the elementary charge, l is the adparticle bond length, and Up to now, we considered adsorption of a single particle at zero temperature. For finite coverages nd A¯~10 . It is wussed in .n-type substrate or, conversely, decrease (increase) the conductivity of a p-type substrate. Second, the adsorbed particles (adparticles) serve as additional scattering centers, which generally must influence the surface mobility The effect of adsorption on the substrate appears in mainly two effects. One is the change l oxides ,24. A thloped in ,26, wherAnalysis ,26 of exIn , we haveInterest in graphene flared up after the publication of K.S. Novoselova, A.K. Geim et al., In which they demonstrated the possibility of obtaining graphene sheets using micromechanical cleavage of bulk crystalline graphite . This wa8 Ω cm. Schottky diodes based on the graphene/SiC structure, obtained by thermal destruction of SiC substrates, are characterized by high uniformity of characteristics.Until now, graphene samples obtained by this technology have the best structural perfection. It was on these samples that the most important results were obtained, which confirmed the two-dimensional nature of this material. However, their small size, irregular, and unpredictable geometrical shape in advance do not allow their use in industry. Graphene films obtained by thermal destruction of the surface of silicon carbide are the second in terms of structural perfection. Thus, it is possible to obtain structures up to industrially important dimensions; in this case, the dimensions are limited only by the initial SiC substrate, i.e., up to 6 inches (150 mm). The orientation of the obtained graphene films is specified by a SiC substrate, which makes it possible to obtain graphene films with a large area with a preferential azimuthal orientation of domains. This method is based on the dissociative evaporation (sublimation) of SiC components from the surface of a single crystal and the formation of a graphene film from residual carbon atoms  The phenGraphene films grown by CVD on a metal foil are in third place in terms of their structural perfection . This meThe main disadvantage of the method of thermal destruction of the SiC surface is the high cost of SiC substrates. However, the high structural perfection of graphene obtained by the thermal destruction method, as well as the possibility of growing graphene on high-resistance substrates, neutralize this disadvantage.Dissociative evaporation or sublimation of SiC is one of the most important processes that determine the growth of crystals and epitaxial films of this material from its own vapors. The work of S.K. Lilov  presentsAn important step in obtaining a graphene film is the selection of a SiC substrate that will be used for the thermal destruction process.The first criterion for choosing substrates is their crystal perfection. To obtain homogeneous graphene, substrates with a homogeneous crystal structure are required; therefore, it is preferable to use single-crystal SiC substrates. Various structural defects, such as dislocations, micropores, stacking faults, polytypic inclusions, low-angle boundaries, etc., can also negatively affect the uniformity of graphene growth on the substrate surface; therefore, it is necessary to choose substrates with a minimum density of structural defects.The second criterion for choosing substrates is the surface roughness on which graphene growth is planned. Today there are several stages of surface treatment of SiC wafers: Grinding, mechanical polishing, and chemical-mechanical polishing.H and 4H-SiC substrates with a minimum misorientation angle (α ~ 0), the growth was carried out on the (0001) face (Si face). We used semi-insulating (high-resistivity substrates), since they did not require the transfer of a graphene film onto a non-conducting substrate in the further manufacture of sensors.The third criterion for choosing substrates is the crystallographic orientation of the substrate surface, as well as the angle of deflection of the substrate surface from the basal plane . In our experiments, we used 62 and 11 × 11 mm2 in size. Modern commercial SiC wafers are in standard sizes of 2, 3, 4, or 6 inches. The use of such large samples for laboratory research is not profitable, because, firstly, the cost of the material is quite high, and secondly, the characterization of large samples takes a lot of time. Therefore, in order to carry out experiments on developing the technology of graphene growth, the wafers were cut using special equipment for cutting semiconductor substrates into typical specimens 5 × 5 mmxCy components from the substrate surface. Various surface contaminants or surface irregularities of the substrate can contribute to the sublimation process, leading to nonuniform sublimation of molecules from the substrate surface. For the successful development of graphene growth technology, a necessary condition is a high-quality preparation of the SiC surface, which reduces the effect of contamination and surface inhomogeneities on the sublimation process. The growth of graphene on the SiC surface is accompanied by the sublimation of the SiPre-growth etching in a hydrogen atmosphere was used for preliminary cleaning of the SiC substrate surface. The method has been known for a long time ,9 and isTo enable the etching of SiC substrates “in situ” before graphene growth, this technology was adapted to a technological unit for the growth of graphene on SiC. The adaptation consisted in changing the composition of the gas mixture in which the etching is performed, as well as in the selection of a certain technological mode of etching.3H8 [Typically, for etching, the chamber is purged with either pure hydrogen  or with 3H8 . In our The grown graphene samples were characterized by using a combination of three methods: Raman spectroscopy, atomic-force microscopy (AFM), and Kelvin-probe force microscopy (KPFM).2 with spatial resolution of 1 μm. The measurements were carried out at room temperature using a T64000 Raman spectrometer  equipped with a confocal microscope. The spectra were excited using the 532 nm Nd:YAG laser. . To avoid heating and damage to the sample, the laser power was limited to 4 mW. Two main features in the presented spectra, namely the sharp and intense G and 2D lines, are originating from the graphene film [−1 range corresponds to the buffer layer, which is an interface carbon layer located between the graphene film and the 4H-SiC substrate [Raman spectroscopy is widely used as a graphene characterization tool. Analysis of the data obtained by these methods allows one to determine such properties of graphene as number of layers, degree of defectiveness, strain and doping levels, and many more. ene film , while tubstrate .D line, the appearance of which is indicative of presence of structural defects [The  defects , in our D line allows one to easily distinguish monolayer graphene from bi- and multilayer by analyzing the shape of this line. D line FWHM distribution. In the regions with FWHM (2D) between 35 and 40 cm−1, this line had a symmetric Lorentzian form, which pointed to the monolayer nature of graphene in corresponding areas [D line FWHM was increased, the line had an asymmetric shape similar to that reported for bilayer graphene [Double-resonance nature of the 2ng areas . In the graphene  and coul2 area of the sample is shown on An AFM topography map of the 12 × 12 μm2 area of the studied sample is shown in Distribution of surface potential is also capable of providing information on graphene thickness. It is known that the surface potential of bilayer graphene is ~100 mV higher than that of monolayer . The KPFIt was shown in  that graTo clean the graphene detector, a current of about 10 mA is passed through it this is enough to heat the structure so that the gas particles are desorbed. This cleaning mechanism does not affect the degree of efficiency of gas detection: The process of sorption-desorption of gases is completely reversible, that is, it is a reusable detector. It should be noted that, in ,42 Figu. Excess o is the initial resistance in the absence of a detectable gas in the incoming air flow.Purified air was used as a carrier gas. Sensor sensitivity (r) was expressed as a percentage, %, and is defined as the relative change in the sample resistance in the presence of a recorded gas in the gas mixture:2 in the gas mixture (periods of gas supply are indicated as light gray stripes) at 20 °C. Since the NO2 desorption rate at room temperature is very low, annealing at 110 °C was used to return the sensor to its original state after each exposure period [e period ,44.2 concentration of 10 ppb, the amplitude of the sensor response was about 3% when exposed to the gas mixture for 1 h Such sensitivity of the sensors is quite sufficient for environmental monitoring.For NOIt should be noted that one of the serious disadvantages of the graphene gas sensor is the lack of selectivity. Indeed, it is impossible to tell from the change in conductivity which molecule was adsorbed on the graphene surface. Moreover, some molecules give contributions of the opposite sign, so the total change in resistance can be close to zero.A distinctive feature of the graphene film is that the molecules or a group of atoms adsorbed on its surface act as a donor or an acceptor, leading to a change in its electronic state (resistance), which can be detected . This spHowever, the graphene film itself is not a selectively sensitive sensor and can attach various substances and biomolecules to its surface. To use graphene as a biosensor, a special treatment is used, which increases the selectivity of chemical reactions on the graphene surface and creates additional covalent bonds for chemical reactions with other molecules that need to be detected.The antibody–antigen (Ab-Ag) interaction is fundamental to the functioning of the human immune system . ReactioThe concept of the graphene/SiC biosensor developed in his work is based on the creation of conditions for a controlled Ab-Ag interaction on the graphene surface in graphene/SiC chips. It is this interaction that leads to a change in the electronic state of graphene (its resistance), which can be registered. The developed concept of a biosensor is universal for the detection of protein compounds and viruses Only complementary (related) antibodies and antigens take part in the interaction reaction, which achieves the selectivity of the biosensor. To provide biosensing ability, graphene/SiC films are undergoing multistep processing and treatments.H-SiC a size of 11 × 11 mm2. The growth process was carried out in a graphite crucible with induction heating in an argon atmosphere (720–750 Torr) at a temperature of 1700–1800 °С [Graphene films were grown by thermal decomposition of semi-insulating substrates (0001) ± 0.25° 4–1800 °С . The metD) (AFM) images of graphene/SiC samples. A set of elongated terraces having different width are clearly seen in the morphology image of the surface. These steps can facilitate attachment to graphene of large  antibodies of viruses.The presence of the graphene monolayer on the SiC substrate was confirmed by Raman spectra. A specific feature of the morphology of SiC surface after graphene growth is the presence of terraces on the surface, the width and height of which depends on the conditions of graphene growth. As example, 2 chips, which after that were mounted on a holder and welded with gold wires. After that, all current-carrying parts of the holder and contact pads of the chip were covered by a protective varnish. The protective varnish is a compound based on thermo reactive resins with various fillers and additives (VT-25-200). Sensing area of the chip was 1 × 1 mm2 or so.After the graphene film growth and characterization, graphene/SiC chips (dies) were processed for manufacturing biosensors. The processing includes standard photolithography using dry etching, metallization, cutting the substrate into individual chips, and mounting them on a holder. A rectangular chip topology was formed on the surface of a graphene/SiC sample by laser photolithography in combination with ion-reactive etching in argon and etching in oxygen plasma. Ti/Au contacts (5 nm/50 nm) were created by vacuum deposition and explosive photolithography. Then, the graphene/SiC sample was cut into individual 1.5 × 2 mmI-V) characteristics of the manufactured chips were linear, which indicated ohmic contacts and the absence of potential barriers on the contacts that could affect the measurement results.The current-voltage  and their subsequent reduction to phenylamine groups (aminobenzene C6H4NH2) using a two-steps cyclic voltammetry (CV) process [In this project, the process of functionalization of the graphene surface in the chip will be carried out in two stages by creating covalent bonds during the deposition of nitrophenyl groups  (0.025 mg in 50 mL of acetonitrile) and tetrafluoroborate (tetrabutylammonium) tetrafluoroborate (TBA 1.65 g in 50 mL of acetonitrile). The electrochemical reaction between the graphene surface in the chip and the anhydrous electrolyte was carried out in a cell, of which the design allows purging the electrolyte and the space above it with a clean and dry inert gas (argon) to remove traces of moisture from the ambient air. The process was carried out according to a three-electrode scheme. The graphene surface in the chip was a working electrode, a platinum plate served as a counter electrode, and a silver wire (Ag/Ag+) served as a reference electrode.The reaction of attaching of nitrobenzene occurred during cycling of the potential at the working electrode (the graphene surface) in the range from 0 mV to −600 mV and vice versa. In this case, the process current was recorded. At the second step of CV process, the reduction of nitrobenzene attached to graphene to aminobenzene was carried out already in an aqueous solution of 0.1 M KCl and ethyl alcohol (9:1) in an open flask also according to a three-electrode scheme. The electrodes were: A standard silver chloride reference electrode (Ag/AgCl) Esr-10101 , the graphene surface in the chip was a working electrode (anode), and a platinum plate counter electrode. The reduction reaction was also carried out in the mode of cycling the potential on the working electrode from 0mV to −1000 mV and vice versa. After the process, the samples were washed in deionized water and dried in argon. Typical CVs of reduction processes are shown in After functionalization, the deposition (or immobilization) of antibody molecules took place on the created covalent bonds. Then, the graphene surface was passivated (blocked) in a solution of 0.1% BSA in PBS  for 1 hour, followed by washing in pure PBS for 5 minutes. After that, the graphene chip is ready to apply as a biosensor.First, the response of the chip (current through the chip) was investigated during the reaction of complementary antibodies and antigens of the influenza A virus (antibody A-antigen A) on the prepared graphene surface. We used strains of influenza viruses obtained from the Smorodintsev Research Institute of Influenza, St. Petersburg, Russia: influenza virus A/California/07/09 (H1N1pdm09) and influenza virus B/Brisbane/46/15.At the beginning, antibodies to influenza A or B virus were immobilized on chips with functionalized graphene surface for 3 h at 37 °C. The monoclonal antibodies to influenza A or B viruses used in the experiment are directed to nucleoprotein (NP), a highly conserved major protein of the influenza virus associated with RNA (ribonucleic acid). Then, the graphene surface was passivated (blocked) in a solution of 0.1% BSA in PBS  for 1 h, followed by washing in pure PBS for 5 min The graphene chips (sensors) prepared in this way were used in the detection experiments.−15 g/mL to 1 × 10−10 g/mL , 6 dilutions and 12 tubes in total. Since it was initially assumed that chips based on graphene monolayers could be very sensitive sensors, the range of selected concentrations of antigens to be detected was chosen below the detection limit of the PCR (polymerase chain reaction) test widely used in enzyme-linked immunosorbent assay for detecting viruses. This should confirm the advantage of graphene sensors in terms of sensing ability. The experiments described below showed that this choice of the ultra-low concentration range of antigens was justified, and the chips showed their sensitivity down to a concentration of 1 × 10−15 g/mL (1 fg/mL). Note that the work did not set the task of determining the sensitivity limit of the chips being developed for the detection of influenza viruses.Before the sensing experiments, two groups of dilutions were prepared in PBS for influenza A virus and influenza B virus at different concentrations from 1 × 10First, the direct reaction of the complementary antibody and antigen on the surface of graphene in the chip was investigated. The prepared graphene sensor was first incubated with pure PBS , then its response (current passing through the chip) was recorded at DC conditions when, depending on the sensor resistance, a sequence of DC voltage of 20 mV, 40 mV, 60 mV, and 80 mV, was applied between chip contact pads for 20–30 s. Then, a graphene sensor was incubated into a tube with the PBS solution of an antigen A (or B) virus for 20–30 s and its response was recorded. The chip was sequentially incubated in the different antigen virus solutions one by one from low to high concentration of the antigen virus. First, the direct reaction of complementary antibodies and antigen on the surface of graphene in a chip was investigated. An example of the timing diagrams of the chip response during its sequential incubation in PBS solutions of influenza A virus (AV) antigens is given in The data in 2 = 0.96. The dependency in 2 becomes smaller for a DC voltage of 80 mV due to the scatter of the data. We think this scatter reflects the specificity of reactions on graphene surfaces with terraces, which, according to AFM scanning, have the width of up to 1100 nm for chips of this series (EG313). The logarithmic dependence was observed earlier for graphene-based biosensor when studying its response on egg albumin solutions in PBS [The data in s in PBS . Note, iIn continuation of these studies, additional passivation of graphene in an albumin solution (0.1% BSA in PBS) was performed after immobilization of the antibody during the preparation of the chips for the next experiments. In addition, the chips had different widths of terraces on the graphene surface. The timing diagrams of the chip’s response (current through the chip) were similar to those shown in The designations of the chips in this work at different stages of experiments are presented in the −12 g/mL and above. In contrast, EG331-61 chip with wider terraces (up to 4 microns) showed a decrease in chip response with an increase in the concentration of virus A virus antigen with a clear saturation of the response at concentration of 1 × 10−12 g/mL (1 pg/mL) and above.EG313-41 chip, which has a terrace on the surface of graphene about 1 µm wide, shows the dependence of the increased response of the chip (current through the chip) with the concentration of antigen A in the solution that is well approximated by logarithmic function with the parameter R2-0.94. In contrast, the chip with wider terraces (up to 4 microns) showed a decrease in chip response with an increase in the concentration of virus A virus antigen with a clear saturation of the response at concentrations of 1 × 10During the functionalization of graphene, unsaturated covalent bonds are created on its surface that promote to the attachment (immobilization) of the necessary antibodies. At the detection process, only complementary (related) antigens can react with immobilized antibodies noticeably changing the electronic state of graphene. This is the main principle of operation the sensors that are being developed. The interaction of the remaining non-complementary molecules with the graphene surface does not have the character of a chemical reaction, but rather occurs due to weak van der Waals forces, possibly due to defects and imperfections of the graphene/SiC substrate composition. This interaction can be further screened to reduce its effect on the electronic properties of graphene by passivating the graphene surface with neutral molecules like albumin. However, the attachment of molecules to the graphene surface that are non-complementary to the immobilized antibody can have a significant effect on the resulting chip response (current through the chip).We believe that a decrease and saturation of the chip response (current through the chip) in Too small of a number of sites with an immobilized virus A antibody creates conditions when the virus A antigens, the concentration of which is higher than the A virus antigens, are forced to directly attach to the graphene surface due to van der Waals forces, thus significantly affecting the nature of the change in the chip response. Apparently, the graphene surface treatment and graphene functionalization conditions should take into account the specifics of graphene morphology, in particular, the width and height of terraces on its surface.Special experiments were performed to demonstrate specificity of the antibody–antigen interaction on the graphene surface. The experiments were carried out in two stages.The procedure for the first stage of the experiment was the same as described above with one exception. The only difference was that the prepared chip with the immobilized antibody was immersed (incubated) in solutions of non-complementary antigens of viruses. In other words, the chip with the immobilized antibodies of the virus A was immersed in solutions with the antigens of the virus B and its response (current through the chip) was recorded. Similarly, the chip with the immobilized antibodies of virus B was incubated in solutions with the antigen of the virus A.At the second stage of the experiment, the same chip was immersed for 20 s in other solutions but with virus B antigens (second incubation) that were complementary (related) to the antibody virus B immobilized on the chip. The chip response (current through the chip) was also recorded. After the experiments, the responses of graphene chip (current through the chip) were compared and studied.As before, the timing diagrams of the chip response (current through the chip) obtained at both stages of the experiment were similar to those shown in In this case, the spread between the maximum and minimum response values for the EG260-9 chip with narrow terraces (400–600 nm) reaches less than 200 nA, and up to 530–550 nm for other chips with large terraces width.2 0.9–0.97.The results of the second stage of the experiments are shown in −10 g/mL (100 pg/mL), which is possibly due to the saturation of antibodies on the graphene surface by the reaction with antigens in a PBS solution. When approximating the experimental results, this point was not taken into account.For the EG260-9 chip results in For the EG313-15 chip with moderately wide steps on the surface (1 μm), a similar logarithmic dependence was observed in 2 to 0.9 when approximating the experimental results. It should be noted that in this study the EG313 series chips most often showed the dependence of the response on the concentration of antibodies A or B in the form of a logarithmic function (parameter R2 more than 0.9) over the entire range of investigated concentrations.The scatter of the data reduced the parameter R−15 g/mL (1 fg/mL) in PBS solution. A similar maximum response value was observed for the EG331-61 chip in The EG332-13 chip in We attribute this feature to the fact that in highly dilute solutions the antigen interacts not only with immobilized complementary antibody molecules on the surface, but also directly deposited on the graphene surface if the sites with antibodies are located at a great distance from each other or there are simply few of them. The presented results for chips with wide steps in Note also that the passivation of the graphene surface in chips with albumin is necessary rather to saturate the covalent bonds that have not attached the antigen than to passivate the graphene surface . Real pa−15 g/mL to 1 × 10−10 g/mL is shown.In conclusion, a series of experiments on the detection of virus antigens A and B with chips (sensors) based on graphene monolayer films on SiC was carried out. The sensitivity of the chips for the detection of diluted solutions of virus antigens in PBS solutions in the concentration range from 1 × 10The specificity of the reaсtion antibody A—antigen B and antibody B—antigen A on the graphene surface was demonstrated. The results confirm the principle of operation of the sensor based on the reaction of interaction of a complementary antibody and an antigen on the graphene surface. The surface morphology of a graphene monolayer, in particular the width of characteristic terraces, affects the response of the chip (current through the chip) when detecting influenza viruses.The advent of graphene opened a new page in solid state physics—the production and study of two-dimensional materials. The development of research rather quickly raised the question of the possibility of practical application of these materials. It was obvious that the method of mechanical exfoliation, which produced the first samples of graphene, was not suitable for industrial production.In this work, we considered the most promising technology for producing graphene films, namely, thermal destruction of the silicon carbide surface. This technology makes it possible to obtain films with a sufficiently high structural perfection, and when using semi-insulating SiC, there is no need to transfer the grown graphene to a dielectric substrate. To create devices, one can use post-growth technologies common for semiconductor production.The presence of electrophysical parameters of graphene such as the maximum ratio of area to volume, a low concentration of carriers in combination with their high mobility, and a low noise intensity makes it possible to obtain supersensitive resistive sensors on its basis. The practical application of graphene gas sensors is hindered by the lack of selectivity in the registration of various gases. The use of an antigen—antibody pair allows one to solve the problem of biosensor selectivity and opens up very wide possibilities for the use of graphene-based sensors in medicine and biology. This approach may lead to the creation of portable biosensors capable of detecting diagnostically significant markers of diseases in biological fluids in the express analysis mode.


In this study, the three-phase structure consisting of epoxy resin, carbon nanotubes (CNTs), and graphene, which is assumed to be the surface of carbon fiber, was simulated using molecular dynamics. Models in which the CNT number and initial position of CNT are varied were prepared in this study. Relaxation calculation for each three-phase model was implemented, and the movement of molecules was investigated. When CNTs are located between the graphene and epoxy at initial, how the epoxy approaches to graphene was discussed. Besides, interaction energies between CNT/graphene, CNT/epoxy, and graphene/epoxy were evaluated after relaxations. The value of the interaction energy between two individual molecules  among three-phase structure were obtained, respectively, and those mechanisms were discussed in this study. Carbon fiber reinforced plastic (CFRP) uses resin as a base material and carbon fiber as a reinforcing agent. Lightweight, high strength, and high stiffness are the essential properties of CFRP. Therefore, it is used in aircraft, wind turbines, satellites . The excRecently, many studies have been conducted using molecular dynamics (MD) simulations, including several studies on the molecular interface that is related to a component of materials ,37,38,39Yu B et al.  emphasizThere are some studies on the interface of the graphene/CNTs/epoxy resin model ,43. ZhanIn this study, we focused on the interaction between two individual molecules in a three-phase structure and calculated the interaction energy between two individual molecules, considering the influence of another molecule on the three-phase structure. We emphasized the interaction between epoxy resin and CNTs, which are arranged in parallel with graphene, and also emphasized the π–π interaction between benzenes. We observed the behavior of CNTs and epoxy resin and compared the interaction energy between CNTs-epoxy resin and CNTs-graphene. Our overarching aim was to clarify the structure of graphene/CNTs/epoxy resin.x, y, z) =  (Å); CNTs  and , with diameters of 0.5420 and 1.084 nm, respectively. J-OCTA 5.0 software  was used for analysis and VSOP  as the MD engine. J-OCTA5.0 enabled us to create CNTs and to input force field parameters easier. The DREIDING force field parameters were used [We created a full atomic model. To model the three-phase structure, we prepared each molecule: epoxy resin (number of particles: 8960); three graphene sheets of cell size:  =  (Å). We created the graphene with 1944 carbon atoms. Subsequently, three graphene sheets were stacked in the z-direction with cell size:  =  (Å). The molecular structure is shown in We made epoxy resin using bisphenol A diglycidyl ether of bisphenol A (DGEBA), with a molecular weight of 344.4, as an epoxy monomer, and ethylenediamine (EDA), with a molecular weight of 60.10, as the curing agent. The structural formula of each reagent is presented in z-direction and created a total of six types of three-phase structures: (a) two CNTs ; (b) three CNTs ; (c) two CNTs ; (d) two CNTs , considering temperature changes; (e) four CNTs  parallel arrangements; (f) four CNTs  vertical arrangements. In the actual structure, CNTs adhered to the surface of the carbon fiber in a dispersed state. Models with CNTs  parallel and vertical arrangements were prepared, respectively, to simulate a similar structure. The molecular structures are shown in x, y, z) =  (Å). For the model with CNT  in z-direction was 190.0 Å. CNT  had a larger diameter than CNT . Thus, we made room for the entire structure by extending the z-direction of the cell. The graphene placed at the bottom was fixed. We considered periodic boundary conditions in the x, y, and z directions. We arranged the epoxy resin, CNTs, and graphene from top to bottom in the The relaxation calculation procedure for each three-phase structure is presented below:(1) The canonical ensemble which is performed with constant volume, temperature, and number of particles (NVT ensemble) was created at a temperature of 300 K. Step time was 0.5 fs. The total number of steps was 1000. Relaxation time was 2 ns.z-direction. The step time was 0.5 fs. The total number of steps was 1000. Relaxation time was 2 ns. There was an exception; the initial temperature was set to 600 K for one model with two CNTs . Compression was performed, while the temperature was lowered from 600 K to 300 K to investigate the behavior and interaction energy difference when a temperature change from high to low occurred at constant pressure.(2) The isothermal-isobaric ensemble (NPT ensemble) was set at a temperature of 300 K and an atmospheric pressure of 0.1 MPa in the (3) The NVT ensemble was created at a temperature of 300 K. Step time was 0.5 fs. The total number of steps was 1000. Relaxation time was 2 ns. The model with four CNTs  arranged vertically was also examined with the relaxation time increased to 10 ns.The procedure used the Nose-Hoover method for temperature control and the Parrinello-Rahman method for pressure control.After relaxation, the behavior of each molecule was observed, and the interaction energy was derived. The interaction energy between one molecule and other molecules was calculated using Equations (1)–(3), respectively.We also calculated the interaction energy between two individual molecules. The interaction energy between epoxy and graphene in the system was After calculating the interaction energy values, we used absolute values for each of the interaction energy values to make it easier to compare them.We observed the molecular behavior during relaxation in the NVT ensemble. In all six structure types, immediately after starting relaxation, the epoxy resin above the CNTs was drawn toward the fixed graphene. Next, we confirmed the cell compression in the NPT ensemble. The structure after relaxation in the NVT ensemble is shown in xy plane than that of a small-diameter CNTs, and thus we inferred that this was caused by more stable π–π interactions with graphene. Considering temperature, the model subjected to temperature change showed a larger value than the model subjected to a constant temperature. However, it was a numerical value that could be treated as an error. Finally, the amount of interaction energy changed depending on the arrangement of the CNTs. The interaction energy of the model with four CNTs  vertical arrangement was lower than that of the model with parallel arrangements. This is because the epoxy resin did not reach the CNTs at the bottom of the structure, and consequently, the amount of interaction with graphene was lower. The values of We obtained the values of the interaction energy between one molecule and other molecules. The values of xy plane was arranged parallel to the benzene in the graphene. The benzenes arranged in parallel show strong π–π interaction, whereas the interaction between the non-parallel benzenes shows weak π–π interaction [The interaction energy values for eraction . Consequeraction . ConsequWe analyzed a three-phase structure composed of epoxy resin, CNTs, and graphene using MD simulation. First, we confirmed the structure of the molecules after relaxation. The epoxy resin penetrated in between the small-diameter CNTs but did not penetrate in between the large-diameter CNTs. In the model with the CNTs arranged vertically, it was observed that the epoxy resin didn’t reach the graphene because the CNTs become an obstacle. Furthermore, we obtained the interaction energy between two individual molecules. The interaction energy value increased as the CNT diameter increased and also as the number of CNTs increased. Based on


Background: In light of the COVID-19 pandemic and resulting demand for innovative hospital management we organized an interactive online discussion for medical students and healthcare professionals about hospital management during the crisis.Objective: The event offered an opportunity to learn from a hospital crisis management. We looked at how this new online format compares to a traditional discussion event. Methods: We used an online platform with four guests, a moderator and about 100 attendees. During the event we gathered demographic facts through an interactive questionnaire tool and an extensive evaluation afterwards.Results: The event was rated with an overall grade of 1.4  and participants agreed that this format should be organized again . 70% of audience members preferred the online format of the event. Due to the high volume, only about 30%  of the questions posed by the audience were addressed.Conclusion: Firstly, most participants preferred the event to be online, contrary to our expectation. Secondly, the handling of the amount of individual questions posed significant challenges.Finally, the number of attendees and questions suggested a continuing demand among students and physicians for further education regarding hospital management, especially regarding COVID-19. These findings also require a critical look at future formats and topics of podium discussions in medical education. The online format might be a good alternative to face-to-face lectures.  MeCuM-SiGma  is a course designed to teach the basics of healthcare management and policy to medical students , 2], , , 5]..5].The COVID-19 pandemic made increasingly clear that hospital management is vital in preventing shortages, allocating staff efficiently and providing the best care possible in an overextended healthcare system , 7]. It. It7]. IThe entire event was held via an online platform (Zoom). The audience was muted for the duration of the event and only submitted questions via chat. The total length of the event was about 2 hours. During the event, we gathered demographic facts about the audience using an interactive questionnaire (60% response rate). Participants also completed a post-event evaluation form (30% response rate).142 people registered for the event. The maximum number of simultaneously logged in guests was 100. At 1,5 hours some participants left the chatroom, 70 participants remained until the end. 80% of the respondents of our live survey were medical students and 16% were physicians. Most participants did not have any hospital management experience (69%). In the follow-up evaluation (n=30) the mean age was 30 years (SD 10) and 47% of participants were female. The event was rated with an overall grade of 1.4  and participants agreed that this format should be organized again next year . The grading was comparable to four similar in-person events . 69% of participants stated that they were doing something else on their computer and they generally rated the possibility of parallel work as positive . Surprisingly, 70% of audience members preferred the online format. Participants indicated that they were unhappy with the handling of the posed questions. 35 questions were asked, 40% about hospital management during the crisis, 20% about future planning, 20% about policy and 20% other categories. Few questions were asked about personal or student topics. Due to the high volume of questions the moderator could only address about 30% of the questions posed.This case report is about a one-time event; hence we are cautious to draw general conclusions. However, our results show some interesting trends. The event was evaluated positively. Participants favored being able to complete other tasks simultaneously. It has been shown before that online multitasking is more common than at in-person events , also thThe handling of questions posed significant challenges. Contrary to classroom events, where questions are asked individually, new online formats, especially chat boxes, allow a simultaneous posing of questions. Although many audience members asked questions (ca. 35%), indicating high engagement, the participants were unhappy that many questions went unaddressed. Based on our experience organizing similar in-person events, less questions are asked in person even when the overall ratings of the event are comparable.The number of attendees and questions asked suggests a robust demand among medical students and physicians for further education regarding hospital management, especially on the topic of COVID-19. These findings require a critical look at the format of future podium discussions in medical education. Many participants preferred the online format and topic. Online discussions can be a good alternative to, or additional feature of, in-person lectures even post-COVID-19. It is advisable to have a concept to deal with a high volume of questions during online discussions. In the future we will collect unanswered questions and ask guests to answer them in written form or as a podcast after the event. In regard to learners’ attention and amount of questions, it remains to be examined whether the anonymity of an online event is advantageous.The authors declare that they have no competing interests.


The investigated genes displayed a unique impact on TDP-43 aggregation, generating distinct types of cytoplasmic inclusions, similar to those already described as resembling prion strains, which could represent the basis for neurodegenerative disease heterogeneity.Amyotrophic lateral sclerosis is a progressive neurodegenerative disorder, characterized by cytoplasmic inclusions of RNA-binding protein TDP-43. Despite decades of research and identification of more than 50 genes associated with amyotrophic lateral sclerosis (ALS), the cause of TDP-43 translocation from the nucleus and its aggregation in the cytoplasm still remains unknown. Our study addressed the impact of selected ALS-associated genes on TDP-43 aggregation behavior in wild-type and aggregation prone TDP-43 in vitro cell models. These were developed by deleting TDP-43 nuclear localization signal and stepwise shortening its low-complexity region. The SH-SY5Y cells were co-transfected with the constructs of aggregation-prone TDP-43 and wild-type or mutant ALS-associated genes  N-terminal oligomerization domain, a classical bipartite nuclear localization signal (NLS), two RNA recognition motifs (RRM1 and RRM2) and a low-complexity domain (LCD) [Amyotrophic lateral sclerosis (ALS) is a fatal progressive neurodegenerative disease pathologically characterized by cytoplasmic deposits of misfolded proteins in the affected neurons. The main component of these inclusions represents ubiquitinated, phosphorylated and cleaved TAR DNA-binding protein 43 (TDP-43) . Under pin (LCD) ,6. Whilein (LCD) ,8,9. So in (LCD) ,19,20,21in (LCD) . Still, in (LCD) .N-terminal domain in TDP-43 aggregation is somewhat controversial: while some argue that the oligomerization of TDP-43 via its N-terminal domain allows interactions with other partner proteins and RNA, thereby antagonizing its pathological aggregation, others suggest that it enhances the propensity of the intrinsically disordered C-terminal region towards aggregation [N-terminal domain reduces propensity of TDP-43 to undergo LLPS and to form aggregates [Recently, a liquid-liquid phase separation (LLPS) of RNA-binding proteins, such as TDP-43, has been implicated as a possible inception mechanism for protein aggregation and subsequent self-templating, ultimately resulting in various types of irreversible inclusions, i.e., amyloid-like fibrils in neurodegenerative disease . The mairegation ,32. It hgregates ,34. Moregregates ,37,38,39Mounting evidence suggests that cytoplasmic accumulations of TDP-43 exhibit prion-like characteristics . In addiN-terminal region of TDP-43 intact, as it is necessary for its oligomerization and phase-separation, although some studies have achieved TDP-43 aggregation with only the C-terminal region present [First, we developed a novel in vitro TDP-43 aggregation model in the neuroblastoma SH-SY5Y cell line. To achieve TDP-43 cytoplasmic aggregation, we eliminated NLS from the full-length TDP-43 sequence. Then, we stepwise shortened its LCD (containing IDR and CR domains), to disrupt the physiological conformation of TDP-43 dimers. We left the  present ,48. FullTDP-43 constructs: TDP-43 was subcloned from previously published plasmid  into mKOALS-linked genes: First, a gBlock DNA fragment (IDT) containing HRV 3C site, Gly-Ser-Gly linker and 3xHA was amplified by Phusion™ High-Fidelity DNA Polymerase (primer sequences are listed in ® CRL-2266™) were cultured as a monolayer in DMEM/F-12 (Thermo Fisher Scientific), supplemented with 10% (v/v) FBS (Thermo Fisher Scientific) and penicillin-streptomycin solution (Thermo Fisher Scientific) at 37 °C, in a humidified atmosphere containing 5% CO2. For immunocytochemistry, 1.1 × 105 cells/well were plated on coverslips into 24-well plates, 24 h before transfection. For western blot analysis, 2.2 × 105 cells/well were plated into 12-well plates and 6.5 × 105 cells/well were plated on 6-well plates, 24 h before transfection. Cells were transiently transfected using Xfect transfection reagent according to manufacturer instructions . Co-transfection experiments were carried out with plasmids DNA in ratios 1:1 amounting to 1 µg total DNA/well for 24-well plates, 2.5 µg total DNA/well for 12-well plates and 7.5 µg total DNA/well for 6-well plates. All of the co-transfections were carried out side-by-side at the same time, to allow comparisons between different experimental conditions.Neuroblastoma cells SH-SY5Y  was added to the pellets. The pellets were resuspended by pipetting and centrifuged again at 21,000× g for 30 min at 22 °C. The supernatants were collected as an UREA-soluble fraction. To both RIPA- and UREA-soluble fractions, the 6x SDS loading buffer with 0.3 M DTT was added, and RIPA-soluble fractions were boiled at 100 °C for 10 min. All samples were loaded to Novex WedgeWell 8–16% Tris-Glycine gels (Invitrogen Thermo Fisher Scientific) and run in SDS running buffer at 120 V for 90 min. Proteins were transferred onto Trans-Blot Turbo mini-size nitrocellulose membrane  by Trans-Blot Turbo Transfer System (Bio-Rad) in Trans-Blot Turbo Transfer buffer (Bio-Rad). Membranes were washed once in TBS, blocked in 5% skim milk in 0.1% TBST for 30 min, and then incubated overnight with primary antibodies in 5% skim milk in 0.1% TBST . The next day, the membranes were washed 3 times in 0.1% TBST and incubated with secondary antibodies in 5% skim milk in 0.1% TBST for 1.5 h . Upon three washes in 0.1% TBST, the fluorescence signal was detected using Chemidoc (Bio-Rad).For total cell lysates, 24 h after transfection, cells in 12-well plates were washed 3x with ice-cold PBS, and lysed in 2x SDS loading buffer with 0.1 M DTT. Samples were boiled at 100 °C for 10 min. For RIPA-soluble fraction, cells in 6-well plates were washed 3x with ice-cold PBS and lysed in 200 µL RIPA buffer , containing protease inhibitors  and phosphatase inhibitors . Samples were sonicated using an ultrasonic probe  and centrifuged at 21,000× Twenty-four hours after transfection, cells were washed 3x with PBS, fixed in 4% PFA for 30 min and washed with PBS again. Then, they were permeabilized with 0.1% TX-100 in PBS for 10 min, blocked in 3% BSA in PBS for 30 min and incubated with primary antibodies (anti-HA-tag (C29F4) rabbit polyclonal Cell Signaling #3724, 1:500), overnight at 4 °C. The next day, the coverslips were washed, incubated with secondary antibodies  for 2 h, incubated in DAPI solution (0.1 μg/mL) (Thermo Fisher Scientific) for 15 min, and mounted on microscope slides with ProLong™ Gold Antifade Mountant (Thermo Fisher Scientific).SEM. The difference between averages was tested by ordinary one-way ANOVA followed by Tukey multiple comparisons test, using GraphPad Prism 6. The p-value < 0.05 was considered statistically significant. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.Slides were analyzed by confocal microscopy , using ZEN software. Three experiments were performed in duplicates for each experimental condition, and a minimum of 15 visual fields, each containing between 50–70 cells from each duplicate were taken. Overall, between 550 and 3400 transfected cells were analyzed per each experimental condition. The percentage of transfected cells harboring TDP-43 aggregates was quantified by manual counting. A further analysis of the number of aggregates per cell and their size were performed with ImageJ Shape Descriptors plugin . All data were recorded as averages ± C-terminal domain on TDP-43 aggregation, SH-SY5Y cells were transfected with various mKO2 tagged TDP-43 constructs, lacking NLS (dNLS) and different parts of LCD —see C-terminal deletions of CR (dNLSd299) or IDR1 (dNLSd267) of TDP-43, decreased the percentage of cells with dNLSd299 (6.9 ± 0.57%) and dNLSd267 (4.1 ± 1.37%) aggregates. Further aggregate analyses within each individual cell revealed that the expression of dNLS resulted in the highest number of cytoplasmic aggregates per individual cell (14.1 ± 0.80), compared to the expression of any other TDP-43 truncated form (2) and dNLSd299 (4.8 ± 0.61 µm2) constructs  was used as a baseline control of the aggregate formation  and dNLSd343 (1.2 ± 0.14 µm2) aggregates in comparison with the cells co-transfected with control HAonly (dNLS (2.1 ± 0.34 µm2) and dNLSd343 (3.9 ± 0.39 µm2)). The decreased aggregate size appeared more pronounced in case of dNLSd343 than dNLS cells co-transfected with either wild-type or mutant hnRNPA1  and MATR3mut (3.7 ± 0.30 µm2) evidently increased the size of aggregates in cells co-transfected with dNLS  and VCPmut (4.2 ± 0.24 µm2) co-transfected cells, compared to HAonly (2.1 ± 0.34 µm2) (2) and VCPmut (2.5 ± 0.35 µm2) with dNLSd343, suggesting the involvement of IDR2 domain of TDP-43 in VCP interactions, and its necessity for TDP-43 aggregate maturation.The co-transfection of dNLS or dNLSd343 with VCPmut C resulte.34 µm2) C,D. Addi.34 µm2) C. No sucSimilar to VCPmut, the co-transfection of TDP-43 dNLS construct with UBQLN2mut  39.0 ± A. On theDespite the overwhelming majority of ALS cases being characterized by cytoplasmic deposits of TDP-43 protein in the affected cells, ALS patients display large phenotypic variability . As was N-terminal domain spatially separates aggregation-prone LCD [C-terminal sequence. The TDP-43 fragments were designed based on the borders of TDP-43 LCD segments determined by Schmidt and colleagues [Therefore, our study aimed to explore the influence of ALS-related genes and their mutations on aggregation pattern of TDP-43 in vitro. First, we developed a TDP-43 aggregation model in neuroblastoma SH-SY5Y cell line. To ensure cytoplasmic localization of TDP-43, we deleted NLS from the full-length sequence. As physiological TDP-43 oligomerization via its rone LCD , we trielleagues . Like otlleagues ,55, we slleagues , our expExpression of TDP-43 dNLS and dNLSd343 exhibited two dissimilar yet distinct aggregation patterns: dNLS displayed numerous dispersed and small aggregates, whereas dNLSd343 displayed fewer large bulk aggregates. Therefore, we further investigated both of them in the context of the influence ALS-associated genes may have on TDP-43 aggregation. We selected four different genes involved in ALS pathogenesis, each of them with a distinct role within the cell. Four chosen ALS-associated genes in their wild-type and mutant form were co-expressed with TDP-43wt, dNLS, dNLSd343 and KO2only in SH-SY5Y cells. The expression of all transfected constructs was confirmed by Western blotting. Even though the co-transfections of ALS-associated genes’ constructs with dNLSd343 displayed expression at really low levels, as compared to other TDP-43 constructs, they produced higher percentage of transfected cells with aggregates.C-terminal part of TDP-43 directly interacts with C-terminal domain of hnRNPA1 [C-terminal domain form smaller aggregates compared to a full-length protein [C-terminal domains spatially separate aggregation-prone LCDs and reduce the number of large aggregates, as observed in our study. Interestingly, even though hnRNPA1 undergoes LLPS and can form irreversible fibrils, which are enhanced by ALS-linked mutation D262V [Notably, hnRNPA1 is a member of the hnRNP protein family, involved in splicing, mRNA stabilization, miRNA biogenesis and transcriptional regulation ,57,58,59 hnRNPA1  and that hnRNPA1 , we can  protein . This ison D262V ,27,63, wN-terminal sequence of MATR3 exhibits low complexity and is able to undergo phase separation to form liquid-like droplets in the nucleus [MATR3 is also an RNA-binding protein, localized in the nuclear matrix and involved in various tasks concerning nucleic acids, such as chromatin organization, DNA replication, transcription and repair, RNA processing, transport, stability and alternative splicing ,65,66,67 nucleus ,71. The  nucleus , possiblIn contrast to previously discussed proteins mainly associated with RNA processes, one of VCP’s main duties is facilitating the proteasomal degradation of damaged or misfolded proteins by binding to polyubiquinated proteins and delivering them to the proteasome complex ,74,75. SLike VCP, UBQLN2 participates in proteolytic processes, such as delivering ubiquitinated proteins to the proteasome. Besides, it is also involved in autophagy, cell signaling, cell cycle progression and cytoskeletal association . SimilarOver the recent years, the extent of ALS heterogeneity, as well as its clinical, pathological and genetic overlap with several other degenerative disorders has become increasingly evident . NeverthHowever, determining the influence of ALS-associated genes on the aggregation pattern of TDP-43 remains the first step in elucidating the mechanisms of TDP-43 aggregation. It would be important to confirm these differences in TDP-43 aggregation patterns directly in the aggregates extracted from post mortem tissue or from motor neurons derived from ALS patients, with distinct mutations in ALS-associated genes. Additional studies, revealing the effects of TDP-43 interactors with the potential to reduce or accelerate TDP-43 aggregation in combination with different mutations of ALS-associated genes, are definitely needed.In summary, our results underline the significance of comparative research in the ALS field and provide an understanding of how different mechanisms interact at the molecular level and lead to neurodegeneration that may prove crucial in future for the successful development of therapeutics.