The use of light diffraction for the microbiological diagnosis of bacterial colonies was a significant breakthrough with widespread implications for the food industry and clinical practice. We previously confirmed that optical sensors for bacterial colony light diffraction can be used for bacterial identification. This paper is focused on the novel perspectives of this method based on digital in-line holography (DIH), which is able to reconstruct the amplitude and phase properties of examined objects, as well as the amplitude and phase patterns of the optical field scattered/diffracted by the bacterial colony in any chosen observation plane behind the object from single digital hologram. Analysis of the amplitude and phase patterns inside a colony revealed its unique optical properties, which are associated with the internal structure and geometry of the bacterial colony. Moreover, on a computational level, it is possible to select the desired scattered/diffracted pattern within the entire observation volume that exhibits the largest amount of unique, differentiating bacterial features. These properties distinguish this method from the already proposed sensing techniques based on light diffraction/scattering of bacterial colonies. The reconstructed diffraction patterns have a similar spatial distribution as the recorded Fresnel patterns, previously applied for bacterial identification with over 98% accuracy, but they are characterized by both intensity and phase distributions. Our results using digital holography provide new optical discriminators of bacterial species revealed in one single step in form of new optical signatures of bacterial colonies: digital holograms, reconstructed amplitude and phase patterns, as well as diffraction patterns from all observation space, which exhibit species-dependent features. To the best of our knowledge, this is the first report on bacterial colony analysis via digital holography and our study represents an innovative approach to the subject. A variety of biosensors are routinely used for bacterial detection and identification –4. OpticEscherichia coli, also demonstrated that it is possible to identify bacterial strains with a 82% recognition rate [We previously demonstrated that colonies from different bacterial species and strains generate specific diffraction signatures that can be used for microbiological diagnosis, as both the amplitude and phase spatial light are species- and strain-specific ,11. The ion rate . Recentlion rate . FurtherThe main goal of this paper is to extend optical examinations by determining the amplitude and phase properties of bacterial colonies using a Point-Source Digital In-Line Holography (PSDIH) sensor. Recently, we demonstrated the suitability of digital holography for bacteria characterization . This teEscherichia coli and Staphylococcus intermedius, are analyzed with both PSDIHM and classical optical microscopy in order to characterize their amplitude and phase properties. Furthermore, the process of hologram reconstruction is applied to evaluate the spatial distribution of the optical field diffracted by a colony in various observation planes behind the complex object. In comparison to the already proposed scattering/diffraction method for bacteria identification, here it will be demonstrated that digital holography enables obtaining new optical signatures of bacterial colonies: digital holograms, reconstructed amplitude and phase patterns, and their diffraction patterns from the entire observation space. These unique features can be treated as novel bacterial species optical discriminators. The aim of the study is to demonstrate the new perspectives in the characterization of species-dependent optical signatures. Contrary to bacterial identification by forward light-scattering sensors, the DHM enables reconstruction of multiple optical signatures of bacterial colonies from one single digital hologram  used in our study is depicted in ξ = , λ is the light wavelength, and We adopted the numerical reconstruction of holograms based on the Helmholtz-Kirchhoff transform, originally proposed in :K(r¯)=∫In previous applications –26, I(ξ¯Escherichia coli (PCM 0119) and Staphylococcus intermedius (PCM 2405) were first incubated for 24 h at 37°C. Respectively, 10−6 and 10−7 dilutions were seeded on the surface of Columbia agar (Oxoid) solid nutrient medium in Petri dishes to obtain 10–15 colonies per plate, and were incubated at 37°C for 20 h. To avoid variation in light attenuation, the same volume of nutrient medium was used in each case (10 ml).The samples were prepared in the microbiology laboratory of the Department of Environmental Engineering at the Warsaw University of Technology. Bacterial suspensions of A spectroscopic study was performed in the spectral range of 300–800 nm with a resolution of 2 nm. The absorption spectra of bacterial colonies were measured using an AvaSpec 3648 spectrometer (Avantes) with a reflection probe. The absorption spectra of the Columbia nutrient medium (Oxoid) were recorded by the same spectrometer working in the transmission configuration.x’ = Mx and y’ = My are relationships connecting the coordinates x, y in the object plane with the coordinates x’, y’ in the image plane. Considering the fact that only the intensity of the optical field is recorded in the conventional transmission microscope, the phase modulation is totally lost. The intensity of the optical field in the image plane can be described as follows:To explain the correlation between the reconstructed image, recorded by the PSDIHS, and the structure of the examined bacterial colonies, additional examinations were performed using a Nikon Eclipse 2000 optical transmission and phase contrast microscope . Based on the images, the transmission coefficient of the bacterial colony was determined. Based on wave optics, the complex amplitude U of the optical field in the image plane in transmission mode can be described by the following expression :U is the discrete intensity value of the colony image pixel, and The microscopic image enables obtaining the rescaled two-dimensional transmission coefficient http://rsb.info.nih.gov/ij) [The special image processing algorithms and features extraction developed in our group, were exploited for the statistical analysis of the recorded optical signatures of bacterial colonies ,15–17. T.gov/ij)  in order.gov/ij) .In PSDIH, it is particularly important to preserve the appropriate transmission properties of the illuminated object to allow the possibility of recording the high-contrast interference patterns of the non-scattered and scattered waves. Therefore, it is necessary to determine the absorption properties of the bacterial colonies see . For thePrevious examinations of the absorption properties of Columbia nutrient medium (Oxoid) demonstrated that this medium has a significant absorbance for the wavelengths from 400 nm to 425 nm . TherefoEscherichia coli colonies  can be associated with the process of colony growth and bacterial cell migration away from the center of the colony, where the oldest cells are located. Local changes in the refractive index  can affect the light diffraction of colonies. In case of E. coli, the phase map has a significantly different structure, indicated by quasi-spherical phase modulation. It contains round fringes with a homogenous structure inside the region of the colony, indicating that the strongest phase modulation occurs on the edges of the zones with different transmission, and can be responsible for the unique spatial distribution of the colony Fresnel patterns (shown in the next sections). This tendency is also observed on phase contrast images of S. intermedius colonies  distribution inside the colony shows that each colony has a unique species-dependent phase distribution image see . In casenies see , where tThus, in terms of classical optics, bacterial colonies can be considered as amplitude and phase light modulators, with different species-dependent amplitude and phase properties, affecting the spatial distribution of the incoming optical field. Moreover, it should be noted that colonies are biological objects that evolve over time during incubation; therefore, their light-modulating properties are also time dependent.A numerical reconstruction was performed according to the algorithm presented in the Materials and Methods section. Representative results are presented in E. coli and S. intermedius colonies using the PSDIH technique, and previously recorded Fresnel patterns (see S. intermedius, the central low-intensity zone in the diffraction pattern was observed in both the numerically reconstructed and the experimentally recorded intensity pattern, as expected based on the low light transmission in this region of the colony. Therefore, the light transformation by this type of colony is generally only affected by the light diffraction at the edges of the colony, since the phase map of the space region occupied by the colony indicates high homogeneity of its internal structure. The phase modulation of the incoming optical field for this colony depends mainly on the colony profile leading increased convergence of the diffracted field.The intensity of the Fresnel patterns of the transformed optical field can be treated as specific optical scattering/diffraction signatures that differentiate bacterial species ,17. We derns see . The recE. coli colonies, the light diffraction occurs in different, circular transmission zones inside the colony, responsible for the presence of intensity rings in both the numerically reconstructed intensity pattern and the experimentally recorded Fresnel diffraction pattern. The central intensity ring occurs on the boundaries of the bacterial colony center, where the oldest bacterial cells are located and the highest concentration of extracellular substance is found. The second intensity ring results from the light diffraction on the bacterial colony edge. Moreover, the presence of additional radial spokes between the two intensity rings in both patterns results from the internal heterogeneity of the colony. This heterogeneity is caused by the migration of young cells from the colony center, leading to local changes in refractive index.For The results demonstrate that the reconstructed phase and intensity patterns of the light diffracted by bacterial colonies exhibit similar unique features as the Fresnel diffraction patterns, enabling identification of bacteria with nearly 99% accuracy. Therefore, they can also be used for bacterial identification. However, for experimentally recorded Fresnel patterns, an additional speckle effect is observed. It is probably caused by the roughness of the colony surface . MoreoveIn case of PSDIH holograms of bacterial colonies, the area occupied by the colony was limited by partitioning zones, and the features were extracted according to the algorithm described in previous Sections. The first and second principal components of the holograms are plotted and two different analyzed bacteria species have been marked by different colors see . ObtaineS. intermedius can be associated with low transmittance observed for all colonies of these bacteria species.The same tendency see  is obserIn case of the reconstructed phase images of bacterial colonies see , the anaThe reconstructed diffraction intensity patterns of both bacteria species at chosen distance 2 cm from the bacterial colony were also analyzed in term of PCA see . The obtPerformed analysis of the features extracted from the optical signatures of bacterial colonies obtained by PSDIH points out the possibility of differentiation of two analyzed bacteria species.The main goal of this work was to demonstrate the novel application of point-source digital in-line holography for the characterization of bacterial colonies and its potential use for microbiological investigation. The main advantage of digital holography is the possibility to reconstruct the amplitude and phase properties of examined objects, as well as the amplitude and phase patterns of the optical field scattered/diffracted by the object in a chosen observation plane behind the object from one single digital hologram. The proposed method non-contact and non-destructive, offers label-free examination of bacterial samples. To the best of our knowledge, this report is the first attempt at characterizing the species-dependent properties of bacterial colonies and their diffraction patterns by digital in-line holography.The analysis of the amplitude and phase patterns inside the colony revealed their unique species-dependent optical properties, which are associated with the internal structure and geometry of the bacterial colony. Moreover, the single measurement digital hologram recording and its numerical reconstruction enable obtaining a reference database of the bacterial diffraction signatures from all observation spaces. As such, it allows for the extraction of additional differentiating features, in contrast to the already proposed methods based on single scattering/diffraction patterns recorded in a fixed observation plane. This method can provide new optical discriminators for bacterial species, which can extend the classification vector and improve the bacterial identification accuracy. Comparison of the reconstructed diffraction intensity patterns obtained with PSDIHM with previously recorded Fresnel diffraction patterns of the same colonies demonstrated that both patterns are highly similar and highlight the same unique features associated with each bacterial species. This indicates the possibility of using digital holography for bacterial identification. The potential of bacteria species differentiation by digital holographic signatures was also demonstrated by means of the PCA analysis of examined optical signatures of bacterial colonies. It was shown that the analyzed optical signatures obtained by digital holography exhibit unique species-dependent features.Decreasing the incubation time can improve the transmission properties of the colonies and the quality of the numerically reconstructed amplitude and phase patterns. Future research will be focused on more extended investigation of potential application of digital holographic sensors for different bacteria species/strains characterization. Proposed method has non-contact and non-destructive character, and enables label-free investigation of bacteria samples.


LiDAR and cameras have been broadly utilized in computer vision and autonomous vehicle applications. However, in order to convert data between the local coordinate systems, we must estimate the rigid body transformation between the sensors. In this paper, we propose a robust extrinsic calibration algorithm that can be implemented easily and has small calibration error. The extrinsic calibration parameters are estimated by minimizing the distance between corresponding features projected onto the image plane. The features are edge and centerline features on a v-shaped calibration target. The proposed algorithm contributes two ways to improve the calibration accuracy. First, we use different weights to distance between a point and a line feature according to the correspondence accuracy of the features. Second, we apply a penalizing function to exclude the influence of outliers in the calibration datasets. Additionally, based on our robust calibration approach for a single LiDAR-camera pair, we introduce a joint calibration that estimates the extrinsic parameters of multiple sensors at once by minimizing one objective function with loop closing constraints. We conduct several experiments to evaluate the performance of our extrinsic calibration algorithm. The experimental results show that our calibration method has better performance than the other approaches. In recent years, an increasing amount of interest and research effort has been put toward autonomous vehicles from both commercial and military sectors. For safer and more robust navigation, autonomous vehicle should utilize all sensors mounted on the vehicle to perceive and understand the scene around. For instance, the vehicle should be able to detect objects, classify the environment and analyze the condition of the road surface. Although a vision sensor provides rich information, it also has weaknesses, such as a narrow field of view and poor behavior in rapid illumination changes. LiDAR overcomes such drawbacks of the vision sensor. Although LiDAR provides sparser data, it is equipped with a wider field of view, highly accurate depth measurement and robustness to environmental change. Perception systems with sensory fusion have shown better results in various literature works ,2,3.To obtain accurate sensor measurements, we should estimate their intrinsic and extrinsic parameters. Generally, the sensors should be calibrated in order to convert data between the local coordinate systems of the sensors. Calibration can be divided into two parts: intrinsic calibration, in which the sensors’ intrinsic parameters, such as focal length, skew parameter and image center, are estimated; and extrinsic calibration, in which the rigid body transformation between the sensors is estimated. Specifically, to optimally combine LiDAR and camera measurements, accurate extrinsic calibration of the six degrees of freedom transformation between the sensors is required. In other words, we should know their relative pose with rotation and translation from each other to effectively use the data from both sensors. Extrinsic calibration between a LiDAR and a camera is roughly classified into two categories: direct and indirect correspondence searches.The extrinsic calibration problem can be solved by directly finding corresponding features in the LiDAR and camera data ,5. HowevTo address this problem, researchers have proposed using constraints derived from lines and depth edges, rather than points. In these previous works, two types of 3D features are commonly used: points lying at depth edges ,7 and poRecent approaches for extrinsic calibration between cameras and LiDARs have focused on automatic and targetless method ,11,12. HIn this paper, we address the problem of extrinsic calibration between a 2D/3D LiDAR and a camera. Our extrinsic calibration algorithm follows the existing basic procedure, but provides several advanced techniques to improve the calibration accuracy and a joint calibration method of multiple sensors. We use a v-shape calibration target consisting of two planes with checker patterns, as shown in The contributions of this paper are three-fold: (1) we introduce new extrinsic calibration approaches to improve the performance of the existing approaches, the weighted and robust calibration algorithms; (2) we propose a joint calibration method of multiple sensors with loop-closing constraints; (3) we provide extensive experimental comparisons with state-of-the-art approaches and statistical analyses of the proposed calibration approach.There are several approaches to estimate the extrinsic parameters between a LiDAR and a camera. These approaches can be classified based on whether the correspondences are measured in the same modality or in separate modalities.The first approach is to directly search for correspondences with a sensor that can observe the LiDAR beam. If the camera is an IR camera, it is possible to detect the LiDAR spots on the image directly. Calibration targets, such as poles or planar boards, can be used to determine which laser point corresponds to an observed image point. For example, if the LiDAR beam hits a pole, we can easily detect that point in the 3D data and also in the image. If we use only a regular camera, the same procedure can be performed using an IR scope by marking the laser position on the target with tape to make it visible in the camera image ,5.The second approach is to indirectly estimate the correspondences by finding features separately in each modality. This approach can be also classified by whether the optimization is done in 2D or 3D and by what type of features are used. The approach proposed by Zhang optimizes in 3D . Given tet al. addressed automatic extrinsic calibration by maximizing mutual information between image and 3D LiDAR data [et al. suggest automatic online calibration using edges of the image and the discontinuity of LiDAR points. These approaches have difficulty handling low density LiDAR (such as 2D LiDAR) with respect to camera extrinsic calibration because they need relatively dense 3D points to match dense image data. Scott et al. suggest automatic extrinsic calibration between 2D LiDAR and the camera [Automatic and targetless approaches are increasingly popular extrinsic calibration methods for cameras and LiDARs. Pandey DAR data . The aute camera . This apLi  and WasiWe implemented Li’s and Wasielewski’s algorithms to evaluate the calibration performance and found that the algorithms do not provide sufficiently accurate results. Li’s approach is not accurate due to sparse laser sampling. Although Wasielewski used highly accurate corresponding points lying on corners, he used only one corresponding point per image, and therefore, a large number of images is needed.Our approach builds on the ideas of Li and Wasielewski to address the problems of each approach. Based on an early version ,16, thisIn order to combine data from a camera and a LiDAR, the extrinsic and intrinsic parameters must be estimated. The transformation is represented by rotation s is the skew parameter [A point arameter .Our extrinsic calibration algorithm consists of three steps: data acquisition, feature extraction and optimization. These steps are described in the following subsections.The calibration target we designed consists of two planar boards arranged in a v-shape . We markWe extract three line features =∑iIn many systems and applications, the combination of a LiDAR and a camera is broadly utilized because they are complementary to each other. In this section, we introduce new approaches to improve the performance of the basic approach. We observed two characteristics in the basic approach: some points are more reliable than the others, and line features can be noisy due to manual extractions. Therefore, we extended the basic approach in two ways. First we applied different weights to the distance error for the center features versus the edge features because the center feature is more accurate than the others. Second, we incorporated a robust optimization approach to handle the effect of outliers in datasets.N is the number of image and LiDAR scan pairs. The center and right residuals  and the LiDAR data (σ = 0–50 mm).The effect of the calibration accuracy by the sensor noise is analyzed in a simulation environment that considers a 0.5We evaluate the performance of the proposed extrinsic calibration approaches explained in Our performance evaluation is four-fold; in the first experiment, we evaluated the performance of our baseline algorithm and the two extensions: the weighting method and the robust optimization. We then compared our algorithm to two state-of-the-art previously published algorithms. In the third and fourth experiments, we evaluated the effect of the number of scan/image pairs and the range and pose of the calibration target on calibration accuracy.We compared the performance of our baseline approach and the two extensions described in We compared our method to Li’s and Wasielewski’s algorithms in terms of the error measures described in We evaluated the line alignment accuracy as a function of the number of image/scan pairs. This evaluation was done using 10-fold cross-validation. The number of testing image/scan pairs was randomly selected from the 250 pairs. As shown in We determined the effect of the pose and range of the calibration target. To do this experiment, we first labeled image/scan pairs according to the range and pose of the calibration target. The range was divided into two categories: near range (<10 m) and far range (≥10 m). We grouped the pose based on the roll angle of the target: straight , which is usually acquired by a checkerboard detection algorithm. We estimated the extrinsic parameters in each noise condition with 100 pairs. We evaluate the performance of the joint calibration using a 3D LiDAR and two cameras mentioned in X, Y, Z axes) accuracy with respect to the number of scan/image pairs. This experiment validates the reliability of the extrinsic parameter from the real test environment. The X, Y and Z axes are defined as right, down and forward, respectively, relative to the sensor. The experiment indicates our robust method is twice as robust as Wasielewski’s method given the scan/image pair, and the joint calibration method performs slightly better than the robust method. Each extrinsic parameter has different standard deviations and pitch angles. Translation along the Y axis has a higher standard deviation compared to the other parameters. The v-shaped calibration target is responsible for this error. Wasielewski’s method and our proposed method both use the vertical line from the v-shaped calibration board as features. The change in vertical line position is constrained with sensor the configuration because the scan line has to intersect the target’s vertical line. Therefore, variation in pitch angle and translation along the Y axis affect the sensor noise; whereas the roll, yaw angle and translation along X and Z axes are relatively easier to estimate with the vertical line.The alignment accuracy of our robust method is twice as accurate as the compared state-of-the-art algorithms.Our robust method requires fewer image/scan pairs to achieve the same calibration accuracy as the previous methods.Our method performs robustly regardless of the pose and range of the calibration target.With the loop-closing constraints, our joint calibration has better performance than existing state-of-the-art algorithms.We have presented an extrinsic calibration algorithm compensating for the drawbacks of existing approaches and providing highly accurate calibration performance. We first proposed a robust-weighted extrinsic calibration algorithm to improve the calibration accuracy between a LiDAR and a single camera. We further developed the idea and proposed the joint calibration algorithm with loop closing constraints for a sensor system with single LiDAR and two cameras, which outperforms the existing calibration algorithms. We conducted several experiments to evaluate the performance and to compare to existing state-of-the-art algorithms. The main findings of our experiments are:The proposed joint calibration algorithm is only feasible under a constrained sensor configuration, but the loop-closing constraint method can estimate the extrinsic parameters of the entire sensor system at once with a single objective function. If there exist overlapping regions between sensors and correspondences can be obtained, the proposed joint calibration algorithm can be applied, and more accurate parameters estimated than the existing state-of-the-art algorithms without the loop closing constraint can be obtained, as shown in the experiments.


Blunt head trauma is a common cause of death and disability in children worldwide. Cranial computed tomography (CT), the reference standard for the diagnosis of traumatic brain injury (TBI), exposes children to ionizing radiation which has been linked to the development of brain tumors, leukemia, and other cancers. We describe the methods used to develop and test the effectiveness of a decision aid to facilitate shared decision-making with parents regarding whether to obtain a head CT scan or to further observe their child at home.This is a protocol for a multicenter clinician-level parallel randomized trial to compare an intervention group receiving a decision aid, ‘Head CT Choice’, to a control group receiving usual care. The trial will be conducted at five diverse emergency departments (EDs) in Minnesota and California. Clinicians will be randomized to decision aid or usual care. Parents visiting the ED with children who are less than 18-years-old, have experienced blunt head trauma within 24 hours, and have one or two risk factors for clinically-important TBI (ciTBI) from the Pediatric Emergency Care Applied Research Network head injury clinical prediction rules will be eligible for enrollment. We will measure the effect of Head CT Choice on: (1) parent knowledge regarding their child’s risk of ciTBI, the available diagnostic options, and the risks of radiation exposure associated with a cranial CT scan (primary outcome); (2) parent engagement in the decision-making process; (3) the degree of conflict parents experience related to feeling uninformed; (4) patient and clinician satisfaction with the decision made; (5) the rate of ciTBI at seven days; (6) the proportion of patients in whom a cranial CT scan is obtained; and (7) seven-day healthcare utilization. To capture these outcomes, we will administer parent and clinician surveys immediately after each clinical encounter, obtain video recordings of parent-clinician discussions, administer parent healthcare utilization diaries, analyze hospital billing records, review the electronic medical record, and conduct telephone follow-up.This multicenter trial will robustly assess the effectiveness of a decision aid on patient-centered outcomes, safety, and healthcare utilization in parents of children with minor head trauma in five diverse EDs.NCT02063087. Registration date February 13, 2014.ClinicalTrials.gov registration number:  Blunt head trauma is a common cause of death and disability in children worldwide and accounts for approximately 52,000 deaths and 275,000 hospital admissions in the United States annually . Each yeA cranial computed tomography (CT) scan, the reference standard test for the emergent diagnosis of traumatic brain injury (TBI) in children with blunt head trauma, exposes children to ionizing radiation which has been linked to the development of brain tumors, leukemia, and other cancers ,4. Furthet al. derived and validated two clinical prediction rules to accurately identify children at very low risk for clinically-important TBIs (ciTBIs) [One method to reduce CT use in patients with blunt head trauma is through evidence-based clinical prediction rules . In 2009(ciTBIs)  and are (ciTBIs) . Two rulShared decision-making (SDM) is a process of decision-making in medicine that has several key features: the involvement of the patient  and the clinician, a sharing of information by both parties, and both parties taking steps to reach an agreement about which management option to implement . While STo facilitate SDM between clinicians and parents of children with minor head trauma at low-moderate risk for ciTBI, we sought to develop and test a decision aid, ‘Head CT Choice’. Specifically, we aimed to incorporate risk estimates for ciTBI from the Pediatric Emergency Care Applied Research Network (PECARN) prediction rules, along with the perspectives of parents and other stakeholders, in an iterative development process to produce a decision aid that is ready for testing. We hypothesized that use of the decision aid will significantly increase parents’ knowledge and satisfaction and safely tailor the rate of cranial CT scan and seven-day healthcare utilization to risk-informed parent preferences. In this manuscript, we describe the methods and protocol used to develop and refine the Head CT Choice decision aid and how we will test its effectiveness in a multicenter randomized trial.This practical  multicenThe decision aid was developed and refined at the Mayo Clinic in Rochester, Minnesota (United States). The clinical trial will take place in five EDs in the United States: four in Minnesota and one in California: Mayo Clinic , University of Minnesota Amplatz Children’s Hospital , Children’s Hospitals and Clinics of Minnesota Minneapolis , Children’s Hospitals and Clinics of Minnesota St. Paul , and University of California, Davis Medical Center (a university-based academic ED serving a largely urban population).Parents and other key stakeholders were engaged early on in the design of this trial and will continue to be engaged throughout the entire investigation; they will comprise the Patient and Stakeholder Advisory Council (PSAC). The PSAC consists of an ED Patient Advisory Council (PAC) and a parent representative. The ED PAC consists of five individuals who have contributed the patient’s perspective to several practice and quality improvement initiatives at the Mayo Clinic in Rochester over the years - a Masters level ED quality specialist, three patients, and a nurse representative. The ED PAC reviewed and provided feedback on the study design and grant proposal and will continue to inform on the conduct of the trial, interpretation of the results, and dissemination of the study findings. The parent representative, who both provides her own perspective and serves as a liaison for the views of the ED PAC, has experience as a parent of a child with minor head trauma who was evaluated in the ED. The parent representative assisted in the development and iterative refinement of the Head CT Choice decision aid, provided feedback on the grant proposal submitted for funding, selected the primary outcome for the study, is an active member on the investigative steering committee, and participates in the study as a co-investigator.Eligible participants will be parents seeking care for a child or adolescent who is less than 18-years-old, has experienced blunt head trauma (above the eyebrows and not isolated to face or eyes) within 24 hours, and has at least one of the PECARN risk factors for ciTBI  [Given the risk of contamination when randomizing at the patient level, we will randomize at the clinician level. Randomizing at the clinician level will obviate the risk of contamination associated with randomizing at the patient level. To decrease the risk of contamination by the sharing of information regarding the intervention between clinicians, we will emphasize to participating clinicians the importance of not sharing information about the intervention with their colleagues during the enrollment period. In addition, study coordinators will monitor for contamination at the time of patient enrollment and through review of the video recordings of clinician-patient discussions. Clinicians will be dynamically randomized and stratified  by site Study coordinators will identify potentially eligible parent/patient dyads based on a chief complaint related to head trauma recorded at the time of ED registration and communication with treating clinicians in real-time. Senior resident physicians who often first evaluate the patient in the settings in which the trial will be conducted will be instructed to obtain the PECARN risk factors when conducting the initial history and physical examination and to not discuss the diagnostic options with the parent Figure . Once thA multidisciplinary research team including clinicians, health service researchers, a graphic designer, a radiation physicist, and patient representatives collaboratively developed the initial Head CT Choice decision aid. Using methods we have employed to develop other decision aids -17, we dIn the original PECARN minor blunt head trauma study, only a summary estimate of the risk of ciTBI in the moderate risk group (0.9% for younger than two years and 0.8% for two years and older) was reported in the published manuscript . To maxiIn the process of decision aid development and refinement the following themes consistently emerged: (1) clarifying the differences between concussion and TBI, given recent social media attention on concussion; (2) communication of individual patient risk using natural frequencies, a consistent denominator, a prose description of the natural frequencies, and pictographs; (3) limiting the amount of information to that which is relevant to the decision at hand and best facilitates a conversation between the parent and clinician without undue focus on the decision aid itself; and (4) clearly outlining the choice of a head CT scan during the ED visit, home observation if no CT scan is obtained, or having the clinician make the decision on the parent’s behalf.The Head CT Choice decision aid , whether there were any concomitant substantial non-head injuries diagnosed, how long the patient was observed in the ED, whether a head CT scan or other imaging was obtained, any findings on the head CT scan, ED length of stay, and the patient’s type of departure from the ED .A study coordinator will identify the primary clinician caring for the patient at the time of enrollment and collect data regarding whether they are a faculty physician, fellow, or advanced practice provider (nurse practitioner or physician assistant). The faculty physicians’ and fellows’ specialty training will also be collected .The outcomes were selected based on input from key stakeholders, including parent representatives, practicing clinicians, researchers (including shared decision-making experts), and health policy decision makers. In discussions with patient representatives it became clear that knowledge of the risk of ciTBI and the advantages and disadvantages of a head CT scan versus home observation were of greatest importance and so parent knowledge was selected as the primary outcome. All other outcomes will be secondary outcomes.We will assess parent knowledge by means of a post-visit survey administered immediately after the clinical encounter  scale ,24. The We will measure the degree of conflict parents experience using the validated decisional conflict scale (DCS)  use. These measures will be obtained by health record review, review of itemized hospital charges on the Universal Billing form-92 and Universal Billing form-04 forms (summary billing statements), and parental report at the time of the seven-day follow-up telephone call. To assist parents in collecting utilization data, we will provide a form  , we antial power . Under tWe will conduct the study according to the intention-to-treat principle, including all parent/patient dyads in the arm to which they were randomized, regardless of whether they received the intervention assigned. We will adhere to the CONSORT guidelines  to transχ2 tests for dichotomous outcomes, adjusted for clustering by clinician and stratified by study site [We will compare outcomes between study arms using t-tests for continuous outcomes and udy site . If therudy site .For the assessment of healthcare utilization, we will compare utilization descriptively and using multivariable models, using two-part or one-part generalized linear regression models. We will use the Park test to assess the appropriate distribution, and use a two-part model for outcomes where more than 10% of the subjects have zero outcome measures. We will also analyze the results using a subset of patients who primarily receive all of their healthcare at the participating centers. We expect this will provide a sensitivity analysis of the overall trial results based on self-reporting.We will perform descriptive analyses to describe any potential heterogeneity of treatment effect (HTE) and facilitate synthesis of subgroup results in future meta-analyses. We will conduct descriptive HTE analyses by age, gender, parent race/ethnicity, and highest attained parental education level. The outcomes assessed with HTE analyses will be the same as those assessed in the trial. We will also conduct interaction testing to determine the interaction between the decision aid and each pre-specified patient characteristic.We will make every effort to minimize the occurrence of missing data. Items self-reported by parents at the seven-day follow-up telephone call will attempt to be verified  by medical record and healthcare billing review. A study analyst will conduct frequency reports every two weeks to identify and obtain missing data. Patients with missing outcome data will not be included in the assessment of that outcome. Rates of missing data will be reported as well as known reasons for missing data. For data used to adjust study comparisons, we will use multiple imputation to account for any data that are missing at random.An independent data and safety monitoring board (DSMB) will monitor safety, scientific, and ethical aspects of the study. The DSMB has already met (prior to beginning enrollment) and will meet every six months throughout the duration of the study. Though every effort will be made to minimize post-randomization exclusions, patients will be excluded if they are found to meet exclusion criteria that were not recognized at the time of enrollment or they choose to withdraw . Any potWe have described the methods employed to develop and test the first decision aid for minor blunt head trauma in children; Head CT Choice. With the decision aid developed, we will conduct a multicenter clinician-level parallel randomized trial to measure the effectiveness of the decision aid on patient-centered outcome measures, safety, and healthcare utilization in parents of children with minor head trauma. In the context of prior and ongoing work on the development and implementation of the PECARN clinical prediction rules, the current study informs and expands on the incorporation of parental preferences, clinician experience, and other factors that influence the decision of whether to obtain a head CT scan in children at moderate risk for ciTBI. We anticipate that the development and testing of a decision aid for use in this moderate risk group will equip clinicians with the tools needed to educate, empower, and engage parents in the decision-making process. Use of this aid will also facilitate risk communication, thus strengthening the doctor-patient relationship in the context of an emergency care interaction limited by time, the lack of continuity of care, and the need for clinicians to provide care for multiple patients simultaneously.Given that we are randomizing at the clinician level, there is some risk of contamination if clinicians randomized to usual care get access to the decision aid and gain experience with using it in clinical encounters with parents of children with minor head trauma. We will take several steps to minimize the risk of contamination. First, we will emphasize to clinician participants the importance of not sharing the decision aid with their colleagues. We will also have study coordinators monitor for this in the process of conducting the trial. Second, using the PECARN public access dataset, we have generated a calculator that provides individual risk estimates for each of the isolated PECARN risk factors and for any two risk factors combined, in addition to the exact proportions and 95% CI’s. We have verified the accuracy of these risk estimates with the principal investigator of the PECARN head trauma study (NK), and these estimates are not accessible to clinicians at the point-of-care. Third, only the site coordinators will have access to copies of the decision aid and clinicians will not be provided a copy of the decision aid in the usual care arm. Fourth, site coordinators will be carefully trained to confirm the accuracy of each of the PECARN variables and to obtain sign-off from the treating clinician, but to keep the clinician blinded to the risk estimate for ciTBI unless that clinician is randomized to the decision aid. Fifth, we will make every effort to obtain video and audio data of the discussion between the clinician and the patient regarding whether to obtain a head CT scan during the ED visit or to further observe their child at home in both the intervention and control arms, and we will monitor for contamination by review of these data. Finally, if contamination does occur, we anticipate this will bias the effect estimates in each arm toward the null hypothesis.It is likely that not all clinicians will be willing to participate in the trial or have their discussions with the patient to be video recorded. However, in previous (14) and ongoing trials over 90% of the clinicians have agreed to participate. In addition, we have >99% power to detect the degree of difference in patient engagement in the decision making process that has been observed on video-recordings in prior trials, so we anticipate having sufficient power to detect a difference in this outcome measure even if some clinicians do not provide consent to video-recording.Obtaining head CT scans in children at a very low risk of TBI unnecessarily exposes children to the potentially harmful effects of radiation and increases healthcare utilization. Developing and testing the effect of a patient-centered decision aid, Head CT Choice, in a pragmatic multicenter clinician-level parallel randomized clinical trial has the potential to more closely tailor CT use to risk-informed parental preferences and improve the experience of care for parents of children with minor head trauma in the context of a busy and overcrowded ED care delivery system.Enrollment started April 1, 2014 and we anticipate enrollment will be complete in March 2016.ciTBI: Clinically-important traumatic brain injury; CT: Computed tomography; DCS: Decisional conflict scale; DSMB: Data safety and monitoring board; ED: Emergency department; GCS: Glasgow coma scale; IRB: Institutional review board; MRI: Magnetic resonance imaging; OPTION: Observing patient involvement in decision-making; PAC: Patient advisory council; PECARN: Pediatric emergency care applied research network; PSAC: Patient and stakeholder advisory council; SDM: Shared decision-making; TBI: Traumatic brain injury.The authors declare that they have no competing interests.EH: conceived, designed, and obtained funding for the study, and drafted and provided critical revisions to the manuscript. KW: wrote sections of and provided critical revisions to the manuscript, contributed to the design of the study. AK: contributed to the conception and design of the study and provided critical revisions to the manuscript. JL: contributed to the design of the study and provided critical revisions to the manuscript. PD: contributed to the conception and design of the study, data analysis and interpretation for the development of the PECARN risk calculator from the publicly available dataset, and provided critical revisions to the manuscript. LT: contributed to the design of the study by critically reviewing and refining the decision aid and provided critical revisions to the manuscript. SW: contributed to the design of the study by providing input on outcome classification for cases of potential ciTBI and provided critical revisions to the manuscript. JLH: contributed to the design of the study by participating in the development of the decision aid and provided critical revisions to the manuscript. LP: contributed to the design of the study by developing the standardized data collection forms and surveys and provided critical revisions to the manuscript. AL: contributed to the design of the study by designing and refining the knowledge questions included in the parent post-visit survey and provided critical revisions to the manuscript. JW: contributed to the design of the study by representing a parent’s perspective in developing and refining the decision aid and prioritization of study outcomes and provided critical revisions to the manuscript. KS: contributed to the design of the study by designing and refining the decision aid based on parents’ and other stakeholders’ input and provided critical revisions to the manuscript. NS: contributed to the conception and design of the study by developing the healthcare utilization analysis, drafted sections of the manuscript, and provided critical revisions the manuscript. MB: contributed to the conception and design of the study by developing the statistical analysis plan and study database and provided critical revisions to the manuscript. JH: contributed to the conception and design of the study by developing the statistical analysis plan, drafting portions of the manuscript, and provided critical revisions to the manuscript. VM: contributed to the conception and design of the study by defining key study outcomes and providing insight into how to meaningfully engage parents, parent representatives, and the ED patient advisory council in the study, and provided critical revisions to the manuscript. NK: provided input on study conception and design, ensured accuracy of analysis and interpretation of the PECARN public access dataset in the development of the risk calculator for ciTBI, assisted in iterative refinement of the decision aid, and provided critical revisions to the manuscript. All authors read and approved the final manuscript.Head CT Choice eligibility assessment case report form. CT, computed tomography; CSF, cerebral spinal fluid; DA, decision aid; ED, Emergency Department; GCS, Glasgow Coma Scale; PECARN, Pediatric Emergency Care Applied Research Network; VP, ventriculoperitoneal.Click here for fileThe head CT choice decision aid. The decision aid (DA) first graphically highlights key differences between concussion and traumatic brain injury to frame and focus the discussion on the risk for traumatic brain injury. The DA communicates the child’s risk for traumatic brain injury using a prose description of natural frequencies and a pictogram . The second page clearly outlines the decision that is to be made (head CT scan in the ED versus home observation with no CT scan) and educates the parent in what to watch for and what should prompt a return visit to the ED should they, in collaboration with their clinician, opt for home observation. There is also a table that compares the key advantages and disadvantages of each management option  and invites the parent to circle the issues that are most important to them. Finally, the DA outlines the three management options  and includes check boxes to document the decision along with a reminder to the parent that they will have the opportunity to revisit the decision with their clinician while in the ED. The third and final page includes a space to provide a contact phone number should the parent need to contact a healthcare provider after leaving the ED.Click here for fileParent pre-encounter numeracy and decision-making preferences survey.Click here for fileParent post-encounter survey.Click here for filePatient healthcare services diary.Click here for fileClinician post-encounter survey.Click here for file


The primary goal of metagenomic studies is to analyze and evaluate the rich microbial communities present in all natural environments. The construction and utilization of a large index required by alignment-based methods for thousands of microbial genomes can be computationally prohibitive. To avoid this computational cost, we investigated three different variations of an alignment-free method for profiling abundances of microbial communities.ijF represents the frequency of marker i in genome j. The occurrence vector b represents the frequencies of markers in reads. We would like to find an optimal solution x, the abundance vector in which jx represents the abundance of genome j. To find the abundance vector x, we solve the linear equation Fx = b. The methods to choose F and b are the key factor to find the optimal value of x. We introduced a concept of genome specific marker (GSM), which is a kmer that occurs in only one genome and no other. We exhaustively determine such markers from the entire dataset and represent the frequencies of these markers in the matrix F. Given a set of reads from a metagenomic dataset, we compute the frequency of GSM as b. Then, three variations can be formulated, respectively, as a linear programming problem (LP), a least-square approximation problem (L2), and an L1-approximation problem.The main idea of the method is reformulate the problem of determining abundance of microbial genomes as finding optimal solutions of linear equations that satisfy specific constraints. A set of genomic markers for the entire set of genomes is represented by a matrix F, where So far, our investigation on two data sets consisting of 100 and 1105 microbial genomes showed that the linear programming formulation (LP) yielded the best prediction of abundances of microbial genomes. This result was consistent across different levels of abundances. The LP variant also achieved better results across the board compared to a popular metagenomic profiler, FOCUS[In the future, we need to investigate deeper into the matrix F which consists not only of the GSM, but also the kmers that occur in more than one genome.


Confirmatory factor analysis in sample 2 (n = 300) showed the good fit of this two-factor model. Next, we examined construct validity also investigating the correlations between the IN-OUT DASQ, the Big Five Questionnaire and the Positive and Negative Affect Schedule in sample 3 (n = 153). The SCE and OCE scales had robust internal consistency and reliability, though the capacity to discriminate higher inward and outward participants was stronger in SCE. Although further validation research is required, the present study suggests the IN-OUT DASQ has the potential to be a measurement tool for detecting individual differences in social behavior and social affective neuroscience.The issue of individual differences has always been an important area of research in psychology and, more recently, neuroimaging. A major source of interindividual variability stems from differences in basic affective dispositions. In order to make a contribution to this field of research, we have developed a new type of assessment – the In-Out dispositional affective style questionnaire (IN-OUT DASQ) – to measure the proneness between two different ways of feeling situated: a predominantly body-bound one in the case of the inward tendency and an externally anchored one in the case of the outward tendency . The IN- Personality and social psychology have taken up conceptual and methodological challenges to understand how individual differences affect social behaviors . On one In recent years, this subject has been expanded to include neuroimaging techniques. Indeed, it has become possible to identify the relationship between neural mechanisms underlying behaviors and some individual characteristics , showingAs In the present study, the concept of dispositional affect emphasizes the need to account for the way in which different persons, in dealing with others and the different circumstances of everyday life, feels situated in the environment . Being eThe nature of emotions has remained one of the longest standing debates in the biological and social sciences. Indeed, there are several perspectives on basic and non-basic emotions. There is a general agreement that basic emotions must have direct causal powers over motivation and behavior, at least in early developmental stages. In all cases, this argument is based on evolutionary principles . If an eThis way of emotioning may be described by using the words employed by One could sum this up by suggesting that by the recurrent affective engagement with significant people the emoter comes to acquire over time a better knowledge of families of basic emotions rather than non-basic, or vice versa. In accordance with these assumptions, we outlined the two general affective dispositions, inward and outward. The distinction between inward and outward tendencies was seen to be based on whether basic or non-basic emotions are prevalently elicited, as well as on the combination between the two dimensions they define . The twoThe more those relationships generate specific episodes and interactions which the organism is biologically ready to interpret as being relevant to survival, the more the emoter’s response will involve the activation of basic emotions . As a reUnlike basic emotions, those emotions which emerge through mediated affective engagement, because of their limited viscerality, can change more quickly and more easily, since they tax the system’s visceral resources less . Such chTaking part in a discourse can also give rise to a reference system. As highlighted by As we have emphasized, one perceives alterity and simultaneously co-perceives oneself. This might explain why the so-called interdependent self-construal disposition tends not only to assimilate others self cognitively, emotionally, and perceptually , but alsAccording to this theoretical approach, our underlying assumption in affective neuroscience research is that the two dispositional affective styles can contribute to account for interindividual variability in brain activity. That is, individual differences in structuring the affective domain can be associated to the activation of different neural areas in response to the same emotional stimuli. In our first functional magnetic resonance imaging (fMRI) study  the inwaIn a further fMRI study , we hypoThe aim of the present study was to improve the means at our disposal to describe inward and outward dispositions and to discriminate between people with higher inward and outward pronenesses. Accordingly, the focus will be on the prevalent properties of people’s affective engagement with oneself, the world, and others. The constructs are discussed separately and in their extreme. Of course, in individuals, what seem to be reified here exist only as tendencies of varying strength.The objectives of the analysis may be divided in two broad classes: (1) item development, scale construction, and assessment; (2) assessment of reliability, factorial validity, and construct validity. In the following section the procedures used for item writing, data collection, and analysis are described in detail.Items were developed to measure the emotional makeup composing inward and outward dispositional affective styles, as previously described. A pool of suitable items was created by describing inward and outward attitudes toward life situations. It included items which referred, for instance, to the need for consent and approval, sensitivity to judgment, and vulnerability to criticism  as well as items which referred to the need for emotional over-control in situations which, otherwise, would be felt as potentially dangerous . The items were written clearly and concisely in order to tap dispositions in the realm of a common person’s experience. Each item was then w rated high or low by two experts in a blind fashion with respect to their relevance vis-à-vis to the constructs as we have defined. Concordance between the two experts was 100%. According to the dispositional affective styles, two scales were then established: Self-centric engagement  and Other-centric engagement . The 60 potential items were randomly ordered as a single scale. Respondents were asked to rate on a 7-point scale  the representativeness or frequency of each item in their current time of life.One of our aims was to assess the validity of inward and outward scales. We hypothesized an oblique two-factor structure to explore the data. We expected a correlation between the two-factors because of our model assumptions. Indeed, the two scales referred to the two general constructs that are not mutually exclusive but are partially overlapping. For instance, sensitivity to judgment can overlap with a need for emotional over-control.Our second purpose was to differentiate participants with higher or lower proneness on each of the two constructs – inwardness and outwardness. Consistent with our assumptions, we predicted a slight correlation between the two scales, and that the high inward respondents would score higher on the SCE scale, whereas the high outward respondents would score higher on the OCE scale. This question was addressed by assessing the predictive performances of the scales. Further details are given in the following sections.In addition to examining construct validity, we also investigated the correlations between the In-Out dispositional affective style questionnaire (IN-OUT DASQ) and personality traits using the Big Five Questionnaire BFQ; , and affIn order to assess the construct validity, the participants were classified in low vs. high inward, and low vs. high outward through a semi-structured interview which was administered independently by two trained investigators who were blind to each other’s results. The aim of the semi-structured interview was to reconstruct the sense of personal stability by the assessment of emotional activation, duration and regulation in two meaningful emotional experiences triggering anger and fear. The steps of the semi-structured interview have been described in detail in our previous study . In ordeAn initial exploratory factor analysis (EFA) was conducted in a random sample of 292 Italian volunteers with various types of job, possessing different educational qualifications and being of various ages , balanced by level of education . Volunteers were recruited through flyers at places of work and universities, and through word of mouth by colleagues and collaborators of our Institute. Exclusion criteria included any significant psychiatric conditions as evaluated with the Structured Clinical Interview (SCID). Participants were asked to respond to the items on the basis of the following instructions: “There are no right or wrong answers for the following questions. Please answer based on your most frequent way of being, feeling, and behaving.” In order to avoid any potential effect of interactions between the level of anxiety and the inability to identify and describe personal affective states, after completing the IN-OUT DASQ participants also responded to the State-Trait Anxiety Inventory STAI;  and to TThe study was approved by the Comitato Etico Indipendente Locale of the Azienda Ospedaliera “Ospedale Policlinico Consorziale” of Bari. Informed written consent was obtained from all participants before participation.In a preliminary step of the analysis, frequency distributions were examined for each item to identify problematic patterns, such as extreme skewness, mean scores near the top or bottom end of the Likert scale and limited variability. In order to identify excessively redundant item pairs, inter-item correlations were also examined. Then, the remaining items were used for the development of the SCE and OCE scales. The unidimensionality of each scale was ascertained through an item-level EFA. The items were selected through a forward step procedure, in which at each step the item that determined the maximum increase of Cronbach’s alpha was included in the scale. Scores for each scale were obtained by summing responses to all items.The factorial structure of the final scales was assessed through an item-level EFA, using the principal axis extraction method. Two analyses were conducted to assess separately the internal consistency of each scale. In addition, an analysis was carried out on the entire item pool to assess the overall factor structure. The number of factors was determined by examining the scree plot and retaining the factors corresponding to the first larger eigenvalues, until the slope of the graph changes from rapid to slow decline. In addition, a more formal approach was employed by assessing the minimum average partial (MAP) criterion . In the Construct validity was assessed by evaluating the performances of the scale scores in differentiating the groups of participants ascertained by the semi-structured interviews, namely high inward vs. low inward, and high outward vs. low outward. To this aim, we used the area under a receiver operating characteristic (AUROC) curve . The AURIn order to evaluate the predictive performances of the scales, the classification of the participants into two mutually exclusive groups were determined by dichotomizing scale scores, and compared with the groups delineated as a result of the semi-structured interviews . SeveralThe initial factor structure identified in the EFA provided the hypothesized factor structure for the separate CFA performed on a second sample. WLSMV (weighted least squares means and variance adjusted) estimation method was used to account for non-normality of item distributions. The model fit of three factor solutions: (1) one factor; (2) two orthogonal factors for SCE and OCE items respectively; (3) two oblique factors; was compared by root mean square error of approximation (RMSEA), Bentler’s comparative fit index (CFI), and Tucker–Lewis index (TLI). Acceptable fit of the model was defined as: RMSEA < 0.1, and CFI, TLI > 0.95.The association of SCE and OCE with BFQ and PANAS scales was assessed through bivariate correlations and semipartial correlations . SemiparAll analyses were carried out using the R software  with theThe initial pool consisted of 60 items divided into the SCE scale (25 items) and the OCE scale (35 items). The average SCE scores ranged from 2.50 to 5.33 and standard deviations from 1.37 to 1.97. The degree of skewness was overall admissible, with values from -1.16 to 0.99. Cronbach’s alpha was equal to 0.897, close to the value of McDonald’s Omega, 0.903 . The ICCAfter the preliminary verification of item distributions, the item pool included 39 items, 14 of the SCE scale, 25 of the OCE scale. The excluded items had very weak (13 items) or not expected (seven items) values of inter-item correlations. The only redundant pair of items (with a correlation higher than 0.8) was excluded to avoid an inflated estimated reliability. In the selected pool of SCE items, inter-item correlations ranged between -0.117 and 0.599, with an average value of 0.291, whereas in OCE pool the range was between -0.174 and 0.732, with an average value of 0.282.Tables 1 and 2). All the items included in the final SCE scale described the need for emotional over-control in situations that, otherwise, would be felt as potentially dangerous. On the other hand, the final OCE items referred to the need for approval, and sensitivity to judgment.The two separate EFAs yielded 11 SCE items and 16 OCE items with loadings greater than 0.4 in absolute value on the first factor, thus showing an appreciable internal consistency of the two scales. The final scales included seven items each .The results of the EFA analyses of the final scales are reported in In the overall analysis, a change in slope (“elbow”) was found at the third eigenvalue, thus suggesting a two-factor solution. The minimum of average squared partial correlations was reached at the second eigenvalue, thus supporting the result above. To assess the association of the items with the two oblique factors, we reported the reference vector correlations , which mTable 1, the SCE items were more highly correlated with the second principal axis, whereas the OCE items were more highly correlated with the first principal axis. However, the cross correlations between SCE items and the first axis and between OCE items and the second axis were not negligible. This result revealed a moderate correlation between SCE and OCE scales, between the need of control , the need of others’ approval , and the sense of guilt . Nevertheless, there were item correlations within the two scales consistent with the core of the two dispositions investigated here. Indeed, within the SCE scale there was a higher correlation coefficient between the need of control , the danger of an unexpected event (item 6), and the anticipation of dangers . On the other hand, within the OCE scale is worth noting the highest correlation coefficient between the sense of guilt (item 5), the sense of emptiness , and the need of approval .As shown in post hoc” technique . The factor loadings on the second and third factorial axes are shown in Figure 2. The points representing the selected SCE items and OCE items respectively formed two quite separate clusters. The proximity of the elements of each cluster revealed a pattern of correlation of the projections of items on the plane spanned by the second and third axes, thus providing some evidence of internal consistency for both SCE and OCE items. We did not investigate further results  because post hoc procedures are not suitable for assessing them  and close to the correlations between principal axes obtained in previous analyses.The descriptive statistics and reliability coefficients are reported in According to the semi-structured interviews, the 256 participants consisted in 62 high inward and 194 low inward, and 99 high outward and 157 low outward. The sample proportions of high inward and high outward were 24.2%  and 38.7%  respectively. We expected a priori that high inward would have scored higher on the SCE scale, and high outward would have scored higher on the OCE scale.Figure 3). The average scores of the SCE scale were 31.3 [standard error (SE): 0.56] and 23.5 (SE: 0.52) in high and low inward respectively. The difference in SCE scores between the two groups was significantly greater than zero (Mann–Whitney test: p < 0.0001). About the OCE scale, the average scores were 26.2 (SE: 0.58) and 28.2 (SE: 0.59) in high and low outward respectively. The difference between the two groups was significant in the test data (p = 0.01) but not in the retest (p = 0.3). Thus, there was poor evidence supporting the second expectation. Accordingly, further analyses were not carried out for the OCE scale.Therefore, the distributions of scale scores in the target groups were evaluated. The box plots showed that SCE scores were rather separated between high and low inward, whereas OCE scores did not differentiate between high and low outward  was observed between the semi-structured interviews and the OCE scale classification, although with a rather high error in classifying high inward. Further investigations are required to refine the assessment of this trend.Table 5). The SCE scores showed a moderate negative correlation with Neuroticism  and a moderate positive correlation with Negative Affect , though the semipartial correlations were weaker . On the other hand, OCE scores showed a weak to moderate negative correlation with Neuroticism  and a positive correlation with Negative Affect , even if the semipartial correlations were both not significant .Next, the bivariate correlations between the DASQ, BFQ, and PANAS scales were examined  compared to the others . These results showed a moderate fit with the hypothesized oblique two-factor structure model.The aim of the present study was to construct a research tool to describe inward and outward dispositions and to individuate the highest level of proneness between the inward and outward dispositional affective styles. Two scales of seven items each were finally assessed: the SCE and the OCE, respectively as a disposition index for inwardness and outwardness. Our predictions were partially confirmed, with some unexpected results.post hoc” techniques may be deficient, the partial correlation analysis confirmed that the two scales have their own internal consistency.According to our theoretical assumptions, inward and outward dispositions were operationalized as unipolar constructs. Consistent with this contention, the EFA confirmed a two-factor solution providing evidence for the unidimensionality of the SCE and OCE scales. This result was moderately confirmed by the CFA. Both the factorial analyses revealed a high correlation between these two scales. As expected, this correlation in itself is not in contrast with our theoretical assumptions. Indeed, these two general dispositions should not be thought as categorical stances that people take in an exclusive way. As general tendencies, these engagements with himself/herself and with others can be combined from a minimum to a maximum degree, in different nuances, and differently over time. Indeed, the need of control, the need of others’ approval, and the sense of guilt are all attitudes that can coexist. We controlled also for a potential confounding latent factor coming from a common variance which may account for such a correlation. Although “The results concerning the discriminant capacity were encouraging. Although our current aim was ambitious, these findings showed at least a trend in the expected direction. As we predicted, the SCE scale discriminated against high inwardness. Indeed, high inward respondents scored higher than low inward respondents in SCE. The correlations between the SCE items were fully consistent with the inwardness construct. Indeed, there was evidence of a higher correlation between the sense of frailty, danger and its anticipation, and the need of control of loved ones. The meaning of these correlations refers to the core traits of this predominant modality of emotional engagement with the self and with the environment. On one hand, it showed that the more respondents were inwardly prone, the more emotional disposition was prevalently focused on a state of alarm from which fear can be suddenly elicited. It revealed the need to face and anticipate conditions that may alter a personal stability by generating the anticipation of potential dangers and increasing a sense of control. On the other hand, the high outward respondents scored lower than low outward respondents on the SCE. According to our theoretical assumptions, this result provides evidence about the inverse relationship between high inwardness and high outwardness.Unfortunately, our expectations concerning the OCE scale were only partially confirmed. The correlations between the OCE items were consistent with the outwardness construct. Indeed, there was the highest correlation between the feeling of guilt, the sense of emptiness, and the feeling of personal loss, as well as between the need of approval. All these correlations assessed central themes of the OCE disposition. The “guilt-emptiness-feeling of personal loss” correlation is certainly one of the most significant for understanding outwardness. Because these subjects keep their the sense of personal stability by anchoring their identity to others as external reference points, the possibility of losing this reference system can give way to a feeling of emptiness. As is known, the loss of a significant person gives way to a feeling of guilt and of emptiness. People more prone to the outwardness experience more frequently have feelings of guilt and void when they lose the other as a source of reference. This can generate a wide spectrum of discomfort, even a depressive disorder. On the other hand, the correlation between the need of approval and getting lost in a partner refers to the attempt to synchronize their feelings with others as external reference points.Nevertheless, the OCE discriminant capacity was poor as showed by the ROC curve. Although the OCE scale revealed some basic attitudes at the core of outwardness, it was not sufficiently sensitive to individuate those that better fit to high levels of outwardness. This result might refer to the interaction between the wording of the items and the outward subject’s sensitivity to discourse as a source of self-reference. We speculate that it is as if the respondents had felt “positioned” by some items. Indeed, outward respondents, both high and low, tended to give a neutral score to those items which were worded in a more direct way.The robust reliability suggests a good temporal stability of both the measures and the phenomena. It helps to increase the robustness of the scales and their development. Due to the multifaceted structures of the inwardness and outwardness, the sensitivity of the measures employed can be improved also by using those means that estimate other dispositions in other domains such as cognitive, motivational and interpersonal attitudes. Indeed, though the scores on the DASQ were found to be distinct from BQF and PANAS constructs, further research is required to assess other relationships in order to place OCE and SCE scales within a broader nomological network.We acknowledge that the present study has some limitations. First, the low discriminant capacity of the OCE scale means that it cannot be used to estimate high vs. low outwardness without the semi-structured interview. We argue that the presence of neutral response undermined the OCE items more than SCE items. Since it was an exploratory study, we made this choice to avoid forcing a response. On one hand, this choice allowed us to better explore general dispositions in a large sample. On the other hand, it might have interacted with the outwardness subject’s sensitivity. In this respect, the higher outward respondents might have a more marked attitude to use the questions as a temporary source of information for recognizing their own emotional experience. This could have influenced the discriminative capacity of the OCE scale. It could be that this phenomenon might be better controlled through items worded both positively and negatively within the OCE scale. The SCE scale did not assign a priority to the understanding of the gut aspects of emotions in relationships with others and with the world. Since it is a more marked sensitivity in inwardness, this may constitute a limitation. Although such interoceptive awareness requires the investigation of behavioral tasks , the SCE scale could be improved by the enhancement of the interoceptive sensitivity.Overall, our previous findings indicate that differentiating the high level of inward and outward tendency in relationships with others and the world is a potential strategy for understanding and measuring individual differences. In the present study, we explored a means which is useful in this field of empirical research. It is important to bear in mind, however, that though our results provide evidence for the two constructs and their reliability, further studies are required to confirm the factorial model and its validity, also taking into account their multifaceted structures. In addition, the relationships between personality traits and dispositional affective styles still require investigation. Since this subject is many-sided, we started at the most basic level, i.e., testing a first model. Therefore, it would be suitable to continue the research line at a more complex level by including new hypotheses and new models. The questionnaire still required a proper psychological assessment (interview). Far from being exhaustive, the present study is an attempt to address the issue of individual differences from an affective dispositional point of view.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.


Super-resolution fluorescence microscopy has become a powerful tool to resolve structural information that is not accessible to traditional diffraction-limited imaging techniques such as confocal microscopy. Stochastic optical reconstruction microscopy (STORM) and photoactivation localization microscopy (PALM) are promising super-resolution techniques due to their relative ease of implementation and instrumentation on standard microscopes. However, the application of STORM is critically limited by its long sampling time. Several recent works have been focused on improving the STORM imaging speed by making use of the information from emitters with overlapping point spread functions (PSF). In this work, we present a fast and efficient algorithm that takes into account the blinking statistics of independent fluorescence emitters. We achieve sub-diffraction lateral resolution of 100 nm from 5 to 7 seconds of imaging. Our method is insensitive to background and can be applied to different types of fluorescence sources, including but not limited to the organic dyes and quantum dots that we demonstrate in this work. The information provided by fluorescence imaging is essentially limited by the resolution, defined as the finest structure that the imaging technique is able to resolve. The resolution is critically limited by the diffraction of the objective aperture, which places physical challenges to obtaining information from the acquired images. Recently, several novel imaging techniques has been developed aiming to break the diffraction limit, namely super-resolution imaging. These techniques can be categorized into three different types. The first type utilizes a spatially or temporally engineered illumination pattern to either reduce the volume of the detected target in a controllable way, as in stimulated emission depletion (STED) microscopy et al. used a software package from astronomy research to separate closely located Gaussians in a technique called DAOSTORM The second group of methods resolves the distribution of fluorescent sources based on single particle localization. Stochastic optical reconstruction microscopy (STORM) et al. resolved the localization of densely distributed individual quantum dots from the spatial covariance of the pixel intensity fluctuations using independent component analysis (ICA) et al. to yield super-resolution images at a greatly improved temporal resolution of seconds Instead of resolving the localization of emitters based on single switching events, a third group of approaches extracts localization information from the statistics of pixel intensity fluctuations. In these approaches, overlapping emitters are actually preferred since a higher density of provides higher intensity variance. Many different kinds of emitters including fluorescent proteins, organic dyes In this work, we introduce a new image reconstruction algorithm belonging to the third category named spatial covariance reconstructive (SCORE) algorithm. We start from the fluorescent intensity covariance between pixels of a stack of images, combine the prior knowledge of the shape of the PSF to map the distribution probability of individual emitters. Our method builds upon the common advantages of the statistical approaches: insensitivity to background, no upper limit to the fluorescent emitter on-time, far higher information density per frame, low requirements on the number of frames, and ease of implementation from standard epi-fluorescence instruments. Through principal component data compression, we only consider components that have significant contribution to the variance of pixel intensities, and thus this method reduces image noise and computational cost. We quantitatively compare the results of STORM and SCORE using simulated data, where the quality is defined as the Kullback-Leibler divergence from the known ground truth to the resulted images. As demonstrations, we applied SCORE to images of microtubules in HeLa cells labeled with either organic dyes and quantum dots. In both cases, we are able to achieve sub-diffraction resolution of better than 135 nm and 90 nm, respectively, within a few seconds of imaging. The resolution is limited by our labeling quality, and better imaging resolution can be obtained by using fluorophores that have more robust intensity fluctuations.M fluorescent emitters located at positions T images of these emitters, whose images are governed by the instantaneous intensity of each emitter We consider The problem of image reconstruction is to find the best estimate for the emitter positions atistics . The difThe principal components can be obtained from the covariance matrix between pixels in a time-series of imagesDimensional reduction in principal component analysis can be achieved by eliminating those modes with less than a threshold that retains meaningful signals while reducing noise. The eigenvalue spectrum from a typical set of blinking emitter images shows a kink that can be used to separate signal from background noise . We deteThe distance of an arbitrarily placed PSF to the eigen-subspace depends on how close this PSF truly resembles a fluctuating emitter. Quantitatively, we utilize this property to estimate the likelihood of finding a PSF at a particular location The relationship between the emitter density and the Euclidean distance is not readily obvious. Therefore, we take an approach that approximates the probability density and then optimizes the distribution so that it resembles the eigen-mode variances obtained from the images. The distance distribution In matrix notation, we define the coordinates of a set of normalized Gaussian functions The optimized solution is obtained through a gradient descent method, and we name this optimization process to refine the intensity distribution estimate as “variance shaping”. Simulations suggest that variance shaping indeed provides more accurate estimates than the simple SCORE at the cost of slight increase in computation time. Practically, for large image sizes, because the intensity fluctuation correlation between pixels is localized to single PSFs, large images are sliced into small overlapping regions, typically with a width of 6–10 times of the PSF size and processed independently in parallel. The individual regions are stitched together into the large image weighted by the total variance of each region.The quality of single-emitter based methods such as STORM and PALM is determined by many factors including emitter brightness, switching duty cycle, and the number of frames that can be acquired. In addition, the localization precision for a single emitter scales with the width of the PSF and inversely with the square root of the number of photons received by the camera. Further reductions in precision occur in the presence of camera noise and ambient light collection. The on-off duty cycle of the emitters places an upper bound on the allowed emitter labeling density to achieve single emitter localization in a diffraction-limited area, which in turn defines the maximum spatial frequency of resolvable features according to the Nyquist criterion for a finite number of images collected. However, the actual density of localized emitters in the reconstructed image is proportional to the number of frames and the emitter duty cycle. It has been shown experimentally that image reconstruction quality can limited by either the localization precision or the emitter density, depending on the choice of the specific fluorophore To demonstrate the ability of SCORE to achieve super-resolution imaging using highly overlapping emitter PSFs, we first analyzed a series of simulated images. In the simulations, the width of the PSF, 0–150 nm . We placTo quantify the quality of the reconstructed images, we interpret each image as a probability distribution of emitter density, and use the Kullback-Leibler (KL) divergence to describe the distance between the ground truth and the images. The KL divergence is defined asThe KL divergences between STORM or SCORE images and the ground truth are shown in e result .Another factor limiting the quality of the reconstructed image is the localization precision of each emitter, which is determined by its brightness and the level of background noise 2. After a brief, few-second, exposure to the red laser, the majority of the fluorophores were switched off. We then added a millisecond laser pulse of 405-nm wavelength to stochastically switch on fluorescent molecules between camera acquisition cycles. After and initial 3–5 s burst where many molecules become activated, the duty cycle leveled of to a steady low value for minutes. Images were acquired at 100 frames per second to capture the fast dynamics of fluorophore switching.As a demonstration, we applied SCORE imaging to fluorescentl microtubules labeled with an organic Alexa dyes and quantum dots (QDots). Microtubules from fixed HeLa cells were stained with anti-tubulin antibodies conjugated to the Alexa Fluor 647 fluorescent dye and imaged with epi-fluorescence microscopy. A 50 mW, 647 nm solid-state red laser was kept on during the entire image acquisition, yielding an estimated 1–10 kW/cmWe analyzed the first 5 seconds of data (from 500 frames) using SCORE after the UV activation laser was turned on, when the duty cycle was the highest . From onAnother type of fluorescent source that is bright and has intrinsic intensity fluctuations are QDots. In conventional imaging applications, the variability in brightness of QDots are often considered as negative factors. However, these intensity variations are crucial for fluctuation-based super-resolution techniques such as SCORE Super-resolution imaging is now achievable on a conventional epi-fluorescence microscope with little to no modification to the optical design. The fine structural information embedded in a sequence of fluorescence images can be restored using single particle localization as implemented in STORM and PALM, or intensity fluctuation statistics as in SOFI, ICA and SCORE. STORM/PALM and related localization-based methods have become increasingly popular due to their outstanding spatial resolution. The quality of the reconstructed images are limited by essentially two factors: the localization precision, determined by the emitter brightness and background noise, and the sampling density, set by the fluorophore duty cycle, labeling density, and acquisition time. Either factor can be the bottleneck of the final image quality. Moreover, the duty cycle of the emitters is usually set much lower than the optimal value for experimentally practical reasons. Therefore, STORM/PALM typically require thousands of images to gain dense sampling due to the essential non-overlapping condition. In contrast, by looking at the covariance between the intensities of pixels statistically, SCORE is not limited by the non-overlapping condition, and is able to reconstruct images with comparable quality from far fewer frames that contain denser information. In addition, any improvements in emitter brightness and its variation, the number of frames acuired, higher labeling density, and lowered background noise contribute to better statistics, therefore the imaging quality is no longer limited by a single bottleneck. In particular, a higher labeling density is always preferred for SCORE. In the case of low emitter density, single particle localization methods make use of information that the statistical methods ignore, and are able to resolve probe locations with better accuracy at the cost of a substantially longer acquisition time.et al. resolved the localization of a finite number of quantum dots from the temporal sequence of the eigen modes using ICA, however the ability to resolve individual emitters quickly becomes intractable if several emitters are located in one PSF area. Instead of attempting to resolve individual emitters with their explicit temporal blinking sequences as ICA does, our method focuses on the total variance and covariance derived from the ensemble average, and thus it is capable of estimating a continuous distribution, and is not limited to a small number of discrete points.SCORE is closely related, but different from existing statistical methods such as SOFI Because the covariance matrix does not depend on the basal intensity at each pixel, SCORE will reject any temporally non-drifting backgrounds such as an autofluorescence signal. This property allows SCORE to analyze images with only a portion of emitters fluctuating in a background of constantly fluorescing molecules. Because the fluorescence intermittence takes place at much faster time scale than the photobleaching, it is applicable to temporally high-pass filter the intensity sequence at each pixel to remove the slowly varying background signal before calculating the covariance. The out-of-focus light can be treated as background light since the intensity correlation of defocused light is also delocalized and spatially convolved into more uniform signals in time. Thus the contribution to the covariance becomes smaller as the emitter resides further from the focal plane.et al. have successfully used SOFI to image Dronpa-labeled Lyn kinase Many different types of fluorescent sources undergo intensity fluctuations on fast time scales, and thus can serve as potential candidates for SCORE analysis. In this work, we used organic dyes and quantum dots to demonstrate SCORE imaging. Organic dyes can switch between bright and dark states in certain chemical environments, but they have a limited number of switching cycles before bleaching, and therefore limit the SCORE image Even tough the computational complexity is often not considered as a major factor in choosing algorithm-based methods for super-resolution imaging, performance can become a practical limitation in certain circumstances. Because SCORE is based on analysis of the covariance of the entire image stack instead of a frame-by-frame analysis as in deconSTORM and CSSTORM, its speed is typically conSTORM . This peHuman HeLa cells were cultured as described in Quantum dot labeled HeLa cells were prepared and treated in the same way described above. Cells incubated with primary antibody were washed with PBS 3 times, and incubated with 20 nM anti-mouse IgG labeled with QDot 655 (Life Technology) in PBS and 6% w/v BSA for 30 minutes. Stained cells were washed in PBS and the slide was mounted on the microscope for imaging.in vivo images were taken on a home-built microscope with on Olympus 60× 1.4 NA oil-immersion objective. A 50 mW 647 nm solid-state laser (CrystaLaser) was used as the excitation and deactivation source, and a 100 mW 405 solid-state laser (Coherent) was used as the activation laser. Images were collected using an EMCCD camera . Quantum dot labeled microtubule images were taken on a Nikon TE-2000 inverted microscope. A home-built 20 mW 532 nm diode laser was used as the excitation source. The images were collected with an EMCCD camera  controlled by LabVIEW .Alexa Fluor 647 labeled Microtubule For SCORE analysis, image stacks of Alexa Fluor 647 labeled microtubule were assumed to have a fixed background with a smoothly decaying intensity. The decaying background was estimated by fitting a single exponential as a function of time at each pixel, and then subtracted from the raw images before SCORE analysis. The image field is divided into overlapping regions of interest with size of STORM images in the simulations were reconstructed from the Gaussian fit of the individual frames, since all emitters were located with 1 PSF width, no separate or Gaussian mixture fit was possible or necessary. The STORM images were generated and rendered from the localization results, and each detected emitter is displayed as a 2D Gaussian function whose width scales with the inverse square root of the emitter intensity as described in File S1Supporting material.(PDF)Click here for additional data file.Figure S1The principle of variance optimization in SCORE. (a) The first 10 eigen modes of a 8×8 pixel portion of 500 frames from experimental data. (b) The variance of the 500 frames (upper panel) and the SCORE image (lower panel). (c) The variances in the basis of eigen modes . The red squares are the experimental variances, the blue line is the fit using a double-exponential function, and the green solid circles are the calculated variances from the reconstructed image. (d) The calculated covariance matrix of the reconstructed image. The covariance matrix of the experimental data is a diagonal matrix with diagonal elements shown in (c).(EPS)Click here for additional data file.