The complexity of skiing movements urges recreational alpine skiers and competitors to undertake many specific skill trainings not only during the season but also during the off-season using alternative sports. In AS, the role of the outside leg is crucial for successful turn performance. By measuring kinematic and kinetic parameters, we could define whether there is an objective similarity of the role and the movements of the outside leg while performing a turn in AS to those in the most used additional activity, IS. The sample consisted of ten female alpine ski instructors . Overall, 280 turns were analyzed (140 for AS and 140 for IS). For the purposes of this study, the variable sample consisted of 14 variables in total. For the detection of differences between short turn performance in AS and IS, MANOVA was used. The main findings of our study are defined similarities in pressure distribution during IS and AS and noticeable differences in the kinematic parameters of the outside leg between the mentioned activities. Based on the gathered results, recreational alpine skiers should be aware that IS cannot be used for the purpose of AS adoption, but rather as a dry-land additional activity for AS preparation. Alpine skiing (AS) is a specific activity consisting of complex and uncommon movements of the human body . SpecifiIn addition, the edging angle is another important factor that secures the skier’s reliable support on the snow surface. If all of the abovementioned factors are considered, each phase of the turn will be successfully performed without skidding and sliding ,5,6.The outside leg is more exposed to skidding when compared to the inside leg when the steepness of the terrain and applied pressure on both legs are the same. Therefore, the role of the outside leg is especially important in the conditions of very steep and icy terrain. That is the main reason for shifting the pressure predominantly on the outside leg, which is placed further from the projection of the center of mass . In ordeThe complexity of the skiing movements urges alpine ski competitors to perform a large number of specific skills trainings not only during the season but also during the off-season using alternative sports. Those must include similar body positions, relations between body segments, coordination structures, general movements and muscle contractions when compared to the primary activity .One of the most frequently used alternative activity for physical and technical preparation for AS is inline skating (IS) . IS enabComparing the turn execution on roller skates and skis, it can be assumed that alpine skiers can benefit in terms of technical training and physical conditioning by using IS as an additional activity . ResearcIn AS, as already mentioned, the role of the outside leg is considered to be crucial in successful turn performance. The inside leg has the role of a support, while the outside leg mostly controls the direction, duration and speed, and also prevents the skier from skidding by adjusting the edging angle in the turn . ResearcTo objectively identify and compare the roles of the outside leg in IS and AS, it is necessary to determine the joint angles and pressure forces that occur while performing a turn.Combined kinematic and kinetic analysis can provide objective evaluation of the outside leg movements and pressure distributions while skating and skiing. By measuring kinematic and kinetic parameters in this research, we could define whether there is an objective similarity of the role and the movements of the outside leg while performing a turn in IS and AS. The results gained emphasize the function of IS as an additional activity for developing and maintaining technical and physical conditioning outside the skiing season for competitive but also recreational level alpine skiers, who do not have the opportunity to spend a great amount of time on the ski slopes. Therefore, alternative activities are even more necessary to prepare them for their short skiing season.We hypothesized that the short turn execution during AS induces a higher pressure on the outside foot than it does in IS due to the slope steepness. Regarding the pressure distribution, we assumed there would be no significant differences in the load distribution during the turn execution in both activities. Furthermore, we assumed there would be similarities in the kinematic parameters of the lower limbs during short turn performance in IS and AS.Participants: The sample consisted of ten female alpine ski instructors . They did not report any prior injuries that could affect their AS and IS technique or kinetic and kinematic variables while performing turns in both activities. All participants had previous experience in inline skating and had finished basic inline skating school. Participants gave their written consent to participate in this study after being informed in detail about the aims and protocol of the research. The Faculty of Kinesiology, University of Zagreb (Croatia) Ethics Committee approved the study, which was performed following the ethical standards of the Declaration of Helsinki.Variables: The mentioned variables were selected based on relevant studies focused on the kinematic and kinetic analysis of AS technique ,19,20,21Analyses of kinetic and kinematic parameters were conducted on short parallel turns in two activities—AS and IS. Overall, 280 turns were analyzed (140 for AS and 140 for IS). For the purposes of this study, the variable sample consisted of 14 variables in total. The following kinetic variables were measured: the maximum force of the right foot in the left turn (Max_R_LT); the force of the lateral side of the right foot in the left turn (Lat_R_LT); the force of the medial side of the right foot in the left turn (Med_R_LT); the force of the right heel in the left turn (He_R_LT); the maximum force of the left foot in the right turn (Max_L_RT); the force of the lateral side of the left foot in the right turn (Lat_L_RT); the force of the medial side of the left foot in the right turn (Med_L_RT); and the force of the left heel in the right turn (HE_F_L_RT). All results are shown in newtons (N). Pressure data are also presented in terms of mean body weight (MBW= pressure (kg)/mean body weight of all participants (kg)).The following kinematic variables were measured (180° = knee and hip fully extended): the angle of the right knee flexion in the left turn (R_KNEE_LT); the angle of the right hip flexion in the left turn (R_HIP_F_LT); the angle of the right hip abduction in the left turn (R_HIP_AB_LT); the angle of the left knee flexion in the right turn (L_KNEE_RT); the angle of the left hip flexion in the right turn (L_HIP_F_RT); and the angle of the left hip abduction in the right turn (L_HIP_AB_RT). All results are shown in degrees (°).All data were obtained at the moment when participants’ feet were in a position parallel to the fall line . For theThe pressure distribution (kinetic variables) during AS and IS was measured with insoles designed for pressure detection . Due to their construction (2 mm thin and very light), insoles had minimal influence on turn performance during testing of both dynamic activities. For the purposes of this study, output rate was set at 100 Hz and the data were derived from the corresponding software . The reliability and validity of Novel pressure insoles for analyzing pressure distribution were confirmed in previous studies of similar activities ,22.Kinematic parameters were measured by an Xsens MVN Link inertial suit system. The system consisted of 17 three-dimensional accelerometers/gyroscopes/magnetometers and a battery. The output rate was set at 240 Hz, which ensures real-time human motion analysis without affecting the movement or rate of motion. Data were derived from the corresponding MVN BIOMECH software . Previous studies confirmed the reliability and validity of the Xsens kinematic suit for analyzing kinematic parameters (joint angles) in activities similar to those in this study ,23.Protocol of investigation: The protocol was the same for all participants and included measuring anthropometric characteristics, adjusting the Xsens suit and adjusting suitable pressure insoles. Anthropometric characteristics were used for adjusting the sensors and calibration of the Xsens system. The calibration was performed according to the standard of procedure advised by the manufacturer . In addition, standard calibration of pressure insoles was performed according to the manufacturer’s advice . All turns were recorded with a video camera (Panasonic GH 5) for the purpose of synchronizing both kinetic and kinematic systems. In order to successfully synchronize the systems, participants were asked to alternately lift their skis or skates two times off the surface just before starting their descent. That was the starting moment when the time lapse of both systems was aligned.Before testing procedures in AS, participants performed a free warm up run and a trial run in a defined corridor. Then, kinematic and kinetic parameters were measured with corresponding systems as participants performed short parallel turns in the defined corridor. The protocol of investigation was very similar to that used for the IS measurements. After adjusting kinematic and kinetic systems, participants had a free warm up run and then a trial run in the defined corridor. Afterwards, measurement of predefined kinematic and kinetic parameters was conducted while performing short parallel turns in the defined corridor. Participants received detailed instructions regarding short parallel turn performance both on skis and skates. Overall testing was conducted for four days; two days for measuring turns in AS and two days for measuring turns in IS. Testing procedures on the ski slope were performed in the morning hours to secure better snow conditions. The average incline of the slope was 20°. Participants had suitable skiing equipment . Short parallel ski turns were performed in a 3 m wide corridor, according to protocols defined in alpine ski schools. Each turn had to be performed from one end of the corridor to another. Each participant performed 16 turns, but due to mistakes in motor movement , several turns were excluded from further analysis.Skating turns were performed in sunny weather conditions in order to secure a dry surface. The corridor width was 1 m and the average incline was 10°. Participants also performed 16 turns, but some of them were excluded from further analysis due to certain mistakes in motor movement. The defined corridor for both skiing and skating turns is presented in p < 0.05. With the use of the G*power program, the sample size (number of turns) was calculated (n = 122), which was needed for the measurement procedure with statistical significance of p < 0.05; statistical power 0.95; effect size 0.25; 2 groups.Statistical analysis: Statistical package Statistica version 13.5.0.17  was used for data analysis. Basic descriptive parameters for all measured variables were calculated. The normality of data distribution was tested by the Kolmogorov–Smirnov test. MANOVA was used for the detection of differences between turn performance in AS and IS. The results were considered significant when Differences in kinematic and kinetic parameters between IS and AS were tested by MANOVA; results are shown in p < 0.01).Results shown in Basic descriptive parameters of each tested kinematic variable along with the results of MANOVA are presented in p < 0.01). In the left turn, the knee flexion differed significantly between IS and AS, with higher angle values detected in IS than it was in AS (157.43° compared to 139.56°). In addition, the flexion of the right hip was significantly different, with higher angle values determined while performing a turn in AS (145.01° compared to 139.03). Moreover, the hip abduction was significantly greater while performing a turn in AS than it was in IS (163.68° compared to 170.73°).The results were the same when analyzing right turns. The knee flexion was greater while performing a short turn in AS compared to IS (140.30° compared to 159.93°). The hip was more flexed while performing a short turn in AS than it was in IS (138.33° compared to 145.39°). Regarding the hip abduction, it was determined to be greater during AS than it was in IS (163.00° compared to 170.51°).Basic descriptive parameters of each tested kinetic variable, along with results of MANOVA, are presented in p = 0.23). In relation to the MBW, the measured maximum force in AS was 1.27 MBW and in IS it was 0.97 MBW. Regarding the pressure distribution in both activities, the highest values of distribution were noted on the heel . The next highest proportions of pressure were located the on medial side of the foot . The lowest pressure values in the left turn in both activities were measured on the lateral side of the foot .Furthermore, the measured forces of the outside foot in the right turn were also higher in AS than those in IS . In relaThe aim of this study was to objectively determine and compare the roles of the outside leg while performing short turns in IS and AS. The main findings of our study are defined similarities in pressure distribution during IS and AS and noticeable differences in kinematic parameters of the outside leg between the mentioned activities. Those findings are not completely in accordance with previously stated hypotheses. Therefore, based on the results of this study, recreational alpine skier should be aware that IS cannot be used for the purpose of AS adoption but rather as a dry-land additional activity for preparation for AS.p < 0.01). The highest values of maximal foot pressure were noticed in AS in both turns . Also, when comparing the ratio of maximum foot pressure and MBW, higher values were detected in AS . The mentioned results can be explained by some objective differences between the two activities. The steepness of the terrain directly affects the speed and gravitational force influencing the skier. Compared to IS, AS is performed usually on steeper slopes which consequently leads to higher speeds and higher centrifugal forces. Therefore, the skier must apply a higher foot pressure to master the speed, control the direction and overcome the high centrifugal force during a turn. As already stated, to successfully perform the turn on a steeper terrain, the skier must apply pressure predominantly on the outside leg [There were statistically significant differences between IS and AS in almost all of the measured kinetic parameters . Differences between the observed activities were similar in both turns. While performing a turn in AS, it was noticed that the side arc (hip abduction) was greater than that in IS . Moreover, the knee was more flexed during AS compared to IS . In addition, greater flexion was determined in the hip joint . Based on those results, it can be stated that while performing a short turn a skier’s body is in a lower position with an emphasized side arc. These results are in line with those gathered from the kinetic analysis. Due to higher maximal forces on the outside leg, it is necessary to master the forces by gradually flexing the lower body segments and to adopt a body position with an emphasized hip abduction of the outside leg. By maintaining the mentioned side arc throughout the turn, it is possible to maintain the high centrifugal force without skidding and sliding.Regarding kinematic parameters, even though the coordination of movements and the sequence of lower limb actions is very similar in AS and IS, there were statistically significant differences in all of the measured kinematic variables (Novel research focused on the kinematic analysis of recreational-level IS is scarce. Even more limited are studies concentrating on the specific implementation of IS as an additional activity for AS technique development.One of the rare studies that was focused on a comparison of AS and IS was conducted by Kroll et al. . The autEven though we determined some clear differences in kinematic aspects of the turn performance between IS and AS, based on our and some similar studies it can be concluded that the mechanism of turn execution is similar ,29,30,31When observing IS as an additional activity for AS competitors, IS is also performed on less steep slopes. In such a way, the speed and the direction can be controlled while the rhythm and the tempo are similar to those achieved during AS. In our research, the focus was on recreational skiers whose level of skiing technique was not as high as that of skiing competitors. From that standpoint, it is even more necessary to adapt the IS training to the conditions and environments that are appropriate for recreational skiers. This enables them to perform IS training by themselves on available slopes in parks or other environments. Regarding training and developing ski technique, based on the above mentioned it is recommended to use IS as an additional activity in the preparation period of the season. During that period, alpine skiers train simpler course settings and elements. Turns are basic left–right with the same gate distance and gate off-set, while the courses are usually set on a flat terrain. Therefore, inline skating with its already mentioned characteristics could be used as an extra technical training with similar goals. When discussing recreational level alpine skiing, IS can provide the greatest benefits when used in periods when recreational level alpine skiers are in the first phase of short turn adoption. During that phase of the learning process, it is usually executed on a less steep terrain. In that case the forces are smaller and it is more suitable for the learning process of a short turn. Information about the timing of specific body movements that ensure the optimal control of the direction and speed could be crucial for accomplishing the aim of alpine ski schools—to enable skiers to be independent in mastering complex skiing elements. The obtained similarities and differences in some of the observed parameters of AS and IS can contribute to the development of the teaching process of each skiing technique. Since the results indicate similarities in pressure distribution when comparing AS and IS, the implementation of IS can help in mastering the pressure transfer in each phase of the turn. In addition, the coordination of movements and the sequence of lower limb actions are very similar in both activities. However, it has to be emphasized that the final values of kinematic parameters are slightly different due to the terrain and equipment, so the execution of the turn cannot be the same. Considering the mentioned differences, it is important to include IS as an additional activity only when recreational skiers have mastered the basics of AS turn performance. Only then can these skiers recognize the real contribution of IS in the learning process of pressure transfer and distribution. If the above-mentioned condition is not fulfilled, the skiers may aim to excessively simulate the movements during IS, which could maximize the potential injury risks and interfere with the learning process of AS. IS could also be used to master the rhythm for easier and smoother turn performance and for the timely performance of each movement, from the initial to the final phase of the turn. One of the problems that can be solved by using IS in the preparation period is oversteering. Oversteering can lead to a reduced control of the direction and an impaired dynamic balance, which can cause falls and injuries on the ski slope. IS helps in gaining a feel for steering, which prevents the skis turning faster than they do in their “natural” radius. Severe knee injuries can be caused if the skis turn faster due to an excessive edging angle that is not appropriate to the slope steepness and gate offset. Therefore, and as already mentioned, due to the different position of wheels in relation to the foot in IS, a bigger lever is created for the same knee movement compared to the AS. Hence, IS could be a useful tool in learning the optimal amplitude for executing turns and consequently prevent serious injuries.The presented study was focused on the kinematic and kinetic analysis of the role of the outside leg when performing short parallel turns in AS and IS. In order to come to a clear conclusion whether it is justified to use IS as an additional activity for recreational alpine skiers, it is necessary to conduct an overall biomechanical analysis of the whole-body movement, including both the inside and outside leg and trunk movements. In addition, an electromyography analysis of the lower body’s muscle activity should be conducted to get an insight into the sequence of movements in each phase of the turn. Furthermore, to make an objective comparison of the two activities, it is necessary to completely replicate the conditions and the protocol in which the measurements are conducted. The corridor width and steepness of the slope differ due to general differences in the equipment and technical structure of the turn performance of each activity. Usually, training sessions in IS are performed in accordance with a temporal and geometrical extension of AS turns. However, due to abovementioned characteristics of both activities, the steepness of the terrain and corridor width cannot be exactly the same for both activities. In this way, the risk of potential injuries caused by an inadequate terrain steepness can be minimized.The results of the conducted kinematic and kinetic analysis of the role of the outside leg in AS and IS pointed to clear similarities in the ratio of pressure distribution while performing short parallel turns. Furthermore, one of the main findings is determined differences in the kinematic parameters of the outside leg between AS and IS. The kinematic analysis pointed to differences in the knee and hip angle of the outside leg, which has a role in controlling the speed and direction during the descent. The kinematic and kinetic analyses were in accordance with each other. The maximal pressure was higher during AS, and it was to be expected that greater knee and hip flexion and hip abduction were to be found in AS. On the other hand, the pressure distribution was similar in AS and IS, meaning that the outside leg had the role of maintaining a dynamic balance and stability during short turn execution in both activities.Although the motor knowledge necessary for the adoption of AS and IS is similar, it is important to be aware that there are objective differences which need to be taken into consideration when using IS as an additional activity for recreational skiers. IS can be used for solving more complex problems of skiing technique and adopting some specific high-level motor skills. Therefore, we recommend IS as an additional activity for skiers who have developed at least a basic AS technique in order to avoid interference with the learning process.


The improvement in device consistency allows for more reliable, homogeneous graphene devices, that can be fabricated at wafer-scale for sensing and biosensing applications.Graphene-based point-of-care (PoC) and chemical sensors can be fabricated using photolithographic processes at wafer-scale. However, these approaches are known to leave polymer residues on the graphene surface, which are difficult to remove completely. In addition, graphene growth and transfer processes can introduce defects into the graphene layer. Both defects and resist contamination can affect the homogeneity of graphene-based PoC sensors, leading to inconsistent device performance and unreliable sensing. Sensor reliability is also affected by the harsh chemical environments used for chemical functionalisation of graphene PoC sensors, which can degrade parts of the sensor device. Therefore, a reliable, wafer-scale method of passivation, which isolates the graphene from the rest of the device, protecting the less robust device features from any aggressive chemicals, must be devised. This work covers the application of molecular vapour deposition technology to create a dielectric passivation film that protects graphene-based biosensing devices from harsh chemicals. We utilise a previously reported “healing effect” of Al The demand for point-of-care (PoC) devices is increasing, with the identification of new pathogens and increased testing for infectious diseases, such as COVID-19 . Standar2 carbon atoms, arranged in a flat honeycomb-like lattice [2 carbon-carbon bonds in the graphene to sp3 bonds and can be achieved using various functionalisation methods, such as diazotization [Discovered in 2004 by Andre Geim and Konstatin Novoselov, graphene is a near-transparent two-dimensional (2D) structure that consists of hybridised sp lattice . It is o lattice ,6, and i lattice . Graphen lattice , biosens lattice ,13,14,15 lattice , superca lattice , solar p lattice , battery lattice , and poi lattice . Due to  lattice . Work ha lattice  and the  lattice ,13. Bior lattice . There a lattice ,25,26. N lattice . Covalentization ,29. The tization .2O3) deposition directly on top of the graphene [However, whilst graphene is chemically robust, other elements of graphene biosensors, for example, the metal electrode that interconnects to the active graphene layer, can be degraded by the functionalization chemistry or by exposure to the test analyte fluids. These chemical interactions can interfere with the electrical and electrochemical transduction in the graphene sensor device and affect device reliability. Therefore, it is desirable to confine exposure to chemical interactions to the active graphene component of the device only, during solution-based functionalisation processes or biosensing measurements that occur in the solution. This confinement can be achieved using a passivation layer to provide a protective barrier between any liquid media and the metal electrodes, whilst allowing full contact with the graphene . Previougraphene ,32. ThesHigh-κ dielectrics are commonly used for passivation layers in semiconductor devices ,34,35 an2O3 passivation layer, deposited using molecular vapour deposition, for use in graphene sensors and biosensors. Following the Al2O3 deposition on graphene, the Al2O3 etch rate was optimised to allow for controlled etching with minimal photoresist mask degradation. Graphene surfaces of passivated and non-passivated graphene devices were electrochemically functionalised with poly (pDAN). The condition of the metal tracks in both devices were then characterised. ALD Al2O3 passivation processes have also been reported to reduce organic polymer contaminants present on the graphene surface, related to photolithographic processing [2O3 passivation layer. Al2O3 passivation using MVD is shown to produce reproducible graphene biosensors for fast and reliable point-of-care diagnostics in liquid media.In this study, we report the development of an Alocessing . In this2/525 μm Si wafers using PMMA-based wet transfer were supplied by Graphenea Inc  [2SO4) solution was supplied by Sigma-Aldrich . Type II DI water with the ASTM D1193 standard and a resistance of 18 MΩ.cm was produced using a Merck Millipore Elix 3 water purification system .Chemical vapour deposited (CVD) monolayer graphene grown on Cu substrate and transferred on 300 nm thermal SiO, Spain) . Micropo2O3 film thickness was measured using a J.A. Woollam M-2000 spectroscopic ellipsometer  at various locations at a 65–75° angle, in steps of 5°. Once measured, using CompleteEASE software , the data are fitted with a Cauchy model. The surface morphology was characterised using a Keyence VHX-950F Series microscope , a Hitachi S4800 SEM , and a JPK NanoWizard II AFM . SEM and EDX images were taken on the Hitachi S4800  with an acceleration of 10 kV and an emission current of 10 μA. The AC tapping mode atomic force microscopy (AFM) images were taken using NCHV AFM probes, supplied by Bruker Ltd. , with a resonant frequency, spring constant, and tip radius of 320 kHz, 40 N/m, and 8 nm, respectively. The AFM data were analysed using Gwyddion software . Optical microscope images were taken with a Keyence VHX-950F Series Microscope . Raman spectra were acquired using a Renishaw Qontor inVia Raman microscope  with a 532 nm laser at 10 mW with a ×100 objective lens, and the data were analysed using a custom MATLAB script . X-ray photoelectron spectroscopy (XPS) was performed using a Kratos Axis Supra XPS  with an Al Kα monochromatic source, with an emission current of 15 mA and a pass energy of 20 eV. Where applicable, adventitious carbon was etched off the surface using a 5 keV Ar gas cluster ion source (GCIS) at 45 nA for 100 s during the XPS measurement. Each sample had a minimum of three measurements performed to ensure that the resultant scans were an accurate representation of the graphene surface. Data analyses from XPS measurements were performed using CasaXPS software .The Al2 plasma, at 80 W power, and 7 × 10−1 mBar pressure, for 5 min using a Quorum Emitech K1050X RF Plasma Asher , before the remaining photoresist (used to protect the graphene during plasma etching) was removed by submerging the wafer in DMSO, warmed to 80 °C, for 1 h, revealing the graphene channels  before photolithographic patterning using a bi-layer resist process (LOR 3A/S1805) B, by thechannels C. Once tchannels D. The Crchannels E. Once lecursors F using apsometry .2O3. The optimised TMAH concentration and resulting etch rate are discussed later in this study. Once the Al2O3 is etched, with the graphene exposed, the photoresist mask was subsequently removed by immersing the wafer in NI555 resist remover at 80 °C for 1 h, revealing the graphene devices  and 10 mM DAN in a three-electrode system, with an Ag/AgCl reference electrode and a Pt wire serving as the counter electrode. The working electrode is the graphene chip, with the graphene immersed in the H2SO4/DAN solution. After setting up the three-electrode system, cyclic voltammetry (CV) scans were performed for five cycles at 50 mV/s from −0.9 to 0.6 V.The graphene channels in the devices are modified by electrochemically functionalising the surface with DAN, electropolymerising it to form pDAN. These processes were performed using an Autolab PGSTAT302N  in a standard three-electrode cell. The pDAN functionalisation process utilises 0.25 M sulfuric acid  and were measured periodically via ellipsometry to determine the overall etch rate  and after Al2O3 MVD passivation (“Passivated”). Raman spectroscopy was measured on unprocessed graphene (“Blank”); graphene after device fabrication at two stages, before AlD/IG) can be used to quantify the ratio between sp3 and sp2 bonds, indicative of structural defects in graphene [D/IG of Blank, Processed, and Passivated graphene in a histogram. The ID/IG of the blank graphene averages 0.057 with a large majority of measurements in the 0.03 to 0.06 range. These defects may be due to PMMA residue remaining on the surface after the graphene transfer. After graphene device fabrication, but before MVD deposition, the average ID/IG increased to 0.062 with the range of many of the ratios being much larger, between 0.03 to 0.09. As explained in D/IG values and a higher average ID/IG. Once the graphene is encapsulated with the MVD Al2O3 layer and the graphene windows have been etched out, the graphene is once again characterised using Raman spectroscopy. The number of defects significantly decreased with the ID/IG being significantly lower, at 0.015. The range is also greatly reduced, with the majority of the ID/IG readings being near the 0.0 to 0.02 range. The decrease in the ID/IG means that a resist removal effect had taken place on the graphene surface, once it has been in contact with the Al2O3. In a publication by Do Van Lam et al., it has been reported that ALD Al2O3 has various types of “healing effects” in CVD graphene, such as resist residue, defects, and grain boundaries. These residue and defect areas provide nucleation sites for the ALD Al2O3 to grow on [2O cycles require binding to surface -OH functional groups, any surface contaminants providing those hydroxyl groups can be used by the MVD Al2O3 growth process [2O3, which is consistent with a drop in the ID/IG.The ratio between the D-peak and G-peak intensities  sulphate mixture, for APTES functionalisation ,30. If ls forces . The eles forces  uses dil2SO4 solution, diluted down from 95–98% (~18 M) concentrated H2SO4, and was electropolymerised onto both the non-passivated and passivated CVD graphene devices at a scan rate of 50 mV/s, between −0.6 and 0.9 V, for five cycles, with the CV graphs shown in 2 functional groups for further bio-functionalisation. The position of the oxidation and reduction peaks during electropolymerisation are similar between the non-passivated and passivated CV graphs, located at 0.075 and −0.39 V, 0.071 and −0.38 V, respectively. A small, broad oxidation peak is present at 0.32 V for the passivated graphene device, which represents the irreversible oxidation of the DAN monomers during the polymerisation step [Moreover, 10 mM of DAN was mixed via sonication with 0.25 M Hion step .2SO4 solution, increasing the electron transfer in the electrochemical reaction [It has been reported that the increase in current density, across the working electrode, after each cycle is evident that the DAN is polymerising on top of the CVD graphene . This isreaction . The catAfter five cycles of electropolymerisation, the non-passivated graphene devices developed damage along the metal tracks which can be seen under an optical microscope. Areas of peeling metal are visible and are marked with red arrows in 2O3 deposition, rejuvenating the graphene. This can be seen from the XPS data, where the sp2 carbon component increases from 57.16 to 70.17%, showing a decrease in non-graphitic carbon present on the graphene surface, and a decrease in the nitrogen concentration of 50%, associated with reduced quantities of surface residue resist. A reliable Al2O3 wet etching process has been created and optimised, capable of patterning Al2O3 with a photoresist mask without negatively affecting the graphene substrate or the integrity of the Al2O3 layer. This improvement in graphene device consistency and the effective protection, that the Al2O3 passivation layer provides, lays the foundation for much more reliable graphene biosensing platforms, which can be integrated for commercial applications and point-of-care testing.We have demonstrated a fabrication process to improve the reliability of graphene biosensing devices using a novel MVD dielectric deposition passivation layer for graphene sensor devices, protecting the metal electrodes from aggressive chemicals. The process aids in cleaning and restoring the graphene surface, removing residual resist, and improving reproducibility and device consistency, an essential key development aspect for graphene-based biosensors. Raman analysis demonstrated an increase in a large range of defects present on the graphene surface after graphene lithographic device processing, which was subsequently greatly reduced and homogenised after Al


This study seeks to investigate the interaction profile of the L5 protein of oncolytic adenovirus with the overexpressed surface receptors of pancreatic cancer. This is an important area of research because pancreatic cancer is one of the most fatal malignancies with a very low patient survival rate. Multiple therapies to date to improve the survival rate are reported; however, they show a comparatively low success rate. Among them, oncolytic virus therapy is a type of immunotherapy that is currently under deliberation by researchers for multiple cancer types in various clinical trials. Talimogene laherparepvec (T-VEC) is the first oncolytic virus approved by the US Food and Drug Administration (FDA) for melanoma. The oncolytic virus not only kills cancer cells but also activates the anticancer immune response. Therefore, it is preferred over others to deal with aggressive pancreatic cancer. The efficacy of therapy primarily depends on how effectively the oncolytic virus enters and infects the cancer cell. Cell surface receptors and their interactions with virus coat proteins are a crucial step for oncolytic virus entry and a pivotal determinant. The L5 proteins of the virus coat are the first to interact with host cell surface receptors. Therefore, the objective of this study is to analyze the interaction profile of the L5 protein of oncolytic adenovirus with overexpressed surface receptors of pancreatic cancer. The L5 proteins of three adenovirus serotypes HAdV2, HAdV5, and HAdV3 were utilized in this study. Overexpressed pancreatic cancer receptors include SLC2A1, MET, IL1RAP, NPR3, GABRP, SLC6A6, and TMPRSS4. The protein structures of viral and cancer cell protein were docked using the High Ambiguity Driven protein–protein DOCKing (HADDOCK) server. The binding affinity and interaction profile of viral proteins against all the receptors were analyzed. Results suggest that the HAdV3 L5 protein shows better interaction as compared to HAdV2 and HAdV5 by elucidating high binding affinity with 4 receptors . The current study proposed that HAdV5 or HAdV2 virus pseudotyped with the L5 protein of HAdV3 can be able to effectively infect pancreatic cancer cells. Moreover, the current study surmises that the affinity maturation of HAdV3 L5 can enhance virus attachment with all the receptors of cancer cells. Pancreatic cancer is the most fatal and extremely aggressive malignancy with a high recurrence and mortality rate . ChemothAmong a range of cancer therapies, oncolytic virus therapy is a novel targeted immunotherapy and has obtained noticeable attention. Viruses selectively exterminate cancer cells through lysis resulting in antitumor immune simulation. The specificity and effectiveness of oncolytic viruses make them an attractive therapeutic approach. However, success lies under the goal to modify  viruses for enhanced tumor selectively and immune stimulation. Furthermore, the co-administration of oncolytic viruses with other therapeutic agents has also been found to be very effective . The verHuman adenovirus is a commonly used oncolytic virus against various cancer types. Gendicine and Oncorine are the two adenoviruses that are currently approved for the treatment of cancer in China . ONXY-15log2FC > 1) in all the datasets and also identified in The Cancer Genome Atlas (TCGA) cohort. These genes include MET, NPR3, IL1RAP, SLC2A1, SLC6A6, GABRP, and TMPRSS4, which encode for cellular membrane receptors (Adenovirus cell attachment is instigated by the interaction of the knob domain region of the fiber protein with the human cell receptors . The CAReceptors . The oveeceptors –27.SLC2A1 gene encodes for glucose transporter type 1 (Glut1), which is a member of the GLUT protein family. It is responsible for glucose transport across the cell membrane. The structure of SLC2A1 comprises 12 transmembrane helices, with 6 extracellular and 7 cytoplasmic domains , 29. Carα chain and transmembrane 140-kDa β chains (β -catenin (Wnt) pathways. These signaling pathways cause cell proliferation, evading apoptosis and leading to the development of angiogenesis and invasiveness  also known as NPR-C is a member of the glycosylated receptor family. This is present in the form of a dimer, and it is responsible for the regulation of natriuretic peptide (NP) hormones in the blood . Three NSLC6A6 encodes for multipass membrane transport protein. It is a member of the solute carrier 6 (SLC6) family of sodium and chloride ion-dependent transporter proteins , 42. TheAll the above-enlisted receptors have a direct or indirect link with the progression of pancreatic cancer. In this study first, the structures of all receptors are retrieved. For SLC2A1, MET, IL1RAP, and NPR3 receptors, Protein Data Bank (PDB) structures are available, while for other receptors, machine learning-based structure prediction is utilized to generate the protein structure. The structures of the L5 proteins for all three serotypes are downloaded from PDB. All the receptors are docked with the HAdV2, HAdV3, and HAdV5 L5 proteins. The binding affinity and interaction pattern of each complex are analyzed to identify which target receptor effectively binds with the L5 proteins. For the positive control, the interaction pattern of CAR and DSG2 with the HAdV2, HAdV3, and HAdV5 L5 proteins is analyzed and compared with pancreatic cancer receptors. The interaction analysis of CR1 with the HAdV5 L5 protein and CD46 with the HAdV3 L5 protein is also performed to compare the binding affinity of these receptors with pancreatic cancer receptors. NPR3, GABRP, SLC6A6, and TMPRSS4 showed the highest binding affinity with the HAdV3 L5 protein, while SLC2A1 and IL1RAP show better interaction with HAdV2.The overall workflow of this study includes structure retrieval and preparation of human receptors and virus L5 protein. Then the docking of receptors with L5 and interaction analysis of both molecules was performed. The overall workflow of the study is given in https://www.uniprot.org/) against each UniProt ID provided in https://blast.ncbi.nlm.nih.gov/Blast.cgi) was performed to determine percentage sequence identity based on which structural homologs were identified. The MET, SLC2Al, NPR3, IL1RAP, CAR, DSG2, CD46, and CR1% identity was greater than 97%, which means that the protein structure for these receptors was already available. For the SLC2A1 receptor, multiple PDB structures with a similarity >99% were identified with a sequence length of 492 amino acids. Out of all hits, a structure with high resolution (2.4 Å) with PDB ID 6THA was selected and downloaded from PDB (https://www.rcsb.org/). The PDB ID 1KY0 was selected for the NPR3 receptor based on the PSI-Blast result. The 1KY0 structure of the NPR3 extracellular domain is present with 88% sequence coverage and a high-resolution (2.40 Å) X-ray diffraction structure. The MET receptor comprises a large extracellular domain, a transmembrane region, and an intracellular domain with a sequence length of 1,390 amino acids. The extracellular domain comprises 25 to 932 amino acid residues. Two PDB structures with similarity >99% and 57% sequence coverage were identified through PSI-Blast. The PDB structures 2UZX (2.80 Å) and 6GCU (6.00 Å) are further analyzed. Both cover the extracellular domain region but have a missing loop region. To model the missing loop regions for MET, a homology protein model was generated using Swiss-Model (https://swissmodel.expasy.org/), using 2UZX as the PDB template.The sequences of receptors were retrieved from UniProt (https://zhanglab.ccmb.med.umich.edu/I-TASSER/) (http://raptorx.uchicago.edu/) (https://robetta.bakerlab.org/)  was selected, with 100% percentage identity and 34% sequence coverage identified through PSI-Blast. The selected PDB structure comprises amino-terminal immunoglobulin domain (D1). This D1 domain is necessary and sufficient for HAdV binding with CAR . For theTASSER/) , RaptorXgo.edu/) , and macab.org/) . TrRosetab.org/) . Then thMolecular dynamic (MD) simulation of selected models of TrRosetta server for proteins was performed. GROMACS  was used for energy minimization and MD simulation of all proteins . The OPLhttps://www.uniprot.org/) against each UniProt ID provided in https://blast.ncbi.nlm.nih.gov/Blast.cgi) was performed to determine the percentage sequence identity basis on which PDB structures were determined. The percentage identity and sequence coverage of selected PDB structures are provided in https://www.rcsb.org/). For HAdV2 and HAdV3, high-resolution PDB structures IQIU (2.40 Å) and 1H7Z (1.60 Å) were selected. PDB structure for both serotypes comprises the head region and a small portion of the shaft region. For HAdV5, L5 4ATZ PDB was selected with a resolution of 1.95 Å and comprises the knob region. Although the sequence coverage for all the L5 proteins was less, it was considered for this study because the structure of the knob region is required to analyze its interaction pattern with pancreatic cancer receptors.The sequences of the L5 protein for all serotypes were retrieved from UniProt  to determine active site residues or protein interface residues  server for protein–protein docking of both molecules (it0) rigid body energy minimization, (it1) semi-flexible refinement in torsion angle space, and (itw) refinement in explicit solvent refinement. The HADDOCK scoring function is the linear combination of energies and buried surface area in all three stages of docking. Docking run through HADDOCK software is computationally extensive, so the server provides users with an easy-to-use interface and removes the burden of computational resources required for installation and docking run . After that, binding affinity (ΔG) and dissociation constant (dK) of the protein–protein complex were calculated using PRODIGY (PROtein binDIng enerGY prediction) (https://wenmr.science.uu.nl/prodigy/)  . Prodigyrodigy/) . Other tFor the docking run, structures of receptors and L5 protein were prepared. For SLC2A1, MET, NPR3, and IL1RAP, receptors and L5 proteins with known PDB structures were employed, while structures of GABRP, TMPRSS4, and SLC6A6 were modeled.The PDB structures of GABRP, TMPRSS4, and SLC6A6 proteins were not available. The PSI-Blast result for GABRP shows 48.34% identity, SLC6A6 47.34%, and TMPRSS4 37.99% Table 1.The protonated structures of pancreatic cancer receptors were docked with the protonated HAdV2 L5 protein using the GURU interface of the HADDOCK server. The HADDOCK generates water-refined interaction conformations of both interacting molecules and groups similar conformations in clusters. The superimposed structures of all structures in one cluster were generated S13, aloβ turn and H2 domain), 175 to 188 (3 β 1 γ 2 β turns and H10 domain), 295 to 308 (H18 domain and β turn), 355 to 366 (3 β turns corresponding to H22 domain), and 426 to 431 (H24 domain). The residues of two chains of the HAdV2 L5 protein complex interact with SLC2A1. In chain B, residue numbers include 439 to 443 (β turn), 523 to 528 (H5 domain and β turn), and 566 to 570 (β turn). In chain C, residue numbers include 412 to 415 (β hairpin), 449 to 460 (β turn and F stand), 469 to 472 (β and γ turn), 505 to 513 (γ turn and H4 domain), and 538 to 547 (β hairpin turn).Cluster 2 was selected for the SLC2A1 interaction complex with the L5 protein HAdV2 (HADDOCK score −64.6 ± 16.0 and Z-score −1.8) Table 4.β and γ turn) and 639 to 646 (β hairpin turn). Chain B residues include 267 to 273 (β and γ hairpin turn), 308 to 311 (H3 domain), 381 to 384 (β turn), 392 to 398 (β turn hairpin), and 421 to 425 (F sheet). The residues of two chains of the HAdV2 L5 protein interact with the MET receptor. Chain B residue numbers include 409 to 417 (β β hairpin turn), 441 to 447 (H2 domain), 467 to 476 (β γ β turn), and 544 to 547 (β β hairpin turn). The C chain residues include 412 to 416 (β hairpin) and 449 to 451 (β turn).For MET, cluster 18 (HADDOCK score −79.5 ± 1.1 and Z-score −2.0) was selected out of all generated clusters Table 4.β hairpin turn). In the B chain of the L5 protein interacts with the IL1RAP receptor, its residues include 407 to 410 (β hairpin turn), 414 to 419 (β hairpin turn), 441 to 451 (β β turn and H2 domain), and 474 to 477 (β turn). For NPR3, cluster 3 (HADDOCK score −55.0 ± 14.4 and Z-score −1.4) was selected (β β turn), 95 to 100 , 121 to 124 (H2 domain), and 380 to 383 (β β turn). The B and C chains of the L5 protein interact with the NPR3 receptor. B chain residues include 439 to 447 (β turn and H2 domain), 523 to 528 , and 566 to 570 (β turn). Chain C residues include 446 to 456 (H2 domain and β turn) and 507 to 512 (γ turn and H4 domain).Only one cluster with 4 conformations was generated for the interaction of IL1RAP and HAdV2 L5 in HADDOCK Table 4.β β turn, and start of H2 domain), 31 to 39 (two β turns), 70 to 73, 108 to 110 (β turn), 131 to 141 (β turn and A sheet), 204 to 211 (α γ β turn), and 241 to 244 (H7 domain). The two chains of the L5 protein interact with the GABRP receptor. Chain B residues include 402 to 410 , 415 to 420 (β hairpin turn), 439 to 448 (eta turn and H2 domain), 474 to 477 (β turn), and 484 to 486 (β hairpin turn and E sheet). Chain C residues include 463 to 470 (β γ turn), 501 to 514 (β β γ turn and H4 domain), and 538 to 552 (H6 domain and β β β hairpin turn).For GABRP, cluster 2 (HADDOCK score 85.9 ± 8.6 and Z-score −1.9) was selected Table 4.β β turn), 163 to 167 (β β turn), 180 to 183 (β turn), 201 to 205 (loop), and 216 to 222 (H13 domain). The two chains of L5 proteins B and C interact with the SLC6A6 receptor. The residues of chain B include 403 to 420 (β β β hairpin turn), 468 to 477 (β γ β turn), and 483 to 486 (β hairpin and E sheet). Chain C residues include 501 to 507 (β β β turn) and 581 and 582. For TMPRSS4, cluster 8 (HADDOCK score 139.9 ± 9.5 and Z-score −1.9) was selected (β turn), 282 to 290 (β γ β hairpin turn), 331 to 339 (β hairpin turn), 363 to 365 (γ β β hairpin turn), 383 to 387 (β β turn), and 405 to 410 (β hairpin turn). Chain B of the L5 protein interacts with TMPRSS4, and its residues are 406 to 420 (β β β hairpin turn), 439 to 450 (β turn and H2 domain), and 469 to 477 (β γ β turn); other interacting residues include 488, 490, 544, 547, and 566. The secondary structure of SLC2A1, MET, IL1RAP, NPR3, GABRP, SLC6A6, and TMPRSS4 showing the interacting domains of receptors is given in For SLC6A6, cluster 1 (HADDOCK score −115.8 ± 6.9 and Z-score −1.6) was selected Table 4,β turn), 27 to 44, 94 to 100 (β hairpin turn and H1 domain), and 102, 104, and 106. Chains B and C of the L5 protein trimer interact with the CAR receptor. The residues of chain B include 406 to 410 (β hairpin loop), 416 to 420 (ta hairpin loop), 474 to 477 (β turn), 484, and 485. The residues of chain C include 501 to 509 (β γ turn), 548 to 550 (β hairpin loop), and 581.The best possible interaction complex for CAR and DSG2 was obtained after docking, with the best HADDOCK score and lowest Z-score then selected for refinement. For CAR, cluster 3 (HADDOCK score −57.2 ± 11.9 and Z-score −1.0) was selected (β γ β turn), 230 to 232, 237 to 242 , 251 to 257 (β hairpin loop), 294 to 298 (β turn), and 271, 273, 275, and 301. Chains A and B of the L5 protein trimer interact with the DSG2 receptor. The residues of chain A include 408, 409 (β hairpin loop), 468 to 477 (β γ β turn), and 482 to 485 . The residues of chain B include 461 to 464 (ta turn), 501, 502, 506 (β turn), 541 to 551 (β β hairpin loop), and 581. The list of interacting residues is provided in For DSG2, cluster 5 (HADDOCK score −66.5 ± 11.8 and Z-score −1.1) was selected (β turn), 181 to 183 (γ turn), 299 to 300 (H18 domain), 304 to 308 (start of H19 domain), 355 to 361 , and 426 to 432 . Chains A and C of the L5 protein trimer interact with the SLC2A1 receptor. The residues of chain A include 174 to 181 , 261 to 263 (β hairpin turn), and 300 to 304 (β turn). The residues of chain C include 188 to 196 (B sheet after H1 domain), 242 to 246 (γ and β turn), 289 to 293 (B sheet), 276, 279, 147, and 149.The best possible interaction complex for all receptors was obtained after docking, with the best HADDOCK score and lowest Z-score then selected for refinement. For SLC2A1, cluster 3 (HADDOCK score 126.4 ± 2.4 and Z-score −1.7) was selected (β γ hairpin turn), 379 to 384 (β turn and F sheet), 392 to 404 (β β hairpin turn), and 419 and 421. The two chains of the L5 protein interact with the MET receptor. Chain A residues include 260 to 263 (ta hairpin turn). Chain C residues include 197 to 205 (β turn), 249 to 253 (B sheet), and 281 to 288 ; other interacting residues include 296, 298, 154, 156, and 217. For IL1RAP, cluster 4 (HADDOCK score −44.2 ± 4.5 and Z-score −1.6) was selected (β turn and k sheet) and 115 to 119 . The two chains are the L5 protein interacting with the IL1RAP receptor. Chain A residues include 258 to 264 (β hairpin turn). Chain C residues include 190 to 194 (B sheet), 241 to 43 (γ and β turn), 250, 252, 261, 277 to 281 (β hairpin turn), and 289 to 293 (B sheet).For MET, cluster 5 (HADDOCK score −70.6 ± 7.2 and Z-score −2.4) was selected Table 4.β sheet). Chain B residues are 47 to 54 , 95 to 99 (β turn), 102 to 104 (A sheet before H2 domain), and 118 to 126 . The two chains of the L5 protein interact with the NPR3 receptor. The residues of chain A include 178, 257 to 261 (β hairpin turn), and 299 to 304 (β turn). The residues of chains B include 145 to 150 (β hairpin turn), 182 to 196 (H1 domain), 241 to 247 (γ β turn), 278, 289, and 179.For NPR3, cluster 4 (HADDOCK score −81.0 ± 7.4 and Z-score −1.3) was selected Table 4.β, β, β, β turn, H2 domain, β turn), 28 to 34 (β turn), 71 to 74 , 132 to 141 , 203 to 211 , and 241 to 244 (H7 domain). The two chains of the L5 protein interact with the GABRP receptor. Chain A residues include 174 to 178 (A sheet before H1 domain), 257 to 261 (β hairpin turn), and 299 to 304 (β turn). The C chain residues include 144 to 149 (β hairpin turn), 178 to 194 (H1 domain and B sheet), 240 to 247 (γ β turn), 275 to 280 (β hairpin turn), 300 to 302, and 250.For GABRP, cluster 2 (HADDOCK score 71.4 ± 8.2 and Z-score −2.5) was selected Table 4.−1) and the highest interactions (147) with HAdV3 than other serotypes (β turn), 163 to 170 , 178 to 190 , 197 to 203 (H12 domain), and 215 to 222 (H13 domain); other residues in fluids include 449, 147, and 151. The L5 protein residues that interact with SLC6A6 are chain A 258 to 265 (β hairpin turn). Chain C residues include 145 to 151 (β hairpin turn), 182 to 196 (H1 domain and B sheet), 268 to 279 , and 287 to 293 (B sheet). For TMPRSS4, cluster 3 (HADDOCK score 153.1 ± 2.7 and Z-score −1.2) was selected , 245 to 257 , 276 to 285 , 331 to 339 (β hairpin turn), 384 to 387 , and 405 to 408 (β turn). The two chains of the L5 protein interact with TMPRSS4. Chain A residues include 258 to 263 (β hairpin turn). Chain C residues include 146 to 150 (β hairpin turn), 178 to 183 , 185 to 196 (B sheet after H1 domain), 241 to 247 , 275 to 281 , and 285 to 293 (B sheet). The list of interacting residues for all interaction complexes is provided in For SLC6A6, cluster 2 (HADDOCK score 4.8 ± 10.8 and Z-score −1.8) was selected (erotypes Table 4.β turn), 23 to 50 , 92 to 109 , and 131. Chains A and C of the L5 protein trimer interact with the CAR receptor. The residues of chain A include 258 to 265 (β hairpin loop) and 296 to 301 (β turn). The residues of chain C include 146 to 149 (β hairpin loop), 178 to 196 , 242, 244, 245, 250 (γ and β turn), and 291 to 294 .The best possible interaction complex for CAR and DSG2 receptors was obtained after docking, with the best HADDOCK score and lowest Z-score then selected for refinement. For CAR, cluster 1 (HADDOCK score −78.2 ± 4.0 and Z-score −1.3) was selected (β γ β turn), 223 to 232 (β β β turn), 247 to 250 (β hairpin loop), 272 to 275 (β turn), 294 to 297 , 301, and 306. Chains A and C of the L5 protein trimer interact with the DSG2 receptor. The residues of chain A include 146, 149, 178, 179, and 299 to 302 (β turn). The residues of chain C include 145 to 153 (β hairpin loop), 177 to 179, 190 to 196 , 241 to 245 (γ β turn), 272 to 278 (γ hairpin loop), and 285 to 289 (B sheet).For DSG2, cluster 1 (HADDOCK score −82.4 ± 9.2 and Z-score −1.1) was selected (β turn), 92 to 109 , 112, 115 to 118 (γ hairpin loop), 126 to 131 (β turn), 148, 149, 156 to 159 (D sheet), and 182 to 184 (β hairpin loop). Chains A and C of the L5 protein trimer interact with the CD46 receptor. The residues of chain A include 178, 182, 185, 258 to 262 (β hairpin loop), and 298 to 303. The residues of chain C include 145 to 149 (β hairpin loop), 178, 179, 182, 185 to 196 , 242 to 247 , and 287 to 293 (B sheet). The list of interacting residues for all interaction complexes is provided in For CD46, cluster 1 (HADDOCK score −83.8 ± 13.2 and Z-score −1.7) was selected (β turn), 356 to 362 , and 426 to 432 (part of H24 domain). The two chains of the L5 protein interact with SLC2A1. Chain A residues include 396 to 399 , 404 to 410 (β hairpin turn), 476-477 (H2 domain), and 481 to 492 . Chain C residues include 501 to 513 .The best possible interaction complex generated by docking (HADDOCK) was then selected for refinement and interaction analysis. For SLC2A1, cluster 4 (HADDOCK score −66.3 ± 3.8 and Z-score −1.4) was selected (−1) (β turn), 582 to 586 (J sheet), 615 to 623 (H10 domain and β hairpin turn), and 700 to 706 (M sheet and β hairpin turn). Other residents include 40, 459 to 461, 521, 528, and 553. Chains A and B of the L5 protein interact with MET. Chain A residues include 396 to 399 , 476 to 477 (H2 domain), and 481 to 496 . Other important residues include 580 and 581. For IL1RAP, cluster 5 (HADDOCK score −44.2 ± 4.5 and Z-score −1.6) was selected  and 485 to 492 (A sheet and loop).For MET, cluster 36 (HADDOCK score −78.8 ± 3.7 and Z-score −1.7) was selected (−1) Table 4.β turn), 474 to 477 (H2 domain), 482 to 492 (β hairpin turn and A sheet), and 404. For GABRP, cluster 12 (HADDOCK score 63.8 ± 5.4 and Z-score −2.3) was selected , 29 to 38 (β β turn), 71 to 74 , 131 to 141 , 204 to 209 (β γ β turn), and 243 to 248 (H7 domain). For GABRP, the two chains of the L5 protein interact with the receptor. Chain A residues include 404 to 409 (β hairpin turn), 474 to 479 (H2 domain), 481 to 490 (β hairpin turn and A sheet), and 466. Chain B residues include 501 to 508 (α β β turn), 543 to 550 (γ β γ turn and β hairpin turn), and 581.For NPR3, cluster 9 (HADDOCK score −52.7 ± 11.0 and Z-score −2.1) was selected Table 4.β, β turn), 179 to 185 (β turn), and 201 to 220 ; other important residues include 147, 151, 154, and 158. Chain A residues of the L5 protein interact with SLC6A6 including 396 to 399 , 404 to 409 , and 474 to 490 . Chain B residues include 492 to 497 (A sheet), 580, and 581. For TMPRSS4, cluster 1 (HADDOCK score 88.5 ± 0.9 and Z-score of −1.0) was selected (β turn), 282 to 287 , 331 to 339 (β hairpin turn), 382 to 387 , and 405 to 408 (β turn). The residues of chain A of the L5 protein interact with TMPRSS4 including 396 to 398 , 463 to 469 (β turn) 474 to 497 , and 581. The list of interacting residues for all interaction complexes is provided in For SLC6A6, cluster 1 (HADDOCK score −76.9 ± 2.7 and Z-score of −1.5) was selected Table 4.etaβ β  turn and C sheet), 106 to 111 (C sheet and β turn), and 113. Chain A of the L5 protein trimer interacts with the CAR receptor. The residues of chain A include 412, 416, 417 (β hairpin loop), 466 to 479 (β turn and H2 domain), and 487 to 492 (A sheet).The best possible interaction complex for all receptors was obtained after docking, with the best HADDOCK score and lowest Z-score then selected for refinement. For CAR, cluster 2 (HADDOCK score −66.9 ± 2.3 and Z-score −1.6) was selected , 207 to 209 (γ β turn), 212 to 219 , 221 to 225 (E sheet), 245, and 247. Chain A of the HAdV5 L5 protein interacts with the DSG2 receptor. The residues of chain A include 417, 461 to 479 (β β turn and H2 domain), 482 to 492 (β hairpin loop and A sheet), and 544 to 549 (γ β hairpin loop).For DSG2, cluster 3 (HADDOCK score 126.4 ± 2.4 and Z-score −1.7) was selected (β turn), 33, 34, 75 to 78 (β hairpin loop), 82 to 87 (β hairpin loop), and 95 to 106 (β γ turn). Chains A and B of the HAdV5 L5 protein interact with the receptor. The residues of chain A include 404 to 408 (β hairpin loop), 462 to 477 (β β β turn and H2 domain), 482 to 492 (β hairpin loop and A sheet), 544, and 546. Chain B residues include 501 to 508 (β β β turn), 548, and 549. The interaction profile of CR1 domains 15, 16, and 17 with the HAdV5 L5 protein was also determined. Cluster 1 (HADDOCK score −75.9 ± 4.4 and Z-score −2.5) was selected (β hairpin loop), 1,087 to 1,094 (β hairpin loop and Y sheet), and 1,110 to 1,119 (Y sheet and β hairpin loop). Chain A of the HAdV5 L5 protein interacts with the receptor. The residues of chain A include 404, 417, 462 to 471 (β β β turn), 474 to 479 (H2 domain), 485 to 493 (A sheet), and 544 to 547 (γ hairpin loop). The secondary structures of CAR, DSG2, and CR1 showing the interacting domains of receptors are given in For CR1 domain 1 and 2 interaction with HAdV5, cluster 3 (HADDOCK score −86.1 ± 8.3 and Z-score −1.8) was selected . The replacement mutation or deletion of any residue out of the above-given list results in ablating the HAdV5 L5 protein interaction with the CAR receptor  , Tyr477 receptor . Anotherreceptor . We alsoβ turn), and Glu426 to Pro431 . The MET has the lowest binding affinity with the L5 protein, out of all the receptors. Only HAdV5 makes the most number of interactions with a total of 93 with a binding affinity of −10.8. MET has no common residues that interact with all L5 proteins. The IL1RAP shows a high binding affinity of −11.5 kcal mol−1 with a total of 75 interactions with HAdV2. The list of IL1RAP residues, which show interaction with all three L5 proteins, is Arg77 to Ile83 , Phe85, Arg86, Arg117, Asn118, and Thr119 (RNT). NPR3 shows the highest binding affinity with HAdV3 L5 with a total of 92 interactions. The NPR3 residues, which show interaction with all three L5 proteins, are Ala47, Leu48, Pro49, Pro50 , Pro95, Gly96, and Thr97 .The SLC2A1 receptor shows a high binding affinity with all three L5 proteins. The list of SLC2A1 residues that show interaction with all three L5 proteins is Asp177, Asn182, Lys183, Glu299, Lys300, Gln304, Leu358 to Leu361 , Gly31 to Asp34 , Ser37, Ser71 to Ser73 , Glu132 to Asn137 , Leu139, Arg141, His204 to Gln209 , Leu243, and Tyr244. The list of SLC6A6 residues that show interaction with all three L5 proteins is Tyr147, Gln151, Gln154, Asn163, His164, Ser165, Trp166, Asn167 , Lys180, Ser181, Val182, Ser183 , Arg201, Asn202, Val203 , and Leu216, Lys217, Trp218, and Asp219 . The list of TMPRSS4 residues that show interaction with all three L5 proteins is Gln227, His228, His245, Arg248, Lys249, His250 , Asn282 to Lys287 , Phe331 to Met339 , Gln384, Gly385, Ser387, and Ser405 to Tyr408 .The GABRP shows the highest number of interactions with all the L5 proteins with a binding affinity of more than −15 kcal molvia HAdV5. They have found that (Ad.5/3-CTV-M7) has an antitumor effect on primary and distant site tumor growth (in metastasis). This study showed that Ad.5/3-CTV-M7 could be utilized as a therapy against pancreatic cancer. Our study also exhibited the same outcome, as the HAdV3 L5 protein interacts better than the HAdV2 and HAdV5 L5 proteins with pancreatic cancer cell receptors.In this study, we attempt to identify better interacting adenovirus L5 protein with pancreatic cancer receptors, so that serotype can be used more effectively as an oncolytic virus. The HAdV3 L5 shows better interaction with 4 receptors NPR3, GABRP, SLC6A6, and TMPRSS4 with the highest number of interactions and better binding affinity. HAdV2 shows a better interaction profile with SLC2A1 and IL1RAP with high binding affinity, while HAdV5 interacts well with MET. The affinity maturation can be performed by mutating the fiber knob of the HAdV3 to enhance its interaction with the SLC2A1, MET, and IL1RAP specifically and also escalate the binding affinities with other receptors. David Curiel’s lab research was able to increase the efficacy of HAdV5 against prostate cancer by recombination of HAdV5 with the HAdV3 L5 protein , 66. In Oncolytic virus therapy is a promising immunotherapy approach that can be used for the treatment of pancreatic cancer. The virus’s entry entirely depends on the attachment of the virus with the cancer cell surface receptors. In the current study, the attachment or interaction profile of 3 adenovirus serotypes with the 7 pancreatic cancer cell receptors is analyzed. The L5 proteins of 3 serotypes of adenovirus HAdV2, HAdV3, and HAdV5 are docked with the seven highly expressed pancreatic cancer receptors SLC2A1, MET, IL1RAP, NPR3, GABRP, SLC6A6, and TMPRSS4. The binding affinity of the L5 proteins with human receptors is analyzed. The HAdV3 L5 protein displays a better interaction profile and high binding affinities with 4 receptors NPR3, GABRP, SLC6A6, and TMPRSS4, while HAdV2 shows better results with SLC2A1 and IL1RAP. It is proposed that affinity maturation of HAdV3 can be performed by incorporating the important interacting residues of HAdV2 and HAdV5, to enhance its binding affinity with the remaining 3 receptors SLC2A1, MET, and IL1RAP. In the future, we will perform a wet lab analysis for these interactions to further validate our results.The original contributions presented in the study are included in the article/Ethical approval/written informed consent was not required for the study of animals/human participants in accordance with the local legislation and institutional requirements.MN and RP conceived and designed the study. MN conducted the analysis and wrote the manuscript. All authors took part in the analytical discussions and critical review of the manuscript.The National University of Sciences and Technology (NUST) will pay the publication fee for this article.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Sustainable water processing techniques have been extensively investigated and are capable of improving water quality. Among the techniques, photocatalytic technology has shown great potential in recent years as a low cost, environmentally friendly and sustainable technology. However, the major challenge in the industrial development of photocatalyst technology is to develop an ideal photocatalyst which must have high photocatalytic activity, a large specific surface area, harvest sunlight and shows recyclability. Keeping these views, the present review highlighted the synthesis approaches of graphene/metal oxide nanocomposite, characterization techniques and their prominent applications in photocatalysis. Various parameters such as photocatalyst loading, structure of photocatalyst, temperature, pH, effect of oxidizing species and wavelength of light were addressed which could affect the rate of degradation. Moreover, the formation of intermediates during photo-oxidation of organic pollutants using these photocatalysts is also discussed. The analysis concluded with a synopsis of the importance of graphene-based materials in pollutant removal. Finally, a brief overview of the problems and future approaches in the field is also presented. Drinkabzirconia .2 are the most prominent material for their use as photocatalysts to treat the wastewater. ZnO has shown considerable potential in recent years due to its unique features such as its reasonable cost, strong oxidation capacity, extraordinary photosensitivity, bio consistency, acceptable photocatalytic performance, high chemical stability  excellent stability, 2) low price and low toxicity and 3) improved photocatalytic activity compared to other semiconductor materials , a chemist at Oxford University, and L. Staudenmaier in 1898 . Hummerset of GO .Moreover, based on the surface functionalization in the development of graphene semi-continuous composites with tunable textural and surface chemical features, carboxylic, hydroxyl and epoxy groups combine with valuable functionality compounds such as polymeric materials and metal oxides and accountable to use in different applications . Further2 received considerable interest in the area of the photocatalysis. The lowering of recombination process and improved the resistance to photo-corrosion for the ZnO and TiO2 photo catalyst will be of great concern. The integration of ZnO and TiO2 nanoparticles into GO surface resulting in high stability and preventing graphene-based layers from being joined due to strong van der Waals pressures that exist among graphene-based layers. In material science, synthesis of new, more efficient nanocomposites based on graphene oxide/metal oxide is becoming more and more important and some regularly used techniques are listed as follows.Due to their nano-size and good optoelectronic characteristics, the nanocomposites GO/ZnO and GO/TiOSol-gel is one of the most promising approaches to produce composite, which was originally used in late 1980s, for the synthesis of nanocomposites. The sol-gel technique is a multi-step procedure based on the metal precursors sequentially hydrolyzed for a metal hydroxide resolution followed by an instantaneous condensation to create a 3D gel, as illustrated in The gel produced is dried, which leads to aerogel or xerogel and the desired product being formed afterwards. Aquatic or non-aquatic solvents are utilized, and results are more porous than other nanocomposites and have a larger area. Graphene materials are suitable precursors to the sol-gel approach because of their strong dispersive capacity to react with covalent aqueous or non-watery chemicals and functions. During the last several decades, ZnO-rGO nanocomposites have been developed using sol-gel methods by including nanoparticles of ZnO on the surface of rGO sheets. One study reported by Azarang et al. on the preparation of ZnO-rGO using sol-gel method to investigate the effect of rGO concentration on the optical properties of the nanocomposites. Solvothermal and hydrothermal methods played an important role in various scientific fields either for commercial research purposes or basic research. These approaches are favorable as the process is simple, efficient and low-cost. The methods are also environmental friendly as there are no hazardous organic solvents being used. Usually, water or ethanol was used as the solvent and the nanoparticles are formed under a high temperature and pressure for a given time. Using this one-pot method, the metal oxide can be attached and/or wrapped to the rGO sheets simultaneously with the reduction of graphene oxide . Last fe2 solution (2 ml) obtained from Zn (CH3COO)2 solution and NaOH (1 g) was subjected to liquefaction in 25% NH3.H2O (25 ml) respectively. The mixture was added slowly in presence of NaOH solution (0.1 M) for increasing the pH until ∼10 while the solution was kept stirred in an oil bath until dark brownish liquid produced at temperature 60 ± 2°C. Later, the mixture was being exposed into treatment involving hydrothermal methods for a day (24 h) at 180°C temperature. The generation of the end product was ended by washing it with ethanol, deionized water and lastly, dried up into an oven at 60°C temperature  for 10 h at distinct temperatures which are 98°C and 80°C. The final product was then cooled until achieved 25°C temperature. The cooled sample was washed by using distilled water and ethanol. Ahmad et al. reported that the ZnO/graphene-Ag nanocomposites fabrication used simple solvothermal technique for organic dyes degradation  was produced by Hummers’ method and Zn (OH)perature . Saravanperature . The proation M. . In prev2/GO nanocomposite characteristically synthesized in optimized ratio. First, Zn2+ ions had been deposited evenly on the surface of GO and then turned it into ZnO NPs with the addition of NaOH and NaBH4 at 150°C. ZnO/graphene then produced at the end of reaction after graphene oxide reduced into graphene. Generally, ZnO NPs have grown into a range, 10–20 nm size with distribution of exquisite particle physical size on the surface of graphene layers  with stainless steel-based autoclaves for the same amount of time reaction as in ZnO synthesis. Last step, the end product obtained was washed with water, then dried out in vacuum at temperature 80°C. RGO compounds had excellent electron transportation and improved well surface area that contributed good effects to improve the nanocomposite’s photocatalytic reaction. Sahatiya and Badhulika also reported about an easy as one-step method for single graphene in-situ preparation which doped with zinc oxide (GO-ZnO) nanocomposite through using electrospinning  and aggregated porphyrin nanorods (50–60 nm width) and several hundreds of nanometers in length on the graphene surface  and grinding balls made up of stainless steel (5 mm). They fixed the ration of grinding balls to samples at 20:1 at which the mass of the balls is 500 g and the materials are 25 g. Ethanol was used as dispersant in the process. The materials were milled under the rotate speed of 500 rad/min for 12 h, and then the final product was separated from the grinding balls and dried under 60°C for 6 h. The hybrid composites showed an excellent absorption performance due to the external planar anisotropy with flake shape after ball milled . AdditioComposites preparation of GO/metal oxide is often characterized by several parameters like surface properties, optical activity, size, crystallinity, heat stability, shape, etc. These characteristics are the important informations that is required to develop composites with excellent properties. Herein, the characterization techniques are divided into following types; spectroscopic, microscopic and elemental analysis including crystalline phases analysis using XRD technique. Other characterization on thermal and physical properties of the composites will also be included in the discussion.Fourier transform spectroscopy (FTIR) is widely used techniques to identify organic compounds and in some cases, inorganic compounds. It is a rapid and non-destructive method that could detect a range of functional groups and is sensitive to changes in molecular structure. FTIR measures the absorption of infrared radiation by the sample material against wavelength. From there, the infrared absorption bands identify molecular components and structures. This method is well fitted with regard to surface chemicals, surface chemical residues, and identification on the surface of NPs for organic functional groups . In the case of GO/metal oxide composites, FTIR is best fitted with Raman spectroscopy to get the full view of the composites properties.8 ms−1); h = Planck’s constant i.e. 6.626 × 10−34 J s; 1 eV = 1.6 × 10−19 J and λ = wavelength . UV-vis measure the amount of UV light absorbs by a substance. It can be used to determine analyte concentrations or the chemical conversion of a component. The range of reflection and absorption is measured so that the nanocomposites visible and ultraviolet optical activity is defined . The chavelength . UV-vis velength .2 composite. The electronic properties were analyzed based on the diffuse reflectance spectra that are used to calculate the band gap energy. The calculation is done according to Kubelka-Munk transformed function as follow:n = 2 for permitted indirect transitions, n = 3 for forbidden indirect transitions, n = 1/2 for permitted direct transitions, and n = 3/2 for forbidden direct transitions. In another study by Ruidíaz-Martinez et al., they used UV-vis technique, to study the electronic structure of the rGO-TiOThere are several types of microscopic analysis that frequently used for composites study including scanning electron microscopy (SEM), transmission electron microscopy (TEM). SEM is a technique that may be used to improve the sample’s resolution. The surface morphology, such as determining the exact shape of nanoparticles and topographic analysis, is frequently studied using SEM and TEM methods. The main distinction is that TEM delivers more information about the interior structure and has higher resolution than SEM. The average size of material is also determined using such procedures or approaches. Meanwhile, the AFM method is often employed to collect information on the surface nature, size, shape, topography, roughness, and particle size distribution of nanocomposites . The SEMK = Scherrer constant, Β = full width at half-maximum (FWHM), λ = wavelength of the X-ray, D = particle size and θ = Bragg angle while in Bragg’s Law d is the d-spacing. Besides that, EDX method may be used to determine the types of elements present in a sample as well as their concentration. It is also commonly used to estimate the elemental makeup of composites. Moving forward, XPS is a surface-sensitive quantifiable spectroscopic technique which relies on the photoelectric consequence that can detect the elements present in a material  or on its surface, as well as their chemical states, and the overall electronic structure and density of the electronic states in the material. 2, GO and TiO2-GO composites. The TiO2 and TiO2-GO show two peaks at the binding energies of 458.5 and 464.3 eV for Ti 2p, which was assigned to the Ti 2p1/2 and Ti 2p3/2. The spectrum of TiO2 demonstrated two peaks of O 1s at 529.2 and 532.3 eV. The peaks of O 1s at about 530.3 and 531.7 eV were from the signal of O-H, C=O and C-O of GO. The TiO2 revealed four peaks at the binding energy of 529.2, 530.8, 532, and 533 eV, respectively, corresponding to the oxygen atoms of TiO2 and GO , X-ray photoelectron spectroscopy (XPS) and X-ray diffraction (XRD). XRD is used to examine nanocomposites’ crystalline phase and is distinguished by diffraction patterns for a crystal structure. X-rays may penetrate nanoparticles in order to generate the particular pattern of diffraction . In addi2 and GO .Thermal analysis of composites can be conducted through various instrumentation methods. Among all, thermogravimetric–differential thermal analysis (TG/DTA) is the most reported approaches used to illustrate the material’s thermal stability and thermal potency. Other than that, particle size analysis (PSA) is a method for determining the average size of nanocomposites. Meanwhile, Brunauer–Emmett–Teller (BET) analysis is also can be employed to study the specific surface area and porosity of composites.2, WO3, Fe2O3, SnO2, CuO, etc. Graphene derivatives inhibit corrosion, and the liquidation into the water of metal oxide nanoparticles, other than restricting the recombination of the electron hole, thereby extending the photocatalytic lifetime , which has more area than GO/ZnO nanocomposites, for photocatalysts with highly approachable surfaces . The GO/ZnO nanocomposites preparation through solvothermal method was reported by Atchudan et al.   . A numbe2–graphene composites and adjusted threshold weights for graphene (0.05 wt%)  . The phoP25 TiO2 . Liang eubstrate . The GO/activity . The TiOAu, etc. . These m2 and ZnO, other metal oxide like WO3, Fe2O3, CuO and SnO2 are considered as nontoxic photocatalyst for pollutant removal due to their low-cost, fast response and recovery time. WO3, is an n-type semiconductor, activated under visible light irradiation having small bandgap (2.4–2.8 eV) that makes it a suitable catalyst for degrading organic compounds  degradation via photocatalysis  and hydrogen peroxide (H2O2) into suspension of ZnO/TiO2 is common procedure used to increase the photo-oxidation rate   .The pH level is another key factor determining the degradation of organic compounds during photocatalytic reaction. In essence, pH has a substantial influence on the surface charge of catalyst, contaminant hydrolysis, oxidant and contaminant ionization degree . The sur2/GO composites as photocatalysts.The photocatalysis degradation development may lead to functions at optimized temperature as well as distinctive pressure because the photonic activation carries direct effect on it. This is valuable for water sanitization behaviour and the thermal phase, can be omitted to preserve power . Overall2 for 1,8-diazabicyclo (5.4.0) undec-7-ene photodegradation  or graphene nanocomposites material in the presence of light. In this case, it is required to establish a relationship between parent compound and intermediates, weather these products are more harmful or less harmful than parent compounds utilizing the toxicity test in respect of the degradation products acquired . The GC-MS analysis of an unirradiated and irradiated Ketoprofen solution showed that a single peak  was obtained in first case and several peaks were appeared at retention times (Rt) 4.07, 5.28, 7.27, 10.75, 13.20 and 17.25 in later case as shown in (3) and 2-phenylpropanoic acid (4) and a possible route for the formation of these products can be seen in Few examples which are previously discussed in literature such as Umar et al. studied the ketoprofen and chlorothalonil photodegradation pathway and found intermediate products by using the Mn-doped TiOxidation . For exaRt = 14.15 and 17.01 based on the pattern of mass fragmentation and molecular ions, were characterized as 4 and 3, which indicate a replacement of a cyanide group with a hydroxylated benzene ring group.Similarly, in the case of chlorothalonil, photodegradation and intermediate products are shown in +) peak at m/Z = 284. The peaks of m/Z of 304–306, can be attributable to the center of MB, generated by a central aromatic heterocyclic aperture by the electromagnetic interaction between •OH and sulfhydryl (C -S+ = C), leading to sulfoxide moiety production (C—S(=O)—C)  dye solution . The ESIS(=O)—C) . As a coS(=O)—C) . Low-intS(=O)—C) . MB soluic salts . Based oFurthermore, Rajamanickam et al. studied the degradation of 4-nitrophenol by using the ZnO as photocatalyst . The for2 composite as a photocatalyst. LC–MS was used to examine TBBPA intermediates in the photocatalytic degradation process. The photocatalytic degradation route of TBBPA was postulated based on the identified intermediates. The TBBPA decomposition was nearly 100% within 60 min with the formation of several intermediates, which were discovered by mass spectrometry. The mass spectra peak detected five major production ions at 465 m/z, 401 m/z. 387 m/z, 307 m/z and 227 m/z, which were labeled Products A–E as presented in Similarly, Cao et al., studied the routes for the formation of intermediate products (tetrabromobisphenol (TBBPA)-A) using the graphene–TiOBy/ comparing the mass spectra with identified products from the degradation of TBBPA reported in previous published reports . The pro2 composites was postulated based on the preceding discussion of identified intermediates and prior studies. It was also noticed that TBBPA was photodegraded by three different pathways: debromination, substitution, and dihydroxylation. However, according to an extensive literature survey there were not many studies on discussion of graphene derivatives with ZnO or TiO2 nanocomposite photodegradation by using GC–MS or EIS-MS. Few studies of ZnO or TiO2 were characterized by GC–MS or EIS-MS.Furthermore, the peak area of the above-mentioned intermediates increased, implying the emergence of additional substrates, namely intermediates and products. The peak areas of product A and product D both increased initially and then declined, indicating that their appearance was dominating in the first stage. Then both Product A and Product D were rapidly degraded. After 30 and 10 min, respectively, the peak areas of Product B1/B2 and Product E rose rapidly and reached a maximum. Then, when the irradiation duration was extended, they altered irregularly. Product E was not the end product, as can be observed, and it may have been converted into some tiny organic compounds that were not discovered in our investigation. On the other hand, over the entire 60 min, the peak area of Product C1/C2 rose steadily and constantly. It was discovered that Product C1/C2 was most likely stable and/or that their creation was faster than their degradation during the procedure. Further, the potential mechanism for the photodegradation of TBBPA by graphene–TiO2-based photocatalysts, photocorrosion is more critical than chemical corrosion. To date, numerous researches have concentrated on the improvement of ZnO or TiO2-based photocatalyst photocorrosion resistance and this should be extended to other system too. Further, bioinspiration can be a suitable technique to build new, effective, light-trapped, pollutant-absorbing designs. The synthesis of GO from waste material is an ideal approach to overcome the synthesis problem.To date, a wide variety of nanocomposites from graphene and its derivative with metal oxides are being developed for use in photocatalysis field. The research in this area is still ongoing and continually expanding as they have to overcome the technological and economic barriers in order to be practically viable. There are several concerns about the existing systems that must be addressed. Firstly, there are presently no ways of producing graphene derivatives in huge amounts which are scalable and affordable despite their remarkable applicability. Secondly, researchers have demonstrated that the photocatalytic performance of these graphene-based nanocomposites could be increase by enhancing the absorption of light, load separation and conveyance, and a longer operational life of the nanocomposite systems. Based on this point of view, some constrain need to be focused on to overcome the major scientific and technical problems preventing their utilization in applications at large scale and make it unsuitable at economic importance. For example the synthesis and design of the new graphene-based nanocomposites for photocatalyst still require integral thinking; hence the success of photocatalysis will demand future interdisciplinary effort between researchers and engineers. This approach might be useful in addressing the post-revival, recyclability, and reusability of nanocomposites. Next is the stability in the development of photocatalysts is another significant problem due to their limited useful lives and photocorrosion. For example, ZnO or TiO2 nanocomposites were studied in the expansion of new and futuristic photocatalysis materials. The present review highlighted the literature survey about graphene/ZnO and graphene/TiO2 nanocomposites from 2010 to 2020. The coupling between graphene and photoactive metal oxide semiconductors increases the photocatalytic function of metal oxide for the destruction of different aquatic contaminants such as organic dyes, heavy metal ions and pathogens. Graphene’s unique features in conjunction with nanomaterials’ size-dependent features provide other capabilities such as high adsorption capacity, wider light absorption range and better charging separation capabilities and great stability. The development of graphene/metal oxide nanocomposite-based water treatment technology is a very intriguing but tough challenge for researchers since there still are few issues, such as what the future of these composites will be like, and how environmentally friendly do they become? This also represents an important problem for the recycling and disposal of these expired composites. Strategies for the recycling and disposal in home water purity devices for waste creation will be developed concurrently. Finally, the conclusion is, the graphene/metal oxide nanocomposite has enormous possibilities as an effective photocatalyst, the problems with these materials need to be solved, for example with the nature of the chemical interaction or the bonding of metal oxides and the graphene. The need to study them carefully in order to make a more efficient photocatalyst is not fully known. In order to maximize output from these composites, thorough research on the optimization of the graphene content in the composite is needed.In summary, graphene/ZnO and graphene/TiO


An increasing number of studies have indicated a close link between DNA methylation and tumor metabolism. However, the overall influence of DNA methylation on tumor metabolic characteristics in prostate cancer (PCa) remains unclear.  We first explored the subtypes of DNA methylation modification regulators and tumor metabolic features of 1,205 PCa samples using clustering analysis and gene set variation analysis based on the mRNA levels of DNA methylation modification regulators. A DNA methylation-related score (DMS) was calculated using principal component analysis and the DNA methylation modification-related gene signatures to quantify DNA methylation characteristics. We then performed a meta-analysis to identify the hazard ratio of DMS in the six cohorts. In addition, a nomogram was drawn using univariate and multivariate Cox analyses based on the DMS and clinical variables. Finally, a drug sensitivity analysis of the DMS was performed based on the genomics of drug sensitivity in cancer datasets.  Three PCa clusters showing different DNA methylation modification patterns and tumor metabolic features were identified. A DMS system was established to quantify the characteristics of DNA methylation modification. PCa samples showed a differential metabolic landscape between the high and low DMS groups. The prognostic value of the DMS and nomogram was independently validated in multiple cohorts. A high DMS was associated with increases in the tumor mutation burden, copy number variation, and microsatellite instability; high tumor heterogeneity; and poor prognosis. Finally, DMS was closely related to different types of antitumor treatment.  Improving the understanding of tumor metabolism by characterizing DNA methylation modification patterns and using the DMS may help clinicians predict prognosis and aid in more personalized antitumor therapy strategies for PCa. CDKN24) is a suppressor gene that encodes the protein p16 and affects the cell cycle and hypermethylation in PCa ..β [TGF-βP value <0.001 were selected using the R package limma as DMM-related genes for further analysis [Differentially expressed genes (DEGs) between three DMM patterns with adjusted analysis .We performed further statistical analysis of the prognostic DMM-related genes by performing univariate Cox regression analysis on 2259 DEGs, and 337 DMM-related genes associated with DFS were selected for further analysis. To quantify the characteristics of DNA methylation modification, we performed principal component analysis (PCA) of the meta cohort to generate a DMS system. PC1 and PC2 were extracted to calculate the DMS as shown in the equation below. The advantage of this approach is that it concentrates the score on the largest set of highly correlated (or unrelated) gene blocks in the set while downweighting the contribution of genes that are not tracked by other set members , 20.i−PC2i), where i is the expression of 337 prognostic DMM-related genes. The correlation between clinical variates, DMM regulators, DMS, and DFS of patients with PCa was analyzed by performing univariate analysis. The prognostic model and nomogram were constructed using multivariate Cox regression analysis. Kaplan–Meier (K-M) survival curves were used for prognostic analysis, and log-rank tests were performed to calculate P values. To test the precision of the risk model and nomogram, time-dependent receiver operating characteristic (ROC) analysis was performed using the R package survival ROC 1.0.3. An area under the ROC curve >0.60 indicates that the prediction ability of the model was meaningful, whereas a value of >0.75 indicates an outstanding predictive value of the model. The C-index was calculated using the R package pec. Decision curve analysis was performed using the R package ggDCA.DMS = Σ and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to identify enriched GO and KEGG pathways of selected genes using the R package clusterProfiler with a cutoff of e < 0.05 .t-test was used to compare two groups with normally distributed variables whereas the Mann–Whitney U test was used to compare two groups with nonnormally distributed variables. To compare the three groups, one-way analysis and Kruskal–Wallis tests of variance were used as parametric and nonparametric methods, respectively. Contingency table variables were analyzed using the chi-square test or Fisher's exact test. A combined analysis of the hazard ratio of DMS between the six cohorts was performed by meta-analysis (fixed-effect model). Fisher's exact test was used to calculate the difference for contingency table variables, and the correlation coefficient of two variables was obtained using Spearman's correlation analysis. Statistical significance was defined as a two-tailed P value < 0.05. All statistical analyses were performed using R software .Unpaired Student's P < 0.05), as shown in P < 0.05; P < 0.05; P < 0.05; We next examined the relationship between DMM regulators and DFS through prognostic analysis of PCa. First, we collected data from 1,205 patients with DFS and other clinical information from six independent cohorts . We thenn = 156), DMM pattern B (n = 196), and DMM pattern C (n = 329). We first compared the expression levels of the regulators between the three DMM pattern groups and found significant differences in TET1, TET2, TET3, DNMT3A, DNMT3B, ZBTB33, ZBTB38, ZBTB4, UHRF1, UHRF2, MBD1, MBD3, MBD4, UNG, MECP2, TDG, SMUG1, and NTHL1 expression levels . We also detected three DMM-related gene clusters based on the expression characteristics of these 337 genes using unsupervised cluster analysis .To explore the relationship between DMS and DMM regulators, we calculated the coefficient between the DMS and DMM regulators and compared the expression levels of these regulators between the high and low DMS groups Figures . The resP < 0.05; Spearman correlation: P < 0.05; Figures We also obtained TCGA PRAD 450 K data. First, we calculated the DMS of TCGA PRAD cohort samples and divided these samples into high and low DMS groups based on the median DMS (DMS = 72.10). Unsupervised clustering (single-center method) was performed based on the 500 genes showing the most variable DNA methylation levels in turn based on DNA methylation characteristics. Remarkably, the heat map indicated that the characteristics of DNA methylation were closely associated with the DMS . We thenP < 0.05; Figures To verify the biological functions associated with DMS, we selected the significant differential ssGSEA scores of KEGG pathways and observed significant differences in the ssGSEA scores of metabolic pathways, including propanoate, arachidonic acid, fatty acid, sulfur, linoleic acid, riboflavin, alpha-linoleic acid, and 30/41 metabolic pathways , GSE70768 (log-rank test: P=0.021), GSE116918 (log-rank test: P=0.013), DKFZ (log-rank test: P=0.159), and MSKCC (log-rank test: P=0.068) cohorts  in six datasets  has been reported to reflect tumor heterogeneity . BecauseP < 0.001; Figures Copy number variations (CNVs) occurring upstream of genes regulate gene expression and influence tumor occurrence and development . To explP < 0.001; Microsatellite instability (MSI) is also a crucial indicator of genome instability associated with tumor heterogeneity . We obtaβ using the corresponding gene sets , may promote the progression of PCa, by altering metabolic pathways. Additionally, pattern C and gene cluster C were associated with the longest DFS and best prognosis, and their activated metabolic pathways fatty_acid, ascorbate_and_aldarate, cysteine_and_methionine, histidine, tryptophan, beta_alanine, selenoamino_acid, glutathione, starch_alanine, pyruvate, propanoate, butanoate, and cytochrome_p450(drug) may suppress PCa progression.Considering the heterogeneity of DNA methylation modifications individually, it is necessary to quantify the DNA methylation modification spectrum of each sample. Therefore, we constructed a DMS system and validated it in multiple PCa cohorts. To confirm that the DMS is associated with DNA methylation characteristics, we conducted unsupervised clustering using DNA methylation levels of the top 500 genes with the greatest variation in PCa in the TCGA PRAD cohort. Unexpectedly, there was a close correlation between the DNA methylation status and DMS level (high/low DMS group). Taken together, these findings reveal an association between the transcriptome and DNA methylome and support that the DMS can represent the characteristics of DNA methylation.Moreover, to validate the prognostic value of DMS, we performed hazard stratification and multivariate analysis between the DMS, TMB, Gleason score, and clinical factors in multiple PCa datasets. The results suggested that DMS is an independent prognostic factor and can help improve prognosis prediction in patients with PCa.SPOP and TTN mutation in patients with PCa. In addition, DMS can predict the efficacy of castration, androgen deprivation therapy, and chemotherapy.Finally, our results have clinical implications, as we established a DMS system that can describe DNA methylation characteristics. The prognostic value of the DMS system and nomogram based on clinical variables and DMS was validated in multiple PCa cohorts. The DMS can also be used to evaluate clinicopathological characteristics, such as the TMB, CNV, MSI status, and This study had some limitations. First, the reaction rate of the PCa antitumor therapy cohort was not accessible. The predictive value of the DMS for antitumor therapy in PCa must be further verified in further studies. Second, because of batch effects, the DMS cannot be directly compared between different cohorts without batch correction.In summary, we explored three different metabolic subtypes based on the characteristics of DNA methylation and established a DMS system for PCa. DMS, which is associated with the tumor metabolic status, TMB, CNV, and MSI, is an efficient index for predicting DFS and therapeutic responsiveness and may help facilitate personalized antitumor therapy for patients with PCa.