The large surface-to-volume ratio of electrospun nanofibers offers a considerable number of bioactive agents binding sites, which makes it a promising candidate for a number of biomedical applications. The applications of electrospinning in regenerative medicine, tissue engineering, controlled drug delivery, biosensors, and cancer diagnosis are elaborated. Electrospun nanofiber incorporations in medical device coating, in vitro 3D cancer model, and filtration membrane are also discussed.Electrospinning forms fibers from either an electrically charged polymer solution or polymer melt. Over the past decades, it has become a simple and versatile method for nanofiber production. Hence, it has been explored in many different applications. Commonly used electrospinning assembles fibers from polymer solutions in various solvents, known as solution electrospinning, while melt and near-field electrospinning techniques enhance the versatility of electrospinning. Adaption of additive manufacturing strategy to electrospinning permits precise fiber deposition and predefining pattern construction. This manuscript critically presents the potential of electrospun nanofibers in healthcare applications. Research community drew impetus from the similarity of electrospun nanofibers to the morphology and mechanical properties of fibrous extracellular matrices (ECM) of natural human tissues. Electrospun nanofibrous scaffolds act as ECM analogs for specific tissue cells, stem cells, and tumor cells to realize tissue regeneration, stem cell differentiation, and  As reported by “Research and Markets,” the global market for nanofibers can reach 1 billion U.S. dollars by the end of 2021.μm–1 cm,In solution electrospinning where a polymer solution is elongated and thinned by whipping effect, quick evaporation of solvents results in solidification of the polymer jet and nanofiber deposition, whereas in melt electrospinning , polymerRecently, researchers have adopted additive manufacturing (AM) concept to electrospinning for more accurate control of fiber deposition.Initial applications of electrospinning emerged in air filtration and personal protection purposes. Subsequently, efforts are made for diverse applications in medicine and healthcare, water treatment, damage resistant composites, light weight buildings and construction, mitigation of noise pollution, energy generation and storage, photonics, electronics, and wearables. This paper focuses on medicine and healthcare applications.Bioengineering and biomedical engineering research community drew impetus from the similarity of electrospun nanofibers to the morphology and mechanical properties of fibrous extracellular matrices, extracellular matrix (ECM) of natural human tissues [et al. in 1977.in vitro 3D cancer models, viral and microbial resistant surgical masks, respirators, personal protective equipment, and filtration membranes related to the coronavirus disease 2019 (COVID-19) outbreak are discussed as well. Current challenges in each application are mentioned along with future perspectives.Nanofibers with relatively large surface-to-volume ratio and nanofibrous structure with high porosity make electrospun products potential for tissue engineering and regenerative medicine, drug delivery, biosensors, diagnostics, etc. . The firTissue engineering, as first fully illustrated by Langer and Vacanti,Recent electrospun scaffolds in tissue engineering and regenerative medicine could combine various guidance to address aforementioned problems via a synergistic effect on stem cell differentiation [Mechanical properties incompliance between electrospun scaffolds and native bones is a common problem. Polymers are the most commonly electrospun materials, yet exhibit lower modulus than native hard tissue in general.et al. combined direct writing with solution electrospinning for hierarchical scaffolds fabrication mimicking the zonal organization of articular cartilage.Unlike bone, the major components in cartilage are type II collagen and proteoglycan. There is a zonal organization and distribution of collagen in cartilaginous ECM that the content decreases from the superficial zone to the deep zone. Collagen fibrils are aligned parallel to the articular surface in the superficial zone, while they are oriented perpendicular to the articular surface in the middle and deep zones. For 2D planar mats, the ongoing challenge is to achieve complete cell infiltration through the defects. A 3D nanofibrous scaffold with hierarchical architecture, sufficient compressive strength, and highly interconnected pores is more ideal. Chen Collagen fibers are closely packed in parallel arrays in tendon and ligament. Thus, uniaxially aligned nanofibrous mats are widely applied to tendon and ligament regeneration. Uniaxial aligned nanofibers can be easily collected using a rotating collector or extra parallel electrodes. Adipose derived MSCs and iPSC derived MSCs show tenogenic differentiation on uniaxial nanofibers. However, the bulk of tendon and ligament tissue present highly anisotropic structures. 3D scaffolds with braided, woven, or knitted yarn networks are more favored compared to 2D mats. When including hydrogels into the nanofibrous matrix, it can benefit biomolecule and cell encapsulation. For example, unidirectional PCL nanofibers were once coated with chitosan/hyaluronic acid hydrogel for ligament regeneration.et al. designed a 3D hybrid scaffold that assembled PCL nanofibers with gradients of chondroitin sulfate and bioactive glass into hydrogel.Currently, regeneration of tissue-to-tissue interface remains challenging. Those interfaces contain soft-to-hard interfaces and soft-to-soft interfaces. In the junctions between a soft matrix and a hard matrix , there are gradual variations in matrix composition, architecture, mineral content, and significant difference in mechanical properties.et al. developed PCL/poly (lactic acid) (PLA) nanofibrous scaffolds which followed the mechanical trend of native myotendinous junctions.Muscle-to-tendon interface and interface at the neuromuscular junction are two typical soft-to-soft tissue interfaces. The myotendinous junction connects dense collagen fibers in tendon to softer muscle fibers. The main difficulty in regeneration of myotendinous junction is a comparable stiffness transition to native junctions. For example, Ladd et al. developed honeycomb-patterned scaffolds for better mimicking the myocardium architecture.et al. developed a 3D bioactuator in a tubular shape by loading cardiomyocytes on conductive PLA/PANi nanofibers, which combined topographic, biological, and electrochemical cues together.It is critical to maintain sufficient mechanical strength in the cardiac tissue to sustain myocardium contraction and relaxation. The perimysial fibers in myocardium exhibit a coiled structure and contribute to the interwoven structure of myocardium. Complete replication of such anisotropic organization and mechanical capability of cardiac tissue remains challenging. Liu et al. developed radially aligned electrospun collagen/PCL mats with a circular gradient of biomolecules incorporation.in vitro neural tissue regeneration studies. A nerve guidance conduit (NGC) with a complex, multitubular structure is widely used in in vivo studies. Currently, including all the topographic and biochemical characteristics of the native nerve tissue in the NGC design remains challenging. The size of intraluminal microchannels in NGC can be controlled via sacrificial templates such as sucrose fibers.in vivo axonal regeneration. Further study can focus on integrating biological, topographic, and electrochemical cues in nanofibers for better neural regeneration due to the synergistic effect of those guidance.Both uniaxially and radially aligned nanofibers have been demonstrated to be effective in neural regeneration. Bone marrow derived MSCs can differentiate into Schwann cells on uniaxially oriented PCL nanofibers.There are commercially available vascular grafts for large-size blood vessels regeneration, yet studies of regenerating blood vessels of small diameter  are quite limited. Unlike the grafts for large-diameter arteries, the major concern for small-diameter vascular grafts is maintaining the lumen patency.in vivo.In native ECM, the fibrous structure always exhibits a more complex architecture other than simple unidirectional alignment. Collagen fibrils in skin tissue show a mesh-like or a basketweave-like pattern. Therefore, scaffolds with crossed nanofibers showed higher keratinocytes and fibroblasts migration rate, thus better wound healing performance than either random or unidirectionally aligned nanofibers.The principle of using polymer nanofibers as drug carriers is that the dissolution rate of drugs increases with the increase in surface area of both drugs and carriers.Physical adsorption is the simplest way to introduce drugs to the electrospun matrix, which is prone to an initial burst release and inefficient in sustained drug release.et al. investigated different release kinetics between doxorubicin base and doxorubicin HCl in electrospun PLLA nanofibers.Blend electrospinning and emulsion electrospinning of bioactive drugs and polymers are two typical strategies to incorporate drugs in as-spun nanofibers. Electrospinning of drug and polymer blends with a hand-hold device allows for direct deposition of drug loaded fibrous matrix to the wound site. However, one thing worth noted is that the addition of drugs could affect the properties of electrospinning solution such as solution conductivity and viscosity. When loading meloxicam in PVA solutions, the solution viscosity was elevated and, in turn, resulted in thicker fibers as reported.When processing drugs/polymer blends through electrospinning, preserving the bioactivity of drugs is another challenge. Drugs would be in direct contact with organic solvents, high electric charge, and even mechanical stress during electrospinning. Therefore, the bioactivity of drugs, some labile molecules in particular, will be hindered. To stabilize the drugs, binding them to other molecules may be an option.3-capped mesoporous SiO2 nanoparticles in PLLA electrospun fibers.3 and the acidic environment on the tumor site would stimulate the release of DOX, while in the normal tissue with the physiological pH, only a minor release of such anti-tumor drug was detected. That pH-responsive anti-cancer efficacy can last over 40 days. Trametinib loaded hollow copper silicate was introduced to the PCL/poly  (PDLLA) electrospun matrix for chemo-photothermal therapy of melanoma.One current research focus is on the construction of a “smart” drug delivery system for controlled release in terms of target-specific and triggerable. Incorporating drug loaded nanoparticles and microspheres into electrospun nanofibers is a common strategy for better control of drug release. The host fiber characteristics as well as the particle properties can be both tailored for specific requirements. The drug delivery system containing drugs encapsulated particles and electrospun nanofibers is highly desired in cancer therapeutics. Localized and controlled chemotherapy can be achieved with higher therapeutic efficiency but lower drugs dosage; hence, there is lower toxicity to the surrounding tissue. A pH-sensitive anti-tumor drug delivery system was constructed by encapsulating CaCOBiosensors are normally composed of biofunctional membranes and transducers for biological substances detection, where the sensing membrane is responsible for substances recognition, and transducer converts it into output signalsIncorporation of biomolecules to electrospun nanofibers is common for substance recognition. For example, glucose oxidase is a glucose sensitive enzyme, which has been widely immobilized on electrospun nanofibers for glucose biosensors construction. However, use of enzyme is usually associated with instability and denaturation problems. Therefore, several studies investigated non-enzymatic glucose sensing using carbon, metals, and their oxides as electrodes. In one demonstration, bimetallic nanoparticles CuCo doped electrospun carbon nanofibers were developed for enzyme-free glucose detection.2 nanofibers. This microfluidic biosensor allowed a wide concentration range of target ErbB2 antigen and achieved femtomolar sensitivity. CTCs are cancer cells that shed from the primary tumor and circulated into the bloodstream leading to metastasis.Electrospun nanofibers incorporating biosensor can be used for early cancer diagnosis. Substances to be detected for early cancer diagnosis include specific biomarkers overexpressed by cancer cells, oxygen level, and circulating tumor cells (CTCs). Specific antibodies, surface functional groups, and oxygen sensitive materials can be incorporated to electrospun nanofibers early diagnosis. For instance, epidermal growth factor receptor 2 (ErbB2)-antibody was conjugated to mesoporous ZnO nanofibers for breast cancer diagnosis.et al. coated biodegradable magnesium prosthesis with a porous PCL layer through electrospinning.Electrospun nanofibers can be deposited on medical implants to improve the biocompatibility or acquire additional function. Nanofibrous coating would change the implant surface topography, thus providing topographical cues to surrounding cells and tissue. Incorporating bioactive agents or even cells into nanofibers can achieve multifunctional medical device coating such as drug delivery. Palumbo in vitro cancer models provide an effective way for drug screening, anti-cancer mechanism, and tumor cell biology. Traditional 2D cancer models employ culturing tumor cell monolayer on 2D flasks, which can reflect cancer cell behavior to a certain degree.The in vitro 3D tumor model, electrospun nanofibers play a role in replicating native extracellular environment for the tumor cells. Electrospun nanofibers can realize the biochemical stimuli of native tumor ECM through surface functionalization with biomolecules or drug encapsulation. For instance, perlecan domain IV peptide was conjugated on electrospun PCL/gelatin nanofibers to construct a pharmacokinetic prostate cancer model.in vitro 3D tumor models encounter some challenges including failure in mimicking the tumor angiogenesis, heterotypic cell-cell signaling, biomechanical stimuli, and insufficient cell infiltration. Inclusion of bioreactors in model fabrication can provide mechanical stimulus to cancer cells.Electrospun nanofibers mimic the native structure and composition of ECM for target tissue regeneration or mimic the stem cell niches for stem cell differentiation. Similarly, to construct an Large surface-to-volume ratio, light weight, high porosity, interconnectivity, and microscale interstitial space make electrospun nanofiber meshes an excellent material for filtration applications in terms of personal protective equipment. Conventional protective clothing is based on full barrier protection that is limited in weight and moisture retention.We overviewed the advances of electrospun nanofibers in biomedical applications and highlighted the application in tissue engineering, drug delivery, biosensors, and cancer diagnosis. There are various types of commercial biomedical products based on electrospun nanofibers . ElectroBy optimizing properties, nanofibrous mats in terms of fiber diameter, orientation, morphology, porosity, mechanical properties, and electrospun nanofibrous products can be explored for more specific requirements of different applications. Melt electrospinning and near-field electrospinning can avoid toxic solvents incorporation and high electric field interference, respectively. Inspired by AM, direct writing electrospinning allows development of highly customizable 3D constructs with well-defined features, while those techniques typically generate fibers on micrometer scale, which limits their employment in nanometer scale favored applications. Hence, a complete understanding of electrospinning mechanisms, specifically in the fast acceleration zone that contributes to sufficient thinning of fibers, will benefit the prediction of fiber properties. Simulation and modeling design of such mechanism can help with electrospinning parameters selection prior to the actual experiments. There are concerns associated with the environmental effect of organic solvents during solution electrospinning. How to achieve a “green” process remains to be addressed. Besides, there are difficulties in scale-up production due to the lack of a reliable system for quality control. With a comprehensive understanding of the electrospinning mechanism and better control of nanofiber properties, further developments of electrospinning in healthcare in the following decades can be expected.


The crack propagation and failure of 3D-printed samples with prefabricated K–S fissures (a kinked fissure and a straight fissure) were observed under uniaxial compression, and the strain and displacement of the sample surface were quantified by the digital image correlation (DIC) method. The experimental results show that the branch inclination angle of the kinked fissure is an important factor affecting the crack initial position, and the evolution of the strain field during the failure process of the sample can better reflect the cracking law of the internal fissures. Furthermore, two coalescence modes are classified: Mode I is a tension–shear composite failure formed by the penetration of the tension–shear composite crack; Mode II is a tensile failure that penetrates the whole samples during the failure process without rock bridge damage. In addition, the numerical simulation results were well consistent with the cracking and failure modes. For a preexisting fissure, new cracks form and subsequently coalesce with other preexisting fissures due to a disturbance, which causes the failure of the rock bridge and eventually causes overall damage ,2,3,4,5.Some previous experiments have investigated the failure characteristics of brittle materials with multiple straight fissures. Sagong and Bobet  carried Non-straight fissures extensively exist in natural environments. The experimental materials can be categorized into rock-like materials ,22,23 an2D produced by Tang et al. [In addition, numerical simulation methods are also widely used in fracture mechanics, and they have effectively overcome the shortcomings in crack propagation research. Commonly used numerical simulation methods include the finite element method ,32,33, bg et al.  has beeng et al. . 2D software.Therefore, a photosensitive resin material was used for 3D printing, and samples containing K–S fissures were prepared. Six inclination angles of the branch in the kinked fissure were selected, and uniaxial compression loading of these samples was performed using a rock mechanics servo-controlled testing system. As a result of the transparency of the samples, the crack initiation and propagation process of prefabricated fissures can be clearly observed. In addition, digital image correlation (DIC) technology was used to monitor the evolution of the strain during the whole test. The strength, crack initiation, and propagation process of the sample and the coalescence of the rock bridge between prefabricated fissures were studied. Finally, the samples were numerically simulated using RFPA3 (L × W × H), as shown in The experimental samples were produced by the RS Pro 450 3D printer whose forming range is 450 × 450 × 350 mma1, the branch fracture length of fissure II, b, the main fracture inclination of fissure I, θ1 , the branch fracture inclination of fissure I, β (the angle between fissure II and the y-axis), the length of fissure II, 2a2, the inclination of fissure II, θ2 , the distance between kinked fissure I and straight fissure II, 2c; and the two fissures are coplanar and nonparallel. As shown in Fissure I is a kinked fissure, and fissure II is a straight fissure, as illustrated in β while keeping the other six parameters unchanged , as shown in β, is designed as +45°, +90°, +135°, −45°, −90°, and −135°. In addition, there is a control group containing two nonparallel straight fissures. Each sample type includes four identical samples, and a detailed description of the samples containing different geometry fissures is presented in In these samples, different branch fracture inclination angles were designed by changing It is important to note that the term “fissure” is used to describe a prefabricated artificial defect, and the term “crack” is used to describe new fractures and damages formed under loading.The DIC technique is a widely used full-field measurement technique. Conceptually, the DIC technique is only a particle tracking method that can be used to determine the position of particles (spots) in digital images. More specifically, DIC is a non-contact optical method for analyzing digital images to extract the field displacement surface of specimens . DIC canUniaxial compression tests of the photosensitive resin samples containing intermittent K-S fissures were conducted using a rock mechanics servo-controlled testing system, as shown in The tensile–shear composite failure of the rock bridge is caused by the coalescence of a tensile–shear composite crack in the rock bridge. As shown in (1) The development of tensile–shear composite cracks is in the direction of σ1, and the normal stress on the surface reaches the tensile strength σt of the material.(2) The stress state on the tensile–shear composite crack surface meets the Mohr–Coulomb criterion.Then, the coalescence strength of the rock bridge ish(mm) is crack horizontal spacing, σt(N/mm2) is the uniaxial tensile strength of the sample material, α (º) is the inclination angle of the rock bridge, φ (º) is the angle between σ1(N/mm2) and the crack, fr is the coefficient of friction, cr(N) is the cohesion, l(mm) is the propagation of the branch crack, h0(mm) is the vertical distance between two cracks, Cn is the pressure transfer coefficient, and Ct is the shear transfer coefficient.Among them, # before and after the experiment, and the consistency of failure mode for samples KS + 45#-1, KS + 45#-2, and KS + 45#-3 after the experiments is shown in #-1, KS + 45#-2, and KS + 45#-3 is shown in Therefore, the 3D-printed resin material is stable and can be used to study the macro failure mode of the brittle material.# contains two intermittent straight fissures. Samples KS + 45#, KS + 90#, KS + 135#, KS - 45#, KS - 90#, and KS - 135# all contain a kinked fissure and a straight fissure, and the branch fracture inclination angles are +45°, +90°, +135°, −45°, −90°, and −135°. According to # exhibits an average peak strength of 69.58 Mpa, and for the samples with kinked fissures whose angles are positive, the average peak strength values are not very different from that of sample TS#, 65.90 Mpa (KS + 45#), 69.92 Mpa (KS + 90#), and 72.77 Mpa (KS + 135#). The peak strength of sample KS + 45# decreased by 5.58%, the peak strength of sample KS + 90# exhibited almost no significant change compared with that of sample TS#: it only increased by 0.49%, while the peak strength of sample KS + 135# increased by 4.38%. The maximum strength (KS + 135#) differs from the minimum strength (KS + 45#) by approximately 9.96%. #), 68.09 Mpa (KS - 90#), and 71.93 Mpa (KS - 135#). The peak strength of sample KS - 45# increased by 1.97% compared with that of sample TS#, while that of sample KS-90# decreased by 2.19%, and that of sample KS-135# increased by 3.27%. The maximum strength (KS - 135#) differs from the minimum strength (KS - 45#) by approximately 5.64%.In conclusion, when the inclination angle of the branch of the kinked fissure rotates clockwise, the peak strength increases, and the difference between the maximum strength and the minimum strength is approximately 9.96%. When the inclination angle of the branch of the kinked fissure rotates anticlockwise, the peak strength will not change obviously, and the difference between the maximum strength and the minimum strength is approximately 5.46%.#, KS + 90#, and KS - 45#, were selected as the analysis cases. Three photos of three stages in each sample were selected for DIC analysis. These three phases are marked as I, II, and III. Phase I corresponds to the beginning of the loading stage, phase II corresponds to the stage of sample cracking, and phase III corresponds to the stage before the peak stress. The results of the DIC analysis are shown in #, during Phase I, there is some strain shrinkage at the edge of the sample and near the prefabricated fissure, while the principal strain of the whole sample is almost uniform in all regions , and when β = −45°, −90°, and −135°, the kinked fissures all originate from the crack tip. Two failure modes were identified, as shown in 2D software. The calculation method is based on the finite element theory and statistical damage theory and considers the heterogeneity of the material properties and the randomness of defect distribution. Numerical calculations of the crack propagation of samples with straight fissures and K–S fissures were performed using RFPAThe width and the height of the numerical model are both 60 mm, and a square element grid was used to divide the sample into 200 × 200 = 40,000 square elements. The parameter settings are shown in #. At the beginning of the loading, a significant stress concentration occurred at the prefabricated fissures tips. When the loading was continued for 20 steps, the crack tips of the straight fissures initiated and formed tensile cracks. When the load continued to step 50, the tensile cracks extended along the axial direction. During the development of the tensile cracks, the tips produced a stress concentration zone, and the stress concentration at the tips further guided the propagation of the tensile cracks for step 60. In addition, small cracks appeared at the position of the rock bridge. At step 80, which is the end of the loading, the rock bridge coalesced, two tensile cracks penetrated through the whole sample, and the sample failed. #, KS + 90#, KS + 135# and KS-135# are similar to that of sample TS#, and the rock bridges of these samples were penetrated. # only had tensile cracks that penetrated the entire sample, and the rock bridge was not damaged , the peak strength increases. When the branch inclination angle of the kinked fissure rotates counterclockwise , the peak strength does not change significantly, and the difference between the maximum and minimum strength does not exceed 10%.The primary crack may initiate from the inflection point or the end tip depending on the inclination angle β of the kink branch. When β = +45°, +90°, or +135°, the kinked fissures form crack from the inflection point. When β = −45°, −90°, or −135°), the kinked fissures incur crack from the end tip.The small kink branch may change the failure mode of the samples completely, and the inclination angle β of the kinked fissure has an important effect on the failure mode. When β = +45°, +90°, +135°, or –135°, a tension–shear composite failure mode (Mode I) occur in the rock bridge. When β = −45° and −90°, tensile failure is incurred throughout the whole samples, while the rock bridge does not damage.The numerical simulation failure modes of the models are well consistent with the cracking and failure modes of the physical experimental samples.In this study, 3D printing technology was used to prepare the intermittent K–S fissure samples. Combined with the DIC experimental method, the strain field and failure modes around the K–S fissures under the uniaxial compression load were visually and quantitatively displayed. The main conclusions include the following:Notions:I = Kinked fissureII = Straight fissureθ1= Angle between fissure I and the horizontal axisθ2= Angle between fissure II and the horizontal axis β = Angle between fissure II and the y-axis a1= Main fracture length of fissure I2a2= Length of fissure II2c = Distance between kinked fissure I and straight fissure II2


Here, we aimed to assess this same effect in 44 new participants, who had previously undergone an [18F]DOPA-PET scan to quantify dopamine synthesis capacity. This sample performed the exact same rewarded Stroop paradigm as in the prior study. However, we did not find any correlation between reward effects on cognitive control and striatal dopamine synthesis capacity. Critical differences between the radiotracers [18F]DOPA and [18F]FMT are discussed, as the discrepancy between the current and our previous findings might reflect the use of the potentially less sensitive [18F]DOPA radiotracer in the current study.Reward motivation is known to enhance cognitive control. However, detrimental effects have also been observed, which have been attributed to overdosing of already high baseline dopamine levels by further dopamine increases elicited by reward cues. Aarts et al. (2014) indeed demonstrated, in 14 individuals, that reward effects depended on striatal dopamine synthesis capacity, measured with [ However, negative effects of rewards on cognitive control have also been observed9. For example, it has been demonstrated that when participants received performance-contingent payment for completing various tasks—including tasks that drew primarily on motor skills, memory and creativity—high reward levels had detrimental effects on performance, compared with low and medium reward levels8. The authors argued that high reward levels can shift arousal or motivation levels beyond the optimal level for executing a task, leading to performance decrements, an effect known as choking. However, not everyone chokes under high reward conditions and to gain more insight into this individual variation we must unravel the neural mechanisms underlying these choking effects. Motivational effects have long been associated with striatal dopamine signaling12 and prior work indeed suggested that individual variation in the effects of motivation on cognitive control depends on dopamine-related functioning, such as dopamine cell loss in Parkinson’s disease, midbrain and striatal BOLD activity, loss aversion and dopamine transporter genotype14. Detrimental effects of rewards resonate with the notion of a potential overdosing of the dopamine system: Rewards, eliciting dopamine release15, could have beneficial effects in individuals with low dopamine levels by inducing a shift from sub-optimal to optimal dopamine levels, but detrimental effects in individuals with already high dopamine levels by inducing a shift from optimal to supra-optimal dopamine levels16. Building on this work, our previous study17 directly addressed this issue by assessing the effect of reward on cognitive control as a function of dopamine synthesis capacity, measured with 6-[18F]-fluoro-L-m-tyrosine ([18F]FMT) positron emission tomography (PET). Specifically, participants performed a Stroop task after being promised either a high or a low monetary reward upon successful completion of the task. These monetary incentives were demonstrated to enhance Stroop interference control in participants with low baseline dopamine synthesis capacity in the left caudate nucleus, but impair Stroop interference control in participants with high baseline dopamine synthesis capacity in the left caudate nucleus. This study thus advanced our understanding of differential effects of incentives on cognitive control, by demonstrating that incentive motivation can shift dopamine levels to supra-optimal in participants with already high dopamine levels. It is of note that this effect was present only when participants were uninformed  about the congruency of the upcoming Stroop target and not when Stroop targets were preceded by cues informing subjects about their congruency.Incentive motivation, or motivation activated by external reward cues, is generally thought to enhance cognitive controlDAT1 during rewarded cognitive control18. Moreover, this finding generally concurred with evidence from an fMRI study demonstrating enhanced connectivity between the ventral striatum and left caudate nucleus when cognitive demand for reward was high19. The focus of the effect on the caudate nucleus also converged with functional MRI work from a third research group demonstrating a modulation by reward incentives of specifically the caudate nucleus during (oculomotor) control20. Finally, confidence in a negative correlation between individual differences in baseline dopamine levels and reward effects on cognitive control was further increased following a subsequent study in Parkinson’s disease patients, revealing greater beneficial effects of reward on cognitive control in patients with greater dopamine cell loss, measured with CIT-SPECT13.The finding that a negative correlation between reward effects and dopamine synthesis capacity was present specifically in the left caudate nucleus strengthened evidence from two other prior studies, implicating specifically the left caudate nucleus in the effects of the dopamine transporter gene 21, but also with high likelihood that effect sizes are biased and overestimated22. Therefore, we here aimed to test the effect found by Aarts et al. using a new, larger participant sample, who had already, as part of a previous study, undergone a PET scan with the radiotracer [18F]fluoro-3,4-dihydroxyphenyl-L-alanine ([18F]FDOPA). Specifically, we hypothesized that the effect of anticipated reward on Stroop interference control depends on individual differences in baseline dopamine synthesis capacity in the left caudate nucleus. We supplemented the analyses with voxel-wise correlations of the behavioral measures with dopamine synthesis capacity. Critically, striatal dopamine synthesis capacity in this new sample had already been indexed in the context of a previous study not reported here , using [18F]DOPA PET. This is unlike the original study, in which [18F]FMT PET was used to index striatal dopamine synthesis capacity. While [18F]DOPA PET is considered less sensitive than [18F]FMT PET, due to increased background noise and cell clearance of radiolabeled metabolites, we anticipated that a strong association between striatal dopamine synthesis capacity and motivational effects on cognitive control should surface also with [18F]DOPA PET.However, the sample size (n = 14) of the key PET study providing the direct evidence for baseline-dependency of reward effects on cognitive control in healthy volunteers was very small for a between-subject correlational design. Such a small sample size is associated not only with low positive predictive value25, a topic of great societal relevance today. A preregistration of this study, data and code are available via https://osf.io/ky9s2/.The present attempt at conceptual replication was driven by our goal to increase our confidence in the role of dopamine synthesis capacity in motivated cognitive control and is of particular interest because a robust mechanistic account of the link between incentive motivation and cognitive control will advance our understanding of who chokes under high reward conditions and why18F]DOPA PET study  accepted the invitation to participate in the current study. All participants gave written informed consent according to the declaration of Helsinki and the experiment was conducted in compliance with and was approved by the local ethics committee . One dataset was excluded due to an error rate above 33%  we adhered to Simonsohn26 recommendation to obtain a sample size at least 2.5 times larger than the original sample size (N = 14). The new sample had 90% power27 to detect a correlation of r = 0.55, which is considerably lower than the correlation of r = 0.75 reported in the original study  right-handed and native Dutch-speaking volunteers who had participated in a previous DOPA. Participants received 150 mg of carbidopa and 400 mg of entacapone 50 min before scanning, to minimize peripheral metabolism of [18F]DOPA and thereby increase central [18F]DOPA availability. The procedure started with a low dose CT scan (approximately 0.75 mCi) followed by a bolus injection of [18F]DOPA into an antecubital vein and an 89 min dynamic PET scan (approximately 5 mCi). The data were divided into 24 frames  and reconstructed with weighted attenuation correction and time-of-flight recovery, scatter corrected, and smoothed with a 3 mm full-width-at-half-maximum (FWHM) kernel.PET scans were carried out at the Department of Nuclear Medicine of the Radboud university medical center, using a Siemens PET/CT scanner and the radiotracer DOPA influx constant per minute (Ki) per voxel relative to the grey matter of the cerebellum, using Gjedde-Patlak graphical analysis28. The individual cerebellum grey matter masks were obtained by segmenting the individuals’ anatomical MRI scan, using Freesurfer (https://surfer.nmr.mgh.harvard.edu/). The Ki values were calculated based on the PET frames from the 24th to 89th minute. We then extracted average Ki values from six regions of interest (ROIs)—left and right caudate nucleus, putamen and ventral striatum—defined using masks based on an independent functional connectivity-analysis of the striatum29 . Analyses assessing the relationship between dopamine synthesis capacity in the left caudate nucleus as specified according to Mawlawi et al. and the effect of reward on Stroop interference can be found in the Supplementary information, including Supplementary Fig. i maps were normalized to MNI space and smoothed using an 8 mm FWHM kernel.PET data were preprocessed and analyzed using SPM12 . We corrected for multiple comparisons , resulting in a Bonferroni-corrected alpha value of 0.0042. Pearson’s correlations were calculated between the Ki values of the six ROIs and the effect of reward on Stroop interference in terms of RT on uninformed trials for comparison with the original study17. We supplemented the analyses with voxel-wise correlations between the reward effect on Stroop interference and dopamine synthesis capacity within the voxels comprising the entire striatum . Statistical significance was defined as family-wise error corrected p < 0.05 at peak coordinate, after small volume correction for all voxels within the striatal region of interest.The main effect of interest was the correlation between the effect of reward on Stroop interference (in terms of response times) on uninformed trials and dopamine synthesis capacity in the left caudate nucleus, as was observed in the original study. For completeness, we also explored the other five ROIs. We analyzed response times (RTs) of all correct trials, including trials on which participants were “too late”, and error rates. Participants with error rates above 33% were excluded. We ran separate repeated measures analyses of variance (rmANOVA) for each region of interest and two dependent variables: Stroop interference on RT and on error rate . The within-subjects factors were REWARD  and INFORMATION , and [18F]DOPA uptake shows high test–retest reliability within a time frame of 2 years32, we performed additional regression analyses, separately for each of the six ROIs, to assess whether any effects of the interaction between REWARD and dopamine synthesis capacity on Stroop interference depended on time between the PET scan and the behavioral testing day, while also including age and gender in the model, using the lm function from the stats package in R.Although striatal DOPA and [18F]FMT Ki values.To allow for quantification of evidence for or against our hypotheses, we additionally report Bayesian individual effects analyses performed in JASP (version 0.10.2.0), with default JASP Cauchy priors. The BF18F]DOPA Ki values, time between the PET and behavioral session, overall response times and age) were mean centered.All continuous independent variables  = 185.3, p = 3.438e−17, BFINC = 3.217e+14; error rate: F = 137.7, p = 5.394e−15, BFINC = 6.434e+13), on uninformed than informed trials  = 35.0, p = 4.829e−7, BFINC = 3.217e+14; error rate: F = 34.1, p = 6.224e−7, BFINC = 4.949e+13) and low reward than high reward trials  = 14.2, p = 4.974e−4, BFINC = 3.217e+14; error rate: F = 0.2, p = 0.662, BFINC = 4.949e+13). These results validate the task manipulation, and they are similar to findings in the original study.Participants performed more poorly on incongruent than congruent trials  did not overlap with that of the originally reported effect of r = 0.75. Upon visual inspection of Fig. 30 and used in Aarts et al.17 and the effect of reward on Stroop interference  = -3.4, p = 0.001; Table t(37) = -0.9, p = 0.379). However, we did not observe a significant REWARD (by INFORMATION) by dopamine synthesis capacity interaction effect on Stroop interference  = -4.1, p = 2.0e−4; Table t(39) = -1.9, p = 0.064). However, we did not observe a significant REWARD (by INFORMATION) by dopamine synthesis capacity effect on Stroop interference  =  − 0.3, p = 0.767; Table F = 0.2, p = 0.660), respectively.To establish that the discrepancy between the studies does not reflect differences in the dynamic range of the key variable of interest, we also compared the means and variances of the reward effects on Stroop interference on uninformed trials in terms of RT between the two studies. The two participant samples did not differ significantly from each other in terms of their means and variances Fig. , as reve18F]DOPA PET, on Stroop interference. Bayesian analyses in fact provide evidence in favor of a lack of a relationship between dopamine synthesis capacity and reward effect on Stroop interference. Our conclusion is therefore not consistent with the earlier findings by Aarts et al.17.The current study reveals no evidence for an interaction between monetary incentives and dopamine synthesis capacity, indexed with [18F]DOPA in the present study, as opposed to [18F]FMT used in the original study. [18F]DOPA is a substrate for catechol-O-methyltransferase (COMT) in the periphery. Metabolites can cross the blood–brain-barrier and will distribute evenly throughout the brain, enhancing background noise relative to the use of [18F]FMT, which is not a substrate for COMT34. However, this is mainly a concern when one is interested in brain areas with low dopamine levels, as opposed to the dopamine-rich striatum. Moreover, entacapone was administered before PET scanning to inhibit peripheral COMT metabolism, further reducing the risk of a too low signal-to-noise ratio. [18F]DOPA and [18F]FMT also differ in their metabolic actions after decarboxylation by aromatic amino acid decarboxylase (AAAD), including higher affinity of [18F]DOPA metabolites compared with [18F]FMT metabolites for the vesicular monoamine transporter, leading to increased cell clearance of radiolabeled [18F]DOPA metabolites35. Indeed, differences in aging effects on dopamine synthesis capacity measured with [18F]DOPA and [18F]FMT have been observed, possibly owing to age-related changes in post-AADC metabolism36. However, this would mostly be a concern for extended scanning times, as [18F]DOPA behaves as an irreversibly bound tracer in the first 90 min after tracer injection, during which their uptake rates are tightly correlated35.It is possible that the discrepancy between the findings of the two studies reflects the use of [16, monetary incentives might enhance Stroop interference control in participants with very low average levels of baseline dopamine, whereas those incentives would impair control in participants with very high average levels. Sampling only participants with intermediate dopamine levels should lead to very small reward effects. However, a comparison of reward effects between the two studies demonstrated similar means and variances within the two samples. We therefore argue that the current result decreases our belief in the previously observed correlation between motivational effects on cognitive control and baseline dopamine synthesis capacity.Another possibility is that the discrepancy between the original and the current study was introduced by group differences in sample characteristics. However, differences in overall response times and age did not explain the lack of significant effects in the current study. According to the dopamine overdose hypothesis18, dopamine release37 or dopamine-related disease status39. Similarly, the current failure to replicate does not undermine other studies demonstrating a link between dopamine synthesis capacity and cognitive motivation indexed with other tasks, such as delay discounting40, cognitive effort discounting24 or reward-based reversal learning41. Nevertheless, the presently observed lack of effect reduces our confidence in the link between dopamine synthesis capacity and the effect of a promised reward on Stroop interference and stresses the need for further studies.Notably, this conclusion would not imply that dopamine transmission is not important for the motivation of cognitive control, because brain dopamine levels are a function not only of dopamine synthesis capacity, but also of other factors, including transporter density, dopamine receptor availability, dopamine release and genetic make-up. Thus, the current study cannot refute hypothesized correlations between motivational effects on cognitive control and other measures of dopamine function. For example, the current design does not disconfirm previously demonstrated and replicated links between motivation, cognitive control and polymorphisms in the dopamine transporter geneSupplementary file 1


Herein, we present for the first time a novel potentiometric sensor based on the stimulus-responsive molecularly imprinted polymer (MIP) as a selective receptor for neutral dopamine determination. This smart receptor can change its capabilities to recognize according to external environmental stimuli. Therefore, MIP-binding sites can be regenerated in the polymeric membrane by stimulating with stimulus after each measurement. Based on this effect, reversible detection of the analyte via potentiometric transduction can be achieved. MIPs based on 4-vinylphenylboronic acid as the functional monomer were prepared as the selective receptor. This monomer can successfully bind to dopamine via covalent binding and forming a five- or six-membered cyclic ester in a weakly alkaline aqueous solution. In acidic medium, the produced ester dissociates and regenerates new binding sites in the polymeric membrane. The proposed smart sensor exhibited fast response and good sensitivity towards dopamine with a limit of detection 0.15 µM over the linear range 0.2–10 µM. The selectivity pattern of the proposed ISEs was also evaluated and revealed an enhanced selectivity towards dopamine over several phenolic compounds. Constant-current chronopotentiometry is used for evaluating the short-term potential stability of the proposed ISEs. The obtained results confirm that the stimulus-responsive MIPs provide an attractive way towards reversible MIP-based electrochemical sensors designation. Dopamine is one of the most critical neurotransmitters belonging to the catecholamine and phenethylamine families. It plays important roles in the systems of the human body, such as its role as a chemical messenger in the central nervous, cardiovascular, hormonal and renal systems ,2,3. ChaSeveral analytical methods including high-performance liquid chromatography (HPLC) ,8, capilMolecularly imprinted polymers (MIPs) have attracted wide interest as suitable receptors for all organic and biologic types, due to their advantages in molecular recognition capabilities towards organic and biologic targets ,25,26,27In this work, we are introducing a new reversible potentiometric sensor based on stimulus-responsive MIP for dopamine determination. MIP is synthesized by using vinyl borate as a functional monomer. This functional group can be stimulated by changing the pH of the solution and can covalently bind with dopamine to form a five-membered cyclic ester. Regeneration of the proposed sensor is easily done via changing the solution from alkali to acidic. The sensors were modified with poly  (PEDOT) as a solid-contact transducer. Insertion of the conducting polymer (PEDOT/PSS) into the selective membrane increased the hydrophobicity and redox capacitance with considerable potential stability, which was tested by and constant-current chronopotentiometry. The sensors were successfully applied for dopamine determination in human serum and pharmaceutical formulations. Using these smart MIPs in conjunction with potentiometric sensors could provide an effective way to achieve selective, sensitive and reversible detection of dopamine.−1, Millipore Milli-Q Direct-0.3 purification system). Poly (vinyl chloride) (PVC), 2-nitrophenyloctyl ether (o-NPOE), 4-vinylphenylboronic acid (VPBA), benzoyl peroxide (BPO) and ethylene glycol dimethacrylate (EDGMA) were obtained from Fluka AG . Dopamine, poly /poly-(styrenesulfonate) (PEDOT/PSS), tridodecyl- methyl-ammonium chloride (TDMACl) and tetradodecylammonium tetrakis (4-chlorophenyl) borate (ETH500) were purchased from Sigma Chemicals Co. . Tetrahydrofuran (THF), NaOH, NaCl and HCl were obtained from Acros . All other reagents were analytical grade and used as received. All measurements were performed in 10-mM phosphate buffered solution (PBS) buffer of pH 8 under a constant stirring at room temperature.All aqueous solutions used in this work were prepared using deionized water . Metrohom potentiostat/galvanostat  was used for chronopotentiometry measurements. In these measurements, three-electrode cell containing a reference electrode (Ag/AgCl (3-M KCl)) and an auxiliary electrode (platinum wire) was employed. The applied current is ±1 nA in a solution containing 5-µM dopamine.Man-tailored biomimics (MIPs) were prepared using the free radical polymerization reaction. In brief, 3.0 mmol of cross-linked VPBA monomer with 1.0 mmol of dopamine were dissolved in 20 mL acetonitrile–water mixture (1:1). 0.1-M NaOH was used to adjust the pH of this solution mixture to pH 8. 3.0 mmol of EGDMA was mixed with 80 mg of BPO and added to the reaction mixture. Nitrogen gas stream was diffused into the cocktail solution for 20 min for complete removal of dissolved oxygen and then sealed well. The tube was inserted in an oil bath at 70 °C for 24 h for complete polymerization. Non-imprinted polymers (NIPs) particles were prepared after repeating the previous steps in absence of the template molecule. The resulting powders were washed with 0.1-M HCl and water successively, and then dried under vacuum at 60 °C.To check the binding availability of the prepared pH-stimulus MIP towards dopamine, 50 mg of the prepared MIP was placed into 10 mL 0.5-mM dopamine at pH 8. The mixture was stirred for 1 h at ambient temperature and then centrifuged for 15 min at 6000 rpm. After that, the obtained MIP particles after the centrifugation was washed with de-ionized water and then immersed into 10 mL 0.1-M HCl and left to stir for 1 h at room temperature. The free dopamine concentration was determined by using an UV-Vis spectrometer at the wavelength of 275 nm. This cycle was repeated three times.o-NPOE were dissolved in 3.5 mL THF. The solid-contact ISEs was prepared as follows: (1) Glassy carbon electrode (GCE) was polished with 0.3 µm Al2O3 slurries and rinsed with water, followed with acetone, and left in ethanol for 10 min. The resulting clean GCE was inserted into a piece of matched PVC tubing at the distal end; (2) 15 µL of PEDOT/PSS solution was introduced to the GC substrate and left to dry till a uniform layer with strong adhesion to the GCE surface was obtained; (3) 100 µL of the membrane cocktail was drop-cast onto the transducer layer and allowed to dry for 2 h. The coated wire electrodes (CWEs) were prepared by repeating the same steps without adding the solid-contact material (PEDOT/PSS).The polymeric membranes were prepared as: 20.3 mg of the pH-stimulus MIP or NIP, 3.5 mg of TDMAC, 15.2 mg of ETH 500, 103.4 mg of PVC and 212.6 mg of Electrode regeneration was achieved after each measurement via treating the sensor with 10-mM HCl for 10 min to release out dopamine from the membrane. After that, the sensor was then conditioned in 10-mM PBS buffer of pH 8 for 10 min.The applicability of the proposed ISEs was tested in different human serum samples. The samples were collected from healthy volunteers. The serum was diluted 300 times with 10-mM PBS of pH 8.0 before testing. Finally, 9.0 mL dilute serum solutions were transferred into a 20-mL beaker. The sensor was immersed in conjunction with the reference electrode in the test solution for dopamine analysis.Dopamine was also analyzed using the proposed ISEs in different commercially available drugs: Dopamine Fresenius  , Dopaminect (1mg/tablet)  and Dopaminect (0.5mg/tablet) .To examine dopamine in tablet formulations, 3 tablets were grounded in an agate mortar. A specified amount of 3 finely mixed powder disks, equivalent to one tablet, was transferred to a 100-mL volumetric flask and dissolved in 20 mL aqueous 10-mM PBS of pH 8.0, sonicated for 45 min. The solution is then supplemented to the mark with a 30-mM phosphate buffer solution at pH 8. Possible measurements of these solutions were carried out and the potential readings were recorded and compared to the constructed calibration plot. The preparation of the ampoule sample was followed by diluting the appropriate amount of the drug with 30-mM phosphate buffer solution at pH 8.µm. For the MIP particles, the surface morphology presented in Fig. 1B showed irregular beads with a diameter range from 1.2–1.89 µm. The NIP control polymer was observed to have smoother surface and smaller size than the MIP polymer. This can be attributed to the formation of recognition cavities during the synthesis process. The roughness of MIP particles can lead to high surface area than that of NIP and thus MIP can adsorb analytes of interest much better than the NIP. This can confirm the tracing of the printing process that ensures the MIP efficiency as a suitable ionophore for the recognition of dopamine in the presented sensors.The morphologic forms of both MIP and NIP surfaces were examined using scanning electron microscope (SEM) . Figure Q is the binding capacity (µmol/g), Ci and fC are the initial and final dopamine concentration (µmol/L), respectively, Vs the sample volume (mL) and m is the dried mass of the polymer (g). As illustrated in Cis-diol moiety in the dopamine molecule. In this case, a high binding affinity towards dopamine can be observed from the data obtained from MIP and NIP beads. Switching the sample solution to pH 3 hinders the covalent interaction and results in release of the bounded molecules. Repeating the pH-switching cycles reflects an enhanced reversibility of the binding configuration through the uniformed dopamine release and uptake.The binding availability of the prepared pH-stimulus MIP towards dopamine was evaluated. The binding capacity of either MIP or NIP was calculated according to Equation (1):+) forming MIP/dopamine−/R+ ion association complex. This can afford H+ and X− ions which start moving from the membrane to the aqueous phase revealing the observed anionic response. The observed unexpected anionic response was explained by the net movement of hydrogen ions produced from the phenolic compounds after their interaction with the quaternary ammonium salts in the membrane  foo-NPOE. This can be explained on the basis that dopamine prefers the high polar solvent to be distributed in the sensing membrane. The potential response of the solid-contact sensor towards neutral dopamine is shown in It was reported that the polarity of the membrane solvent not only affects the dissolution of the ionophore in the membrane but also affects the movement of the ion in the membrane phase. So, membrane optimization should be considered in this study. Different plasticizers with different polarities were investigated and their influences on the potential response of the sensing membrane were recorded. As shown in The potential change of MIP membrane-based sensor is much larger than those obtained by the NIP at concentration ranging from 0.2 to 10 µM. The calculated sensitivity of NIP membrane-based sensor (1.2 mV/µM) is much lower than that obtained by MIP-membrane based sensor (5.4 mV/µM). This provides the specific recognition interactions between dopamine and the synthesized MIP in the membrane.− and H+ in the aqueous phase [− concentrations. All these measurements were carried out at 10-mM PBS of pH 8. This behavior is probably due to the concomitant ejection of H+X− from the membrane phase into the aqueous phase could be suppressed by the X− ions in the sample solution.To optimize the potentiometric anionic response of the proposed sensors, the effect of both X- and H+ in the aqueous phase should be optimized. The anionic response towards neutral phenols is facilitated by a decrease in the concentrations of both Xus phase . As show+ concentration on the potentiometric anionic response was also investigated + ions increases. The chosen sample pH is relatively far from the pKa of dopamine  [The effect of Ha = 8.9)  to ensura = 8.9) .pKa values for phenol derivatives used in selectivity measurements lie in the range 7.8–10.5. Hence, pH 8 is the selected value to ensure the presence of un-dissociated forms of these compounds. Experiments have shown that the selectivity arrangement of the MIP based sensor is dopamine > 2,4-dichlorophenol > 2-naphthol > 3-nitrophenol > 2-nitrophenol >p-cresol. The selectivity order of these neutral phenols reflects their acidity and lipophilicity [The selectivity coefficient values of the proposed sensors were evaluated using the so called “modified separate solution method (MSSM)” . The pothilicity . As the hilicity . In addi(ΔE/Δt) of the sensors in absence and presence of PEDOT/PSS layer is 82.1 ± 3.1 μV/s (n = 3) and (40.2 ± 1.5 μV/s) (n = 3), respectively. This reflects that insertion of PEDOT/PSS layer between the membrane and the electronic substrate enhances the high potential stability of the electrodes. Due to the ion-to electron transduction process, there is a clear relationship between the short-term potential stability of the sensor and the double layer capacitance of the solid-contact used. The redox capacitance for the proposed electrodes was calculated to be 12.3 ± 0.8 and 25.5 ± 1.3 μF in absence and presence of PEDOT/PSS, respectively.The potential stability of the solid-contact sensors using PEDOT/PSS is critically evaluated by using constant-current chronopotentiometry . TypicalThe applicability of the proposed ISEs for dopamine determination was checked in some pharmaceutical formulations and human serum samples using the standard addition method. The human samples were diluted to avoid the effect of the matrix. The diluted sample mentioned above was spiked with a certain amount of the three analytes and then analyzed by the standard addition method. The analytical results were shown in  indicatit-test at 95% below critt = 4.3). The results obtained from the proposed potentiometric method are also compared to the method of HPLC from British pharmacopeia, 2009 [F-tests, the results emphasize that there are no significant differences between the results of two methods and revealed the applicability of the proposed sensor as a novel method for the determination of dopamine.Dopamine was also determined in commercially available medicines collected from the domestic market using the standard addition method.The results obtained with measured recovery for each drug are presented in ia, 2009 . From F-A reliable, robust and cost-effective solid-contact ISE based on man-tailored mimics for the potentiometric transduction of neutral dopamine was presented. Sensor manufacturing is based on a combination of the use of PEDOT/PSS and the good adhesion capacity revealed by ETH 500. The MIP particles are dispersed into a PVC membrane and projected onto the glassy carbon electrode. The ISEs displayed extended linear response range 0.2–10 µM, low detection limit 0.15-µM and fast response time (< 10 s).Short-term potential stability was tested by constant-current chronopotentiometry techniques. The presented electrodes revealed good advantages over many of those previously described in terms of durability, ease of manufacture, potential stability, selectivity and accuracy. Advantages and disadvantages of many of the previously suggested potentiometric dopaminesensors are presented for comparison in


Pyogenic granuloma (PG)-like nodular Kaposi’s sarcoma (KS) has been previously demonstrated in several studies. However, to the best of our knowledge, no original study investigating the dermoscopic differential diagnosis of PG and KS exists in the relevant literature. In this study we aimed to identify dermoscopic findings providing useful clues to differential diagnosis between the two entities.Patients with histopathologically confirmed PG or nodular KS were included in the study. Demographic, clinical, dermoscopic, and histopathological findings of the cases were retrospectively reviewed. The most common finding observed in PG was red structureless areas (80.00%), followed by intersecting thick white lines (56.66%), ulceration (36.66%), and collarette scale (33.33%). The most common findings detected in nodular KS were polychromatic structures (56.66%) and red (46.66%) and white (13.33%) structureless areas, respectively.Intersecting thick white lines seem to be the strongest dermoscopic clue to PG. Striate surface scaling (n = 6) was a novel finding identified for PG. Here we also described a new vascular pattern (widespread vessels composing a network) for nodular KS. Pyogenic granuloma (PG), also known as lobular capillaryhemangioma, is a benign vascular proliferation of the skinand mucous membranes. PG is usually characterized bya solitary pink to red dome-shaped nodule. The exactetiopathogenesis of the disease is not clearly known [1].Kaposi’s sarcoma (KS) is a low-grade vascular tumorassociated with human herpesvirus 8 (HHV8) infection[2]. PG and the nodular form of KS may share similarclinical characteristics. The differential diagnosis of thesetwo entities is essential as both of them differ in prognosisand necessitate different management. Histopathologicalexamination still remains the gold standard in this respect[3].PG-like KS has been previously demonstrated in severalstudies [3]. However, to the best of our knowledge, nostudy investigating the dermoscopic differential diagnosisof PG and KS exists in the literature. Here we aimed toThe study was conducted in a tertiary center. Patientswith a histopathological diagnosis of PG or nodularKS between January 2017 and November 2018 wereincluded. Demographic, clinical, dermoscopic, andhistopathological findings of all the patients wereretrospectively reviewed.A thorough dermoscopic examination was performed forall the lesions included and the findings were recorded.The dermoscopic findings observed were described usingKittlerian terminology. Dermoscopic examination wasperformed with a polarized handheld dermoscope with10× magnification . Capture of dermoscopic imageswas performed using a high-resolution mobile cameraphone attached to the dermoscope .The diagnoses of PG and nodular KS were made based onclinical and pathological correlations for all the patients.The histopathological criteria for PG were as follows:presence of vascular proliferation in a lobular fashion,fibrous septations, inflammation, and edema resemblinggranulation tissue with no or rare extravasated red bloodcells .The histopathological criteria for nodular KS wereas follows: presence of spindle cell proliferation formingrelatively circumscribed nodules, slit-like vascular spaces,and lack of remarkable nuclear atypia. Lesions showingnegative HHV8 staining were excluded from the study.Patients with a history of topical or systemic treatmentwere excluded. The presence of histological findings indicating another skin disorder was also an exclusioncriterion.The relationship between two categorical independentvariables was evaluated using the chi-square test.Descriptive statistics for numeric variables were representedas mean ± standard deviation, and for categorical variablesas numbers and % values. SPSS 24.0 for Windows  was used for statistical analysisand P < 0.05 was considered as statistically significant.All the procedures followed the Helsinki Declaration andthe study was approved by the local clinical research ethicscommittee A total of 30 lesions of PG from 30 different patients and30 lesions of KS from 11 different patients were enrolledin the study.The mean age of the patients was 20.43 ± 7.75 years; therewere 16 (53.33%) women and 14 (46.66) men. The mostcommonly affected sites were fingers .Toes , palms , soles , the neck , and the lower lip  were the other localizations. The mean diseaseduration was 25.11 ± 10.81 days.The most common dermoscopic findings observedwere red structureless areas , followed byintersecting thick white lines , ulceration, and collarette scale . Allthe dermoscopic findings detected are shown in the Table.The mean age of the patients was 68.45 ± 11.01 years andthe majority were male . Six patients had asingle lesion, followed by one with eight lesions, one withseven lesions, one with four lesions, one with three lesions,and one with two lesions. The most common localizationof the lesions was a lower extremity , followedby an upper extremity  and the head-neckregion . None of the patients showed HIVpositivity, immunosuppression, or any other malignancy.The most common dermoscopic findings werepolychromatic structures , also knownas “rainbow patterns”. Red  and whitestructureless areas  were the other frequentfindings. All of the dermoscopic findings observed areshown in the Table.PG is a benign vascular lesion mainly affecting the fingers,but it can affect all parts of the skin and mucous membranes.PG can usually be correctly diagnosed with history and the clinical appearance of the lesion [1]. However, it canalso easily be misdiagnosed due to its nonspecific clinicalmorphology. Amelanotic melanoma, cutaneous squamouscell carcinoma, and even metastatic carcinomas are knownimitators of PG [4–8]. Nodular KS  and PG may also share similar clinical appearances [3].Nodular KS usually shows numerous dome-shaped nodularlesions, unlike PG, which often presents with a single lesion[2]. However, it should be kept in mind that KS may presentwith a single lesion and PG may show multiple nodules.In this study, the most common dermoscopic findingsfor PG were reddish structureless (homogeneous) areas . A reddish structureless areawas also the most common dermoscopic feature of PG inthe study of Zaballos et al. [4]. We also observed that 14 ofthe lesions with KS showed red structureless areas . “Bluish-reddish coloration” is a previously describeddermoscopic finding for KS [11]. The red structureless areais not considered as a specific clue to vascular tumors. It canbe seen in many cutaneous conditions, including amelanoticmelanoma and spitz nevus. The histological counterpart ofthe red structureless area in PG and KS is thought to benumerous capillary proliferations in the dermis [12].White intersecting lines, also known as white rails, can be described as whitish bands intersectingthe lesion [4]. White intersecting lines  were the second most frequent dermoscopic findingof PG in the present study. None of the lesions with KSshowed this finding. In the study of Zaballos et al., whiteintersecting lines were found in 74% of the lesions in PGcases [4]. White intersecting lines are not specific to PG andthey can also be seen in melanoma and basal cell carcinoma[4]. White intersecting lines observed in PG reflect fibrousseptations between lobular proliferation of mature vascularstructures [13].White structureless areas  wereanother finding that we observed in both KS and PG. Wethink that this finding reflects the presence of broaderfibrous tissue.Ulceration , hemorrhagic crusts ,and blood spots  are common findings of PG asit may bleed easily [4]. Ulceration , bloodspots , and hemorrhagic crusts  were also observed in dermoscopic examinationof the lesions in cases of PG. Only three KS lesions showedblood spots and crust formation. None of the KS lesionsshowed ulceration or crusts.Peripheral collarette scale is an arcuate squamousstructure surrounding the lesion [4]. This finding wasfound in 10 (33.33%) PG lesions  and 3 (6.66%)KS lesions . The histological counterpart ofcollarette scale is adnexal epidermal acanthosis [13].Peripheral collarette is not a specific sign of PG or KS. Itcan also be seen in melanoma, angiokeratoma, and basalcell carcinoma [4]. We also observed fine striated surfacescaling  in 6 PG lesions while it was notdetected in KS at all. To the best of our knowledge, striatedsurface scaling was not described for PG previously.Polychromatic structures, also known as rainbowpatterns, are described as the presence of many differentcolors juxtaposed next to each other on polarizeddermoscopy [14]. A rainbow pattern was first describedas a specific clue to KS but it has subsequently beenobserved in many conditions including blue nevus,angiokeratoma, hypertrophic scars, stasis dermatitis, andacroangiodermatitis . However, to our knowledge,there is no another study identifying this pattern in PG.The pattern does not have a distinct histological correlationbut it may reflect a vascular lumen-rich pattern of closelyarranged “back-to-back” vascular structures [16]. Vázquez-López et al. suggested the term “dichroism” for the complexinteraction of the lesional skin and polarized light.According to them, light in different statuses of polarizationis absorbed in different amounts as it penetrates into anobject. The heterogeneous and layered nature of the dermisdetermines the absorbance and retardance of polarizedlight, resulting in a spectrum of colors [17]. The pattern was observed in 56.66% of the KS lesions  and16.66% of the PG lesions . However, the rainbowpattern observed in PG was subtle, unlike those of KS.When it comes to the vascular structures, 7 (23.33%) ofthe PG lesions  and 4 (13.33%) of the KS lesions showed the presence of vascular structures.Distribution of the types of vascular structures is detailedin the Table. In the study of Zaballos et al., 45% of the PGlesions showed vascular structures [4]. We observed that 3of the KS lesions showed widespread vessels composing anetwork , which had not been described for KSpreviously.The role of immunosuppression is well known inthe HIV-associated type of KS. However, HIV is usuallynegative in the classical type of KS [18]. In the presentstudy, all of the patients had classical KS and HIV positivitywas not detected at all.In conclusion, the presence of reddish structurelessareas along with intersecting thick white lines seems tobe a strong clue to PG. Polychromatic structures were themain dermoscopic findings of KS; however, 5 of the PGlesions also showed this pattern in a subtle manner. Herewe identified a novel vascular pattern (widespread vesselscomposing a network) for KS, which we observed in 3 KSlesions. Striate surface scaling was another novel findingthat we identified for PG. To our knowledge, this is the onlyoriginal study focusing on the dermoscopic differentiationof PG and KS.


MI was not substantially altered by antimicrobial exposure across all cattle metagenomes, ranging 0.5–4.0%. We highlight that current alignment- and assembly-based methods estimating resistome mobility yield contradictory and incomplete results, likely constrained by approach-specific data inputs, and bioinformatic limitations. We discuss recent laboratory and computational advancements that may enhance resistome risk analysis in clinical, regulatory, and commercial applications.Antimicrobial resistance (AMR) poses a global human and animal health threat, and predicting AMR persistence and transmission remains an intractable challenge. Shotgun metagenomic sequencing can help overcome this by enabling characterization of AMR genes within all bacterial taxa, most of which are uncultivatable in laboratory settings. Shotgun sequencing, therefore, provides a more comprehensive glance at AMR “potential” within samples, i.e., the “resistome.” However, the risk inherent within a given resistome is predicated on the genomic context of various AMR genes, including their presence within mobile genetic elements (MGEs). Therefore, resistome risk stratification can be advanced if AMR profiles are considered in light of the flanking mobilizable genomic milieu , phages, and other MGEs). Because such mediators of horizontal gene transfer (HGT) are involved in uptake by pathogens, investigators are increasingly interested in characterizing that resistome fraction in genomic proximity to HGT mediators, i.e., the “mobilome”; we term this “colocalization.” We explored the utility of common colocalization approaches using alignment- and assembly-based techniques, on clinical (human) and agricultural (cattle) fecal metagenomes, obtained from antimicrobial use trials. Ordination revealed that tulathromycin-treated cattle experienced a shift in ICE and plasmid composition versus untreated animals, though the resistome was unaffected during the monitoring period. Contrarily, the human resistome and mobilome composition both shifted shortly after antimicrobial administration, though this rebounded to pre-treatment status. Bayesian networks revealed statistical AMR-MGE co-occurrence in 19 and 2% of edges from the cattle and human networks, respectively, suggesting a putatively greater mobility potential of AMR in cattle feces. Conversely, using Mobility Index (MI) and overlap analysis, abundance of  Antimicrobial resistance (AMR) is currently among the most urgent issues facing human and animal health . AMR arisets of genes, meaning that bacteria can exchange several AMR genes in a single transfer event. The specifics of HGT are highly variable and difficult to predict due to their complexity. The propensity for two bacteria to exchange AMR genes via HGT will depend on several factors, including the identity and genomic composition of the donor and recipient bacteria; the type of HGT mechanism involved; and the environment surrounding the bacteria at any given time. Due to this complexity, a comprehensive view of HGT and AMR genes across all bacteria would be highly relevant and indeed necessary to fully appreciate the clinical and epidemiologic risks intrinsic to the mobilization and acquisition of AMR genes in bacterial populations . The latter mechanism plays an especially important role in the microbial ecology of AMR because it allows distantly related bacteria to exchange AMR genes. Rates of HGT have been shown to increase under salient environmental conditions, and HGT enables AMR gene transfer between pathogens and non-pathogens . Furtherulations .Recently, several studies have reported the results of resistome and mobilome analysis, where mobilome is defined as all detectable HGT elements within a given metagenomic dataset, including plasmids, integrative conjugative elements (ICE), transposons, and insertional repeat sequences. These studies have yielded insights into potential connections between AMR ecology and HGT potential . The bioThe need to evaluate current resistome-mobilome approaches has reached a critical threshold due to the combination of: increasing generation and availability of short-read metagenomic data; expanding use of short-read metagenomic data for regulatory and surveillance activities; and increasing scientific awareness of the need for more nuanced characterization of resistome risk. Therefore, the goal of this study was to apply, compare and evaluate the most common bioinformatic and statistical approaches for performing resistome-mobilome analysis on shotgun metagenomic data. To do this, we used two publicly available datasets, both alignment- and assembly-based approaches, and several common statistical techniques.Using a general framework described in In the current work, co-occurrence analysis was performed using data from two previously published studies that performed metagenomic Illumina sequencing of DNA from fecal samples. In both studies, feces were collected from healthy individuals before and after antimicrobial drug exposure. Both studies evaluated resistome dynamics over time. To represent a range of metagenomic samples, we chose one study conducted in humans  and anotPRJEB20800  and PRJNA309291 . Both studies reported formal comparison of sequencing depth and other experimental metadata variables between sample groups, and concluded that there was no evidence of sequencing or experimental bias impacting the comparison of resistomes across treatments or individuals. To ensure equal treatment and filtering of reads for purposes of our analysis, both datasets were processed using default parameters of the AMRPlusPlus (v1.0.1) bioinformatic pipeline  or Homo sapiens (version hg19) reference genomes using the Burrows-Wheeler-Aligner (BWA) software  and assembly-based (referred to as “Assembly+BLAST”) techniques, we used MEGARes v 1.0.1  as the r v 2.0.0 , Plasmid v 2.0.0 , and ACL v 2.0.0  databaseMetaCompare pipeline , we visualized the raw abundance of AMR genes and MGEs at various levels of ontology and classification , using KronaTools . Then, pvegdist and decostand function in “Vegan”  to arrive at a stable ordination solution. If necessary, the number of ordination dimensions were iteratively increased until a stress value < 0.05 was achieved. Analysis of similarity (ANOSIM) was utilized as an “omnibus” test  in each dataset over time, Procrustes analysis was used to maximize similarity between NMDS ordinations of AMR and MGE features, and the protest function in “Vegan” was used to obtain a correlation value and significance test statistic (M2). For the human study, Procrustes analysis of the co-occurring resistome and mobilome was performed across all samples for pre-treatment, peak treatment, and post treatment time points. Procrustes analysis for samples in the cattle study were performed by treatment group, and by time within each treatment group. Procrustes analysis has been previously applied in a number of studies including the characterization of resistomes and colocalization of resistant determinants and MGEs  and metaSPAdes. MetaSPAdes was run using default parameters, and IDBA-UD was run as implemented in the MetaCompare pipeline. Resulting assemblies were evaluated using QUAST v 5.0.2 , and sequence identity (>90%) on contigs > 800 bps were used based on common cut-offs described in the literature  was based on e-value < 1 × 10–10, > 60% identity, and accessions were to be included if these were associated with > 90% reference sequence coverage.To parse the metaSPAdes assemblies for resistome-mobilome content, contigs were aligned against the combined MEGARes and MGE database BLAST . An e-vaterature . IDBA-UDaCompare . AMR genboth an AMR gene and an MGE; co-occurring placement within a single contig is considered evidence for putative genomic colocalization : Proportion of contigs that contain AMR genes and no MGEs or pathogen-specific sequences; proportion of contigs with both AMR genes and MGEs; proportion of contigs with AMR genes, MGEs and pathogen sequences. We ran MetaCompare with default settings and reported the resulting risk score for each sample. To perform comparable analysis with the metaSPAdes-generated contigs, we parsed the BLAST outputs to identify contigs that mapped to at least one AMR gene and one MGE (bioinformatic repository of parsing scripts)1; such contigs were considered to contain colocalizations. To confirm the accuracy of this colocalization, we parsed such contigs using BLAST alignment start and stop information. Specifically, we compared the start and stop position of each AMR gene and each MGE within a single contig, and if these positions overlapped, we flagged the contig as containing “overlapping” AMR-MGE alignments. Finally, we calculated a theoretical “mobility index” (MI) for each sample, defined as the fraction of all AMR-harboring contigs that also contained at least one MGE. To evaluate the impact of filtering for AMR-MGE overlap, we reported the raw and overlap-adjusted MIs for each sample.Once AMR genes and MGEs are identified within assembled contigs, the next step is to identify which contigs contain lization . The MetMetaCompare, and metaSPAdes+BLAST) impacts the total complement of specific genes identified, and therefore would impact resistome-mobilome colocalization. To do this we constructed binary heatmaps using the heatmap.2 function in the package “gplots” : 31.98 (11.03–69.65) and 38.31 (9.47–68.07) million paired reads], respectively. To characterize the relative abundance of resistome and mobilome features across both datasets, we used raw counts of alignments to reference AMR and MGE databases. These counts indicated that the mobilome comprised a larger proportion of sequence reads than the resistome, in both sample sets  relative to metaSPAdes+BLAST . Moreover, of the total number of AMR gene groups identified by each assembly method, 72% (human) and 79% (cattle) of AMR genes identified by MetaCompare were not identified by metaSPAdes+BLAST, while 18% (human) and 21% (cattle) of genes identified by metaSPAdes+BLAST were not identified by MetaCompare. A similar pattern was observed for the mobilome , or some combination thereof. However, identity standards or cut-offs are not consistently applied, especially for metagenomic analyses. For example, MetaCompare sets gene mapping thresholds for AMR genes at > 60% identity with minimum alignment length of 25 amino acids, and an E-value < 1 × 10–10. Though metaSPAdes has not been formally benchmarked for AMR genes, previous work utilized a > 90% identity threshold and > 800 bp minimum alignment length to evaluate gene prediction from assemblies  and AmpC resistance. These genes have emerged as a major global source of AMR in gram-negative pathogens, and have been linked to increased mortality, hospitalization length, healthcare cost, and multi-drug resistance , while MGEs in metaSPAdes assemblies were identified using ICEberg, PlasmidFinder, and ACLAME. In addition, MetaCompare applies a 90% gene fraction cutoff in identifying MGEs, which likely results in dramatic filtering of alignments, especially given that many MGEs are several kilobases (or even megabases) in length and the majority of contigs are <2,000 bp. By contrast, most BLAST parsing approaches in the metagenomic literature do not include a gene fraction cutoff, and therefore the metaSPAdes+BLAST results did not include this criterion.As with AMR richness, we identified differences in richness of MGEs across all samples depending on bioinformatic technique. It is likely that the same factors that resulted in disparity in the resistome results (discussed above) also impacted divergences in mobilome results. However, the stark disparity in unique MGE accessions discovered by the two assembly-based methods  can largThese results demonstrate that even when using default parameters, current bioinformatic approaches generate different resistome and mobilome profiles for the same source data. As with many bioinformatic applications, choice of reference database and filtering criteria greatly influence the number and diversity of features detected in the metagenomic data. Because colocalization analysis follows basic resistome and mobilome characterization, the differences in detected resistome and mobilome richness likely lead to differences in colocalization results between the approaches.R = 0.51, P < 0.001; PERMANOVA F = 13.78, P < 0.001). These results were consistent with the major findings of the original publication. These differences were not significantly impacted by dispersion heterogeneity between groups (P = 0.07) at each time point. In the analysis of the mobilome, we detected that ICE , plasmids , and prophages  displayed a concomitant shift in their composition at Days 4 and 8, and reverted to original (Day 0) composition by Day 42. Though beta-dispersion between groups were not significant for plasmids and ICE (P > 0.1), differences between timepoints were significantly affected by dispersion for prophage genes (P = 0.02). The prophage component therefore is likely explained by both the temporal variation before after antibiotic administration, as well as by inter-group differences in the human fecal samples. Procrustes analysis was performed to assess the degree of correlation between the mobilome and resistome in human fecal samples by superimposing metaMDS ordinations of each. Procrustes revealed strong correlation  in the resistome and mobilome  over time.To assess systematic changes in resistome and mobilome composition before and after antimicrobial exposures in the human and cattle trials, NMDS ordination was performed using Hellinger-adjusted Euclidean distances obtained from the transformation of normalized counts of genes at the class and mechanism levels. For the human trial, ordination revealed a markedly altered Days 4 and 8 post-treatment resistome relative to pre-treatment (Day 0), while the resistome reverted closer to its original state by Days 42 (P > 0.05). While the ICE component of Day 0 samples was too sparse to analyze, by Day 11, the ICE composition had changed between treated and control groups . The plasmidome composition differed between treatment and control groups at Day 0  and Day 11 . The prophage and other MGE components, however, did not differ significantly by treatment group. For comparison between treated and untreated groups there was significant heterogeneity in dispersion for all analyzable components of the resistome (P < 0.05), Though the resistome did not differ between treated and control cattle, it shifted significantly over time in both groups of cattle , as did the plasmidome  Untreated: ANOSIM R = 0.17, P < 0.01; PERMANOVA F = 3.89, P < 0.01) (P > 0.05). All other components of the mobilome remained unchanged over time in both groups. As with the human dataset, Procrustes analysis was performed on superimposed ordinations of the cattle mobilome and resistome, revealing significant correlation  between treatment groups  and across time .A similar exploration of the resistome and mobilome composition was undertaken for the cattle dataset. At the mechanism and class levels we detected no differences in the composition of the resistome between feedlot cattle receiving a single dose of tulathromycin and control groups at Day 0 (pre-treatment) and Day 11 ( < 0.01) . DispersStaphylococcus aureus has been directly linked to accumulation of MGEs encoding methicillin resistance and virulence  are considered among the most promiscuous in the human resistome , gentamycin (aminoglycoside), and vancomycin (glycopeptide), there was little evidence of co-occurrence of MGEs with resistance mechanisms for these classes of drugs. Instead, an edge was identified between a macrolide-lincosamide-streptogramin (MLS) mechanism and the CTnGERM1 ICE family. This was the only predicted AMR-MGE edge identified in the human dataset. This association may have been incidental given that macrolide resistance genes are among the most relatively abundant genes in the human gut resistome , and somesistome . The lacBased on human clinical isolates, though MGE-mediated transfer of AMR genes occurs more commonly among related microbial taxa, resistance conjugation between distantly related bacteria has been extensively documented . TherefoMetaCompare) and metaSPAdes. On average across both datasets, metaSPAdes produced 323,000 contigs per sample compared to 271,000 for IDBA-UD assembler of the MetaCompare pipeline. The N50 for metaSPAdes assemblies was significantly higher than for IDBA-UD assemblies, even when controlling for dataset , suggesting that, on average, metaSPAdes produced significantly longer contigs than IDBA-UD  for each sample which reflects the total fraction of contigs with at least one AMR region that is also flanked by at least one nearby MGE region, relative to all AMR-containing contigs within the sample. In critically evaluating the colocalization identified by metaSPAdes+BLAST, we noted many instances in which the start and stop alignment positions for the AMR gene overlapped substantially with the start and stop positions of the MGE. Upon closer inspection, it became apparent that the MGE reference databases contained MGE accessions that included accessory or cargo sequences, including AMR genes. This “identity contamination” in current-day MGE reference databases presents an inherent impediment to colocalization analysis of assembled contigs, and additional work must be done to correct for co-occurrence misclassification. For instance, a region of a contig that maps to the MetaCompare results. For example, for one human subject, adjusted MI was at ∼2% prior to antimicrobial exposures, but then increased ∼75% and in all cases mobility potential remained elevated at > 20% at 4 days after receiving the last dose. The overlap-adjusted MIs decreased to roughly baseline by Days 42 and 180 of the total study period. On the other hand, in the cattle dataset, mobility potential among those animals exposed to tulathromycin metaphylaxis did not significantly differ from control animals. Moreover, across all animals, mobility potential did not significantly differ over time. Though not a primary focus of the study, it is noteworthy that human samples at Days 0 and 180 had a generally similar adjusted MI as that seen across all cattle samples and that the mean adjusted MI across all human samples associated with recent antimicrobial exposure was 10-fold greater than adjusted MIs of cattle samples . This difference in mobility index among humans and animals when exposed to antimicrobials should be further explored in future work involving samples appropriately statistically powered for such analyses. Though we are noting differences in MI between human and animal trials to illustrate the way in which mobility analysis of resistomes can lend itself to hazard stratification and prioritization, it should be noted that a number of factors hinder a valid comparison of resistome mobility potential between the two datasets. Both studies collected a relatively small number of samples from a limited population set; both populations were administered different antimicrobial regimens to achieve different clinical endpoints; and metagenomes from both studies were collected, processed, and sequenced using different laboratory, instrumental, and computational protocols. Therefore, a robust comparison of the resistomes in these two datasets is not supported.To avoid such examples of misclassification and obtain a more accurate estimate of the number of contigs with colocalizations, we performed overlap analysis and calculated both a raw and an adjusted Mobility Index (MI), as described in section “Materials and Methods.” The disparity between raw and overlap-adjusted MIs reached 1–2 orders of magnitude , highligleast several thousand base-pairs. As demonstrated, even metagenomic-specific assemblers produce relatively fragmented assemblies with small N50 values; the likelihood of reconstructing MGEs and AMR “cargo” genes, especially those in excess of ∼1000 bp, is low given this fact. We demonstrated the importance of high-quality assemblies by showing that, although MetaCompare identified more unique AMR gene groups than metaSPAdes+BLAST (MetaCompare contained a significantly shorter N50 than the assemblies produced by metaSPAdes. Our findings are consistent with previous work comparing the metaSPAdes assembler with other assemblers in gene identification (–50) hits to multiple families of ICE, plasmid, prophage and other MGEs to the same regions of a given contig  ERP022986 , SRA NC.NN and IS designed this study and provided oversight for all other aspects of the study. IS, NN, KM, CB, and CD oversaw and performed bioinformatic analysis, while IS and NN performed all related statistical analysis. KM and IS performed the colocalization analysis of assemblies. IS, NN, and CB contributed equally to drafting and refinement of the manuscript. All authors approved the final manuscript prior to submission.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Molecular aging markers provide the opportunity for biological age determination in humans and to study factors, such as genetic determinants, affecting the ageing process. In males with Klinefelter syndrome , which is the most common sex chromosome aneuploidy, age-related morbidity and mortality are increased, and a significantly reduced life span has been observed. The aim of this study was to investigate whether Klinefelter patients exhibit molecular signs of premature ageing. We studied, specifically, age-associated DNA methylation patterns (by pyrosequencing) and relative telomere length  in blood in a cohort of Klinefelter patients  aged 18-71 years and compared them to the data of age-matched healthy male  and female controls (n = 50). Age-associated DNA methylation patterns were not indicative of accelerated ageing in Klinefelter men. Significantly longer telomeres were found in the young Klinefelter subjects aged 18-24 years . However, telomere length in subsequent age groups showed no difference to controls. Gonosomal aneuploidy in Klinefelter syndrome is associated with higher baseline TL at adolescent age, but comparable TL with progressive age in other age groups. Aging is generally regarded as a steady, uniform process of functional decline in cells and tissues. The pace of aging however, differs between individuals as it is influenced by genetic background, lifestyle, and disease ,2. To inThe classical method for “biological age” assessment is the determination of genomic telomere length (TL) . TelomerAnother biomarker of aging, the more recently introduced 'epigenetic clock', is based on age-related linear changes in DNA methylation. These changes can be employed for epigenetic age prediction -13. IncrKlinefelter syndrome (KS), the most common sex chromosome aberration in males , is caused by the presence of at least one supernumerary X chromosome . The diagnosis of males with KS includes small testes, infertility, increased gonadotropin and normal to low testosterone levels, and clinical symptoms of androgen deficiency such as decreased libido, impaired erectile function, anaemia and decreased bone mineral density may be observed ,23. AffeWe hypothesised that patients with KS exhibit molecular aging signatures indicative of premature aging, and therefore investigated molecular aging markers, i.e. telomere length and DNA methylation markers in affected males as well as in healthy male and female controls.KS patients were selected from the internal database of the Centre of Reproductive Medicine and Andrology (CeRA), Münster, Germany ('Androbase') . The cliAll subjects provided written informed consent to the analysis of genetic material as approved by the Ethics Committee of the University and the State Medical Board .Genomic DNA was extracted from Ethylenedi-aminetatraacetic acid (EDTA) blood samples using the FlexiGene DNA kit . DNA concentration was measured by spectrophotometry (NanoDrop ND-1000) and 350 ng were bisulfite-converted .Primers for DNA amplification and pyrosequencing  were preASPA), cg25809905 (ITGA2B), and cg17861230 (PDE4C), respectively.Predicted age (in years) = 67.96 - 81.09 α + 4.22 β + 109.72 γ where α, β, and γ are the methylation values for cg02228185  as described previously ,29. Brieet al.  and calcStatistical tests and data visualisation were performed using R 3.3.1 . Decision for a statistical test was based on the analysis of data distribution and homoscedasticity by Shapiro-Wilk test and Levene’s test, respectively. When no normal distribution of data could be assumed, non-parametric tests were utilised. Differences between slopes of linear curves were tested using analysis of variance (ANOVA) between two linear models.et al. . Vaziri .33. Vazipatients . A similpatients ,24.Since we noticed similarities between the two aneuploidy conditions (KS and DS) regarding TL, we speculate whether telomere attrition is linked to abnormal chromosome segregation. Indeed, previous studies showed an association between the control of telomere length and chromosome segregation through nuclear factors mediating post-translational protein modifications, i.e. a lack of SUMO E3 ligase results in defects in chromosome segregation as well as an increase in TL ,36.In order to evaluate whether the additional X-chromosome accounts for longer telomeres in Klinefelter syndrome, we added the female control group. However, since telomere lengths are not similar between Klinefelter patients and women, it is unlikely that genes expressed on the additional X-chromosome contribute to this phenomenon. Although the number of female controls included in our study is rather small, this view is also corroborated by the finding that women with Turner Syndrome (X0) exhibit similar TL to controls .In this study we only used two molecular markers of aging previously found to be highly informative for the determination of biological and cellular aging (for a comprehensive review see ). In facThe present study cohort comprises clinically well-characterised subjects and consists of a relatively large sample size. However, future longitudinal studies in Klinefelter syndrome are needed to follow the progression of molecular markers at an individual level.In summary, we evaluated molecular aging markers in KS patients and describe increased blood TL in young KS patients with normalization in later age groups, while biological/epigenetic age remains unchanged. It remains to be elucidated whether the telomere length kinetics in KS is linked to the pathophysiology of KS, its numerous comorbidities, and the reduced lifespan or to as yet unidentified factors, and also, if a period of accelerated telomere loss occurs, it might have yet unidentified consequences for the future health of KS patients.